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The great majority of algorithms employed in the study of lattice field theory are based on Monte Carlo's importance sampling method, i.e. on probability interpretation of the Boltzmann weight. Unfortunately in many theories of interest one…

高能物理 - 格点 · 物理学 2016-06-03 Lorenzo Bongiovanni

We consider a hybrid Monte Carlo algorithm which is applicable to lattice theories defined on Lefschetz thimbles. In the algorithm, any point (field configuration) on a thimble is parametrized uniquely by the flow-direction and the…

高能物理 - 格点 · 物理学 2015-06-17 H. Fujii , D. Honda , M. Kato , Y. Kikukawa , S. Komatsu , T. Sano

It is sometimes speculated that the sign problem that afflicts many quantum field theories might be reduced or even eliminated by choosing an alternative domain of integration within a complexified extension of the path integral (in the…

高能物理 - 格点 · 物理学 2015-07-14 AuroraScience Collaboration , Marco Cristoforetti , Francesco Di Renzo , Luigi Scorzato

The generalized Lefschetz thimble method is a promising approach that attempts to solve the sign problem in Monte Carlo methods by deforming the integration contour using the flow equation. Here we point out a general problem that occurs…

高能物理 - 格点 · 物理学 2024-04-26 Jun Nishimura , Katsuta Sakai , Atis Yosprakob

The sign problem of relativistic field theories at finite fermion chemical potential has been approached by deforming the domain of integration into complex field space. We present a method for selecting a deformed manifold of integration…

高能物理 - 格点 · 物理学 2018-10-17 Scott Lawrence

The numerical sign problem is a major obstacle to the quantitative understanding of many important physical systems with first-principles calculations. Typical examples for such systems include finite-density QCD, strongly-correlated…

高能物理 - 格点 · 物理学 2022-05-03 Masafumi Fukuma , Nobuyuki Matsumoto , Yusuke Namekawa

A method is developed which speeds up averaging in quantum simulations where minus signs cause difficulties. A Langevin equation method in conjunction with a replication algorithm is used enabling one to average over a continuously varying…

comp-gas · 物理学 2009-10-22 J. M. Deutsch

A solution to the sign problem is the so-called "Lefschetz thimble approach" where the domain of integration for field variables in the path integral is deformed from the real axis to a sub-manifold in the complex space. For properly chosen…

高能物理 - 格点 · 物理学 2016-06-01 Andrei Alexandru , Gokce Basar , Paulo F. Bedaque , Gregory W. Ridgway , Neill C. Warrington

We suggest an approach for simulating theories with a sign problem that relies on optimisation of complex integration contours that are not restricted to lie along Lefschetz thimbles. To that end we consider the toy model of a…

高能物理 - 格点 · 物理学 2018-12-11 Francis Bursa , Michael Kroyter

The Picard-Lefschetz theory has been attracting much attention as a tool to evaluate a multi-variable integral with a complex weight, which appears in various important problems in theoretical physics. The idea is to deform the integration…

高能物理 - 格点 · 物理学 2022-06-10 Genki Fujisawa , Jun Nishimura , Katsuta Sakai , Atis Yosprakob

Many fascinating systems suffer from a severe (complex action) sign problem preventing us from calculating them with Markov Chain Monte Carlo simulations. One promising method to alleviate the sign problem is the transformation of the…

强关联电子 · 物理学 2022-11-18 Marcel Rodekamp , Christoph Gäntgen

Lattice Monte Carlo calculations of interacting systems on non-bipartite lattices exhibit an oscillatory imaginary phase known as the phase or sign problem, even at zero chemical potential. One method to alleviate the sign problem is to…

强关联电子 · 物理学 2021-03-31 Jan-Lukas Wynen , Evan Berkowitz , Stefan Krieg , Thomas Luu , Johann Ostmeyer

Nowadays the term 'sign problem' is used to identify two different problems. The ideas to overcome the first type of the 'sign problem' of strongly oscillating complex valued imtegrand in the Feynman path integrals comes from…

统计力学 · 物理学 2020-03-04 Vladimir Filinov , Alexander Larkin

The complex Langevin approach is a promising method for the numerical treatment of systems with a sign problem, for which conventional lattice field theory techniques based on importance sampling cannot be applied. However, complex Langevin…

高能物理 - 格点 · 物理学 2026-04-15 Michael Mandl

Deforming the domain of integration after complexification of the field variables is an intriguing idea to tackle the sign problem. In thimble regularization the domain of integration is deformed into an union of manifolds called Lefschetz…

高能物理 - 格点 · 物理学 2021-11-30 Kevin Zambello , Francesco Di Renzo , Simran Singh

One of the main challenges in simulations on Lefschetz thimbles is the computation of the relative weights of contributing thimbles. In this paper we propose a solution to that problem by means of computing those weights using a reweighting…

In recent years, there has been remarkable progress in theoretical justification of the complex Langevin method, which is a promising method for evading the sign problem in the path integral with a complex weight. There still remains,…

高能物理 - 格点 · 物理学 2015-12-09 Jun Nishimura , Shinji Shimasaki

We consider a generalization of the Thirring model in 2+1 dimensions at finite density. We employ stochastic quantization and check for the applicability in the finite density case to circumvent the sign problem. To this end we derive…

高能物理 - 格点 · 物理学 2013-05-23 Jan M. Pawlowski , Christian Zielinski

Path integrals with complex actions are encountered for many physical systems ranging from spin- or mass-imbalanced atomic gases and graphene to quantum chromo-dynamics at finite density to the non-equilibrium evolution of quantum systems.…

高能物理 - 格点 · 物理学 2022-09-01 Lukas Kades , Martin Gärttner , Thomas Gasenzer , Jan M. Pawlowski

Monte Carlo simulations are useful tools for modeling quantum systems, but in some cases they suffer from a sign problem, leading to an exponential slow down in their convergence to a value. While solving the sign problem is generically…

量子物理 · 物理学 2022-12-21 T. C. Mooney , Jacob Bringewatt , Neill C. Warrington , Lucas T. Brady