The Non-Linear Sigma Model (NLSM) is an example of a field theory on a target space exhibiting intricate geometry. One remarkable characteristic of the NLSM is asymptotic freedom, which triggers interest in perturbative calculations. In the lattice formulation of NLSM, one would naturally rely on Numerical Stochastic Perturbation Theory (NSPT) to conduct high-order computations. However, when dealing with low-dimensional systems, NSPT reveals increasing statistical fluctuations with higher and higher orders. This of course does not come as a surprise and one is ready to live with this, as long as the noise is not going to completely kill the signal, which unfortunately in some models does take place. We investigate how, in the O(N) context, this behaviour strongly depends on N. As expected, larger N values make higher-order computations feasible.

Taming NSPT fluctuations in O(N) Non-Linear Sigma Model: simulations in the large N regime / Baglioni, P.; Di Renzo, F.. - In: POS PROCEEDINGS OF SCIENCE. - ISSN 1824-8039. - 451:(2024). (Intervento presentato al convegno 2023 European Network for Particle Physics, Lattice Field Theory and Extreme Computing, EuroPLEx 2023 tenutosi a Humboldt-Universitat zu Berlin, D nel 11 September 2023 through 15 September 2023) [10.22323/1.451.0030].

Taming NSPT fluctuations in O(N) Non-Linear Sigma Model: simulations in the large N regime

Baglioni P.
;
Di Renzo F.
2024-01-01

Abstract

The Non-Linear Sigma Model (NLSM) is an example of a field theory on a target space exhibiting intricate geometry. One remarkable characteristic of the NLSM is asymptotic freedom, which triggers interest in perturbative calculations. In the lattice formulation of NLSM, one would naturally rely on Numerical Stochastic Perturbation Theory (NSPT) to conduct high-order computations. However, when dealing with low-dimensional systems, NSPT reveals increasing statistical fluctuations with higher and higher orders. This of course does not come as a surprise and one is ready to live with this, as long as the noise is not going to completely kill the signal, which unfortunately in some models does take place. We investigate how, in the O(N) context, this behaviour strongly depends on N. As expected, larger N values make higher-order computations feasible.
2024
Taming NSPT fluctuations in O(N) Non-Linear Sigma Model: simulations in the large N regime / Baglioni, P.; Di Renzo, F.. - In: POS PROCEEDINGS OF SCIENCE. - ISSN 1824-8039. - 451:(2024). (Intervento presentato al convegno 2023 European Network for Particle Physics, Lattice Field Theory and Extreme Computing, EuroPLEx 2023 tenutosi a Humboldt-Universitat zu Berlin, D nel 11 September 2023 through 15 September 2023) [10.22323/1.451.0030].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/3018977
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