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This repository contains all raw data that were used to draw conclusions and generate figures for the paper: "Many-body quantum sign structures as non-glassy Ising models" by Westerhout, T., Katsnelson, M. I., & Bagrov, A. A. Abstract: The non-trivial phase structure of the eigenstates of many-body quantum systems severely limits the applicability of quantum Monte Carlo, variational, and machine learning methods. Here, we study real-valued signful ground-state wave functions of frustrated quantum spin systems and, assuming that the tasks of finding wave function amplitudes and signs can be separated, show that the signs can be easily bootstrapped from the amplitudes. We map the problem of finding the sign structure to an auxiliary classical Ising model defined on a subset of the Hilbert space basis. We show that the Ising model does not exhibit significant frustrations even for highly frustrated parental quantum systems, and is solvable with a fully deterministic O(K log K)-time combinatorial algorithm (where K is the Ising model size). Given the ground state amplitudes, we reconstruct the signs of the ground states of several frustrated quantum models, thereby revealing the hidden simplicity of many-body sign structures.
exact diagonalization, spin systems, variational Monte Carlo, quantum many body, sign problem, neural networks, ising model
exact diagonalization, spin systems, variational Monte Carlo, quantum many body, sign problem, neural networks, ising model
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