QIS & Computational Physics

QIS and Computational Physics

The LBNL QuantISED Quest Program brings together research initiatives started with FY18 QuantISED funding. The program has three research components: QIS for HEP, HEP for QIS, and Quantum computation. While each of these components has a well defined scope, there is a strong connection between them, making for a unified program that benefits from having all three elements. The program aims to be a hub for technology development. To that effect, already strong partnerships with university groups have been expanded, to benefit from expertise across and outside HEP.

Six institutes are partnered with LBNL: UC Berkeley, Caltech, U. of Massachusetts Amherst, Princeton U., Texas A&M U., and Yale U.

The QIS for HEP work aims to reach single quantum sensing, exploiting QIS developments, to enable future world leading searches for particle dark matter (DM) at low mass (MeV range down to sub-eV). It includes both sensor and target material R&D to make future experiments possible. Sensor development will focus on: Transition Edge Sensors (TES) and Kinetic Inductance Detectors (KID) for measuring athermal phonon energy, and Superconducting Nanowire Single Photon Detectors (SNSPD) for infrared photons and single He atoms. Superfluid He work will develop quantum evaporation of atoms from the liquid He surface and ejection of electrons specially prepared on He films (originally developed as qubits). All these technologies aim at measuring quanta with energies of 1-10\,meV- two orders of magnitude better than present state-of-the-art. Additionally, development of opto-mechanical cavities in liquid He aims to reach the $\mu$eV range for discrete energies. Theoretical work on DM coupling to coherent excitations informs this development and also finds new quantum materials that can enhance DM detection, some of which will be produced and measured.

The HEP for QIS work applies the above experience, theory, and sensors to study and improve superconducting qubit devices. It also applies particle physics data acquisition methods to control and read out qubits and qutrits. The above DM techniques are fundamentally about the production, transport, and measurement of quasiparticles (coherent excitations) in DM target materials.
Such quasiparticles are a major concern for qubit performance, as their presence causes degradation. With the above tools, both experimental and theoretical, we can study this problem in a systematic way, leading to better qubit device modeling and fabrication. For superconducting qubit readout, present technology does not scale to large systems. Development will focus on room temperature FPGA-based control and readout electronics, and cold transmission and multiplexing techniques.

Complementary to the above device-oriented work, the program will develop quantum computing applications in three directions. It will use quantum computing to calculate and simulate particle physics processes that are intractable with classical computers: notably collisions with many final state particles, of great interest for Large Hadron Collider physics. The program will emulate on ternary logic quantum devices (qutrits) the process of information scrambling and recovery thought to take place in black holes, as well as investigating the ground state of such devices. And it will use quantum computing hardware and algorithms to study highly combinatorial pattern recognition tasks necessary to analyze data from particle physics experiments.