Year: 2024
Type: preprint
Abstract: Quantum dynamics can be analyzed via the structure of energy eigenstates. However, in the many-body setting, preparing eigenstates associated with finite temperatures requires time scaling exponentially with system size. In this work we present an efficient quantum search algorithm which produces quasi-stationary states, having energies supported within narrow windows of a dense many-body spectrum. In time scaling polynomially with system size, the algorithm produces states with inverse polynomial energy width, which can in turn be used to analyze many-body dynamics out to polynomial times. The algorithm is based on quantum singular value transformations and quantum signal processing, and provides a quadratic speedup over measurement-based approaches. We discuss how this algorithm can be used as a primitive to investigate the mechanisms underlying thermalization and hydrodynamics in many-body quantum systems.
Source: arXiv (Cornell University)
Authors: Garratt, Samuel J., Choi, Soonwon
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: G149988304, G2595738051, Second Phase of the QuantEmX Scientist Exchange Program, G543303420, CAREER: Probing Quantum Matter using Programmable Quantum Simulators, THE GEOMETRY AND FLOW OF QUANTUM INFORMATION: FROM QUANTUM GRAVITY TO QUANTUM TECHNOLOGY, G638484911, Center for Ultracold Atoms, Programs on Critical Problems in Physics, Astrophysics and Biophysics at the Aspen Center for Physics, THE GEOMETRY AND FLOW OF QUANTUM INFORMATION: FROM QUANTUM GRAVITY TO QUANTUM TECHNOLOGY
OpenAlex ID: W4400601294