Zero and Finite Temperature Quantum Simulations Powered by Quantum Magic

TL;DR

This paper presents a quantum information-inspired method that simplifies many-body Hamiltonians, enabling more efficient quantum simulations of quantum chemistry at zero and finite temperatures on near-term devices.

Contribution

The authors introduce a class of classical-identified similarity transformations that simplify Hamiltonians, improving quantum chemistry calculations on near-term quantum hardware.

Findings

Significant performance improvements in free energy calculations.

Outperforms traditional Hartree-Fock solutions.

Performance gap widens with higher transformation quality.

Abstract

We introduce a quantum information theory-inspired method to improve the characterization of many-body Hamiltonians on near-term quantum devices. We design a new class of similarity transformations that, when applied as a preprocessing step, can substantially simplify a Hamiltonian for subsequent analysis on quantum hardware. By design, these transformations can be identified and applied efficiently using purely classical resources. In practice, these transformations allow us to shorten requisite physical circuit-depths, overcoming constraints imposed by imperfect near-term hardware. Importantly, the quality of our transformations is tunable: we define a 'ladder' of transformations that yields increasingly simple Hamiltonians at the cost of more classical computation. Using quantum chemistry as a benchmark application, we demonstrate that our protocol leads to significant performance improvements for zero and finite temperature free energy calculations on both digital and analog quantum hardware. Specifically, our energy estimates not only outperform traditional Hartree-Fock solutions, but this performance gap also consistently widens as we tune up the quality of our transformations. In short, our quantum information-based approach opens promising new pathways to realizing useful and feasible quantum chemistry algorithms on near-term hardware.