Symmetry-Protected Basin Localization in Variational Quantum Eigensolvers

TL;DR

This paper introduces a geometry-conditioned preconditioner for variational quantum eigensolvers that significantly improves basin localization and reduces initialization errors in molecular simulations.

Contribution

The authors develop a $SE(3)$ covariance-based preconditioner that maps nuclear geometry into circuit parameters, enhancing basin localization and optimization success.

Findings

Reduces Hartree--Fock initialization errors by up to 6250 times.

Achieves sub-millihartree errors in several molecules.

Ensures high success probability in disordered H$_{10}$ chains.

Abstract

Variational quantum eigensolvers fail before optimization begins when strong correlation splits the molecular energy landscape into competing basins and the initial state selects a non-ground-state basin. We introduce a geometry-conditioned preconditioner $\mathcal{P}_{\mathrm{eq}}:\mathbf{R}\mapsto\boldsymbol{\theta}_0$ constrained by the $SE(3)$ covariance of the molecular Hamiltonian, so that nuclear geometry is mapped directly into circuit parameters in the correlated ground-state basin. This basin localization changes the relevant gradient statistics from concentration controlled to curvature controlled. In statevector benchmarks on six stretched molecules, $\mathcal{P}_{\mathrm{eq}}$ reduces Hartree--Fock initialization errors by factors of $38\times$--$6250\times$, reaches sub-mHa initialization in CO, LiH, and H$_8$, and places N$_2$, H$_2$O, and BeH$_2$ in the mHa-scale correlated basin. In disordered H$_{10}$ chains, equivariant basin targeting and stochastic escape reach unit success probability at fixed optimization budget. The procedure performs basin selection before the shot-limited quantum loop; the quantum circuit then refines correlation inside the selected basin.