Direct Estimation of the Density of States for Fermionic Systems

TL;DR

This paper presents quantum algorithms for estimating the density of states in fermionic systems, enabling efficient thermodynamic property calculations on near-term quantum devices with robustness to noise.

Contribution

The authors introduce a method to estimate the DOS for specific subspaces, compatible with noisy quantum hardware, and demonstrate its effectiveness on fermionic models.

Findings

Efficient DOS estimation for fermionic subspaces.

Robustness against noise and algorithmic errors.

Compatibility with NISQ variational techniques.

Abstract

Simulating time evolution is one of the most natural applications of quantum computers and is thus one of the most promising prospects for achieving practical quantum advantage. Here, we develop quantum algorithms to extract thermodynamic properties by estimating the density of states (DOS), a central object in quantum statistical mechanics. We introduce several innovations that significantly improve the practicality and extend the generality of previous techniques. First, our approach allows one to estimate the DOS only for a specific subspace of the full Hilbert space. This is crucial for fermionic systems, since both canonical and grand canonical ensemble thermal equilibrium properties depend on subspaces of fixed number. Second, in our approach, by time evolving very simple, random initial states, such as randomly chosen computational basis states, we can exactly recover the DOS on average. Third, due to circuit-depth limitations, we only reconstruct the DOS up to a convolution with a Gaussian window - thus all imperfections that shift the energy levels by less than the width of the convolution window will not significantly affect the estimated DOS. For these reasons we find the approach is a promising candidate for early quantum advantage as even short-time, noisy dynamics can yield a semi-quantitative reconstruction of the DOS (convolution with a broad Gaussian window), while early fault tolerant devices will likely enable higher resolution DOS reconstruction through longer time evolutions. We demonstrate the practicality of our approach in representative Fermi-Hubbard and spin models and indeed find that our approach is highly robust against algorithmic errors in the time evolution and against gate noise. We further demonstrate that our approach is compatible with NISQ-friendly variational techniques, introducing and leveraging a new technique for variational time evolution.