Quantum computing
Creating new computing paradigms capable of solving research problems that state-of-the-art exascale computers cannot solve.
LLNL is home to some of the world’s most powerful supercomputers, but even those powerful resources don’t meet the increasing computational demands of our national security mission. Quantum technologies may be part of the solution.
The Quantum Design and Integration Testbed is a nexus for quantum computing research at LLNL. It offers a state-of-the-art research environment for device- and system- level research with superconducting quantum processors. This unique experimental platform supports research on the materials science of quantum devices, on novel quantum hardware, on system engineering to improve the classical control of quantum systems, and on quantum algorithms.
Working collaboratively in the testbed’s codesign environment, device and system developers work side-by-side with physicists and chemists to explore mission-relevant applications of quantum computing. The testbed provides both a stable system that LLNL researchers and their collaborators can access, enabling them to study how to control quantum computers and their future integration with high performance computing and experimental platforms for improving quantum coherent devices.
In addition to enabling scientific breakthroughs, the testbed plays a key role in LLNL’s efforts to develop staff expertise in quantum information systems. It provides opportunities for tomorrow’s quantum experts to gain the knowledge they need to meet future challenges.
LLNL’s quantum computing research reaches beyond the testbed. LLNL’s expertise in advanced manufacturing, detailed physical modeling, and numerical optimization has enabled us to make key advances and demonstrations for other hardware platforms and to refute early claims of quantum advantage.
Learn more about quantum computing at LLNL
- Low-frequency correlated charge-noise measurements across multiple energy transitions in a tantalum transmon
- Quandary: Scalable Quantum Optimal Control
- Quandary: An open-source C++ package for high-performance optimal control of open quantum systems
- New research proves quantum computing errors correlated, ties them to cosmic rays
- High-fidelity software-defined quantum logic on a superconducting qudit
- Pareto-Efficient Quantum Circuit Simulation Using Tensor Contraction Deferral
Quantum simulation and algorithms
Enabling direct simulation of complex quantum phenomena, such as nucleon scattering and the physics of matter at extreme conditions.
Today’s small, noisy quantum computers allow us to simulate many body dynamics and develop quantum algorithms for pathfinder applications in our mission space. These applications will provide initial demonstrations of advantageous quantum technologies, informing the next generation of hardware and ensuring that, as the hardware scales, it meets our mission needs.
For example, LLNL scientists are developing quantum algorithms to model nuclear dynamics and exploring ways to scale those algorithms to larger quantum systems. These efforts involve close collaboration between LLNL’s nuclear theorists and quantum hardware experts. Quantum algorithms also hold promise for simulating high-energy-density science phenomena, such as fusion plasmas and warm-dense matter regimes.
Learn more about quantum simulation and algorithm research at LLNL
- Quantum algorithm for the advection-diffusion equation and the Koopman-von Neumann approach to nonlinear dynamical systems
- Evaluation of phase shifts for nonrelativistic elastic scattering using quantum computers
- Preparing angular momentum eigenstates using engineered quantum walks
- Simulating Nonlinear Radiation Diffusion Through Quantum Computing
Quantum sensing
Using highly precise sensing capabilities to image living cells, understand decoherence in qubits, and detect hidden objects.
For many years, LLNL researchers have developed quantum sensing technologies that are based on quantum phenomena but do not involve entanglement. For example, the Axion Dark Matter Experiment, first developed at LLNL, uses superconducting detectors to search for these elusive low-mass particles. Our researchers also develop micromagnetic calorimeters that are used in radioactive isotope forensics.
Now that entanglement is being used in sensing technologies, LLNL scientists are developing gravity sensors based on ultra-cold atoms, ultra-precise nuclear clocks, single-photon detectors and emitters, and magnetic field detectors. This type of technology supports mission-relevant challenges such as uncovering heavy-mass shielding and tunnel detection. In addition, we are exploring new signal-processing techniques that exploit the enhanced sensitivity enabled by quantum technology. As the technology continues to mature, research teams are exploring ways to adapt it to read out signals from future quantum computers and enable improved control.
Learn more about LLNL’s quantum sensing research
Material research and development
Our materials science experts are developing and optimizing advanced materials that will serve as the essential building blocks of scalable quantum systems. Because quantum devices are exceptionally sensitive to noise and loss from material defects and impurities, LLNL scientists combine multi-scale modeling techniques and experiments to understand and mitigate microscopic defects in materials used to develop quantum devices.
Our scientists also design novel materials that will enable the development of new types of quantum systems. For example, we are developing topological materials that can help address the scalability requirements for quantum hardware. In addition, we are exploring novel fabrication processes to expand design options, provide a high degree of customizability, and improve performance.
Learn more about quantum material research at LLNL
- Edge magnetoplasmon dispersion and time-resolved plasmon transport in a quantum anomalous Hall insulator
- Simulating noise on a quantum processor: interactions between a qubit and resonant two-level system bath
- Electric-field noise from thermally activated fluctuators in a surface ion trap
- High-kinetic inductance additive manufactured superconducting microwave cavity
Quantum–coherent device development
The building blocks of a quantum system are its highly specialized components, which enable a system to be isolated enough to probe its quantum state. At LLNL, our teams are exploring novel ways to fabricate macroscopic quantum mechanical circuits, which can help us scale the capabilities of devices used in quantum computing and sensing. To reduce noise sensitivity in ion-based quantum processors, we leverage our advanced manufacturing expertise to develop three-dimensional ion traps, while also exploring novel control methods such as microwave gates.
We also leverage our expertise in photon science to develop new imaging modalities that leverage the multiple dimensions of entanglement found in photon pairs to obtain 3D images. In addition, we are exploring how defect centers (impurities) in semiconductor materials can be exploited to enable single-photon emitters and other types of quantum photonics that could be used in quantum devices.
Learn more about LLNL’s research in quantum–coherent device development
Quantum systems engineering
Quantum systems require classical interfaces to allow control and measurement by conventional computing hardware. Drawing on their expertise in photon science and computer science, LLNL researchers are developing scalable quantum–classical interfaces that are optimized to enable low noise, high-fidelity control and measurement—and achieve useful information retrieval from quantum systems.
Our scientists are also exploring ways to integrate quantum resources with LLNL’s high performance computing (HPC) resources. For example, we are developing noise-resilient quantum computing protocols that can be used to explore hybrid algorithms, which are distributed between classical and quantum platforms. These pathfinder protocols are the prototypes for future computing environments where HPC resources can leverage quantum processor units to address specific types of challenges, similar to how graphical processing units are incorporated into HPC resources today.
