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 mission of the Fusion Energy Sciences (FES) program “to bring a star to earth” holds promise for solving energy needs for the foreseeable future.

This goal is one of the most challenging endeavors ever undertaken by humankind and quantum computing will be core to its success. By improving quantum algorithms, our work will deliver improvements in measurement sensitivity, information processing, and computing power to enable FES's mission.

Learn More About Fusion Energy Sciences High-performance Computing Code →

Quantum computing relies on sophisticated superconducting devices. Although those devices are achieving longer and longer coherence times, materials noise and loss processes nevertheless exhibit quantum effects that complicate and even spoil quantum simulations.

We're working to get better insight into the materials that affect quantum information systems by characterizing a selection of quantum device materials with a newly developed sensor that can extract information about μeV energy scale defects and inform quantum hardware optimization.

This modeling will allow for a detailed microscopic understanding of coupled defects, their interactions, emergent dynamics, and ultimate effect on a quantum circuit.

Learn More About Detecting the Material Origin of μeV Energy Scale Defects →

Atomic nuclei are the core of matter and the fuel of stars. As if that weren't enough to captivate physicists, these collections of protons and neutrons are also archetypal quantum many-body systems that give rise to remarkable collective phenomena.

Our innovative approach to the many-nucleon problem describes the interaction of two neutrons via infinitesimal time steps that combine classical and quantum computing to propagate a simulation.

From simulating quantum phenomena to speeding up complex calculations to ultra-precise sensing, quantum computing has incredible potential.

While standard approaches to solid-state systems sacrifice sensitivity in an attempt to reduce the impact of environmental noise, we think there's a better way.

We hypothesize that tackling decoherence head-on by removing its physical sources would open the door to a wide range of approaches for scaling up quantum computation devices, while also extending coherence times.

Learn More Quantum Probes of the Materials Origins of Decoherence →

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.

The classical-quantum interface is a key part of any quantum computer, but this meshing of technologies can impact both the quality of the data researchers can gather and the size and scale of quantum computing devices.

To improve the performance and scalability of superconducting quantum computing systems, we're building a new classical-quantum interface based on radio frequency (RF) photonics that should enable faster gates (quantum logical operations) without sacrificing coherence.

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.

- E.T. Holland, Y.J. Rosen, N. Materise, N. Woollett, T. Voisin, Y.M. Wang, S.G. Torres, J. Mireles, G. Carosi, J.L DuBois, High-kinetic inductance additive manufactured superconducting microwave cavity,
*Appl. Phys. Lett.***111**, 202602 (2017), doi: 10.1063/1.5000241. - N. Adelstein, D. Lee, J.L. DuBois, K.G. Ray, J.B. Varley, V. Lordi, Magnetic stability of oxygen defects on the SiO2 surface,
*AIP Advances***7**, 025110 (2017), doi: 10.1063/1.4977194. - M. Reagor, W. Pfaff, C. Axline, R. W. Heeres, N. Ofek, K. Sliwa, E.T. Holland, C. Wang, J. Blumoff, K. Chou, M. J. Hatridge, L. Frunzio, M.H. Devoret, L. Jiang, R.J. Schoelkopf, Quantum memory with millisecond coherence in circuit QED,
*Phys. Rev. B***94**, 014506 (2016), doi: 10.1103/PhysRevB.94.014506. - Y.J. Rosen, M.S. Khalil, A.L. Burin, K.D. Osborn, Random-Defect Laser: Manipulating Lossy Two-Level Systems to Produce a Circuit with Coherent Gain,
*Phys. Rev. Lett.***116**, 163601 (2016), doi: 10.1103/PhysRevLett.116.163601. - E.T. Holland, B. Vlastakis, R.W. Heeres, M.J. Reagor, U. Vool, Z. Leghtas, L. Frunzio, G. Kirchmair, M.H. Devoret, M. Mirrahimi, R.J. Schoelkopf, Single-photon Resolved Cross-Kerr Interaction for Autonomous Stabilization of Photon-number States,
*Phys. Rev. Lett.***115**, 180501 (2015), doi: 10.1103/PhysRevLett.115.180501. - R.W. Heeres, B. Vlastakis, E.T. Holland, S. Krastanov, V.V. Albert, L. Frunzio, L. Jiang, R.J. Schoelkopf, Cavity State Manipulation Using Photon-Number Selective Phase Gates,
*Phys. Rev. Lett.***115**, 137002 (2015), doi: 10.1103/PhysRevLett.115.137002. - H.M. Iftekhar Jaim, J.A. Aguilar, B. Sarabi, Y.J. Rosen, A.N. Ramanayaka, E.H. Lock, C.J.K. Richardson, K.D. Osborn, Superconducting TiN Films Sputtered Over a Large Range of Substrate DC Bias,
*IEEE Trans. Appl. Supercond.***25**, 3 (2015), doi: 10.1109/TASC.2014.2366036. - Lee, J.L DuBois, V. Lordi, Identification of the Local Sources of Paramagnetic Noise in Superconducting Qubit Devices Fabricated on α−Al2O3 Substrates Using Density-Functional Calculations,
*Phys. Rev. Lett.*112, 017001 (2014), doi: 10.1103/PhysRevLett.112.017001. - M. Reagor, H. Paik, G. Catelani, L. Sun, C. Axline, E.T. Holland, I.M. Pop, N.A. Masluk, T. Brecht, L. Frunzio, M.H. Devoret, L.I. Glazman, R. J. Schoelkopf, Reaching 10 ms single photon lifetimes for superconducting aluminum cavities,
*Appl. Phys. Lett.***102,**19 (2013), doi: 10.1063/1.4807015.

Jonathan DuBois

Group Leader, Quantum Coherent Device Physics Group

+19254221406