Quantum many-body simulation of finite-temperature systems with sampling a series expansion of a quantum imaginary-time evolution
Simulating thermal-equilibrium properties at finite temperature is crucial for studying quantum many-body systems. Quantum computers are expected to enable us to simulate large systems at finite temperatures, overcoming challenges faced by classical computers, like the sign problem of the quantum Mo...
Saved in:
Main Authors | , , , , , , , |
---|---|
Format | Journal Article |
Language | English |
Published |
11.09.2024
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Simulating thermal-equilibrium properties at finite temperature is crucial
for studying quantum many-body systems. Quantum computers are expected to
enable us to simulate large systems at finite temperatures, overcoming
challenges faced by classical computers, like the sign problem of the quantum
Monte-Carlo technique. Conventional methods suitable for fault-tolerant quantum
computing (FTQC) devices are designed for studying large-scale quantum
many-body systems but require a large number of ancilla qubits and a deep
quantum circuit with many basic gates, making them unsuitable for the early
stage of the FTQC era, at which the availability of qubits and quantum gates is
limited. In this paper, we propose a method suitable for quantum devices in
this early stage to calculate the thermal-equilibrium expectation value of an
observable at finite temperatures. Our proposal, named the Markov-chain Monte
Carlo with sampled pairs of unitaries (MCMC-SPU) algorithm, involves sampling
simple quantum circuits and generating the corresponding statistical ensembles.
This approach addresses the issues of resource demand and the decay in
probability associated with postselection of measurement outcomes on ancilla
qubits. We validate our proposal with numerical simulation on the
one-dimensional transverse-field Ising model as an illustrative example. |
---|---|
DOI: | 10.48550/arxiv.2409.07070 |