Efficient Quantum Gibbs Sampling with Local Circuits
Dominik Hahn, Ryan Sweke, Abhinav Deshpande, Oles Shtanko

TL;DR
This paper introduces a new quantum algorithm for efficiently preparing thermal states using local circuits, enabling practical quantum simulations of equilibrium phenomena on near-term hardware.
Contribution
It presents a method that avoids complex block encoding, leveraging local circuits and Trotterization for efficient quantum Gibbs sampling, with proven rapid mixing at high temperatures.
Findings
Numerical simulations show the method is feasible on current quantum hardware.
The approach achieves small approximation errors in thermal state preparation.
It provides the first provably efficient quantum thermalization protocol suitable for near-term devices.
Abstract
The problem of simulating the thermal behavior of quantum systems remains a central open challenge in quantum computing. Unlike well-established quantum algorithms for unitary dynamics, \emph{provably efficient} algorithms for preparing thermal states -- crucial for probing equilibrium behavior -- became available only recently with breakthrough algorithms based on the simulation of well-designed dissipative processes, a quantum-analogue to Markov chain Monte Carlo (MCMC) algorithms. We show a way to implement these algorithms avoiding expensive block encoding and relying only on dense local circuits, akin to Hamiltonian simulation. Specifically, our method leverages spatial truncation and Trotterization of exact quasilocal dissipative processes. We rigorously prove that the approximations we use have little effect on rapid mixing at high temperatures and allow convergence to the…
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