Algorithmic Quantum Simulations of Quantum Thermodynamics

TL;DR

This paper introduces quantum algorithms for simulating quantum thermodynamics on quantum computers, enabling the calculation of thermodynamic properties with high accuracy for complex materials.

Contribution

It develops a general quantum kernel function expansion framework for computing thermodynamic potentials, demonstrated on superconducting qubits with exact agreement.

Findings

Quantum simulations match exact results for Ising and XY models.

The approach computes thermodynamic properties like entropy and heat capacity.

Framework applicable to material design and drug development.

Abstract

Characterizing quantum phases-of-matter at finite-temperature is essential for understanding complex materials and large-scale thermodynamic phenomena. Here, we develop algorithmic protocols for simulating quantum thermodynamics on quantum hardware through quantum kernel function expansion (QKFE), producing the free energy as an analytic function of temperature with uniform convergence. These protocols are demonstrated by simulating transverse field Ising and XY models with superconducting qubits. In both analogue and digital implementations of the QKFE algorithms, we exhibit quantitative agreement of our quantum simulation experiments with the exact results. Our approach provides a general framework for computing thermodynamic potentials on programmable quantum devices, granting access to key thermodynamic properties such as entropy, heat capacity and criticality, with far-reaching implications for material design and drug development.