26 July 2026 to 1 August 2026
University of Maryland, College Park
US/Eastern timezone

Projected Density Matrix Sampling for Quantum Lattice Hamiltonians

28 Jul 2026, 16:10
20m
Benjamin Banneker B (Adele H. Stamp Student Union)

Benjamin Banneker B

Adele H. Stamp Student Union

3972 Campus Dr, College Park, MD 20742
Algorithms and artificial intelligence Algorithms and artificial intelligence

Speaker

Prof. Shailesh Chandrasekharan (Duke University)

Description

We present a continuous-time path-integral Monte Carlo method for computing the low-lying spectrum of generic quantum lattice Hamiltonians, motivated in part by applications to qubit regularizations of quantum field theories. The method is based on projecting the thermal density matrix, $e^{-\beta H}$, onto a subspace spanned by a chosen set of linearly independent states. It is free of Trotter discretization errors and systematically converges, with increasing $\beta$, to low-energy states that have finite overlap with the projection subspace. While most effective for systems without a sign problem, it can also provide information about low-energy spectra of systems with sign-problems. Some applications are presented to illustrate the method.

Author

Prof. Shailesh Chandrasekharan (Duke University)

Presentation materials