Hydrodynamic Backflow for Easing the Fermion Sign in Finite-Temperature Electron Path Integral Simulations
Ingvars Vitenburgs, Jarvist Moore Frost

TL;DR
This paper introduces a hydrodynamical backflow coordinate transformation to mitigate the Fermion sign problem in finite-temperature electron path integral simulations, enabling more accurate and scalable quantum matter modeling.
Contribution
A semi-analytic approach for optimal backflow parameters is developed, significantly reducing the sign problem and computational complexity in electron simulations.
Findings
Backflow transformations reduce the sign problem by multiple orders of magnitude.
Total energy calculations for up to 32 electrons agree with previous studies.
The main computational bottleneck is the $O(N^3)$ Jacobian calculation.
Abstract
Some notable systems, such as room-temperature superconductors and materials for controlled nuclear fusion, require an accurate description of finite-temperature quantum matter. Stochastic path integral methods are finite-temperature and numerically exact, but scale poorly with system size due the notorious Fermion sign problem. To somewhat mitigate this, we use a hydrodynamical backflow coordinate transformation. Our first attempt was a continuous normalizing flow machine learning approach to determine the optimal parameters. We found this to reduce the error of the total energy, approximately, three times at medium sign severity. Numerical issues challenged training effectively. Thus, a semi-analytic approach was developed to estimate the optimal parameters. We do this by using a derived expression dependent on a Bosonic observable. Hence, the calculation of these values does not have…
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