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Doctor of Philosophy (PhD) in Quantum Computing

• Request Information

Earn a doctorate degree in Quantum Computing, help lead innovation in a growing industry

The PhD in Quantum Computing is a unique doctoral program designed to meet the immediate industry need for innovative researchers and practitioners. Professionals will graduate with the skills necessary to become key leaders in the advancement, expansion, and support of the this rapidly growing industry. 

Students in this program will conduct extensive and sustained original research on the applications of Quantum Computing, which harnesses and exploits the laws of quantum mechanics to process a vast number of calculations simultaneously. Faculty of this program are industry experts devoted to providing students deep proficiency in this area using an interdisciplinary methodology, cutting-edge courses, and dynamic faculty skill sets.

Graduates with the Ph.D. in Quantum Computing can expect to fill executive and senior-level positions in commercial companies as well as local, state, and federal government with a variety of titles such as:

• Quantum Senior Scientist
• Quantum Senior Software Engineer
• Chief, Quantum Computing Solutions
• Vice President, Quantum Solutions
• Senior Director, Quantum Computing
• Senior Quantum Solutions Architect
• Senior Quantum Systems Engineer
• Director, Federal Quantum Research
• Chief, State Quantum Solutions
• Senior State Quantum Applications Engineer
• Senior Director, Financial Quantum Computing

Graduates will also possess the required knowledge in Quantum Computing to serve as a subject matter expert and form their own private company.

Why Capitol?

Learn around your busy schedule

Program is 100% online, with no on-campus classes or residencies required, allowing you the flexibility needed to balance your studies and career.

Proven academic excellence

Study at a university that specializes in industry-focused education in technology fields, with a faculty that includes many industrial and academic experts.

Expert guidance in doctoral research

Capitol’s doctoral programs are supervised by faculty with extensive experience in chairing doctoral dissertations and mentoring students as they launch their academic careers. You’ll receive the guidance you need to successfully complete your doctoral research project and build credentials in the field. 

Key Faculty

Degree Details

This program may be completed with a minimum of 60 credit hours, but may require additional credit hours, depending on the time required to complete the dissertation/publication research. Students who are not prepared to defend after completion of the 60 credits will be required to enroll in RSC-899, a one-credit, eight-week continuation course. Students are required to be continuously enrolled/registered in the RSC-899 course until they successfully complete their dissertation defense/exegesis.

The student will produce, present, and defend a doctoral dissertation after receiving the required approvals from the student’s Committee and the PhD Review Boards.

Prior Achieved Credits May Be Accepted

Educational Objectives:

• Students will integrate and synthesize alternate, divergent, or contradictory perspectives or ideas fully within the field of Quantum Computing.
• Students will demonstrate advanced knowledge and competencies in Quantum Computing.
• Students will analyze existing theories to draw data-supported conclusions in Quantum Computing.
• Students will analyze theories, tools, and frameworks used in Quantum Computing.
• Students will execute a plan to complete a significant piece of scholarly work in Quantum Computing.
• Students will evaluate the legal, social, economic, environmental, and ethical impact of actions within Quantum Computing and demonstrate advanced skill in integrating the results in to the leadership decision-making process.

Learning Outcomes:

Upon graduation:

• Graduates will integrate the theoretical basis and practical applications of Quantum Computing in to their professional work.
• Graduates will demonstrate the highest mastery of Quantum Computing.
• Graduates will evaluate complex problems, synthesize divergent/alternative/contradictory perspectives and ideas fully, and develop advanced solutions to Quantum Computing challenges.
• Graduates will contribute to the body of knowledge in the study of Quantum Computing.

Tuition & Fees

Tuition rates are subject to change.

The following rates are in effect for the 2024-2025 academic year, beginning in Fall 2024 and continuing through Summer 2025:

• The application fee is $100
• The per-credit charge for doctorate courses is $950. This is the same for in-state and out-of-state students.
• Retired military receive a $50 per credit hour tuition discount
• Active duty military receive a $100 per credit hour tuition discount for doctorate level coursework.
• Information technology fee $40 per credit hour.
• High School and Community College full-time faculty and full-time staff receive a 20% discount on tuition for doctoral programs.

Find additional information for 2024-2025 doctorate tuition and fees.

I was able to receive credit for previous work in a PhD in Biomedical Informatics. Capitol Tech enables me to rapidly dive in, complete my research, and degree and bring my skills to the job market quickly in an embryonic but emerging field.

-Forrest Pascal PhD in Quantum Computing

Need more info, or ready to apply?

12 Top Quantum Computing Universities in 2024

• Exclusives , Research

Matt Swayne

• April 18, 2022

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In just a few years, quantum computing and quantum information theory has gone from a fringe subject offered in small classes at odd hours in the corner of the physics building annex to a full complement of classes in well-funded graduate programs being held at leading quantum computing universities.

The question now for many would-be quantum computer students is not, “Are there universities that even offer quantum computing programs” but, rather, “Which of them are leaders at quantum computing research.”

12 Best Quantum Computing Universities

1. the institute for quantum computing — university of waterloo.

The University of Waterloo can proudly declare that, while many colleges avoided offering quantum computing degree programs like cat adoption agencies avoided adoption applications from the Schrodinger family, this Canadian university went all in. And it paid off. Mike Lazaridis, creator of the BlackBerry, funded the university in 2002. He also supported the founding of  Waterloo’s Perimeter Institute for Theoretical Physics, one of the premier quantum science research universities. The quantum computing powerhouse employs about 296 researchers and has published more than 1,500 research papers since its founding. One of the strengths of this school for Quantum Computing is how it combines excellence in academic research with an entrepreneurial drive to commercialize the technology. You can also check out the video to learn more about this quantum computing university.

2. University of Oxford

The University of Oxford has a long history as a quantum computing university. The university’s own David Deutsch first described exactly what a universal quantum computer is way back in 1985. The first working pure state NMR quantum computer was demonstrated at Oxford and University of York. And the university is still position among the top leaders in quantum science. According to the university, they’re in quantum research because of its vast potential. “Quantum computing has the potential to transform areas of our lives such as healthcare, finance and security – and Oxford is pioneering theory, technology and responsible innovation to ensure that its power will bring benefits for all of society.”

3. Harvard University — Harvard Quantum Initiative

Harvard says the Harvard Quantum Initiative in Science and Engineering (HQI) is “a community of researchers with an intense interest in advancing the science and engineering of quantum computers and their applications. Our mission is to help scientists and engineers explore new ways to transform quantum theory into useful systems and devices.” The group said this “second quantum revolution” will build on the first one that created technologies like GPS navigation, global communication, and medical breakthroughs such as magnetic resonance imaging (MRI) — and HQI members are preparing for this revolution.

4. MIT — Center for Theoretical Physics

MIT is a research behemoth. It’s reach now extends deeply into quantum computing and quantum information. The university’s strength in theoretical physics is now leveraged into what they term, quantum information and quantum computing, or QI/QC. Besides building a quantum computer, MIT researchers explore Quantum algorithms and complexity, Quantum information theory, measurement and control and applications and connections. That being said it is not a surprise that MIT stands as one of the top quantum computing universities.

5. National University of Singapore and Nanyang Technological University — Centre for Quantum Technologies

The Center for Quantum Technologies of Singapore was founded to bring together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena. They positioned themselves among the pioneer quantum computing universities. Experts in this new discipline of quantum technologies are applying their discoveries in computing, communications, and sensing.

6. University of California Berkeley

The Berkeley Center for Quantum Information and Computation includes researchers from the colleges of Chemistry, Engineering and Physical Sciences to work on fundamental issues in quantum algorithms, quantum cryptography, quantum information theory, quantum control and the experimental realization of quantum computers and quantum devices.

7. University of Maryland — Joint Quantum Institute

The Joint Quantum Institute (JQI) leads quantum scientists from the Department of Physics of the University of Maryland (UMD), the National Institute of Standards and Technology (NIST) and the Laboratory for Physical Sciences (LPS). Each institution brings major experimental and theoretical research programs that are dedicated to the goals of controlling and exploiting quantum systems, on the level of the world’s top quantum computing universities.

8. University of Science and Technology of China (USTC) – Division of Quantum Physics and Quantum Information

This division of quantum physics and quantum information specializes in the field of quantum optics and quantum information. The division lists its main directions as quantum foundation, fiber-based quantum communication, free-space quantum communication, quantum memory and quantum repeater, optical quantum computing, superconducting quantum computing, quantum simulation with ultra-cold atoms, quantum metrology and related theories. Researchers have also built advanced experimental platforms to conduct cutting-edge research.

9. University of Chicago — Chicago Quantum Exchange (CQE)

The Chicago Quantum Exchange (CQE) is a hub of researchers who are interested in advancing academic and industrial efforts in the science and engineering of quantum information. They encouraged the words best quantum computing universities to promote the exploration of quantum information technologies and the development of new applications. The CQE facilitates interactions between research groups of its member and partner institutions and provides an avenue for developing and fostering collaborations, joint projects, and information exchange. Members of CQE are focused on developing new ways of understanding and exploiting the laws of quantum mechanics, the fundamental yet counterintuitive theory that governs nature at its smallest scales. The overarching aim is to apply research innovations to develop radically new types of devices, materials, and computing techniques. 

10. University of Sydney — Australia

The University of Sydney focuses its quantum science group on addressing the most challenging problems of quantum physics and leveraging these insights to build new technologies. Activities range from fundamental physics and quantum information science through to technology development and incorporate both atomic and condensed matter systems. The scientific pursuits are complemented by deep industry engagement and entrepreneurial activities.

11. Quantum Applications and Research Laboratory at LMU Munich (QAR-Lab)

Preparing students for a future with Quantum Technology is critical for QAR-Lab . The lab expects quantum computing (QC) to perform complex operations that would now have been possible before and will find solutions to traditional problems in shorter times. The Munich-based team of researchers plan to take advantage of the endless possibilities of QC to solve concrete practical problems, from route planning to machine learning, by programming a quantum computer.

12. University of Innsbruck – Quantum Information & Computation

Researchers at the University of Innsbruck’s Quantum Information and Computation department study models for quantum information processing and fundamental aspects of quantum information theory. The focus of their research is the theory of measurement-based quantum computation , which has resulted in a new and more thorough understanding of many-body entanglement as resource, and applications in quantum communication, quantum error correction, and quantum algorithms. As one of the most prominent quantum computing universities, their researchers work on quantum phenomena in bio-molecular systems, relativistic systems, and study the role of quantum mechanics for autonomous and adaptive systems.

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TQI Summary

We came to the end of our journey through quantum computing universities. To sum it up, Quantum computing institutes and unis are gaining much more attention in the quantum computing world, as more and more young prospects are seeking knowledge in this area. Finally, we think that before mentioned universities can provide them with everything they want.

For more market insights, check out our latest quantum computing news here .

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Quantum Computing

Quantum computing promises to be the next paradigm of computing, harnessing the principles of quantum physics to perform computations and conduct tasks impossible for classical architectures. Today, researchers in academia and industry rapidly advance the field by designing new hardware, software, and algorithms that bring quantum computers closer to their great potential for unlocking new knowledge in physics, chemistry, cryptography, and other fields.

UChicago CS boasts many faculty, research groups, and students engaged at the frontier of this groundbreaking technology, exploring new ways of programming, designing, and teaching about quantum computers. The Enabling Practical-Scale Quantum Computing (EPiQC) collaboration, funded by an NSF Expedition in Computing grant and led by UChicago CS Professor Fred Chong, advances the abilities of near-term quantum computers. The department also benefits from deep connections with the Chicago Quantum Exchange, the National Quantum Information Science Research Centers at Argonne and Fermilab, and companies such as IBM and Intel.

Quantum Computing Research and Education

Enabling practical-scale quantum computing (epiqc).

Launched in 2018 with a $10 million “Expeditions in Computing” grant from the National Science Foundation, the multi-institutional EPiQC collaboration seeks to narrow the gap to quantum computers capable of unprecedented feats. Quantum machines may soon be capable of performing calculations in chemistry, physics, and other fields that are extremely difficult or even impossible for today’s computers. The EPiQC mission is to develop new algorithms, software, and machine designs tailored to key properties of quantum device technologies with 100 to 1000 quantum bits — the scale researchers expect to reach over the next decade.

EPiQC is led by Fred Chong, Seymour Goodman Professor of Computer Science at UChicago, and includes collaborators from Duke, MIT, UCSB, Princeton, Argonne, Carnegie Mellon, and Georgia Tech. Faculty and student researchers in EPiQc have received numerous conference best paper and IEEE Top Picks awards, fellowships in industry, and started businesses in the emerging quantum sector. The collaboration also lays the foundation for tomorrow’s quantum computing experts, with innovative curricula, online courses, and museum exhibits reaching students from kindergarten through graduate school.

First-Year PhD Student Co-Authors Outstanding Paper Award Winner at TQC 2022

Three epiqc papers chosen by ieee micro for annual top picks awards, university of chicago and uiuc lead new quantum education program, the uchicago quantum community, chicago quantum exchange, staq: software-tailored architectures for quantum co-design, polsky center for entrepreneurship and innovation, designing the future of quantum computing.

• Seymour Goodman Professor of Computer Science
• Lead Principal Investigator, EPiQC
• Chief Scientist for Quantum Software, ColdQuanta

Fred Chong is the Seymour Goodman Professor in the Department of Computer Science at the University of Chicago and the Chief Scientist for Quantum Software at ColdQuanta. He is also Lead Principal Investigator for the EPiQC Project (Enabling Practical-scale Quantum Computing), an NSF Expedition in Computing. Chong is a member of the National Quantum Advisory Committee (NQIAC) which provides advice to the President and Secretary of Energy on the National Quantum Initiative Program. In 2020, he co-founded Super.tech, a quantum software company, which was acquired by ColdQuanta in 2022. Chong received his Ph.D. from MIT in 1996 and was a faculty member and Chancellor’s fellow at UC Davis from 1997-2005. He was also a Professor of Computer Science, Director of Computer Engineering, and Director of the Greenscale Center for Energy-Efficient Computing at UCSB from 2005-2015. He is a recipient of the NSF CAREER award, the Intel Outstanding Researcher Award , and 13 best paper awards. His research interests include emerging technologies for computing, quantum computing, multicore and embedded architectures, computer security, and sustainable computing. Prof. Chong has been funded by NSF, DOE, Intel, Google, AFOSR, IARPA, DARPA, Mitsubishi, Altera and Xilinx. He has led or co-led over $40M in awarded research, and been co-PI on an additional $41M.

William Fefferman

• Assistant Professor of Computer Science

I am an Assistant Professor in the computer science department at the University of Chicago. Previously, I held research positions at the University of California at Berkeley, advised by Umesh Vazirani, and in QuICS, at the University of Maryland/NIST. I received my Ph.D. in computer science in the Department of Computer and Mathematical Sciences and the Institute for Quantum Information and Matter at Caltech, co-advised by Alexei Kitaev and Chris Umans.

Diana Franklin

• Associate Professor of Computer Science

Diana Franklin is a Research Associate Professor in Computer Science and Director of Computer Science Education at UChicago STEM Education. She leads the CANON (Computing for ANyONe) research labs, currently consisting of four projects involving computer science education involving students ranging from preK through university. She is the lead PI for quantum computing education for EPiQC, an NSF expedition in computing. Her research agenda explores how to create curriculum and computing environments in ways that reach broad audiences.

Robert Rand

I am an Assistant Professor of Computer Science, part of the  Programming Languages Research Group  and the  Chicago Quantum Exchange . My main interest is in applying techniques from programming languages and formal verification to the domain of quantum computation.

Quantum Computing News & Events

Fred chong receives quantrell award for excellence in teaching, non-unital noise adds a new wrinkle to the quantum supremacy debate, argonne scientists use ai to identify new materials for carbon capture, new research unites quantum engineering and artificial intelligence, group from uchicago cs to present four papers at most prestigious international quantum conference, uchicago scientists make new discovery proving entanglement is responsible for computational hardness in quantum systems, virtual bakery game serves up both cupcakes and quantum concepts for k-12 students, assistant professor robert rand receives air force young investigator grant, prof. fred chong reappointed to national quantum initiative advisory committee, professor fred chong named ieee fellow, associate professor diana franklin named acm distinguished member, alumnus pranav gokhale named to crain’s 40 under 40.

Harvard Launches PhD in Quantum Science and Engineering

Drawing on world-class research community, program will prepare leaders of the ‘quantum revolution’.

Harvard University today announced one of the world’s first PhD programs in Quantum Science and Engineering, a new intellectual discipline at the nexus of physics, chemistry, computer science and electrical engineering with the promise to profoundly transform the way we acquire, process and communicate information and interact with the world around us.

The University is already home to a robust quantum science and engineering research community, organized under the Harvard Quantum Initiative . With the launch of the PhD program, Harvard is making the next needed commitment to provide the foundational education for the next generation of innovators and leaders who will push the boundaries of knowledge and transform quantum science and engineering into useful systems, devices and applications. 

“The new PhD program is designed to equip students with the appropriate experimental and theoretical education that reflects the nuanced intellectual approaches brought by both the sciences and engineering,” said faculty co-director Evelyn Hu , Tarr-Coyne Professor of Applied Physics and of Electrical at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS). “The core curriculum dramatically reduces the time to basic quantum proficiency for a community of students who will be the future innovators, researchers and educators in quantum science and engineering.”

“Quantum science and engineering is not just a hybrid of subjects from different disciplines, but an important new area of study in its own right,” said faculty co-director John Doyle , Henry B. Silsbee Professor of Physics. “A Ph.D. program is necessary and foundational to the development of this new discipline.”

Quantum science and engineering is not just a hybrid of subjects from different disciplines, but an important new area of study in its own right.

“America’s continued success leading the quantum revolution depends on accelerating the next generation of talent,” said Dr. Charles Tahan, Assistant Director for Quantum Information Science at the White House Office of Science and Technology Policy and Director of the National Quantum Coordination Office. “It’s nice to see that a key component of Harvard’s education strategy is optimizing how core quantum-relevant concepts are taught.”

The University is also finalizing plans for the comprehensive renovation of a campus building into a new state-of-the-art quantum hub – a shared resource for the quantum community with instructional and research labs, spaces for seminars and workshops, and places for students, faculty, and visiting researchers and collaborators to meet and convene. Harvard’s quantum headquarters will integrate the educational, research, and translational aspects of the diverse field of quantum science and engineering in an architecturally cohesive way. This critical element of Harvard’s quantum strategy was made possible by generous gifts from Stacey L. and David E. Goel ‘93 and several other alumni .

“Existing technologies are reaching the limit of their capacity and cannot drive the innovation we need for the future, specifically in areas like semiconductors and the life sciences,” said David Goel, co-founder and managing general partner of Waltham, Mass.-based Matrix Capital Management Company, LP and one of Harvard’s most ardent supporters. “Quantum is an enabler, providing a multiplier effect on a logarithmic scale. It is a catalyst that drives scientific revolutions and epoch-making paradigm shifts.”

“Harvard is making significant institutional investments in its quantum enterprise and in the creation of a new field,” said Science Division Dean Christopher Stubbs , Samuel C. Moncher Professor of Physics and of Astronomy. Stubbs added that several active searches are underway to broaden Harvard’s faculty strength in this domain, and current faculty are building innovative partnerships around quantum research with industry.

“An incredible foundation has been laid in quantum, and we are now at an inflection point to accelerate that activity,” said SEAS Dean Frank Doyle , John A. and Elizabeth S. Armstrong Professor of Engineering and Applied Sciences.

An incredible foundation has been laid in quantum, and we are now at an inflection point to accelerate that activity.

To enable opportunities to move from basic to applied research to translating ideas into products, Doyle described a vision for “integrated partnerships where we invite partners from the private sector to be embedded on the campus to learn from the researchers in our labs, and where our faculty connect to the private sector and national labs to learn about the cutting-edge applications, as well as help translate basic research into useful tools for society.”

Harvard will admit the first cohort of PhD candidates in Fall 2022 and anticipates enrolling 35 to 40 students in the program. Participating faculty are drawn from physics and chemistry in Harvard’s Division of Science and applied physics, electrical engineering, and computer science in SEAS.

Candidates interested in Harvard’s PhD in Quantum Science and Engineering can learn more about the program philosophy, curriculum, and requirements here .

“This cross disciplinary PhD program will prepare our students to become the leaders and innovators in the emerging field of quantum science and engineering” said Emma Dench, dean of the Graduate School of Arts and Sciences. “Harvard’s interdisciplinary strength and intellectual resources make it the perfect place for them to develop their ideas, grow as scholars, and make discoveries that will change the world.”

Harvard has a long history of leadership in quantum science and engineering. Theoretical physicist and 2005 Nobel laureate Roy Glauber is widely considered the founding father of quantum optics, and 1989 Nobel laureate Norman Ramsey pioneered much of the experimental foundation of quantum science.

Today, Harvard experimental research groups are among the leaders worldwide in areas such as quantum simulations, metrology, quantum communications and computation, and are complemented by strong theoretical groups in computer science, physics, and chemistry.

Topics: Quantum Engineering

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We have 74 quantum computing PhD Projects, Programmes & Scholarships

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quantum computing PhD Projects, Programmes & Scholarships

Cdt-qte: space-time-varying superconducting surfaces for enhanced efficiency quantum computing and quantum wave processing applications, phd research project.

PhD Research Projects are advertised opportunities to examine a pre-defined topic or answer a stated research question. Some projects may also provide scope for you to propose your own ideas and approaches.

Competition Funded PhD Project (Students Worldwide)

This project is in competition for funding with other projects. Usually the project which receives the best applicant will be successful. Unsuccessful projects may still go ahead as self-funded opportunities. Applications for the project are welcome from all suitably qualified candidates, but potential funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

Quantum Computing Foundations, Algorithms, and Complexity

Funded phd project (uk students only).

This research project has funding attached. It is only available to UK citizens or those who have been resident in the UK for a period of 3 years or more. Some projects, which are funded by charities or by the universities themselves may have more stringent restrictions.

Quantum Computing platform with atomic qubits

Simulation-based quantum machine learning for advancing cyber security, self-funded phd students only.

This project does not have funding attached. You will need to have your own means of paying fees and living costs and / or seek separate funding from student finance, charities or trusts.

PhD position in Time-bin ion-photon entanglement for scalable quantum computing

Cdt-qte: integrated photonics for ion-trap quantum computing, cdt-qte: optimisation of antiresonant hollow core fibres for quantum computing, communications and memories, on the development of a framework for quantum resistant distributed ledger technologies, funded phd project (students worldwide).

This project has funding attached, subject to eligibility criteria. Applications for the project are welcome from all suitably qualified candidates, but its funding may be restricted to a limited set of nationalities. You should check the project and department details for more information.

Quantum Machine Learning for Sustainable Energy Optimisation

Quantum reservoir computing for artificial intelligence (ref: sci24-az2), phd studentship in computer science: quantum digital signatures and quantum formal methods, innovating iot security through quantum metamaterials and artificial intelligence, phd studentship in computer science: applying quantum foundations for quantum advantage, rare-earth based photonic devices for quantum information processing, cdt-qte: interfacing semiconductor quantum dots with alkali-atom-based quantum memories.

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Filtering Results

Harvard Launches PhD in Quantum Science and Engineering

Program will prepare leaders of the ‘quantum revolution’

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CAMBRIDGE, MA (Monday, April 26, 2021) – Harvard University today announced one of the world’s first PhD programs in Quantum Science and Engineering , a new intellectual discipline at the nexus of physics, chemistry, computer science, and electrical engineering with the promise to profoundly transform the way we acquire, process and communicate information and interact with the world around us.

“This cross-disciplinary PhD program will prepare our students to become the leaders and innovators in the emerging field of quantum science and engineering,” said Emma Dench, dean of the Graduate School of Arts and Sciences and McLean Professor of Ancient and Modern History and of the Classics. “Harvard’s interdisciplinary strength and intellectual resources make it the perfect place for them to develop their ideas, grow as scholars, and make discoveries that will change the world.”

The University is already home to a robust quantum science and engineering research community, organized under the Harvard Quantum Initiative . With the launch of the PhD program, Harvard is making the next needed commitment to provide foundational education for the next generation of innovators and leaders who will push the boundaries of knowledge and transform quantum science and engineering into useful systems, devices, and applications. 

“The new PhD program is designed to equip students with the appropriate experimental and theoretical education that reflects the nuanced intellectual approaches brought by both the sciences and engineering,” said faculty co-director Evelyn Hu , Tarr-Coyne Professor of Applied Physics and of Electrical Engineering at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS). “The core curriculum dramatically reduces the time to basic quantum proficiency for a community of students who will be the future innovators, researchers, and educators in quantum science and engineering.”

“Quantum science and engineering is not just a hybrid of subjects from different disciplines, but an important new area of study in its own right,” said faculty co-director John Doyle , Henry B. Silsbee Professor of Physics. “A PhD program is necessary and foundational to the development of this new discipline.”

“America’s continued success leading the quantum revolution depends on accelerating the next generation of talent,” said Dr. Charles Tahan, assistant director for quantum information science at the White House Office of Science and Technology Policy and director of the National Quantum Coordination Office. “It’s nice to see that a key component of Harvard’s education strategy is optimizing how core quantum-relevant concepts are taught.”

The University is also finalizing plans for the comprehensive renovation of a campus building into a new state-of-the-art quantum hub—a shared resource for the quantum community with instructional and research labs, spaces for seminars and workshops, and places for students, faculty, and visiting researchers and collaborators to meet and convene. Harvard’s quantum headquarters will integrate the educational, research, and translational aspects of the diverse field of quantum science and engineering in an architecturally cohesive way. This critical element of Harvard’s quantum strategy was made possible by generous gifts from Stacey L. and David E. Goel ‘93 and several other alumni.

“Existing technologies are reaching the limit of their capacity and cannot drive the innovation we need for the future, specifically in areas like semiconductors and the life sciences,” said Goel, co-founder and managing general partner of Waltham, Massachusetts-based Matrix Capital Management Company, LP, and one of Harvard’s most ardent supporters. “Quantum is an enabler, providing a multiplier effect on a logarithmic scale. It is a catalyst that drives scientific revolutions and epoch-making paradigm shifts.”

“Harvard is making significant institutional investments in its quantum enterprise and in the creation of a new field,” said Science Division Dean Christopher Stubbs , Samuel C. Moncher Professor of Physics and of Astronomy. Stubbs added that several active searches are underway to broaden Harvard’s faculty strength in this domain, and current faculty are building innovative partnerships with industry around quantum research.

“An incredible foundation has been laid in quantum, and we are now at an inflection point to accelerate that activity,” said SEAS Dean Frank Doyle , John A. and Elizabeth S. Armstrong Professor of Engineering and Applied Sciences.

To enable opportunities to move from basic to applied research to translating ideas into products, Doyle described a vision for “integrated partnerships where we invite partners from the private sector to be embedded on the campus to learn from the researchers in our labs, and where our faculty connect to the private sector and national labs to learn about the cutting-edge applications and to help translate basic research into useful tools for society.”

Harvard will admit the first cohort of PhD candidates in fall 2022 and anticipates enrolling 35 to 40 students in the program. Participating faculty are drawn from physics and chemistry in Harvard’s Division of Science and in applied physics, electrical engineering, and computer science at SEAS.

The Graduate School of Arts and Sciences provides more information on Harvard’s PhD in Quantum Science and Engineering , including the program philosophy, curriculum, and requirements.

Harvard has a long history of leadership in quantum science and engineering. Theoretical physicist and 2005 Nobel laureate Roy Glauber is widely considered the founding father of quantum optics, and 1989 Nobel laureate Norman Ramsey pioneered much of the experimental foundation of quantum science.

Today, Harvard experimental research groups are among the leaders worldwide in areas such as quantum simulations, metrology, and quantum communications and computation, and are complemented by strong theoretical groups in computer science, physics, and chemistry.

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Our work focuses on developing the next substrate of computing, communication and sensing. We work all the way from new materials to superconducting devices to quantum computers to theory.

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GRADUATE RESEARCH

Quantum Computing

Doctoral student research in quantum computing.

Quantum computing has emerged as an alternative computational model. Realizing the practical acceleration using a Noisy Intermediate-Scale Quantum computer is one of the most important problems of our century. While prototypes are being built now, moving computations to a fully-functional fault-tolerant quantum computer still faces many technical hurdles.

Key challenges are scalability, i.e., the ability to coherently manipulate information stored in a multi-qubit system, and devising efficient algorithmic solutions that take advantage of quantum hardware. At Rice CS, we cover multiple subfields of quantum information science and computing including (hybrid/variational) quantum algorithms and quantum characterization/verification.

Faculty members leading research in Quantum Computing are as follows:

• Nai-Hui Chia  
• Anastasios Kyrillidis
• Tirthak Patel

The videos below represent current student research projects. 

Graduate Research Videos in Quantitative Computing

Quantum Computing

Quantum computing aims to exploit a quantum mechanical representation of information to enable new computers and new communication devices capable of performing tasks that would otherwise be infeasible. In particular, it studies the implications of quantum mechanics for computational complexity, cryptographic security, data transmission, and other aspects of information processing.

Quantum computers promise to address computational challenges with significant applications. For example, quantum simulation can efficiently determine properties of chemical systems and models of condensed matter physics, with potentially revolutionary impact on problems such as drug design and the development of new materials. Quantum computers also enable attacks on classically-secure cryptosystems, motivating the design of novel cryptographic primitives that are secure against quantum attacks. Furthermore, quantum information provides tools to study diverse topics including condensed matter physics, quantum gravity, and the foundations of quantum mechanics through the lens of information and computation.

Ongoing work also applies the principles of classical computer science to the design of quantum computers. Topics under investigation include the development of quantum algorithms, programming languages, compilers, and hardware architectures that offer robust, scalable advantages over classical devices.

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Field expected to usher in era of super-fast computing and innovation across a range of fields

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In the middle of the 20th century, mathematicians, physicists, and engineers at Harvard began work that would lay the foundations for a new field of study, the applications of which would change the world in ways unimaginable at the time. These pioneering computer scientists helped develop the theory and technology that would usher in the digital age.

Harvard is once again taking a leading role in a scientific and technological revolution — this time in the field of quantum science and engineering. Today, the University launched one of the world’s first Ph.D. programs in the subject, providing the foundational education for the next generation of innovators and leaders who will transform quantum science and engineering into next-level systems, devices, and applications.

The new degree is the latest step in the University’s commitment to moving forward as both a leader in research and an innovator in teaching in the field of quantum science and engineering. Harvard launched the Harvard Quantum Initiative in 2018 to foster and grow this new scientific community. And additional future plans call for the creation of a quantum hub on campus to help further integrate efforts and encourage collaboration.

“This is a pivotal time for quantum science and engineering at Harvard,” said President Larry Bacow. “With institutional collaborators including MIT and industry partners, and the support of generous donors, we are making extraordinary progress in discovery and innovation. Our faculty and students are driving progress that will reshape our world through quantum computing, networking, cryptography, materials, and sensing, as well as emerging areas of promise that will yield advances none of us can yet imagine.”

“This cross disciplinary Ph.D. program will prepare our students to become the leaders and innovators in the emerging field of quantum science and engineering,” said Emma Dench, dean of the Graduate School of Arts and Sciences. “Harvard’s interdisciplinary strength and intellectual resources make it the perfect place for them to develop their ideas, grow as scholars, and make discoveries that will change the world.”

At the nexus of physics, chemistry, computer science, and electrical engineering, quantum science and technology promises to profoundly change the way we acquire, process, and communicate information. Imagine a computer that could sequence a person’s genome in a matter of seconds or an un-hackable communications system that could make data breaches a thing of the past. Quantum technology will usher in game-changing innovations in health care, infrastructure, security, drug development, climate-change prediction, machine learning, financial services, and more.

Researchers excited and detected spin waves in a quantum Hall ferromagnet, spending them through the insulating material like waves in a pond.

The University is building partnerships with government agencies and national laboratories to advance quantum technologies and educate the next generation of quantum scientists. Harvard researchers will play a major role in the Department of Energy’s (DOE) Quantum Information Science (QIS) Research Centers, aimed at bolstering the nation’s global competitiveness and security. As part of the centers, Harvard researchers will:

• develop and study the next generation of quantum materials that are resilient, controllable, and scalable;
• use quantum-sensing techniques to explore the exotic properties of quantum materials for applications in numerous quantum technologies;
• construct a quantum simulator out of ultra-cold molecules to attack important problems in materials development and test the performance of new types of quantum computation;
• develop topological quantum materials for manipulating, transferring, and storing information for quantum computers and sensors;
• investigate how quantum computers can meaningfully speed up answers to real-world scientific problems and create new tools to quantify this advantage and performance.

In partnership with the National Science Foundation (NSF) and the White House Office of Science and Technology Policy (OSTP), the Harvard University Center for Integrated Quantum Materials (CIQM) has helped develop curriculum and educator activities that will help K‒12 students engage with quantum information science. CIQM is also collaborating with the Learning Center for the Deaf to create quantum science terms in American Sign Language .

“Breakthrough research happens when you create the right community of scholars around the right ideas at the right time,” said Claudine Gay, the Edgerley Family Dean of the Harvard Faculty of Arts and Sciences. “The Harvard Quantum Initiative builds on Harvard’s historic strength in the core disciplines of quantum science by drawing together cross-cutting faculty talent into a community committed to thinking broadly and boldly about the many problems where quantum innovations may offer a solution. This new approach to quantum science will open the way for new partnerships to advance the field, but perhaps even more importantly, it promises to make Harvard the training ground for the next generation of breakthrough scientists who could change the way we live and work.”

“Harvard’s missions are to excel at education and research, and these are closely related,” said John Doyle, the Henry B. Silsbee Professor of Physics and co-director of HQI. “Being at — and sometimes defining — the frontier of research keeps our education vibrant and meaningful to students. We aim to teach a broad range of students to think about the physical world in this new, quantum way as this is crucial to creating a strong community of future leaders in science and engineering. Tight focus on both research and teaching in quantum will develop Harvard into the leading institution in this area and keep the country at the forefront of this critical area of knowledge.”

Quantum at Harvard: ‘A game-changing’ moment

A conversation with SEAS Dean Frank Doyle, John A. and Elizabeth S. Armstrong Professor of Engineering and Applied Sciences, and Science Division Dean Christopher Stubbs, Samuel C. Moncher Professor of Physics and of Astronomy.

Transcript:

Doyle: We’re at a game changing point in science and technology. We’re poised to enable translation breakthroughs in our applications of that understanding to broadly stated information science, so networking, signal processing, encryption, communications, computing and simulation.

Stubbs: What we’re talking about, looking to the future, exploits the really spooky parts of quantum mechanics, about the relationship of information in spatially separated systems and trying to harness that technologically and bringing it to bear on problems in networking, computing, and sensing systems.

I think we’re learning more about the way the world works every day, and we’re interested here at Harvard in knitting that understanding together across different traditionally separated fields and pulling together an integrated effort that pulls together, computer science, electrical engineering, physics systems engineering, and tries to use these to build new tools to make life better for everybody.

Doyle: Chris, I completely agree, and I would say that one thing, I recognize deeply as the dean on the engineering side is that foundations are critical to achieving success in the domain of innovation or translation, whatever the application space might be. We have to have that core body of knowledge supporting and enabling really a continuum from basic science through applied science, ultimately to engineering. I would also point to the fact that we are modestly scaled compared to some of our peers, which I think empowers us with agility and nimbleness that allows us to quickly assemble the teams that cross the spectrum of these disciplines that we need to harness, and that’s a real strength here at Harvard as well.

Stubbs: I would say we’re making significant institutional investments in this enterprise. We’ve identified a building, working in partnership across the university, that’s going to be put to use for this activity, with new labs, new teaching labs. We will fill that space with colleagues that we intend to bring to campus to strengthen our faculty in this domain. We’re building a strong and vibrant educational program. And I think an important element to include here is that we see this as a way to reach all the way into applications at scale, and we’re building partnerships with industrial partners, ranging from startups-sized companies to major national corporations that are going to have the ability to bring these ideas to bear at scale and impact people’s lives in a positive way.

Doyle: I would say that this opportunity has tremendous potential across a wide array of fields and applications, from more traditional engineering fields like communications, cybersecurity, network science, but across an even broader array of fields including finance (thinking about the new kinds of algorithms that are going to power the future of things like trading and stress testing the market); precision medicine; the quantum principles that we’re going to be able to leverage in devices that will now interrogate at unprecedented scale — spatial and temporal — to bring information back that we can act upon. So it’s virtually a limitless horizon of application opportunities out there.

Stubbs: We’re fortunate in the Boston area to have another university down the road, whose initials are MIT, with which, in particular in this technical domain, we have strong existing partnerships among the faculty. We view this as moving forward arm-in-arm with sister institutions in this region to establish Boston as one of the premier centers in the nation for both innovation, education, and application of this new technology.

Doyle: Our faculties partnering across Harvard and MIT have been doing this for literally decades. So there’s an incredible organic foundation that has been laid in the Greater Cambridge, Greater Boston space that we’re now turning an inflection point to accelerate that activity.

The field of quantum really opens up some exciting partnership opportunities, which we’re exploring with great passion. The notion that the continuum from the university and basic research and applied research, through to getting products in the market, through getting operational networks, operational systems is one that truly is a continuum. So there has to be integrated partnerships, where we invite partners in the private sector in to be embedded on the campus to learn from the researchers in our labs, where we embed our faculty out in the private sector in national labs to learn about the cutting edge applications that need to drive and fuel the research taking place back on the campus. So I really view this as a wonderful new opportunity to rethink the nature of how the private sector and the academy partner to enable the ultimate translation into products, technologies that are going to benefit mankind.

Edited for length.

The University’s location within the Greater Boston ecosystem of innovation and discovery is one of its greatest strengths.

A recent collaboration between Brigham and Women’s Hospital, Harvard Medical School, and University quantum physicists resulted in a proof-of-concept algorithm to dramatically speed up the analysis of nuclear magnetic resonance (NNMR) readings to identify biomarkers of specific diseases and disorders, reducing the process from days to just minutes.

A multidisciplinary team of electrical engineers and physicists from Harvard and MIT are building the infrastructure for tomorrow’s quantum internet , including quantum repeaters, quantum memory storage, and quantum networking nodes, and developing the key technologies to connect quantum processors over local and global scales.

“We are moving forward arm in arm with sister institutions in this region, most notably MIT, to establish Boston as one of the premier centers in the nation for both education and developing technologies that we anticipate will have significant impact on society,” said Christopher Stubbs, science division dean and Samuel C. Moncher Professor of Physics and of Astronomy.

  “We are excited to see the ever-growing opportunities for collaboration in quantum science and engineering at Harvard, in the Boston community, and beyond,” said Evelyn L. Hu, the Tarr-Coyne Professor of Electrical Engineering and Applied Science at SEAS and co-director of the Harvard Quantum Initiative. “Harvard is committed to sustaining that growth and fostering a strong community of students, faculty, and inventors, both locally and nationwide.”

Fiber-optical networks, the backbone of the internet, rely on high-fidelity information conversion from electrical to the optical domain. The researchers combined the best optical material with innovative nanofabrication and design approaches, to realize, energy-efficient, high-speed, low-loss, electro-optic converters for quantum and classical communications.

“Building a vibrant community and ecosystem is essential for bringing the benefits of quantum research to different fields of science and society,” said Mikhail Lukin, George Vasmer Leverett Professor of Physics and co-director of HQI. “Quantum at Harvard aims to integrate unique strengths of university research groups, government labs, established companies, and startups to not only advance foundational quantum science and engineering but also to build and to enable broad access to practical quantum systems.”

To facilitate those collaborations, the University is finalizing plans for the comprehensive renovation of an existing campus building into a new quantum hub — a shared resource for the quantum community with instructional and research labs, seminar and workshop spaces, meeting spaces for students and faculty, and space for visiting researchers and collaborators. The quantum headquarters will integrate the educational, research, and translational aspects of the diverse field of quantum science and engineering in an architecturally cohesive way.

This critical element of Harvard’s quantum strategy was made possible by a generous gift from Stacey L. and David E. Goel ’93 and gifts from several other alumni who stepped forward to support HQI. David Goel, co-founder and managing general partner of Waltham, Mass.-based Matrix Capital Management Co. and one of Harvard’s most ardent supporters, said his gift was inspired both by recognizing Harvard’s “intellectual dynamism and leadership in quantum” and a sense of the utmost urgency to pursue opportunities in this field. “Our existing technologies are reaching the limit of their capacity and cannot drive the innovation we need for the future, specifically in areas like semiconductors, technology, and the life sciences. Quantum is an enabler, providing a multiplier effect on a logarithmic scale. It is a catalyst that drives the kinds of scientific revolutions and epoch-making paradigm shifts.”

Electrodes stretch diamond strings to increase the frequency of atomic vibrations to which an electron is sensitive, just like tightening a guitar string increases the frequency or pitch of the string. The tension quiets a qubit’s environment and improves memory from tens to several hundred nanoseconds, enough time to do many operations on a quantum chip.

Goel credits the academic leaders and their “commitment to ensuring that Harvard’s community will be at the forefront of the science that is already changing the world.”

The University is also building partnerships with industry partners, ranging from startups to major national corporations, that are preparing to bring quantum technologies to the public.

“An incredible foundation has been laid in quantum at Harvard, and we are now at an inflection point to accelerate that activity and build on the momentum that has already made Harvard a leader in the field,” said Frank Doyle, SEAS dean and John A. and Elizabeth S. Armstrong Professor of Engineering and Applied Sciences. “Research happening right now in Harvard labs is significantly advancing our understanding of quantum science and engineering and positioning us to make breathtaking new discoveries and industry-leading translation breakthroughs.”

To enable opportunities to move from basic to applied research to translating ideas into products, Doyle described a vision for “integrated partnerships where we invite partners from the private sector to be embedded on the campus to learn from the researchers in our labs and where our faculty connect to the private sector and national labs to learn about the cutting-edge applications, as well as help translate of basic research into useful tools for society.”

  “We are at the early stages of a technological transformation, similar or maybe even grander than the excitement and the promise that came with the birth of computer science — and Harvard is at the forefront,” Stubbs said.

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Best Doctorates in Quantum Computing: Top PhD Programs, Career Paths, and Salaries

After earning a master’s degree, most graduates set their sights on a doctoral degree or PhD. A PhD is the highest level of education, and earning this esteemed degree will skyrocket your employability potential, industry credibility, and salary range. In this article, we share the best PhDs in Quantum Computing and the expected PhD in Quantum Computing salary.

Besides being highly paid, this field of study offers many exciting opportunities to work with pioneering theory in quantum information technology. PhD in Quantum Computing students will participate in ground-breaking research and upon graduation will be eligible for the best quantum computing jobs in the tech industry.

Find your bootcamp match

What is a phd in quantum computing.

A PhD in Quantum Computing is the highest level of education for professionals in quantum technology. The degree takes four to six years to complete and covers different quantum computing theories, including quantum simulation, quantum sensing, quantum communication, and quantum information theory. The PhD degree facilitates advanced research and facilitates innovative discoveries.

How to Get Into a Quantum Computing PhD Program: Admission Requirements

The core requirements to get into a quantum computing PhD program are a master’s degree in computer science, math, physics, or a related field, a resume highlighting your work experience, letters of recommendation, and a GRE or GMAT score. Additional admission requirements include application fees, English proficiency test scores, transcripts, a statement of purpose, essays, and a high GPA.

Generally, these are the minimum PhD admission requirements, but the prerequisites can differ from school to school. You will find a detailed list of requirements on the selected school’s website.

PhD in Quantum Computing Admission Requirements

• Application form and fee
• Master’s degree in Physics, Computer Science, or a related field
• GRE, GMAT, and English proficiency test scores
• Two or three letters of recommendation
• Statement of purpose
• Transcripts

Quantum Computing PhD Acceptance Rates: How Hard Is It to Get Into a PhD Program in Quantum Computing?

It is extremely hard to get into a PhD program in quantum computing. Quantum computing is difficult to learn, and a PhD demands a lot of attention to detail, research, and one-on-one interactions between students and professors. That means that universities maintain small class sizes to ensure student success.

The Council of Graduate Schools survey indicates that the overall PhD acceptance rate is 22.3 percent . Public universities accept approximately 26.4 percent of applicants, while private universities accept 16.3 percent of applicants. These numbers will vary by school. For example, the University of South Carolina admits 10-15 percent of its PhD applicants , and Harvard University admits approximately seven percent of the doctoral degree applicants.

How to Get Into the Best Universities

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Best PhDs in Quantum Computing: In Brief

Best Universities for Quantum Computing PhDs: Where to Get a PhD in Quantum Computing

The best PhD quantum computing programs offer quality instruction in advanced quantum computing topics, research work, and unique assistantship opportunities. Some institutions also offer the flexibility of online learning.  Keep reading for an overview of the best quantum computing PhD programs, including admission requirements and funding opportunities.

California Institute of Technology , also known as Caltech, is a private institution known for its research in science and engineering. The university was founded in 1891 and offers a wide range of graduate options, including astrophysics, medical engineering, neurobiology, chemistry, applied mechanics, and computing and mathematical sciences.

Caltech is currently involved in several research initiatives where students can contribute through assistantships or coursework.

PhD in Computing and Mathematical Sciences

A PhD in Computing and Mathematical Sciences accommodates students with a background in applied math, economics, electrical engineering, physical sciences, and computer science. You will delve into a wide range of topics such as algorithms, machine learning, signal processing, statistics, data interpretation, and laws of quantum mechanics.

You will participate in quantum and information computation research , where you will learn from world-class faculty and contribute to ongoing research. Additionally, you will select a research advisor who will guide you through the ins and outs of your dissertation.

PhD in Computing and Mathematical Sciences Overview

• Program Length: Six years
• Acceptance Rate: 7%
• Tuition and Fees: $58,467/year
• PhD Funding Opportunities: Assistantships, external fellowship, institute fellowship, parent support program, and federal, institute, and short-term emergency loans

PhD in Computing and Mathematical Sciences Admission Requirements

• A bachelor’s degree or equivalent
• Official and unofficial transcripts
• Three letters of recommendation
• A statement of purpose
• An updated resume
• English proficiency test scores
• $100 application fee or fee waiver form

Capitol Technology University was founded in 1927 and is a premier institution for STEM programs. The graduate school is known for its programs in information technology, business, computer science, and engineering. Capital Tech offers twenty-nine graduate programs, which are all online.

PhD in Quantum Computing

The PhD in Quantum Computing prepares you for many careers. Upon graduation, you can work as a quantum computing director, senior quantum systems engineer, or director of financial quantum computing. The quantum computing industry is growing rapidly, and Capitol aims to equip PhD students with the vital skills that meet industry needs. 

The curriculum features six-credit coursework that takes you from the foundational stages of a dissertation thesis to completion. Students can select between a thesis and publication option to meet graduation requirements. Capitol Tech PhD graduates demonstrate mastery in quantum computing, theoretical basis, and practical applications, as well as proficiency in research.

PhD in Quantum Computing Overview

• Program Length: Two to four years
• Acceptance Rate: N/A
• Tuition and Fees: $933/credit
• PhD Funding Opportunities: Tuition discounts, loans, assistantships, veteran benefits, scholarships
• Master’s in relevant field
• Resume demonstrating at least five years of work experience
• Two recommendation forms
• 1000 to 2000-word essay
• $100 application fee

Founded in 1636, Harvard University is one of the best private Ivy League universities worldwide. The university is known for its commitment to research, high-quality education, and a strong academic community. Harvard's graduate school offers over 50 graduate programs and guarantees five years of funding for all PhD students.

PhD in Quantum Science and Engineering

You will complete this PhD under the Harvard Quantum Initiative , a program only available for PhD students. The degree prepares you for diverse research careers that require knowledge of quantum mechanics methods. 

You will cover quantum simulation, sensing, and computation. PhD students begin research work in their first year through lab rotations and engage in extensive mentoring programs. Communication training is also a part of the program.

PhD in Quantum Science and Engineering Overview

• Program Length: Five years
• Tuition and Fees: $52,456/year for the first two years of study                  
• PhD Funding Opportunities: Fellowships, grants, research assistantships, traineeships, stipends, federal student aid, loans, veteran benefits

PhD in Quantum Science and Engineering Admission Requirements

• Bachelor’s degree in Physics, Mathematics, Chemistry, Computer Science, or a related field
• $105 application fee

Massachusetts Institute of Technology is a private land-grant university founded in 1861. The university is known for its research contributions across various industries. It prioritizes education, research, and innovation. MIT's department of physics contributes to innovation by offering doctoral programs in statistics, data science, and physics.

PhD in Physics, Statistics, and Data Science

At the MIT Physics Department, PhD students will learn probability theory, modeling with machine learning, natural language programming, statistical physics, and linear algebra. As an MIT PhD student, you will acquire essential research skills in probability, statistics, computation, and data analysis, and integrate these into your dissertation thesis. You can choose from a wide selection of research areas and specialize in quantum information science.

PhD in Physics, Statistics, and Data Science Overview

• Program Length: 3-7 years, 5.6 years on average
• Acceptance Rate: 9%
• Tuition and Fees: $27,755/term        
• PhD Funding Opportunities: Fellowships, research assistantships, teaching assistantships

PhD in Physics, Statistics, Data Science Admission Requirement

• $75 application fee
• Unofficial transcripts
• 3-6 letters of recommendation
• Statement of objectives

Purdue University is a  public university founded in 1869 by the Indiana General Assembly. It was named after John Purdue, who contributed over $100,000 to the school’s establishment. Purdue has undergone many upgrades to become one of the leading research institutions worldwide.

Purdue upholds student-centered traditions and prides itself on a solid alumni network comprising former undergraduate and graduate students. Purdue’s graduate school offers over 160 programs. Graduate students have the opportunity to develop innovative projects in different areas, including business, technology, health care, and food consumption.

PhD in Physics                     

Purdue University’s Department of Physics and Astronomy maintains a commitment to producing highly-qualified scientists who thrive in the professional sector. Students will explore different courses and receive mentorship from over 50 faculty members, including members of the National Academy of Sciences.

The program offers many research areas, but you can specialize in quantum information science. This area of study allows you to conduct research in information theory, optical physics, and condensed matter systems. It also qualifies you as a member of the Purdue Quantum Science and Engineering Institute Research Group, where you will contribute to ongoing research at the university.

PhD in Physics Overview

• Program Length: Three to four years
• Acceptance Rate: 30%
• Tuition and Fees: $347.85/ credit (in state), $948.30/ credit (out of state)      
• PhD Funding Opportunities: Assistantships, fellowships, grants, loans, scholarships

PhD in Physics Admission Requirements

• Master’s degree in relevant field
• $60 application fee
• GRE scores (optional)
• Official transcripts

UC Berkeley is a renowned public research university located in sunny California. The university was founded in 1868 and is known for its high academic standards, unique undergraduate programs, and extensive academic offerings. 

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Graduate students at UC Berkeley can select from over 100 graduate degrees and various exchange programs. As a student, you will participate in innovative research while interacting with a diverse student community.

PhD in Physics

The physics department at UC Berkeley has designed this PhD program to provide students with a holistic learning experience. Once you demonstrate your competence to pursue the program, you will begin extensive coursework in quantum mechanics. 

The faculty mentors will advise you on the best quantum research programs before your preliminary exam. Once you pass the exam, you will start your research and submit progress reports until the last stage. Students complete the candidacy and defend their dissertation before a dignified thesis committee.

• Tuition and Fees: $5,721/semester
• PhD Funding Opportunities: Fellowships, federal student loans, scholarships
• Bachelor’s degree in relevant field
• $120 application fee
• 3.0 GPA scores
• Physics GRE test scores (optional)

The University of Chicago is among the leading research universities worldwide. It was founded in 1890 and is known for its state-of-the-art resources, numerous affiliations to innovators and award winners, and an exciting graduate life. Graduate students have access to many doctoral programs in the professional schools, including the Pritzker School of Molecular Engineering.

The Pritzker School of Molecular Engineering offers this degree to successful PhD applicants. This degree lets you interact with industry experts in quantum science. You will learn about fundamental and applied quantum science, explore courses that shape your future within the quantum computing industry, and receive valuable thesis advice from outstanding advisors.

To graduate, you must complete nine core, specialized, and elective courses. Additionally, you will complete the teaching assistantship at the university after approval from the Vice Dean for Education and Outreach and the Dean of Students. You can also apply for work at several quantum research firms like the Chicago Quantum Exchange.

• Tuition and Fees: $19,204/quarter   
• PhD Funding Opportunities: Fellowships, teaching assistantships, research assistantships
• Bachelor’s Degree in a STEM field
• $90 application fee

University of Maryland is a world-renowned public research university founded in 1856. The land-grant institution offers over 230 graduate programs and confers at least 2,800 degrees every year. UMD is known for its extensive research in various fields, including quantum computing, artificial intelligence and robotics, cybersecurity, and computational biology.

PhD in Computer Science

The program targets those looking to expand their knowledge in areas of computer science through research. You must understand computer science fundamentals and demonstrate your ability to engage in extensive research work. Selecting the quantum computing area of study allows you to delve into quantum mechanics for computational complexity, data transmission, information processing, and cryptographic security.

You will work with a world-class faculty to uncover innovations in quantum computers and how quantum computing principles apply to classical computers. The associated faculty currently investigates different topics, including programming languages, quantum algorithms, and hardware architectures. You can also apply for assistantships at the university’s new Quantum Startup Foundry.

PhD in Computer Science Overview

• Program Length: Four years
• Acceptance Rate: 22.8%
• Tuition and Fees: $768/credit (in state), $1,706/credit (out of state)
• PhD Funding Opportunities: Assistantship, fellowship, grants

PhD in Computer Science Admission Requirements

• GRE (optional)
• 3.5 GPA (recommended)

If you are interested in pursuing your quantum computing doctoral abroad, you should apply to the University of Oxford. The University of Oxford is a leading academic institution known for contributing to research and its rigorous academic programs. The university prides itself on years of solid history as one of the oldest universities worldwide, dating back to 1096.   

The university offers a wide range of degree programs, including over 300 graduate courses. PhD students also access many research resources, including dedicated research groups like Quantum Group .

Quantum computing research at the University of Oxford leans into the university’s rich history, combining prior computing milestones with current quantum computing principles. You will pursue a PhD in Computer Science, where you’ll pursue cutting-edge research as part of the Quantum Group, and specialize in quantum science. 

• Acceptance Rate: 18.5%
• Tuition and Fees: $10,766/ year (citizens), $35,670/year (international students)
• PhD Funding Opportunities: Loans, studentships, scholarships, teaching assistantships
• First-class or high second-class bachelor’s degree with honors and a master’s degree in a relevant field
• Detailed resume
• Letters of recommendation
• $93.70 application fee

The University of Waterloo began operations in 1957 and has transformed into a premier public research university. It is a large university, sitting on over 1,000 acres and with an undergraduate enrollment of 36,020 students. Students can select doctoral programs from a list of over 190 graduate programs, including actuarial science, civil engineering, computer science, and nanotechnology.

PhD in Computer Science (Quantum Information)

You will complete this doctoral degree at the Institute of Quantum Computing. Students who select the quantum information area of study explore topics such as quantum biology, nanoelectronics-based quantum information processing, optical quantum information, and quantum devices.

Upon graduation, you will have the expertise to lead and contribute to advanced quantum computing research projects.

PhD in Computer Science (Quantum Information) Overview

• Program Length: Four to five years
• Tuition and Fees: $2,254/term (citizens), $7,396/term (international students)
• PhD Funding Opportunities: Scholarships, university funding, grants, bursaries, loans, assistantships

PhD in Computer Science (Quantum Information) Admission Requirements

• Master’s in Physics with at least 75% standing
• $125 application fee
• Three reference letters
• English proficiency tests
• Letter of admission and study permit for international students

Can You Get a PhD in Quantum Computing Online?

Yes, you can get a PhD in Quantum Computing online. As technology continues to offer more flexibility, universities are adjusting their PhD learning formats, allowing students to complete these degrees at their pace and from desired locations. Below are the top five schools for an online PhD in Quantum Computing.

Best Online PhD Programs in Quantum Computing

How Long Does It Take to Get a PhD in Quantum Computing?

It takes four to seven years to get a PhD in Quantum Computing. Students must complete advanced quantum computing coursework, pass a comprehensive exam, and submit original research work demonstrating quantum computing applications. The original research, also referred to as a dissertation, plays a significant role in determining how long your PhD takes.

Is a PhD in Quantum Computing Hard?

Yes, a PhD in Quantum Computing is hard. You must develop in-depth knowledge of quantum computers and the process of designing, developing, and building fully-functional quantum machines. A PhD in Quantum Computing involves advanced coursework that includes quantum mechanics, physics, computational intelligence, and big data. These courses are very technical and challenging for any student.

You must also submit an extensive original dissertation, which involves a lot of research. Generally, the dissertation totals 70,000 to 100,000 words. You will spend months discovering new quantum computing theories, developing concepts, and defending everything you discover. In a nutshell, you must be ready and committed before pursuing a PhD in Quantum Computing.

How Much Does It Cost to Get a PhD in Quantum Computing?

It costs $8,000-$50,000 per year to get a PhD in Quantum Computing. According to a 2019 survey by the National Center for Education Statistics (NCES), PhD students in public institutions pay an average of $11,495 per year. Meanwhile, private institution tuition and fees average $23,138 per year.

It is important to note that these figures don’t represent the full cost of attendance, and you should also consider the cost of living, transportation, and supplies. You can always find the right estimate on the school’s website or through the admissions team.

How to Pay for a PhD in Quantum Computing: PhD Funding Options

The PhD funding options that students can use to pay for a PhD in Quantum Computing include federal grad student loans, scholarships and grants, fellowships, assistantships, and self-funding.

Funding for quantum computing grad students comes from different sources, including universities, charities, government bodies, and quantum computing research institutions. You can find reliable funding options by talking to your peers, building your portfolio, saving up, or pursuing funded PhD programs in Quantum Computing.

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What Is the Difference Between a Quantum Computing Master’s Degree and PhD?

The differences between a quantum computing master’s degree and PhD are the time frame, coursework, funding, and career opportunities. Generally, students complete a Master’s in Quantum Computing before pursuing a PhD, but it is not mandatory for all academic institutions. A PhD takes approximately four to seven years, whereas you can complete your master’s in two years.

The PhD curriculum is very advanced compared to the master’s degree . You must submit a dissertation of your original research work and complete a comprehensive exam before earning your PhD. A PhD in Quantum Computing is also more expensive, but you have access to more funding avenues, including fellowships and assistantships.

Master’s vs. PhD in Quantum Computing Job Outlook

The job outlook for quantum computing professionals with a master’s degree is slightly higher than those with a PhD in the same field. For example, the Bureau of Labor Statistics estimates computer and information scientists have a 22 percent job growth rate. These include quantum computing researchers, engineers, and scientists.

On the other hand, BLS classifies senior quantum computing professionals under physicists and astronomers, representing an 8 percent job growth rate over the next ten years. The job outlook may differ because a Master’s in Quantum Computing prepares you for industrial-oriented jobs, whereas a PhD is more focused on research and academic careers.

The difference in Salary for Quantum Computing Master’s vs. PhD

The salary difference for quantum computing master’s and PhD holders is slightly different, with PhD graduates earning more. Although there are no specific salary outlooks for quantum computing, PayScale statistics highlight salaries for computing professionals.

Generally, a PhD in Computing makes you eligible for an average salary of $134,000 per year , while a Master’s in Computing will earn you an average of $111,000 per year . Remember, these are blanket figures for computing jobs, and the salary will differ depending on your job title, location, and employer.

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Why You Should Get a PhD in Quantum Computing

You should get a PhD in Quantum Computing because of the career opportunities, higher earning potential, and extensive knowledge and research opportunities this degree provides. In addition, quantum computing is a highly technical field, and pursuing a PhD allows you to explore uncharted areas of this rapidly growing field.

Reasons for Getting a PhD in Quantum Computing

• Research Opportunities. A PhD involves a lot of research work, allowing you to make valuable contributions to the field of quantum computers. You will spend a year or more completing your dissertation of original research and making innovative discoveries, which will enhance your knowledge of quantum computing.
• Higher Earning Potential. A PhD in Quantum Computing is the highest level of education, which means you can negotiate for higher salaries in any job. Although PhD holders have a lower job outlook, they will still earn more than master’s degree holders and undergraduate professionals.
• Career Opportunities. With advancements in quantum technology, more people pursue computing careers, which makes this field a highly competitive industry. Earning a PhD in Quantum Computing places you ahead of your competition. It is a highly technical field that requires extensive knowledge, and employers will prioritize those with advanced credentials.
• Become a Quantum Computing Expert.  Through extensive research, projects, and advanced coursework, you will gain expert-level knowledge of quantum computers and become an expert in all things quantum computing. Quantum computing PhD holders gain advanced skills in various areas, including quantum research, algorithmic thinking, and quantum software tools.
• Reach your Full Potential. Earning a PhD in Quantum Computing allows you to reach your full potential. Pursuing a PhD in Quantum Computing is very hard and tests your resilience. Committing to the end allows you to grow professionally and individually through discipline and dedication.

Getting a PhD in Quantum Computing: Quantum Computing PhD Coursework

Getting a PhD in Quantum Computing involves completing extensive coursework that tackles every area of quantum computing. The standard quantum computing PhD coursework includes advanced courses, comprehensive exams, research work, assistantships, and a dissertation thesis. Below is a further analysis of the coursework, graduation requirements, and career outlook.

Quantum Optics

Quantum optics is an area of physics that focuses on applying quantum mechanics principles to occurrences involving light. You will learn about the nature of individual quanta of light, known as a proton, and its interaction with atoms and molecules. You will also explore the history of quantum optics, the first significant developments, and their applications to quantum computing.

Quantum Information Processing

Quantum information processing (QIP) is a core quantum computing course because it tackles an important part of the quantum computing system. This course will teach you how to process, analyze, and interpret quantum data using quantum information processing techniques. You will also explore quantum circuits, quantum control, quantum error-correction systems, quantum complexity theory, and quantum algorithms.

Implementation of Quantum Information Processors

In this course, you will discover the obstacles to implementing a quantum computing device and how to overcome them. You will learn about minimizing control and manipulation to achieve gate operations and the significance of quantum processors in QIP. You will also discover how quantum processors perform calculations based on probability.

Quantum Material Modeling

Quantum materials include topological insulators, magnets, superconductors, and multiferroics. You will learn how quantum materials affect current theory and contribute to quantum computing. Additionally, the course explores the tools and methods required to analyze, synthesize and manipulate these materials.

Quantum Cryptography   

Quantum cryptography or quantum key contribution refers to the process of encrypting and protecting quantum information using quantum mechanics principles. You will learn to apply quantum cryptography to data transmission, avoiding leaks and hacking incidents.

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How to Get a PhD in Quantum Computing: Doctoral Program Requirements

To get a PhD in Quantum Computing, you must fulfill the doctoral program requirements. The requirements include a dissertation thesis, exam results, course requirements, candidacy, assistantship requirements, residency, and research seminars.

The requirements are diverse and may vary depending on the academic institution. If you are wondering how to get a PhD in Quantum Computing, read the below list detailing five standard graduation requirements for quantum computing PhD students.

You must fulfill all the course requirements as per the university’s prerequisites. The coursework will include core courses, electives, and specialized courses. Students must complete all core courses and select a specific number of courses from the other categories. For example, Harvard University requires you to complete four core courses, add two specializations, and three elective courses.

You will complete qualifying or preliminary exams as part of the degree program. Students will complete a comprehensive exam that demonstrates their academic foundation and knowledge of quantum computing fundamentals. This exam will be administered in written or verbal form and indicates you are ready to begin your dissertation work.

Assistantships involve simultaneously working and learning within the academic institution. You can select a teaching, research, lab, or general graduate assistantship. Although assistantships are a mandatory PhD requirement, you will benefit from tuition waivers, cash compensation, and employee benefits like health insurance. You can confirm all the benefits for each program with the graduate studies department.

A PhD candidacy refers to the stage where you have completed all graduation prerequisites except the dissertation thesis. You will complete all the required courses and pass a qualifying exam before advancing into candidacy. Keep in mind that you must submit an application form to qualify for the candidacy.

All quantum computing PhD students must complete a detailed thesis of original research work in an area of quantum computing. You will explain your research sources, methods, references, and other relevant parts of a dissertation. Furthermore, you must defend your dissertation work in front of a thesis committee that will ask a variety of open-ended questions.

Potential Careers With a Quantum Computing Degree

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PhD in Quantum Computing Salary and Job Outlook

Graduates with a PhD in Quantum Computing enjoy high salaries and access to many job industries. Generally, you will earn between $90,000 and $150,000 or higher depending on your employer. The job outlook is promising because it requires applicants with extensive knowledge in the field, while an increasing number of organizations are implementing quantum computers.

What Can You Do With a PhD in Quantum Computing?

With a PhD in Quantum Computing, you can work as a senior quantum scientist, quantum senior software engineer, quantum optics researcher, and quantum computing research lead. Quantum computing PhD graduates have access to a wide range of career opportunities at senior levels.

You can also apply for jobs across different industries, including health care, academia, Blockchain and cryptocurrencies, supply chain management, cyber security, and finance. Many major companies like IBM Quantum, Microsoft Azure Quantum, Cambridge Quantum, and Amazon are developing quantum computing services.

Best Jobs with a PhD in Quantum Computing

• Quantum computing professor
• Quantum optics researcher
• Quantum error correction researcher
• Quantum software engineer
• Quantum research scientist

What Is the Average Salary for a PhD in Quantum Computing

According to PayScale data, a PhD in Computing makes you eligible for an average salary of $134,000 . This figure includes all computing professionals, but quantum computing professionals have even higher earning potential.

Highest-Paying Quantum Computing Jobs for PhD Grads

Best Quantum Computing Jobs with a Doctorate

A Doctorate in Quantum Computing opens doors to jobs with lucrative salaries and amazing benefits. The best quantum computing jobs with a doctorate are primarily senior roles that come with a wide range of responsibilities. Below, you will explore a detailed overview of the highest-paying jobs for PhD graduates, including job outlook, and responsibilities.

Quantum system managers act as project managers in quantum computing organizations. You will plan, coordinate, and lead the team in implementing quantum computing activities to meet company needs. In addition, you will direct the maintenance of quantum computers, negotiate with vendors, propose new quantum technology, and report to the stakeholders.

• Salary with a Quantum Computing PhD: $159,010
• Job Outlook: 11% job growth from 2020 to 2030
• Number of Jobs: 482,000
• Highest-Paying States : New York, California, New Jersey, Washington, District of Columbia

Quantum physicists explore the physical laws that influence the behavior of atoms, electrons, and photons. You will design and perform experiments, develop and explain scientific theories, develop computer software, write scientific papers, and analyze physical data. This is a broad role that entails a wide selection of duties and requires knowledge of quantum algorithms, machine learning, quantum sensing, and quantum mechanics.

• Salary with a Quantum Computing PhD: $152,430
• Job Outlook: 9% job growth from 2020 to 2030
• Number of Jobs: 19,500
• Highest-Paying States : Pennsylvania, Kansas, Arizona, California, Missouri

Quantum research scientists help quantum computing organizations to solve problems with research. You will apply quantum theory principles to enhance how quantum computers optimize problems and improve performance. You will also analyze performance results, develop computing languages, present research findings, and test software systems operations.

• Salary with a Quantum Computing PhD: $131,490
• Job Outlook: 22% job growth from 2020 to 2030
• Number of Jobs: 33,000
• Highest-Paying States: Oregon, Arizona, Texas, Massachusetts, Washington

A quantum computing engineer applies quantum mechanics principles in designing and executing computing experiments. You will design and implement system improvements and collaborate with other engineers within the company to meet set goals. You must demonstrate expertise in electrical and electronic engineering, computer science, quantum physics, artificial intelligence, and programming languages.

• Salary with a Quantum Computing PhD: $108,774
• Number of Jobs: 1,847,900
• Highest-Paying States: California, Washington, Maryland, New York, Rhode Island

Quantum computing professors teach quantum computing at the university level. You will teach undergraduate or graduate students, depending on your expertise and the experience you gain from the assistantship. Some of your duties will include developing a course outline, planning lessons and preparing assignments, advising students on the right courses, conducting research, and contributing to curriculum changes.

• Salary with a Quantum Computing PhD: $93,070
• Job Outlook: 12% job growth from 2020 to 2030
• Number of Jobs: 1,276,900
• Highest-Paying States: California, Massachusetts, New York, Oregon, Wisconsin

Is a PhD in Quantum Computing Worth It?

Yes, a PhD in Quantum Computing is worth it. A PhD is the highest level of education and gives you in-depth knowledge of quantum computing skills. It comes with a wide selection of benefits including higher earning potential, research opportunities, and senior career opportunities.

The future of quantum computing is promising as more organizations develop quantum computing cloud services and design quantum computers. You can expand your opportunities across different industries and leave your mark on the development of quantum computers.

Additional Reading About Quantum Computing

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PhD in Quantum Computing FAQ

You can get a job in quantum computing by pursuing an accredited education path, improving your quantum computing skills, and gaining experience through internships and entry-level or mid-level jobs. You can also expand your portfolio by working on a wide variety of quantum computing projects. A PhD in the field will be the peak academic achievement on your CV.

No, you don’t need a PhD in quantum computing to pursue senior careers. The quantum computing industry accommodates master’s degree holders for senior roles. However, pursuing a PhD boosts your research capabilities.

Yes, quantum computing is the future. Many organizations are adapting quantum computing applications, and the industry is witnessing a rise in the number of quantum computing startups . The growth also indicates job security throughout the future for quantum computing professionals.

The programming languages you can use in quantum computing include QML, Quantum Lambda Calculus, QMASM, QCL, and Silq. You will learn how to use these languages to translate data into ideas that quantum computers can implement.

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The concept of utilizing quantum resources for computational tasks has opened up a new area of intellectual and practical frontier in computing, ranging from computational complexities, quantum algorithms, quantum computing architectures to construction of commercially viable quantum computers. Duke has been a pioneer in this exciting frontier of a fast-developing field, in quantum error correction, quantum computer architectures and trapped-ion quantum computing hardware development. The research opportunities at Duke are on a rapid growth path, and we will form an epicenter of research and development effort for practical realization of quantum computers.

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About the group.

PhD in Quantum Information

The  PhD in Quantum Information  is designed to provide students with knowledge of quantum information, including both theory and its implementations, advanced expertise in quantum information science and in home program disciplines, as well as training in research. 

This unique interdisciplinary doctoral program is a collaboration between the Institute for Quantum Computing and the following faculties and departments at the University of Waterloo.

Faculty of Mathematics

• David R. Cheriton School of Computer Science
• Applied Mathematics
• Combinatorics and Optimization

Faculty of Engineering

• Electrical and Computer Engineering

Faculty of Science

• Physics and Astronomy

Students will be especially well-prepared for careers as scholars and researchers, with advanced expertise in quantum information science, together with the focus of their home programs. This program is designed to provide students with knowledge of quantum information, including both theory and its implementations, advanced expertise in quantum information science and in home program disciplines, as well as training in research. Further details and program requirements can be found in the graduate academic calendar .

Note: The School of Computer Science does not accept part-time students into the PhD programs unless the applicant is currently an employee of the School.

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Quantum control of an oscillator using a stimulated Josephson nonlinearity (Houck Lab)

Future computers harnessing quantum entanglement and measurement can solve certain problems more efficiently. Research at Princeton spans a large number of physical platforms for quantum computing, from laser cooled neutral atoms and molecules, to superconducting circuits, to electrons confined in solid state defects and patterned electrodes. Our full stack approach spans work on new platforms, device and systems engineering, and new quantum control and quantum error correction schemes.

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Professor Kai-Mei Fu leads establishment of UW Graduate Certificate in Quantum Information Science and Engineering

November 21, 2022

By Wayne Gillam | UW ECE News

The new UW Graduate Certificate in Quantum Information Science and Engineering was established fall quarter 2022 by a multidisciplinary faculty group led by Kai-Mei Fu (above). Fu is the Virginia and Prentice Bloedel Professor of Physics and Electrical and Computer Engineering at the University of Washington. The Certificate can be completed concurrently with a master’s or doctoral degree, and it prepares students for careers and leadership roles in fields related to development of quantum-enabled technologies. Photo by Ryan Hoover

This fall, a new graduate certificate program at the University of Washington began training students in an emerging, fast-growing field that blends information science based on principles of quantum mechanics with development of new technologies. The UW Graduate Certificate in Quantum Information Science and Engineering provides students with a robust, interdisciplinary experience that explores how this new field relates to other areas within science, technology, engineering and mathematics. The Certificate program was established by a multidisciplinary faculty group and is directed by Kai-Mei Fu , who is the Virginia and Prentice Bloedel Professor of Physics and Electrical and Computer Engineering at the University of Washington . Fu led the group in development and implementation of the Certificate curriculum, which was designed to complement and augment students’ existing degree programs. Courses are taught by a select number of UW faculty that have a wide range of expertise in the field. The Certificate can be completed concurrently with a master’s or doctoral degree, and it prepares students for careers and leadership roles in fields related to development of quantum-enabled technologies.

“The people who tend to be drawn to this program are students who have been hearing about quantum information, realize the impact scalable quantum computing systems can have and want to understand how their discipline can actually help make this impact a reality,” Fu said. “If you want to make a difference in this field, then you need a solid base. And if you want to get that base, then you should get the Certificate.”

Interdisciplinary curriculum for graduate students

Students in the program will have access to quantum cloud computers through Microsoft Azure, which will allow them to run experiments and explore how real quantum devices behave in practice.

The student cohort pursuing the Certificate is very diverse, being over 35 percent women and bringing together 60 students from five different departments on campus. Most students are research trainees in the National Science Foundation-funded Accelerating Quantum-Enabled Technologies program; however, the Certificate program is open to any UW graduate student who has met the required prerequisites. The program is an especially good fit for students interested in quantum information science who are studying electrical and computer engineering, physics, computer science and engineering, chemistry, or materials science and engineering. The program curriculum is structured to enhance a graduate student’s research focus.

“This fall, we have three intro courses in the Certificate program that target the expertise of the people we’re training,” Fu said. “We have Introduction to Quantum Information Science and Engineering for Chemists and Materials Scientists , which is offered through the chemistry department, Quantum Information offered through the physics department, and Introduction to Quantum Computing taught through the Allen School. All these courses work together, and any one of them can be a student’s first introductory course.”

Fu is director of the Quantum Defect Laboratory at the UW and co-chair of UW QuantumX, which brings together quantum information science and engineering researchers and educators from across campus. Fu’s strong network and connections, along with support from colleagues, enabled the Certificate program to be quickly established. (Above) Fu inspecting equipment in the Quantum Defect Laboratory. Photo by Dennis Wise | University of Washington

Students in the program will have access to quantum cloud computers through Microsoft Azure , which will allow them to run experiments and explore how real quantum devices behave in practice. They will also gain experience participating in team-based projects that are important to the field and relevant to future employers. Courses that explore cross-disciplinary topics, such as EE 500Q: Quantum Information Science and Engineering Seminar (offered during winter quarter at UW ECE), are at the heart of the Certificate program. EE 500Q provides weekly presentations from quantum scientists across multiple disciplines, covering industry, academia and National Laboratory experiences while exposing students to potential research and career directions. The Certificate program also offers opportunities to make connections with many other people working on quantum-enabled technologies. Fu said that these connections could help students better understand where their own research might fit into a broader picture. Fu added that the projects and teamwork, along with the program courses, help to create a common language between different disciplines.

“If you want to make a difference in this field, then you need a solid base. And if you want to get that base, then you should get the Certificate.” — Professor Kai-Mei Fu

“The reason why an interdisciplinary approach to quantum information science and engineering is important is that, right now, there are challenges at every single level of the quantum hardware stack,” Fu said. “So, if we think of the materials that are developed that go into the devices, the devices that go into the architecture and that on the architecture you’re running software, which is an implementation of some algorithm, you can see how the entire stack is connected. Everything needs to be co-designed and developed together to optimize and maximize performance in these systems.”

The need to develop a workforce with interdisciplinary expertise in this emerging field was behind the idea for the Certificate program itself. Fu talked about the growing demand for those with a strong background in quantum information science and engineering and that National Laboratories, in particular, are eager to hire people with skills in this area.

“Potential employers need really good electrical engineers, computer scientists, chemists and physicists that understand quantum information science and engineering,” Fu said. “Based on that knowledge, it became clear to me and my colleagues that a certificate program, something that could augment a graduate-level degree and demonstrate expertise connected to the individual’s primary research focus, would best serve our students.”

Taught by outstanding faculty at a world-class university

UW ECE professors Arka Majumdar, Sara Mouradian and Rahul Trivedi (from left to right) are instructors in the Certificate program. Majumdar also co-chairs UW QuantumX alongside Fu, and Mouradian will be leading the graduate-level Quantum Information Practicum, which brings students together into teams to work on academic and industry-sponsored projects.

To that end, Fu and her colleagues assembled a team of UW faculty who are leaders in their respective areas of expertise to teach this new curriculum. Fu noted the enthusiasm and support across campus for the Certificate, which enabled the program to be quickly established to meet the needs of a rapidly advancing field.

“The University of Washington has very open, curious and bold faculty who are willing and able to expand research directions across different disciplines,” Fu said. “Even in universities that have had a strong footprint in quantum for a long time, it’s been in specific departments. What is exciting here is that we span a number of University units and departments.”

Fu is a faculty member of the Molecular Engineering & Sciences Institute , the Clean Energy Institute and the Institute for Nano-Engineered Systems . These sorts of cross-campus connections, combined with co-chairing UW QuantumX alongside Arka Majumdar , an instructor in the Certificate program who is a UW associate professor of physics and of electrical and computer engineering, provided Fu with a strong network to draw from.

“QuantumX supports research, training and curriculum development in this area,” Fu said. “Many of the core faculty in the Certificate program are also active faculty in QuantumX. So, it’s all part of a rich ecosystem on campus in quantum information science and engineering.”

As director of the Quantum Defects Lab, Fu’s research focuses on identifying and controlling the quantum properties of point defects in crystals, which has potential applications for both information and sensing technologies. Students pursuing the Certificate stand to benefit from Fu’s expertise as well as that of her colleagues teaching in the Certificate program. Photo by Dennis Wise | University of Washington

The Certificate program has received critical support from the UW College of Engineering , which in 2020 launched a cross-departmental faculty cluster hire in quantum information science and technology. The initiative included new faculty hires in the Paul G. Allen School of Computer Science & Engineering , the UW Department of Materials Science & Engineering and the UW Department of Mechanical Engineering . At UW ECE, the cluster hire brought on board assistant professors Sara Mouradian and Rahul Trivedi . Both faculty members are instructors in the Certificate program, and Mouradian will be leading the graduate-level Quantum Information Practicum, which brings students together into teams to work on academic and industry-sponsored projects.

“I’m excited to teach this capstone course,” Mouradian said. “It’s rare to have such a hands-on course at the graduate level, and it will be a great opportunity for students to take the information they’ve learned in the Certificate program and put it into practice while gaining exposure to industry and National Labs.”

Fu noted that studies led by the National Science Foundation have shown that participating in smaller, independent team projects early in a doctoral degree program can help to accelerate completion of the degree. So, one of the Certificate program’s aims will be to teach graduate students project management and team skills in quantum information science and engineering early in their academic careers. Fu said that there was excitement among faculty about this new capstone course, and combined with other courses in the Certificate program, what will be offered to graduate students overall.

“We’ve built a really serious program in this area, one that is at the forefront of research and education,” Fu said. “Our students will receive a solid foundation, and they are going to go out and make an impact in this field when they graduate.”

To learn more, visit the UW Graduate Certificate in Quantum Information Science and Engineering webpage on the QuantumX website. UW students interested in and eligible for the program should contact Program Coordinator Madeline Miller for information or to notify intent to pursue the Certificate.

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Ph.D Programs for Quantum Computing

I will be finishing my masters in Electrical Engineering in Spring 2022, and I was wondering what the options were regarding Ph.D programs for Quantum Computing. Also, coming from the EE side of things, will I meet the physics requirements necessary for a Ph.D in this area?

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Modular, scalable hardware architecture for a quantum computer

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Quantum computers hold the promise of being able to quickly solve extremely complex problems that might take the world’s most powerful supercomputer decades to crack.

But achieving that performance involves building a system with millions of interconnected building blocks called qubits. Making and controlling so many qubits in a hardware architecture is an enormous challenge that scientists around the world are striving to meet.

Toward this goal, researchers at MIT and MITRE have demonstrated a scalable, modular hardware platform that integrates thousands of interconnected qubits onto a customized integrated circuit. This “quantum-system-on-chip” (QSoC) architecture enables the researchers to precisely tune and control a dense array of qubits. Multiple chips could be connected using optical networking to create a large-scale quantum communication network.

By tuning qubits across 11 frequency channels, this QSoC architecture allows for a new proposed protocol of “entanglement multiplexing” for large-scale quantum computing.

The team spent years perfecting an intricate process for manufacturing two-dimensional arrays of atom-sized qubit microchiplets and transferring thousands of them onto a carefully prepared complementary metal-oxide semiconductor (CMOS) chip. This transfer can be performed in a single step.

“We will need a large number of qubits, and great control over them, to really leverage the power of a quantum system and make it useful. We are proposing a brand new architecture and a fabrication technology that can support the scalability requirements of a hardware system for a quantum computer,” says Linsen Li, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this architecture.

Li’s co-authors include Ruonan Han, an associate professor in EECS, leader of the Terahertz Integrated Electronics Group, and member of the Research Laboratory of Electronics (RLE); senior author Dirk Englund, professor of EECS, principal investigator of the Quantum Photonics and Artificial Intelligence Group and of RLE; as well as others at MIT, Cornell University, the Delft Institute of Technology, the U.S. Army Research Laboratory, and the MITRE Corporation. The paper appears today in Nature .

Diamond microchiplets

While there are many types of qubits, the researchers chose to use diamond color centers because of their scalability advantages. They previously used such qubits to produce integrated quantum chips with photonic circuitry.

Qubits made from diamond color centers are “artificial atoms” that carry quantum information. Because diamond color centers are solid-state systems, the qubit manufacturing is compatible with modern semiconductor fabrication processes. They are also compact and have relatively long coherence times, which refers to the amount of time a qubit’s state remains stable, due to the clean environment provided by the diamond material.

In addition, diamond color centers have photonic interfaces which allows them to be remotely entangled, or connected, with other qubits that aren’t adjacent to them.

“The conventional assumption in the field is that the inhomogeneity of the diamond color center is a drawback compared to identical quantum memory like ions and neutral atoms. However, we turn this challenge into an advantage by embracing the diversity of the artificial atoms: Each atom has its own spectral frequency. This allows us to communicate with individual atoms by voltage tuning them into resonance with a laser, much like tuning the dial on a tiny radio,” says Englund.

This is especially difficult because the researchers must achieve this at a large scale to compensate for the qubit inhomogeneity in a large system.

To communicate across qubits, they need to have multiple such “quantum radios” dialed into the same channel. Achieving this condition becomes near-certain when scaling to thousands of qubits. To this end, the researchers surmounted that challenge by integrating a large array of diamond color center qubits onto a CMOS chip which provides the control dials. The chip can be incorporated with built-in digital logic that rapidly and automatically reconfigures the voltages, enabling the qubits to reach full connectivity.

“This compensates for the in-homogenous nature of the system. With the CMOS platform, we can quickly and dynamically tune all the qubit frequencies,” Li explains.

Lock-and-release fabrication

To build this QSoC, the researchers developed a fabrication process to transfer diamond color center “microchiplets” onto a CMOS backplane at a large scale.

They started by fabricating an array of diamond color center microchiplets from a solid block of diamond. They also designed and fabricated nanoscale optical antennas that enable more efficient collection of the photons emitted by these color center qubits in free space.

Then, they designed and mapped out the chip from the semiconductor foundry. Working in the MIT.nano cleanroom, they post-processed a CMOS chip to add microscale sockets that match up with the diamond microchiplet array.

They built an in-house transfer setup in the lab and applied a lock-and-release process to integrate the two layers by locking the diamond microchiplets into the sockets on the CMOS chip. Since the diamond microchiplets are weakly bonded to the diamond surface, when they release the bulk diamond horizontally, the microchiplets stay in the sockets.

“Because we can control the fabrication of both the diamond and the CMOS chip, we can make a complementary pattern. In this way, we can transfer thousands of diamond chiplets into their corresponding sockets all at the same time,” Li says.

The researchers demonstrated a 500-micron by 500-micron area transfer for an array with 1,024 diamond nanoantennas, but they could use larger diamond arrays and a larger CMOS chip to further scale up the system. In fact, they found that with more qubits, tuning the frequencies actually requires less voltage for this architecture.

“In this case, if you have more qubits, our architecture will work even better,” Li says.

The team tested many nanostructures before they determined the ideal microchiplet array for the lock-and-release process. However, making quantum microchiplets is no easy task, and the process took years to perfect.

“We have iterated and developed the recipe to fabricate these diamond nanostructures in MIT cleanroom, but it is a very complicated process. It took 19 steps of nanofabrication to get the diamond quantum microchiplets, and the steps were not straightforward,” he adds.

Alongside their QSoC, the researchers developed an approach to characterize the system and measure its performance on a large scale. To do this, they built a custom cryo-optical metrology setup.

Using this technique, they demonstrated an entire chip with over 4,000 qubits that could be tuned to the same frequency while maintaining their spin and optical properties. They also built a digital twin simulation that connects the experiment with digitized modeling, which helps them understand the root causes of the observed phenomenon and determine how to efficiently implement the architecture.

In the future, the researchers could boost the performance of their system by refining the materials they used to make qubits or developing more precise control processes. They could also apply this architecture to other solid-state quantum systems.

This work was supported by the MITRE Corporation Quantum Moonshot Program, the U.S. National Science Foundation, the U.S. Army Research Office, the Center for Quantum Networks, and the European Union’s Horizon 2020 Research and Innovation Program.

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Emerging field of quantum computing advances at MSU through $500K Department of Energy grant

Contact: Sarah Nicholas

STARKVILLE, Miss.—A Mississippi State University research team is using more than half a million dollars from the U.S. Department of Energy nuclear physics program to study the emerging field of quantum computing. The research is part of a 2020 goal set by MSU’s Quantum Task Force to explore interdisciplinary programs for training MSU students in the evolving technology of quantum computing and quantum information science.

The three-year, $550,000 grant—Three-body Interactions on a Quantum Computer—is led by principal investigator Gautam Rupak, a professor in MSU’s Department of Physics and Astronomy, and includes co-PIs Mark A. Novotny, professor and department head, and Yaroslav Koshka, a professor in MSU’s Department of Electrical and Computer Engineering.

Quantum computing, a multidisciplinary field combining computer science, physics and mathematics, uses quantum mechanics to solve complex problems faster than classical computers and can create better models for how atoms and nuclei interact with one another, leading to a more precise understanding of molecular structure.

“Though quantum mechanics was developed nearly a century ago, the advent of quantum computers requires a change in paradigm in how we compute physical quantities on such devices,” said Rupak, noting the research team is collaborating with experts in nuclear physics, Noisy Intermediate-Scale Quantum, or NISQ, computers and machine learning.

Rupak said the team will develop and test algorithms on currently available quantum computers to study three-body nuclear forces that will directly impact future research on nuclear structure and reactions over a wide range of atomic masses. This technology will one day enable more accurate predictions of real-time dynamics of complex atomic nuclei which could impact drug and chemical research.

Rupak said the team is trying to solve for the “binding energy of the triton”—a positively-charged particle consisting of a proton and two neutrons, equivalent to the nucleus of an atom of tritium—using current NISQ computers.

For more details about MSU’s College of Arts and Sciences or the Department of Physics and Astronomy, visit www.cas.msstate.edu or www.physics.msstate.edu . To learn more about MSU’s Bagley College of Engineering, visit www.bagley.msstate.edu .

Mississippi State University is taking care of what matters. Learn more at www.msstate.edu .

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Pacific Northwest National Laboratory

Ph.d. intern in quantum computing.

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Overview The Physical and Computational Sciences Directorate (PCSD) researchers lead major R&D efforts in experimental and theoretical interfacial chemistry, chemical analysis, high energy physics, interfacial catalysis, multifunctional materials, and integrated high-performance and data-intensive computing.

PCSD is PNNL’s primary steward for research supported by the Department of Energy’s Offices of Basic Energy Sciences, Advanced Scientific Computing Research, and Nuclear Physics, all within the Department of Energy’s Office of Science.

Additionally, Directorate staff perform research and development for private industry and other government agencies, such as the Department of Defense and NASA. The Directorate’s researchers are members of interdisciplinary teams tackling challenges of national importance that cut across all missions of the Department of Energy.

Responsibilities The High-Performance Computing (HPC) Group at the Pacific Northwest National Laboratory (PNNL) is seeking Ph.D. Interns for this fall with a strong background in distributive quantum computing, quantum computing architecture, numerical simulation of quantum systems, quantum networking, and/or quantum error correction. The candidate will be expected to contribute to world-leading research as part of PNNL within its US Dept. of Energy funded projects. The candidate will be expected to collaborate closely with laboratory personnel in computing and application domains, as well as researchers at collaborating national laboratories, universities, and industry partners on center activities focused on the development, application, benchmarking, compilation, and optimization of quantum architecture and software.

Responsibilities and Accountabilities Include:

• Developing frameworks on mapping existing QASM programs to a new quantum architecture
• Investigating the distillation protocols for networking and magic state
• Developing high-performance simulation tools and environments on classical HPC clusters for efficient quantum circuit simulation
• Research on quantum error mitigation and error correction
• Publish results in top-tier computer architecture conferences and journals, including ISCA, ASPLOS, MICRO, HPCA, and others
• Interact with internal and external research staff and domain scientists for collaboration purposes
• Participate in and potentially lead technical presentations on the work
• Participate in team meetings

Qualifications Minimum Qualifications:

• Candidates must be currently enrolled/matriculated in a PhD program at an accredited college.
• Minimum GPA of 3.0 is required.

Preferred Qualifications:

• Quantum computing or quantum physics background
• Experience with Qiskit
• Experience with GPU programming languages and programming models, including CUDA
• Experience with quantum transpilation or other circuit optimization techniques
• Experience with quantum noise models or quantum error correction code

Hazardous Working Conditions/Environment Not applicable

Testing Designated Position This is not a Testing Designated Position (TDP)

About PNNL Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!

At PNNL, you will find an exciting research environment and excellent benefits including health insurance, flexible work schedules and telework options. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab’s campus is only a 45-minute flight (or ~3 hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.

Commitment to Excellence, Diversity, Equity, Inclusion, and Equal Employment Opportunity Our laboratory is committed to a diverse and inclusive work environment dedicated to solving critical challenges in fundamental sciences, national security, and energy resiliency. We are proud to be an Equal Employment Opportunity and Affirmative Action employer. In support of this commitment, we encourage people of all racial/ethnic identities, women, veterans, and individuals with disabilities to apply for employment.

Pacific Northwest National Laboratory considers all applicants for employment without regard to race, religion, color, sex (including pregnancy, sexual orientation, and gender identity), national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws.

We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at [email protected] .

Drug Free Workplace PNNL is committed to a drug-free workplace supported by Workplace Substance Abuse Program (WSAP) and complies with federal laws prohibiting the possession and use of illegal drugs.

HSPD-12 PIV Credential Requirement In accordance with Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, new employees are required to obtain and maintain a HSPD-12 Personal Identity Verification (PIV) Credential. To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.

Mandatory Requirements Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.

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Notice to Applicants PNNL lists the full pay range for the position in the job posting. Starting pay is calculated from the minimum of the pay range and actual placement in the range is determined based on an individual’s relevant job-related skills, qualifications, and experience. This approach is applicable to all positions, with the exception of positions governed by collective bargaining agreements and certain limited-term positions which have specific pay rules.

As part of our commitment to fair compensation practices, we do not ask for or consider current or past salaries in making compensation offers at hire. Instead, our compensation offers are determined by the specific requirements of the position, prevailing market trends, applicable collective bargaining agreements, pay equity for the position type, and individual qualifications and skills relevant to the performance of the position.

Minimum Salary USD $22.93/Hr. Maximum Salary USD $35.00/Hr.

Quantum computers are like kaleidoscopes − why unusual metaphors help illustrate science and technology

Associate Dean for Research, Purdue University

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Sorin Adam Matei does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

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Quantum computing is like Forrest Gump ’s box of chocolates : You never know what you’re gonna get. Quantum phenomena – the behavior of matter and energy at the atomic and subatomic levels – are not definite, one thing or another. They are opaque clouds of possibility or, more precisely, probabilities. When someone observes a quantum system, it loses its quantum-ness and “collapses” into a definite state.

Quantum phenomena are mysterious and often counterintuitive. This makes quantum computing difficult to understand. People naturally reach for the familiar to attempt to explain the unfamiliar, and for quantum computing this usually means using traditional binary computing as a metaphor. But explaining quantum computing this way leads to major conceptual confusion, because at a base level the two are entirely different animals.

This problem highlights the often mistaken belief that common metaphors are more useful than exotic ones when explaining new technologies. Sometimes the opposite approach is more useful. The freshness of the metaphor should match the novelty of the discovery.

The uniqueness of quantum computers calls for an unusual metaphor. As a communications researcher who studies technology , I believe that quantum computers can be better understood as kaleidoscopes.

Digital certainty vs. quantum probabilities

The gap between understanding classical and quantum computers is a wide chasm. Classical computers store and process information via transistors, which are electronic devices that take binary, deterministic states: one or zero, yes or no. Quantum computers, in contrast, handle information probabilistically at the atomic and subatomic levels.

Classical computers use the flow of electricity to sequentially open and close gates to record or manipulate information. Information flows through circuits, triggering actions through a series of switches that record information as ones and zeros. Using binary math, bits are the foundation of all things digital, from the apps on your phone to the account records at your bank and the Wi-Fi signals bouncing around your home.

In contrast, quantum computers use changes in the quantum states of atoms, ions, electrons or photons. Quantum computers link, or entangle, multiple quantum particles so that changes to one affect all the others. They then introduce interference patterns, like multiple stones tossed into a pond at the same time. Some waves combine to create higher peaks, while some waves and troughs combine to cancel each other out. Carefully calibrated interference patterns guide the quantum computer toward the solution of a problem.

Achieving a quantum leap, conceptually

The term “ bit ” is a metaphor. The word suggests that during calculations, a computer can break up large values into tiny ones – bits of information – which electronic devices such as transistors can more easily process.

Using metaphors like this has a cost, though. They are not perfect. Metaphors are incomplete comparisons that transfer knowledge from something people know well to something they are working to understand. The bit metaphor ignores that the binary method does not deal with many types of different bits at once, as common sense might suggest. Instead, all bits are the same.

The smallest unit of a quantum computer is called the quantum bit, or qubit. But transferring the bit metaphor to quantum computing is even less adequate than using it for classical computing. Transferring a metaphor from one use to another blunts its effect .

The prevalent explanation of quantum computing is that while classical computers can store or process only a zero or one in a transistor or other computational unit, quantum computers supposedly store and handle both zero and one and other values in between at the same time through the process of superposition .

Superposition, however, does not store one or zero or any other number simultaneously. There is only an expectation that the values might be zero or one at the end of the computation. This quantum probability is the polar opposite of the binary method of storing information.

Driven by quantum science’s uncertainty principle, the probability that a qubit stores a one or zero is like Schroedinger’s cat , which can be either dead or alive, depending on when you observe it. But the two different values do not exist simultaneously during superposition. They exist only as probabilities, and an observer cannot determine when or how frequently those values existed before the observation ended the superposition.

Leaving behind these challenges to using traditional binary computing metaphors means embracing new metaphors to explain quantum computing.

Peering into kaleidoscopes

The kaleidoscope metaphor is particularly apt to explain quantum processes. Kaleidoscopes can create infinitely diverse yet orderly patterns using a limited number of colored glass beads, mirror-dividing walls and light. Rotating the kaleidoscope enhances the effect, generating an infinitely variable spectacle of fleeting colors and shapes.

The shapes not only change but can’t be reversed. If you turn the kaleidoscope in the opposite direction, the imagery will generally remain the same, but the exact composition of each shape or even their structures will vary as the beads randomly mingle with each other. In other words, while the beads, light and mirrors could replicate some patterns shown before, these are never absolutely the same.

Using the kaleidoscope metaphor, the solution a quantum computer provides – the final pattern – depends on when you stop the computing process. Quantum computing isn’t about guessing the state of any given particle but using mathematical models of how the interaction among many particles in various states creates patterns, called quantum correlations.

Each final pattern is the answer to a problem posed to the quantum computer, and what you get in a quantum computing operation is a probability that a certain configuration will result.

New metaphors for new worlds

Metaphors make the unknown manageable, approachable and discoverable. Approximating the meaning of a surprising object or phenomenon by extending an existing metaphor is a method that is as old as calling the edge of an ax its “bit” and its flat end its “butt.” The two metaphors take something we understand from everyday life very well, applying it to a technology that needs a specialized explanation of what it does. Calling the cutting edge of an ax a “bit” suggestively indicates what it does, adding the nuance that it changes the object it is applied to. When an ax shapes or splits a piece of wood, it takes a “bite” from it.

Metaphors, however, do much more than provide convenient labels and explanations of new processes. The words people use to describe new concepts change over time, expanding and taking on a life of their own.

When encountering dramatically different ideas, technologies or scientific phenomena, it’s important to use fresh and striking terms as windows to open the mind and increase understanding. Scientists and engineers seeking to explain new concepts would do well to seek out originality and master metaphors – in other words, to think about words the way poets do.

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Toward error-free quantum computing: A symbolic model checking approach to verify quantum circuits

by Japan Advanced Institute of Science and Technology

Quantum computing is a rapidly growing technology that utilizes the laws of quantum physics to solve complex computational problems that are extremely difficult for classical computing. Researchers worldwide have developed many quantum algorithms to take advantage of quantum computing, demonstrating significant improvements over classical algorithms.

Quantum circuits, which are models of quantum computation, are crucial for developing these algorithms. They are used to design and implement quantum algorithms before actual deployment on quantum hardware.

Quantum circuits comprise a sequence of quantum gates, measurements, and initializations of qubits, among other actions. Quantum gates perform quantum computations by operating on qubits, which are the quantum counterparts of classical bits (0s and 1s), and by manipulating the quantum states of the system. Quantum states are the output of quantum circuits, which can be measured to obtain classical outcomes with probabilities, from which further actions can be done.

Since quantum computing is often counter-intuitive and dramatically different from classical computing , the probability of errors is much higher. Hence, it is necessary to verify that quantum circuits have the desired properties and function as intended. This can be done through model checking, a formal verification technique used to verify whether systems satisfy desired properties.

Although some model checkers are dedicated to quantum programs, there is a gap between model-checking quantum programs and quantum circuits due to different representations and no iterations in quantum circuits.

Addressing this gap, Assistant Professor Canh Minh Do and Professor Kazuhiro Ogata from Japan Advanced Institute of Science and Technology (JAIST) proposed a symbolic model checking approach.

Dr. Do explains, "Considering the success of model-checking methods for verification of classical circuits, model-checking of quantum circuits is a promising approach. We developed a symbolic approach for model checking of quantum circuits using laws of quantum mechanics and basic matrix operations using the Maude programming language."

Their approach is detailed in a study published in the journal PeerJ Computer Science .

Maude is a high-level specification/programming language based on rewriting logic, which supports the formal specification and verification of complex systems. It is equipped with a Linear Temporal Logic (LTL) model checker, which checks whether systems satisfy the specified properties.

Additionally, Maude allows the creation of precise mathematical models of systems. The researchers formally specified quantum circuits in Maude, as a series of quantum gates and measurement applications, represented as basic matrix operations using laws of quantum mechanics with the Dirac notation. They specified the initial state and the desired properties of the system in LTL.

By using a set of quantum physics laws and basic matrix operations formalized in our specifications, quantum computation can be reasoned in Maude. They then used the built-in Maude LTL model checker to automatically verify whether quantum circuits satisfy the desired properties.

They used this approach to check several early quantum communication protocols, including Superdense Coding, Quantum Teleportation, Quantum Secret Sharing, Entanglement Swapping, Quantum Gate Teleportation, Two Mirror-image Teleportation, and Quantum Network Coding, each with increasing complexity.

They found that the original version of Quantum Gate Teleportation did not satisfy its desired property. By using this approach, the researchers notably proposed a revised version and confirmed its correctness.

These findings signify the importance of the proposed innovative approach for the verification of quantum circuits. However, the researchers also point out some limitations of their method, requiring further research.

Dr. Do says, "In the future, we aim to extend our symbolic reasoning to handle more quantum gates and more complicated reasoning on complex number operations. We also would like to apply our symbolic approach to model-checking quantum programs and quantum cryptography protocols."

Verifying the intended operation of quantum circuits will be highly valuable in the upcoming era of quantum computing. In this context, the present approach marks the first step toward a general framework for the verification and specification of quantum circuits , paving the way for error-free quantum computing.

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Role of Quantum Computing in Data Science

In the world of data science, a big change is coming that will shake things up: quantum computing . This new technology won’t just improve what we’re already doing—it will completely change how we think about and solve problems in data science.

Quantum Computing in Data Science

In this article, we will explore Why quantum computing is the next big thing in data science? We’ll discuss how it will enhance our ability to process and analyze data, tackle previously intractable problems, and ultimately reshape the landscape of our profession.

Table of Content

What is Quantum Computing?

How is quantum computing relevant to data science, applications of quantum computing in data science, quantum algorithms in data science, challenges and limitations of quantum computing in data science, future prospects of quantum computing in data science.

Quantum computing is a new and exciting field that takes advantage of the strange and powerful principles of quantum mechanics. Imagine computers that can solve tough math problems and simulate complex processes like how molecules form, how plants make energy, and even superconductivity – things that are super hard for regular computers to handle. At the heart of this technology are qubits, or quantum bits. Unlike the bits in your computer that are either 0 or 1, qubits can be both 0 and 1 at the same time.

Key Concepts:

• Qubits : The fundamental unit of quantum information, qubits can exist in multiple states simultaneously.
• Superposition : This principle allows qubits to be in a combination of states at the same time, providing a massive parallel processing advantage.
• Entanglement : A phenomenon where qubits become interconnected such that the state of one qubit can depend on the state of another, no matter the distance between them.
• Speed : Quantum computers can process vast amounts of data and perform complex calculations much faster than classical computers. This speed is particularly beneficial for data-intensive tasks like optimization, machine learning, and simulation.
• Machine Learning : Quantum machine learning algorithms, such as quantum support vector machines and quantum neural networks, have the potential to outperform classical algorithms in certain applications. They can handle large datasets more efficiently and may discover patterns that are challenging for classical algorithms to uncover.
• Data Analysis : Quantum computers can efficiently analyze large datasets using quantum algorithms like Grover’s algorithm, which can significantly speed up the process of searching unstructured data.
• Security : Quantum computing also impacts data science by offering quantum cryptography solutions that are theoretically unbreakable due to the principles of quantum mechanics. This includes quantum key distribution, which enables secure communication channels.
• Optimization : Quantum computing can solve complex optimization problems, which are common in data science, more efficiently than classical computers. This capability is valuable for tasks like portfolio optimization, logistics planning, and resource allocation.
• Simulation : Quantum computers can simulate quantum systems, which is crucial for fields such as quantum chemistry and material science. These simulations can lead to the discovery of new materials and drugs, among other applications.

Quantum computing holds promise for various data science applications, from data analysis to machine learning and optimization.

• Quantum Simulation for Complex Systems: Quantum computers have the potential to simulate complex quantum systems that are practically intractable for classical computers. This capability is particularly useful in fields like chemistry, physics, and materials science, where understanding the behavior of molecules, materials, and other quantum systems is crucial. Quantum simulations can lead to advancements in drug discovery, material design, and fundamental research.
• Quantum Cryptography for Secure Data Communication: Quantum cryptography leverages the principles of quantum mechanics to create secure communication protocols . Quantum key distribution (QKD) enables the creation of encryption keys that are theoretically impossible to intercept without detection. This technology offers a new level of security for data transmission, particularly in fields where data privacy is paramount, such as finance, healthcare, and government communication.
• Quantum-enhanced Machine Learning and Data Analysis: Quantum computing has the potential to revolutionize machine learning and data analysis by enabling the processing of large datasets and complex algorithms at speeds far beyond the capabilities of classical computers. Quantum machine learning algorithms, such as quantum neural networks and quantum clustering algorithms , can provide more efficient solutions to optimization and pattern recognition problems. Quantum computers can also be used to accelerate database searches, data analysis, and pattern recognition tasks, leading to faster and more accurate insights from data.
• Grover’s Algorithm : Grover’s algorithm is a quantum algorithm that provides a quadratic speedup for unstructured search problems. It can be used to search an unsorted database of N items in roughly √N steps, compared to the O(N) steps required by classical algorithms.
• Shor’s Algorithm : Shor’s algorithm is a quantum algorithm for integer factorization, which means finding the prime factors of a composite integer. It provides an exponential speedup over the best known classical algorithms for this task.
• Quantum Machine Learning Algorithms : Quantum machine learning algorithms leverage quantum computing principles to enhance various machine learning tasks. These algorithms often aim to improve efficiency or provide new capabilities beyond classical machine learning.
• Quantum Error Correction: Quantum computers are susceptible to errors due to decoherence and other quantum phenomena. Quantum error correction techniques are essential to mitigate these errors and ensure the reliability of quantum computations.
• Scalability and Quantum Volume: Building large-scale, error-corrected quantum computers is a significant challenge. Quantum volume, a metric that combines the number of qubits, error rates, and connectivity, needs to increase significantly to achieve practical quantum computing capabilities.
• Access and Cost of Quantum Computing: Currently, quantum computing resources are limited and expensive to access. Overcoming this challenge requires the development of more accessible and cost-effective quantum computing platforms.
• Quantum Computing in Big Data Analytics: Quantum computing has the potential to revolutionize big data analytics by enabling the processing of massive datasets in parallel. This could lead to faster insights and more efficient data analysis techniques.
• Integration with Classical Computing Systems: Hybrid quantum-classical computing systems are expected to play a crucial role in the future of computing. These systems will combine the strengths of both quantum and classical computing to solve complex problems efficiently.
• Impact on Data Science and Industry: Quantum computing has the potential to transform various industries by enabling faster and more efficient data analysis, optimization, and simulation. It could lead to breakthroughs in areas such as materials science, finance, and healthcare.

Quantum computing holds immense promise for the field of data science, offering unprecedented computational power and capabilities. Despite current challenges and limitations, ongoing research and advancements in quantum technology are paving the way for a future where quantum computing plays a central role in solving some of the most complex data-driven problems across industries.

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