Exploring Finite Temperature Properties of Materials with Quantum Computers

TL;DR

This paper introduces a quantum algorithm for preparing thermal pure quantum states to efficiently estimate the thermal properties of quantum materials at finite temperatures, addressing limitations of previous methods.

Contribution

The authors develop and compare three circuit implementations for preparing canonical TPQ states on quantum computers, enabling scalable finite temperature simulations.

Findings

The proposed algorithms accurately estimate thermal properties of quantum materials.

The methods show increasing accuracy with system size.

Flexible implementations suitable for near-term quantum computers.

Abstract

Thermal properties of nanomaterials are crucial to not only improving our fundamental understanding of condensed matter systems, but also to developing novel materials for applications spanning research and industry. Since quantum effects arise at the nano-scale, these systems are difficult to simulate on classical computers. Quantum computers can efficiently simulate quantum many-body systems, yet current quantum algorithms for calculating thermal properties of these systems incur significant computational costs in that they either prepare the full thermal state on the quantum computer, or they must sample a number of pure states from a distribution that grows with system size. Canonical thermal pure quantum (TPQ) states provide a promising path to estimating thermal properties of quantum materials as they neither require preparation of the full thermal state nor require a growing number of samples with system size. Here, we present an algorithm for preparing canonical TPQ states on quantum computers. We compare three different circuit implementations for the algorithm and demonstrate their capabilities in estimating thermal properties of quantum materials. Due to its increasing accuracy with system size and flexibility in implementation, we anticipate that this method will enable finite temperature explorations of relevant quantum materials on near-term quantum computers.