Lawrence Livermore National Laboratory

Quantum Coherent Device Physics Group

Developing hardware, algorithms, and control for near-term applications in quantum information, sensing, and computing.

Our research aims to draw from and build a community around intersections in applied mathematics, computer science, quantum information, and device physics to make optimal use of near-term quantum hardware.

Our group has ongoing collaborations with related efforts at LLNL:

  • Microscopic theory and multiscale device modeling
  • Quantum sensing
  • Quantum materials research
  • Microwave photon counting
  • Cryogenic detectors

Learn more about our group by exploring the topics below.


We design solutions to, and explore synergies between, the following research challenges to enable efficient and reliable quantum algorithm development and to inform the quantum hardware co-design process:

  • Gaining insight into conditions for optimal algorithm performance from quantum thermodynamic and quantum geometric information.
  • Developing and applying powerful and scalable high-dimensional minimum-action methods to optimize gate sets and quantum algorithms.
  • Realizing a systematic understanding of methods, limitations, and bounds on performance of passive stabilization of quantum dynamical flows and manifolds.
  • Gaining insight into the instantaneous information content as well as the computational cost associated with extracting information from quantum algorithms as a function of run time.
  • Developing classical machine-learning-based approaches to optimal extraction of quantum resultants.
  • Developing self-consistent criteria for, and faithful read-out methods of, target variables in quantum simulators for verification and validation of simulation results.

The “Beyond Moore’s Law” effort evaluates the potential of the National Nuclear Security Administration’s (NNSA’s) Defense Programs’ applications of computing technologies that go beyond Moore’s Law scaling and Von Neumann architectures. The Advanced Simulation and Computing (ASC) program investigates the application of non-CMOS-based logical devices, as well as quantum and neuromorphic computing algorithms and hardware, for NNSA computing needs. The goal is to gain a detailed understanding and investigate the best technical approaches and benefits of these emerging technologies for NNSA applications and a roadmap for their integration into ASC computing platforms.

The objective of the quantum computing program is to provide a pathway for exploring quantum computing for ASC applications, including applications that work and evaluation of emerging hardware. The scope of this project includes research, development, and evaluation of prototype computing systems and algorithms, as well as developing potential industry and academic collaborations.

Quantum coherent devices offer the potential for unprecedented precision in sensing and the ability to directly simulate quantum phenomena that have no known efficient classical algorithms. Such devices include quantum bits (the fundamental units for quantum computing systems), microwave resonators (a type of superconducting photon detector), superconducting quantum interference devices (very-sensitive magnetometers used to measure extremely subtle magnetic fields), single-electron transistors, and single-photon detectors. The performance of such devices is largely limited by resonant couplings to low-energy states in the constituent materials (i.e., materials-based sources of noise). Overcoming this limitation requires that subtle forms of noise from decoherence in these systems be understood and controlled. This project will likely make a significant contribution to that understanding and control.

We intend to build a robust capability to design, fabricate, and characterize quantum coherent devices for applications in sensing and analog quantum simulation. We will then carry out a series of experiments designed to probe the fundamental limits of noise in these systems. Finally, we will apply these capabilities to develop a next-generation, superconducting quantum-bit-based detector designed to detect hypothetical dark-matter elementary particles called axions. Dark matter is estimated to make up about 23% of the energy density of the universe, with the rest being ordinary matter and a mysterious, repulsive, dark energy.

This research received support from the LLNL Laboratory Directed Research and Development Program (16-SI-004).

For more information, see “Additive Manufacturing Meets Quantum.”

The Department of Energy’s (DOE’s) Office of Advanced Scientific Computing Research is investing in multidisciplinary teams with the goal of initiating an exploration of the suitability of various implementations of quantum computing hardware for science applications. These teams will lay the foundation for a codesign effort to ensure that architectures well-suited for DOE target applications are developed and that major DOE scientific problems can take advantage of the emerging architectures for quantum computing. Co-design refers to a computer system design process in which scientific problem requirements influence architecture design and technology and constraints inform formulation and design of algorithms and software.

It is anticipated that teams will focus on experimental efforts to explore a variety of hardware approaches ranging from different schemes for qubit connectivity to quantum/classical coprocessors and quantum accelerators for classical high-performance computing (HPC). Successful teams will conduct internal research to develop meaningful metrics for evaluating the suitability of selected quantum computing hardware for science applications and collaborate externally with researchers working to develop applications and algorithms relevant to DOE’s science and energy mission.

Quantum coherent computing technologies, though currently far from practical universal computation, now have the requisite coherence times, logical operation fidelities, and circuit topologies to perform specialized computations (for example, quantum simulations) relevant for fundamental research in molecular and materials science, numerical optimization, and high-energy physics, to name a few areas. In light of these recent advances, exploration of how these technologies can be integrated into the HPC community is timely.

We will deploy a flexible architecture to tackle key problems in these disciplines and will naturally establish mutually beneficial collaborations with existing DOE computational science communities. As the technologies proposed in our testbed mature, they have the potential to ultimately exceed the computing power promised by even the DOE Exascale Computing Project.


Our researchers utilize world-class scientific capabilities and modern high-performance computing facilities to support Laboratory programs. Listed below are LLNL’s state-of-the-art capabilities commonly used by our group.

Featured Publications


Jonathan profile picture

Jonathan DuBois

Group Leader, Quantum Coherent Device Physics Group


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Alessandro Castelli

Alessandro Castelli

Postdoctoral Researcher


Luis Martinez

Luis Martinez

Postdoctoral Researcher


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Sean O'kelley

Sean O'kelley

Postdoctoral Researcher


Yaniv profile picture

Yaniv Rosen

Staff Scientist


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Spencer Tomarken

Spencer Tomarken

Postdoctoral Researcher


Xian Wu

Xian Wu

Postdoctoral Researcher