Fermionic Quantum Simulation and Computation
Abstract
Modern materials, such as high-TC superconductors, graphene, and colossal magnetoresistive materials hold enormous potential to revolutionize technology- from lessening energy demand via lightweight electric motors, enabling storage devices with extreme data density and reduced power requirements, to providing the strongest and stiffest materials capable of carrying the highest power densities. Currently, implementing these technologies is hindered by our limited understanding of strongly correlated electronic systems. Even simple models that try to capture the underlying physics cannot be solved analytically or numerically, and necessary approximations are uncontrolled. Here we propose a two-pronged approach to ultimately solve problems involving strongly interacting fermions, half-integer spin particles such as electrons- quantum simulation and quantum computation based on fermionic atoms stored in a crystal of light. The quantum simulation approach provides an analog computation of the properties of extended Fermi-Hubbard models, believed to hold the key for understanding high-TC superconductivity. We will demonstrate fermion pairing and superfluidity in the attractive Hubbard model, realize placquette, bilayer and ladder geometries, and furnish transport properties such as sound and heat diffusivities. In the second, digital approach we will explore quantum computation based on fermionic atoms, using the Pauli principle and fermion antisymmetry to stabilize, encode and process quantum information. This may lead to a new paradigm of fermion-based quantum computation that natively implements the fermion sign. Our experiments will realize fundamental models of condensed matter and nuclear physics in the fully controllable environment of atomic quantum gases, with single-atom resolution imaging and control. They may resolve long-standing open problems of many-fermion systems and establish a new method to perform calculations on strongly interacting fermions not possible on classical computers.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 06, 2024
- Source ID
- FA95502310402
Entities
People
- Martin W. Zwierlein
Organizations
- Air Force Office of Scientific Research
- Massachusetts Institute of Technology
- United States Air Force