NASA Quantum Artificial Intelligence Laboratory (QuAIL)
QuAIL is the space agency’s hub for assessing the potential of quantum computers to impact computational challenges faced by the agency in the decades to come.
NASA’s QuAIL team aims to demonstrate that quantum computing and quantum algorithms may someday dramatically improve the agency’s ability to address difficult optimization and machine learning problems arising in NASA’s aeronautics, Earth and space sciences, and space exploration missions.
NASA’s QuAIL team has extensive and experience utilizing near-term quantum computing hardware to evaluate the potential impact of quantum computing. The team has international recognized approaches to the programming and compilation of optimization problems to near-term quantum processors, both gate-model quantum processors and quantum annealers, enabling efficient utilization of the prototype quantum hardware available for experimenting with quantum and quantum-classical hybrid approaches for exact and approximate optimization and sampling.The has ongoing research developing quantum computational approaches to challenging combinatorial optimization and sampling problems with relevance to areas such as planning and scheduling, fault diagnosis, and machine learning.
A key component of this work is close collaboration with quantum hardware groups. The team’s initial focus was on quantum annealing, since D-Wave quantum annealers were the first quantum computational devices available. As gate-model processors have matured, with gate-model processors with 10s of qubits now available, the group has extended its research to include substantial gate-model efforts in addition to deepening our quantum annealing research. For more information on our research, please see our Research Overview and Publication pages.
The NASA QuAIL team leads the T&E team for the IARPA QEO (quantum enhanced optimization) program, has formal collaborative agreements with quantum hardware groups at Google and Rigetti, and research collaborations with many other entities at the forefront of quantum computing, as well as a three-way agreement between Google-NASA-USRA related to the D-Wave machine hosted at NASA Ames.
The QuAIL group’s expertise spans physics, computer science, mathematics, chemistry, and engineering.
What is Quantum Computing?
Quantum computing is based on quantum bits or qubits. Unlike traditional computers, in which bits must have a value of either zero or one, a qubit can represent a zero, a one, or both values simultaneously. Representing information in qubits allows the information to be processed in ways that have no equivalent in classical computing, taking advantage of phenomena such as quantum tunneling and quantum entanglement. As such, quantum computers may theoretically be able to solve certain problems in a few days that would take millions of years on a classical computer.
News and Events
Dr. Eleanor Rieffel Selected as a 2020 NASA Ames Associate Felllow
July 17, 2020
Dr. Eleanor Rieffel was awarded the 2020 Ames Associate Fellow for her pioneering work in the field of quantum information processing. Her work significantly advances the state of the art in quantum computing and its application to the NASA mission in aeronautics, space exploration, and earth science.
The Ames Associate Fellow is an honorary designation that acknowledges distinguished scientific research or outstanding engineering of a non-management related nature. Appointment as Ames Associate Fellow is for a two-year term. The winning researchers receive a personal award, a research stipend, a travel grant, and will give a lecture to the center.
NASA Ames and Quantum Supremacy
October 24, 2019
In partnership with Google and the Oak Ridge National Laboratory, our researchers in the Quantum Artificial Intelligence Laboratory (QuAIL) group worked to demonstrate the ability to compute in seconds what would take even the largest and most advanced supercomputers thousands of years to achieve, a milestone known as quantum supremacy. This remarkable achievement is featured on the cover of the Oct. 24, 2019 issue of the science journal Nature.
Using our supercomputing facilities, researchers here at Ames advanced techniques for simulating quantum computations – work that helped set the bar for Google’s quantum computer to beat. The achievement of quantum supremacy means that the processing power and control mechanisms now exist for scientists to run their code with confidence and see what happens beyond the limits of what can be done on supercomputers. Experimentation with quantum computing is now possible in a way it never has been before.
This is another example of the great and important work we do here at Ames. The high goals we set, the milestones we achieve, the hard work and dedication we contribute as a community is what continues to allow us to push the boundaries of exploration to new heights.
See Ames’ contribution to quantum supremacy for more information.
Flexible Quantum Circuit Simulator (qFlex) Framework Open Sourced
October 24, 2019
Flexible Quantum Circuit Simulator (qFlex) implements an efficient tensor network, CPU-based simulator of large quantum circuits. qFlex computes exact probability amplitudes, a task that proves essential for the verification of quantum hardware, as well as mimics quantum machines by computing amplitudes with low fidelity. qFlex targets quantum circuits in the range of sizes expected for supremacy experiments based on random quantum circuits, in order to verify and benchmark such experiments.
The qFlex framework is licensed under the Apache License, Version 2.0, and is available for download.
NASA Ames hosts AQC-18
June 25-28, 2018
Adiabatic Quantum Computing (AQC) and Quantum Annealing are computational methods that have been proposed to solve combinatorial optimization and sampling problems. Several efforts are now underway to manufacture processors that implement these strategies. The Seventh International Conference on AQC brings together researchers from different communities to explore this computational paradigm. The goal of the conference is to initiate a dialogue on the challenges that must be overcome to realize useful adiabatic quantum computations in existing or near-term hardware. Read More
Quantum Annealer with more than 2000 qubits installed and operational
August 31, 2017
We upgraded the D-Wave quantum annealer hosted here at NASA Ames to a D-Wave 2000Q system. The newly upgraded system, which resides at the NASA Advanced Supercomputing Facility at NASA’s Ames Research Center, has 2031 quantum bits (qubits) in its working graph—nearly double the number of qubits compared to the previous processor. It has several system enhancements that enable more control over the adiabatic quantum computing process allowing it to solve larger and more complex optimization problems than were previously possible.
Dr. Eleanor Rieffel Selected as a 2020 NASA Ames Associate Fellow
NASA Ames and Quantum Supremacy
Flexible Quantum Circuit Simulator (qFlex) Open Sourced
Adiabatic Quantum Computing (AQC-18) Conference
- A. Akbari Asanjan, M. Memarzadeh, P.A. Lott, E. Rieffel, S. Grabbe, Probabilistic Wildfire Segmentation Using Supervised Deep Generative Model from Satellite Imagery, Remote Sensing 15 (11), 2718 (2023)
- B. Barch, N. Anand, J. Marshall, E. Rieffel, P. Zanardi, Scrambling and operator entanglement in local non-Hermitian quantum systems, arXiv:2305.12054 (2023)
- J. Marshall, N. Anand, Simulation of quantum optics by coherent state decomposition, arXiv:2305.17099 (2023)
- V. Kremenetski, A. Apte, T. Hogg, S. Hadfield, N.M. Tubman, Quantum Alternating Operator Ansatz (QAOA) beyond low depth with gradually changing unitaries, arXiv:2305.04455 (2023)
- A. Morvan, B. Villalonga, X. Mi, S. Mandrà, A. Bengtsson, P.V. Klimov, Z. Chen, et al., Phase transition in Random Circuit Sampling, arXiv:2304.11119 (2023)
- P.A. Kerger, D.E.B. Neira, Z.G. Izquierdo, E.G. Rieffel, Mind the O: Asymptotically Better, but Still Impractical, Quantum Distributed Algorithms , arXiv:2304.02825 (2023)
- T. Templin, M. Memarzadeh, W. Vinci, P.A. Lott, A.A. Asanjan, A.A. Armenakas, et al., Anomaly Detection in Aeronautics Data with Quantum-compatible Discrete Deep Generative Model, arXiv:2303.12302 (2023)
- M. Dupont, B. Evert, M.J. Hodson, B. Sundar, S. Jeffrey, Y. Yamaguchi, et al., Quantum Enhanced Greedy Solver for Optimization Problems, arXiv:2303.05509 (2023)
- T. Lubinski, C. Coffrin, C. McGeoch, P. Sathe, J.Apanavicius, D.E.B. Neira, Optimization applications as quantum performance benchmarks, arXiv:2302.02278 (2023)
- E.J. Gustafson, A.C.Y. Li, A. Kahn, J. Kim, D.M. Kurkcuoglu, M.S. Alam, P.P. Orth, et al., Preparing quantum-many body scars on a quantum computer, arXiv:2301.08226 (2023)
- T. McCourt, C. Neill, K. Lee, C. Quintana, Y. Chen, J. Kelly, J. Marshall, et al., Learning noise via dynamical decoupling of entangled qubits, Physical Review A 107 (5), 052610 (2023)
- N. Suri, J. Barreto, S. Hadfield, N. Wiebe, F. Wudarski, J. Marshall, Two-Unitary Decomposition Algorithm and Open Quantum System Simulation, Quantum 7, 1002 (2023)
- R. Acharya, et al., Suppressing quantum errors by scaling a surface code logical qubit, Nature 614 (7949), 676-681 (2023)
- L.P. García-Pintos, L.T. Brady, J. Bringewatt, Y.K. Liu, Lower Bounds on Quantum Annealing Times, Physical Review Letters 130 (14), 140601 (2023)
- X. Fei, L.T. Brady, J. Larson, S. Leyffer, S. Shen, Binary control pulse optimization for quantum systems, Quantum 7, 892 (2023)
- T.C. Mooney, J. Bringewatt, N.C. Warrington, L.T. Brady, Lefschetz thimble quantum Monte Carlo for spin systems, Physical Review B 106 (21), 214416 (2022)
- D. Chamaki, S. Hadfield, K. Klymko, B. O’Gorman, N.M. Tubman, Self-consistent Quantum Iteratively Sparsified Hamiltonian method (SQuISH): A new algorithm for efficient Hamiltonian simulation and compression, arXiv:2211.16522 (2022)
- C.M. Unsal, L.T. Brady, Quantum Adversarial Learning in Emulation of Monte-Carlo Methods for Max-cut Approximation: QAOA is not optimal, arXiv:2211.13767 (2022)
- J. Sud, S. Hadfield, E. Rieffel, N. Tubman, T. Hogg, A Parameter Setting Heuristic for the Quantum Alternating Operator Ansatz, arXiv:2211.09270 (2022)
- Z.G. Izquierdo, S. Grabbe, H. Idris, Z. Wang, J. Marshall, E. Rieffel, Advantage of Pausing: Parameter Setting for Quantum Annealers, Physical Review Applied 18 (5), 054056 (2022)
- J. Bringewatt, L.T. Brady, Simultaneous stoquasticity, Physical Review A 105 (6), 062601 (2022)
Full Publications List available here
QuAIL Overview Articles:
- E. G. Rieffel, S. Hadfield, T. Hogg, S. Mandrà, J. Marshall, G. Mossi, B. O’Gorman, E. Plamadeala, N. M. Tubman, D. Venturelli, W. Vinci, Z. Wang, M. Wilson, F. Wudarski, R. Biswas, From Ansätze to Z-gates: a NASA View of Quantum Computing, Advances in Parallel Computing, Vol. 34: Future Trends of HPC in a Disruptive Scenario, pp. 133-160 (2019)
- R. Biswas, Z. Jiang, K. Kechezhi, S. Knysh, S. Mandrà, B. O’Gorman, A. Perdomo-Ortiz, A. Petukhov, J. Realpe-Gómez, E. Rieffel, D. Venturelli, F. Vasko, Z. Wang, A NASA perspective on quantum computing: Opportunities and challenges, Parallel Computing, Vol. 64, pp. 81-98 (2017)
M. Sohaib Alam
Humberto Munoz Bauza
David Bernal Neira
Zoe Gonzalez Izquierdo