We've focused on building a strong ecosystem of university, industry and government research in quantum computing. Our topics:

Quantum algorithms

A quantum algorithm is an algorithm able to be run on quantum computation platforms. A quantum software library is available, resulting from a host language added by quantum or classical systems. In comparison, classical systems refer to today's traditional computer, typically limited to a few particles by an exponential increase of required resources of digital computers (memory, computing time) which is considered to be less efficient than quantum simulations.

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Quantum simulations

Classical simulations run on today’s traditional computer, typically limited to few Quantum simulations use quantum phenomena such as entanglement and tunneling to run algorithms meant to simulate the dynamics or the properties of quantum systems (e.g. molecules, materials..).

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Quantum applications
  • Optimization including planning & scheduling and fault diagnostics
  • Machine learning
  • Quantum communication and networks
  • Quantum simulations
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Quantum (and other post-Moore) hardware

Physics-based non-conventional computing devices may use a wide variety of methods derived from physics principles, including spintronic, atomtronics, laser interferometry and quantum computation.

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Members of USRA’s quantum science team aim to advance the industry and the body of knowledge. Their collective expertise, mentorship, and academic abilities may one day lead to an astounding ability to find solutions to difficult optimization problems for missions in the exploration of space, aeronautics, Earth science, and space science.

David Bell, Ph.D.
Director, USRA Research Institute for Advanced Computer Science
David Bell, Ph.D.

Dr. David Bell leads the USRA Quantum Information Sciences program and manages an active research program focused on disruptive technologies, including quantum computing, autonomous systems, and machine learning. Prior to coming to USRA, Dr. Bell held appointments at Xerox’s Palo Alto Research Center and MIT’s Center for Innovation in Product Development. Dr. Bell received his Ph.D. from Cornell University and is co-inventor on multiple patents and an author of around 30 papers.

Email: dbell@usra.edu

Davide Venturelli, Ph.D.
Science Operations Manager, Quantum AI Lab
Davide Venturelli, Ph.D.

Dr. Venturelli graduated from Ecole Normale Superieure de Lyon and obtained his Ph.D. in Numerical Simulations of the Condensed Matter at the International School for Advanced Studies (SISSA) in Trieste and in Nanophysics at the Universite de Grenoble (CNRS/UJF). He worked as a post-doc at Scuola Normale Superiore in Pisa, Italy, in the Condensed Matter and Information Theory group. Before joining QuAIL, his past publications include quantum condensed matter, many-body theory, device designs in collaboration with experimentalists, quantum thermodynamics, quantum phase transitions, and non-equilibrium spin/charge/energy transport in mesoscopic systems. His applied focus in quantum optimization is in complex scheduling, telecommunication networks, and robotics/distributed AI, also in collaborations with academia and the private sector.

Email: dventurelli@usra.edu

Dr. Venturelli's Publications
  • Compiling Quantum Circuits to Realistic Hardware Architectures using Temporal Planners, D. Venturelli, M. Do, E. Rieffel, J. Frank, Quantum Sci. Tech. Vol. 2 (2018) and IJCAI17 arXiv

  • Quantum Annealing via Environment-Mediated Quantum Diffusion, V. Smelyanskiy, D. Venturelli, A. Perdomo-Ortiz, S. Knysh, MI Dykman, Physical Review Letters 118 (6), 066802 (2017) arXiv

  • Quantum Annealing Implementation of Job-Shop Scheduling, D. Venturelli, D. Marchand, G. Rojo, COPLAS Workshop of the 26th International Conference on Automated Planning and Scheduling (2016) arXiv

  • Quantum Optimization of Fully-Connected Spin Glasses, D. Venturelli, S. Mandra, S. Knysh, B. O’Gorman, V. Smelyanskiy, R. Biswas, Physical Review X 5 (3), 031040 (2015) APS open

  • A Case Study in Programming a Quantum Annealer for Hard Operational Planning Problems, E. G. Rieffel, D. Venturelli, B. O’Gorman, M. Do, E. M. Pristay, V. N. Smelyanskiy, Quant. Inf. Process. 1-36 (2014) arXiv

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Zhihui Wang, Ph.D.
Research Scientist
Zhihui Wang, Ph.D.

Dr. Zhihui Wang is a research scientist working for USRA in the Quantum Artificial Intelligence Lab at NASA Ames Research Center. Her research spans various aspects in quantum information processing and quantum computation.  Her expertise lies in quantum control and quantum error suppression in solid state qubit systems, and simulation of quantum many-body systems.  Her recent research focus is in quantum optimization methods and its applications, as well as developing quantum-classical hybrid algorithms suitable for near-term quantum hardware.

Dr. Wang's Publications
  • Near-optimal quantum circuit for Grover's unstructured search using a transverse field, Zhang Jiang, Eleanor Rieffel, Zhihui Wang, Physical Review A 95 (6), 062317, 2017. 
  • The Quantum Approximation Optimization Algorithm for MaxCut: A Fermionic View, Zhihui Wang, Stuart Hadfield, Zhang Jiang, Eleanor Rieffel, arXiv preprint arXiv:1706.02998, 2017.

  • Explorations of quantum-classical approaches to scheduling a mars lander activity problem. T Tran, Z Wang, M Do, E Rieffel, J Frank, B O’Gorman, D Venturelli, and J C Beck, AAAI 2016 Workshop on Planning for Hybrid Systems, 641, 2016.

  • Defining and detecting quantum speedup, Troels F. Rønnow, Zhihui Wang, Joshua Job, Sergio Boixo, Sergei V. Isakov, David Wecker, John M. Martinis, Daniel A. Lidar, and Matthias Troyer. Science, 345, 420, 2014.

  • Evidence for quantum annealing with more than one hundred qubits, Sergio Boixo, Troels F Rønnow, Sergei V Isakov, Zhihui Wang, David Wecker, Daniel A Lidar, John M Martinis, and Matthias Troyer. Nature Physics, 10, 218, 2014.

  • Spin decoherence and electron spin bath noise of a nitrogen-vacancy center in diamond, Zhihui Wang and Susumu Takahashi, Physical Review B 87 (11), 115122, 2013.

  • Decoherence-protected quantum gates for a hybrid solid-state spin register, T Van der Sar, ZH Wang, MS Blok, H Bernien, TH Taminiau, DM Toyli, DA Lidar, DD Awschalom, R Hanson, VV Dobrovitski, Nature 484 (7392), 82-86, 2012.

  • Effect of pulse error accumulation on dynamical decoupling of the electron spins of phosphorus donors in silicon, ZH Wang, W Zhang, AM Tyryshkin, SA Lyon, JW Ager, EE Haller, VV Dobrovitski, Physical Review B 85 (8), 085206, 2012.

  • Time-optimal rotation of a spin 1/2: Application to the NV center spin in diamond, ZH Wang, VV Dobrovitski, Physical Review B 84 (4), 045303, 2011.

  • Universal dynamical decoupling of a single solid-state spin from a spin bath, G De Lange, ZH Wang, D Riste, VV Dobrovitski, R Hanson, Science 330, 60, 2010. 


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Stuart Hadfield, Ph.D.
Research Scientist
Stuart Hadfield, Ph.D.

Dr. Hadfield’s research seeks to better understand the power of quantum computers. He studies quantum algorithms, information, and complexity, with applications to problems in physics, chemistry, and engineering, and seek computational problems and results elucidating where quantum computers have demonstrable advantages over classical algorithms. He is further interested in the mathematical foundations of quantum physics and computation. 

In particular, Dr. Hadfield is currently exploring the ability of quantum computers to provide practical and theoretical advantages for i) the simulation of physical systems and ii) approximately solving hard optimization problems. Moreover, a significant goal is to find problems and applications where near-term quantum computing devices may provide practical advantages over the best classical approaches. 

Dr. Hadfield's Publications


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Kostyantyn Kechedzhi, Ph.D.
Research Scientist
Kostyantyn Kechedzhi, Ph.D.

Dr. Kechedzhi works at USRA at NASA Ames as a member of the NASA Quantum Artificial Intelligence Laboratory (QuAIL). He has presented at various institutions, such as Michigan State University, Google’s Adiabatic Quantum Computing Conference 2016, The Abdus Salam International Centre for Theoretical Physics, and the Southwest Quantum Information and Technology network at the University of New Mexico.


Collaborate with us

USRA conducts quantum computing research, development and education programs that engage a broad ecosystem of collaborators from universities, government organizations, and the private sector.  There are multiple ways to collaborate including obtaining free-time on quantum computing resources; collaborating on research and education projects involving quantum hardware, quantum algorithms and quantum applications; and collaborating on research and education proposals to funding organizations.

Thank you to our major partners, Google and NASA Ames Research Center, without whom this research and development would not be possible.



Feynman Quantum Computing Academy at NASA Ames

An experience in the USRA-NASA-Google Quantum Artificial Intelligence Laboratory (QuAIL) at NASA Ames Research Center’s Advanced Supercomputing Facility introduces graduate students to scientific opportunities in quantum information sciences and trains them to do research related to the most advanced quantum computing platforms. Students will receive valuable experience working on teams, undertaking projects in advanced computing, and developing quantum and classical methods to solve problems in important application or fundamental domains.

Students, which need to be enrolled in a Ph.D. program or have otherwise previous quantum computing research experience, are accepted to a 12-to-24 week program. Applications are open all year round. These students work in close collaboration with quantum scientists, receiving hands-on training, and undertake individualized research projects. Students will also participate in seminars and workshops with researchers from other organizations doing quantum research, including those from academic institutions, government laboratories, and commercial organizations. Participants receive a stipend to cover living expenses and travel during the program.

Points of Contact

David Bell, Ph.D. Director, USRA Research Institute for Advanced Computer Science (RIACS), and Chief Technologist, NASA Academic Mission Services

Davide Venturelli, Ph.D., Senior Quantum Information Scientist, USRA RIACS; and Science Operations Manager, Quantum Artificial Intelligence Laboratory

Academy Students
Academy Students at the 2018 Adiabatic Quantum Computing Conference at NASA Ames