Dimensionality reduction through tensor factorization : application to \textit{ab initio} nuclear physics calculations

Fuente: arXiv
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Main Authors: Frosini, Mikael, Duguet, Thomas, Tamagno, Pierre, Zurek, Lars
Format: Preprint
Published: 2024
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_version_ 1866910541700661248
author Frosini, Mikael
Duguet, Thomas
Tamagno, Pierre
Zurek, Lars
author_facet Frosini, Mikael
Duguet, Thomas
Tamagno, Pierre
Zurek, Lars
contents The construction of predictive models of atomic nuclei from first principles is a challenging (yet necessary) task towards the systematic generation of theoretical predictions (and associated uncertainties) to support nuclear data evaluation. The consistent description of the rich phenomenology of nuclear systems indeed requires the introduction of reductionist approaches that construct nuclei directly from interacting nucleons by solving the associated quantum many-body problem. In this context, so-called \textit{ab initio} methods offer a promising route by deriving controlled (and systematically improvable) approximations both to the inter-nucleon interaction and to the solutions of the many-body problem. From a technical point of view, approximately solving the many-body Schrödinger equation in heavy open-shell systems typically requires the construction and contraction of large mode-4 (mode-6) tensors that need to be stored repeatedly. Recently, a new dimensionality reduction method based on randomized singular value decomposition has been introduced to reduce the numerical cost of many-body perturbation theory. This work applies this lightweight formalism to the study of the Germanium isotopic chain, where standard approaches would be too expansive to run. Inclusion of triaxiality is found to improve the overall agreement with experimental data on differential quantities.
format Preprint
id arxiv_https___arxiv_org_abs_2407_17971
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Dimensionality reduction through tensor factorization : application to \textit{ab initio} nuclear physics calculations
Frosini, Mikael
Duguet, Thomas
Tamagno, Pierre
Zurek, Lars
Nuclear Theory
The construction of predictive models of atomic nuclei from first principles is a challenging (yet necessary) task towards the systematic generation of theoretical predictions (and associated uncertainties) to support nuclear data evaluation. The consistent description of the rich phenomenology of nuclear systems indeed requires the introduction of reductionist approaches that construct nuclei directly from interacting nucleons by solving the associated quantum many-body problem. In this context, so-called \textit{ab initio} methods offer a promising route by deriving controlled (and systematically improvable) approximations both to the inter-nucleon interaction and to the solutions of the many-body problem. From a technical point of view, approximately solving the many-body Schrödinger equation in heavy open-shell systems typically requires the construction and contraction of large mode-4 (mode-6) tensors that need to be stored repeatedly. Recently, a new dimensionality reduction method based on randomized singular value decomposition has been introduced to reduce the numerical cost of many-body perturbation theory. This work applies this lightweight formalism to the study of the Germanium isotopic chain, where standard approaches would be too expansive to run. Inclusion of triaxiality is found to improve the overall agreement with experimental data on differential quantities.
title Dimensionality reduction through tensor factorization : application to \textit{ab initio} nuclear physics calculations
topic Nuclear Theory
url https://arxiv.org/abs/2407.17971