Algorithm for initializing a generalized fermionic Gaussian state on a quantum computer

TL;DR

This paper develops an analytical method for efficiently evaluating expectation values of fermionic operators in generalized Gaussian states, enabling improved variational algorithms for quantum many-body problems on quantum computers.

Contribution

It derives explicit iterative expressions for expectation values and introduces a gradient-based optimization algorithm for fermionic Gaussian states, enhancing quantum variational methods.

Findings

Provides closed-form energy functional and gradient expressions.

Introduces a simple gradient descent algorithm with guaranteed energy decrease.

Suggests improved initial states for quantum algorithms.

Abstract

We present explicit expressions for the central piece of a variational method developed by Shi et al. which extends variational wave functions that are efficiently computable on classical computers beyond mean-field to generalized Gaussian states [1]. In particular, we derive iterative analytical expressions for the evaluation of expectation values of products of fermionic creation and annihilation operators in a Grassmann variable-free representation. Using this result we find a closed expression for the energy functional and its gradient of a general fermionic quantum many-body Hamiltonian. We present a simple gradient-descent-based algorithm that can be used as an optimization subroutine in combination with imaginary time evolution, which by construction guarantees a monotonic decrease of the energy in each iteration step. Due to the simplicity of the quantum circuit implementing the variational state Ansatz, the results of the algorithms discussed here and in [1] could serve as an improved, beyond mean-field initial state in quantum computation. [1] Tao Shi, Eugene Demler, and J. Ignacio Cirac. Variational study of fermionic and bosonic systems with non-gaussian states: Theory and applications. Annals of Physics, 390: 245-302, 2018.