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Related papers: Reweighting Lefschetz Thimbles

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The complex Langevin (CL) method shows significant potential in addressing the numerical sign problem. Nonetheless, it often produces incorrect results when used without any stabilization techniques. Leveraging insights from previous…

High Energy Physics - Lattice · Physics 2024-12-17 Kirill Boguslavski , Paul Hotzy , David I. Müller

The reweighting method developed in Glasgow to circumvent the lattice action becoming complex at finite density suffers from a pathological onset transition thought to be due to the reweighting. We present a new reweighting scheme based on…

High Energy Physics - Lattice · Physics 2008-11-26 P. R. Crompton

The method of relative weights, coupled with mean field theory, is applied to the problem of simulating gauge theories with dynamical staggered fermions at finite densities. We present initial results and discuss issues so far encountered.

High Energy Physics - Lattice · Physics 2016-11-07 Jeff Greensite , Roman Höllwieser

The Lefschetz-thimble approach to path integrals is applied to a one-site model of electrons, i.e., the one-site Hubbard model. Since the one-site Hubbard model shows a non-analytic behavior at the zero temperature and its path integral…

High Energy Physics - Theory · Physics 2016-03-03 Yuya Tanizaki , Yoshimasa Hidaka , Tomoya Hayata

Path reweighting is a principally exact method to estimate dynamic properties from biased simulations - provided that the path probability ratio matches the stochastic integrator used in the simulation. Previously reported path probability…

Chemical Physics · Physics 2021-03-02 Stefanie Kieninger , Bettina G. Keller

We present density response estimators for Monte Carlo simulations that are based on a reweighting procedure, where the samples of an unperturbed system are used to estimate the properties of a system perturbed by an external harmonic…

The fermion sign problem appearing in the mean-field approximation is considered, and the systematic computational scheme of the free energy is devised by using the Lefschetz-thimble method. We show that the Lefschetz-thimble method…

High Energy Physics - Theory · Physics 2015-06-03 Yuya Tanizaki , Hiromichi Nishimura , Kouji Kashiwa

The concept of Lefschetz thimble decomposition is one of the most promising possible modifications of Quantum Monte Carlo (QMC) algorithms aimed at alleviating the sign problem which appears in many interesting physical situations, e.g. in…

Strongly Correlated Electrons · Physics 2017-12-07 M. V. Ulybyshev , S. N. Valgushev

Picard--Lefschetz theory is applied to path integrals of quantum mechanics, in order to compute real-time dynamics directly. After discussing basic properties of real-time path integrals on Lefschetz thimbles, we demonstrate its…

Mathematical Physics · Physics 2014-09-30 Yuya Tanizaki , Takayuki Koike

Matrix element reweighting is a powerful experimental technique widely employed to maximize the amount of information that can be extracted from a collider data set. We present a procedure that allows to automatically evaluate the weights…

High Energy Physics - Phenomenology · Physics 2011-02-02 P. Artoisenet , V. Lemaître , F. Maltoni , O. Mattelaer

We develop a new real-variable method for weighted $L^p$ estimates. The method is applied to the study of weighted $W^{1, 2}$ estimates in Lipschitz domains for weak solutions of second-order elliptic systems in divergence form with bounded…

Analysis of PDEs · Mathematics 2020-04-08 Zhongwei Shen

We propose a framework to study the properties of the Lefschetz thimbles decomposition for lattice fermion models approaching the thermodynamic limit. The proposed set of algorithms includes the Schur complement solver and the exact…

Strongly Correlated Electrons · Physics 2020-01-29 Maksim Ulybyshev , Christopher Winterowd , Savvas Zafeiropoulos

Reweighting is not a new method in lattice QCD, but a comprehensive analysis is missing in the literature. We close this gap by presenting: (i) a proof of an integral representation of the complex determinant of a complex matrix, (ii) a…

High Energy Physics - Lattice · Physics 2014-04-28 Björn Leder , Jacob Finkenrath , Francesco Knechtli

A simple reweighting scheme is proposed for Monte Carlo simulations of interacting particle systems, permitting one to study various parameter values in a single study, and improving efficiency by an order of magnitude. Unlike earlier…

Statistical Mechanics · Physics 2009-10-31 Ronald Dickman

We propose a new method for the determination of the weight factor for the simulated tempering method. In this method a short replica-exchange simulation is performed and the simulated tempering weight factor is obtained by the…

Statistical Mechanics · Physics 2009-10-31 A. Mitsutake , Y. Okamoto

Many Monte Carlo light transport simulations use multiple importance sampling (MIS) to weight between different path sampling strategies. We propose to use the path throughput to compute the MIS weights instead of the commonly used…

Graphics · Computer Science 2018-09-07 Johannes Jendersie

Direct numerical evaluation of the real-time path integral has a well-known sign problem that makes convergence exponentially slow. One promising remedy is to use Picard-Lefschetz theory to flow the domain of the field variables into the…

High Energy Physics - Lattice · Physics 2019-06-19 Zong-Gang Mou , Paul M. Saffin , Anders Tranberg , Simon Woodward

For Paley-Wiener functions on weighted combinatorial finite or infinite graphs we develop a weighted sampling theory in which samples are defined as inner products with weight functions (measuring devices). Three reconstruction methods are…

Functional Analysis · Mathematics 2019-06-11 Isaac Z. Pesenson

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…

High Energy Physics - Lattice · Physics 2015-06-17 H. Fujii , D. Honda , M. Kato , Y. Kikukawa , S. Komatsu , T. Sano

We study the problem of network regression, where one is interested in how the topology of a network changes as a function of Euclidean covariates. We build upon recent developments in generalized regression models on metric spaces based on…

Machine Learning · Statistics 2024-06-19 Alex G. Zalles , Kai M. Hung , Ann E. Finneran , Lydia Beaudrot , César A. Uribe