Expanding Control of Quantum Processor Units

Jonathan DuBois | 19-ERD-013

Project Overview

First proposed in the 1980s by Richard Feynman, quantum computers are a new computational platform that promises exponential improvements in computational resources for certain problems, such as the simulation of many-particle systems described by nonrelativistic quantum mechanics. This computational "speed up" promises to make the exact simulation of dynamical processes such as nuclear and chemical reactions tractable, simulations that are out of reach even in the age of exascale computing. Early demonstrations using a minimal discrete gate set on current, relatively small size, superconducting quantum devices have shown promise for simulating such quantum systems. However, limitations in gate error rates and quantum-device noise undermine their efficacy when simulating real-time (unitary) evolution. Because of this, the solution of even small problems on presently available quantum computing resources has been limited. This strongly motivates the development of alternative, noise-resilient protocols capable of producing a more efficient mapping into the quantum hardware of the interactions of microscopic systems.

In this project, we implemented one of these new approaches, quantum optimal control. Instead of treating the system as a black box, we instead use the physically characterized system parameters to calculate a set of custom gates that act as subroutines that we run to simulate, for example, timesteps in the target system evolution. This approach leverages open quantum system control and, in collaboration with applications teams in nuclear physics and fusion energy science, enabled a 2-3 order-of-magnitude increase in system performance over current state of the art for the targeted quantum simulation problem. In addition to this pioneering work in software defined logic, we demonstrated full characterization and control of the Lawrence Livermore National Laboratory (LLNL)-developed quantum processor. We also developed staff and institutional expertise in the design, fabrication, characterization, and control of superconducting quantum computing platforms which enables us and NNSA to be more agile responding to problems where quantum resources can speed up computations.

Mission Impact

Infrastructure investments in the Quantum Device and Integration Testbed (QuDIT) through this project resulted in a centralized resource for experimental quantum computing at LLNL. This new capability brought a nascent, disruptive computing technology to the Laboratory, supporting LLNL's core competency in high-performance computing, simulation, and data sciences. Supporting this effort, we brought in new staff including an early career staff member hire, two staff conversions, and three postdoctoral researchers. These resources have, in turn, allowed us to improve the quantum literacy of the broader scientific and technical workforce at the Lab. Science and technology tools and capabilities developed under this project make LLNL and NNSA more agile as we prepare to meet future national security challenges and enable us to explore solutions to emerging security challenges associated with technological surprise. Capabilities developed under this project have catalyzed multiple, highly interdisciplinary, research directions including new DOE Office of Science projects from Basic Energy Sciences, Advanced Scientific Computing Research, Nuclear Physics and Fusion Energy Sciences, as well as four new LDRD Exploratory Research projects and three LDRD Feasibility Study projects. These projects all advance the science, technology and engineering competencies that are the foundations of the NNSA mission.

Publications, Presentations, and Patents

Wilen, Christopher D, S Abdullah, NA Kurinsky, C Stanford, L Cardani, G d'Imperio, C Tomei, et al. "Correlated Charge Noise and Relaxation Errors in Superconducting Qubits." Nature 594, no. 7863. 2021: 369-73.

Shi, Yuan, Alessandro R. Castelli, Xian Wu, Ilon Joseph, Vasily Geyko, Frank R. Graziani, Stephen B. Libby, et al. "Simulating Non-Native Cubic Interactions on Noisy Quantum Machines." Physical Review A 103, 062608. 2021.

Günther, Stefanie, N Anders Petersson, and Jonathan L DuBois. "Quantum Optimal Control for Pure-State Preparation Using One Initial State," AVS Quantum Science 3, 043801. 2021.

Goldschmidt, Andy, Eurika Kaiser, Jonathan L Dubois, Steven L Brunton, and J Nathan Kutz. "Bilinear Dynamic Mode Decomposition for Quantum Control," New Journal of Physics 23, 033035. 2021.

Chaves, Kevin R, Xian Wu, Yaniv J Rosen, and Jonathan L DuBois. "Nonlinear Signal Distortion Corrections through Quantum Sensing," Applied Physics Letters 118, 014001. 2021.

Wu, Xian, Spencer L Tomarken, N Anders Petersson, Luis A Martinez, Yaniv J Rosen, and Jonathan L DuBois. "High-Fidelity Software-Defined Quantum Logic on a Superconducting Qubit," Physical Review Letters 125, 170502. 2020.

Martinez, Luis A, Yaniv J Rosen, and Jonathan L DuBois. "Improving Qubit Readout with Hidden Markov Models," Physical Review A 102, 062426. 2020.

Holland, Eric T, Kyle A Wendt, Konstantinos Kravvaris, Xian Wu, W Erich Ormand, Jonathan L DuBois, Sofia Quaglioni, and Francesco Pederiva. "Optimal Control for the Quantum Simulation of Nuclear Dynamics," Physical Review A 101, 062307. 2020.

Wu, Xian, Spencer Tomarken, N Anders Petersson, Luis Martinez, Yaniv Rosen, Kyle Wendt, Konstantinos Kravvaris, Sofia Quaglioni, and Jonathan DuBois. "Quantum Optimal Control for High-Fidelity Arbitrary Quantum Logic on a Superconducting Qudit." Bulletin of the American Physical Society, APS March Meeting, virtual, March 15-19, 2021.

Winer, Gal, Spencer Tomarken, Ilan Mitnikov, Arthur Strauss, Steven Frankel, Jonathan DuBois, Lior Ella, and Yonatan Cohen. "Booting a Quantum Computer: A Qua-Based Graph Framework for Automatic Qubit Calibration, Measurement, and Execution of Hybrid Classical-Quantum Algorithms." Bulletin of the American Physical Society, APS March Meeting, virtual, March 15-19, 2021.

Petersson, N Anders, Stefanie Guenther, Spencer Tomarken, and Jonathan DuBois. "Numerical Optimal Control of Open Quantum Systems." Bulletin of the American Physical Society, APS March Meeting, virtual, March 15-19, 2021.

Wu, Xian, Luis Martinez, Yaniv Rosen, and Jonathan DuBois. "Full Characterization and Universal Control of a Superconducting 3d Transmon Qudit." Bulletin of the American Physical Society, APS March Meeting, virtual, March 2-6, 2020.

Tomarken, Spencer, and Jonathan DuBois. "High Sensitivity Spectral Characterization of Local Microwave Fields Using Two-Photon Absorption Processes of a Transmon Qudit." Bulletin of the American Physical Society, APS March Meeting, virtual, March 2-6, 2020.

Shi, Yuan, Alessandro Castelli, Ilon Joseph, Vasily Geyko, Frank Graziani, Stephen Libby, Jeffrey Parker, Yaniv Rosen, and Jonathan DuBois. "Quantum Simulation of Nonlinear Three-Wave Interactions with Engineered Cubic Couplings." Bulletin of the American Physical Society, APS March Meeting, virtual, March 2-6, 2020.

Martinez, Luis, Yaniv Rosen, and Jonathan DuBois. "Improving Multilevel Qudit Readout Fidelity During Relaxation Events Via Hidden Markov Models." Bulletin of the American Physical Society, APS March Meeting, virtual, March 2-6, 2020.

Joseph, Ilon, Alessandro Castelli, Jonathan DuBois, Vasily Geyko, Frank Graziani, Stephen Libby, Jeffrey Parker, Yaniv Rosen, and Yuan Shi. "Quantum Simulation of Nonlinear Classical Dynamics." Bulletin of the American Physical Society, APS March Meeting, virtual, March 2-6, 2020.

Chan, Jacky, Apurva Gowda, Peter DeVore, Brandon Buckley, Jonathan DuBois, and Jason Chou. "High-Fidelity, Scalable Quantum-Classical Control Interface Using Photonics." Bulletin of the American Physical Society, APS March Meeting, virtual, March 2-6, 2020.

Castelli, Alessandro, Yuan Shi, Ilon Joseph, Vasily Geyko, Frank Graziani, Stephen Libby, Jeffrey Parker, Yaniv Rosen, and Jonathan DuBois. "Experimental Realization of a Nonlinear 3-Wave Mixing Gate for Quantum Simulation." Bulletin of the American Physical Society, APS March Meeting, virtual, March 2-6, 2020.