Generating Generalised Ground-State Ansatzes from Few-Body Examples

Fuente: arXiv
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Main Authors: Lourens, Matt, Sinayskiy, Ilya, Kriel, Johannes N., Petruccione, Francesco
Format: Preprint
Published: 2025
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author Lourens, Matt
Sinayskiy, Ilya
Kriel, Johannes N.
Petruccione, Francesco
author_facet Lourens, Matt
Sinayskiy, Ilya
Kriel, Johannes N.
Petruccione, Francesco
contents We introduce a method that generates ground-state ansatzes for quantum many-body systems which are both analytically tractable and accurate over wide parameter regimes. Our approach leverages a custom symbolic language to construct tensor network states (TNS) via an evolutionary algorithm. This language provides operations that allow the generated TNS to automatically scale with system size. Consequently, we can evaluate ansatz fitness for small systems, which is computationally efficient, while favouring structures that continue to perform well with increasing system size. This ensures that the ansatz captures robust features of the ground state structure. Remarkably, we find analytically tractable ansatzes with a degree of universality, which encode correlations, capture finite-size effects, accurately predict ground-state energies, and offer a good description of critical phenomena. We demonstrate this method on the Lipkin-Meshkov-Glick model (LMG) and the quantum transverse-field Ising model (TFIM), where the same ansatz was independently generated for both. The simple structure of the ansatz allows us to obtain exact expressions for the expectation values of local observables as well as for correlation functions. In addition, it permits symmetries that are broken in the ansatz to be restored, which provides a systematic means of improving the accuracy of the ansatz.
format Preprint
id arxiv_https___arxiv_org_abs_2503_00497
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Generating Generalised Ground-State Ansatzes from Few-Body Examples
Lourens, Matt
Sinayskiy, Ilya
Kriel, Johannes N.
Petruccione, Francesco
Quantum Physics
Strongly Correlated Electrons
We introduce a method that generates ground-state ansatzes for quantum many-body systems which are both analytically tractable and accurate over wide parameter regimes. Our approach leverages a custom symbolic language to construct tensor network states (TNS) via an evolutionary algorithm. This language provides operations that allow the generated TNS to automatically scale with system size. Consequently, we can evaluate ansatz fitness for small systems, which is computationally efficient, while favouring structures that continue to perform well with increasing system size. This ensures that the ansatz captures robust features of the ground state structure. Remarkably, we find analytically tractable ansatzes with a degree of universality, which encode correlations, capture finite-size effects, accurately predict ground-state energies, and offer a good description of critical phenomena. We demonstrate this method on the Lipkin-Meshkov-Glick model (LMG) and the quantum transverse-field Ising model (TFIM), where the same ansatz was independently generated for both. The simple structure of the ansatz allows us to obtain exact expressions for the expectation values of local observables as well as for correlation functions. In addition, it permits symmetries that are broken in the ansatz to be restored, which provides a systematic means of improving the accuracy of the ansatz.
title Generating Generalised Ground-State Ansatzes from Few-Body Examples
topic Quantum Physics
Strongly Correlated Electrons
url https://arxiv.org/abs/2503.00497