Unitary Encoding of Thermal States via Thermofield Dynamics on Quantum Computers

TL;DR

This paper introduces a NISQ-friendly quantum algorithm for preparing and evolving thermal states using Thermofield Dynamics, enabling thermal quantum simulations on near-term quantum devices.

Contribution

The authors develop a gate-based quantum algorithm that efficiently prepares finite-temperature states with linear circuit depth, suitable for NISQ hardware.

Findings

Benchmark results show magnetization matches exact analytical results.

Temperature-dependent damping observed in simulations agrees with analytical predictions.

The protocol is scalable and suitable for studying dissipative phenomena.

Abstract

Quantum computing has attracted the attention of the scientific community in the past few decades. However, despite some relevant advantages, near-term quantum devices remain severely limited by thermal effects, which induce decoherence and restrict coherent control at finite temperature. In this regard, this work reports a gate-based quantum algorithm that prepares the finite-temperature vacuum of Thermofield Dynamics (TFD) and tracks its real-time evolution. The circuit depth scales linearly with system size and requires only single-qubit rotations and nearest-neighbor CNOT gates, making it NISQ-friendly. We benchmark the protocol on the PennyLane simulator: magnetization of a spin-$1/2$ particle in a magnetic field agrees with the exact result $M(\beta)=\tanh(\beta\omega/2)$ to machine precision, and the coherent precession acquires a temperature-dependent damping that quantitatively matches the analytical TFD prediction. Our work provides a ready-to-deploy toolbox for thermal quantum simulations and opens a route to study dissipative phase transitions, quantum thermodynamics and thermal machine-learning models on near-term devices.