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Lattice models with complex actions are important for the understanding of matter at finite densities, but not accessible by the standard Monte Carlo techniques due to the sign problem. Here we derive a new approach for avoiding the complex…

High Energy Physics - Lattice · Physics 2017-09-06 Vasily Sazonov

The standard perturbative weak-coupling expansions in lattice models are asymptotic. The reason for this is hidden in the incorrect interchange of the summation and integration. However, substituting the Gaussian initial approximation of…

High Energy Physics - Theory · Physics 2017-01-04 Aleksandr S. Ivanov , Vasily K. Sazonov

We introduce a Monte Carlo method, as a modification of existing cluster algorithms, which allows simulations directly on systems of infinite size, and for quantum models also at beta=infinity. All two-point functions can be obtained,…

Statistical Mechanics · Physics 2007-05-23 H. G. Evertz , W. von der Linden

We present a comprehensive discussion on lattice techniques for the simulation of scalar and gauge field dynamics in an expanding universe. After reviewing the continuum formulation of scalar and gauge field interactions in Minkowski and…

Cosmology and Nongalactic Astrophysics · Physics 2021-11-08 Daniel G. Figueroa , Adrien Florio , Francisco Torrenti , Wessel Valkenburg

In this paper we consider interpolation problem connected with series by integer shifts of Gaussians. Known approaches for these problems met numerical difficulties. Due to it another method is considered based on finite-rank approximations…

Classical Analysis and ODEs · Mathematics 2020-07-07 S. M. Sitnik , A. S. Timashov , S. N. Ushakov

We present a simple and powerful method for extrapolating finite-volume Monte Carlo data to infinite volume, based on finite-size-scaling theory. We discuss carefully its systematic and statistical errors, and we illustrate it using three…

High Energy Physics - Lattice · Physics 2009-10-28 Sergio Caracciolo , Robert G. Edwards , Sabino J. Ferreira , Andrea Pelissetto , Alan D. Sokal

Introducing inequality constraints in Gaussian process (GP) models can lead to more realistic uncertainties in learning a great variety of real-world problems. We consider the finite-dimensional Gaussian approach from Maatouk and Bay (2017)…

Machine Learning · Statistics 2021-11-04 Andrés F. López-Lopera , François Bachoc , Nicolas Durrande , Olivier Roustant

A quantum Monte Carlo algorithm for the transverse Ising model with arbitrary short- or long-range interactions is presented. The algorithm is based on sampling the diagonal matrix elements of the power series expansion of the density…

Statistical Mechanics · Physics 2007-05-23 Anders W. Sandvik

We present a simple and powerful method for extrapolating finite-volume Monte Carlo data to infinite volume, based on finite-size-scaling theory. We discuss carefully its systematic and statistical errors, and we illustrate it using three…

High Energy Physics - Lattice · Physics 2009-10-22 Sergio Caracciolo , Robert G. Edwards , Sabino José Ferreira , Andrea Pelissetto , Alan D. Sokal

New algorithm of the finite lattice method is presented to generate the high-temperature expansion series of the Ising model. It enables us to obtain much longer series in three dimensions when compared not only to the previous algorithm of…

High Energy Physics - Lattice · Physics 2009-11-07 H. Arisue , T. Fujiwara

As the particle count escalates, the computational demands of diverse simulation algorithms surge, paralleled by a marked enhancement in accuracy. The question arises whether this heightened precision asymptotically dwindles towards zero or…

Computational Physics · Physics 2025-01-08 Yonglong Ding

Due to their flexibility, Gaussian processes (GPs) have been widely used in nonparametric function estimation. A prior information about the underlying function is often available. For instance, the physical system (computer model output)…

Methodology · Statistics 2017-11-21 Hassan Maatouk

We develop and implement new probabilistic strategy for proving basic results about long time behaviour for interacting diffusion processes on unbounded lattice. The concept of the solution used is rather weak as we construct the process as…

Probability · Mathematics 2016-11-08 Frantisek Zak

This paper presents a new model called infinite mixtures of multivariate Gaussian processes, which can be used to learn vector-valued functions and applied to multitask learning. As an extension of the single multivariate Gaussian process,…

Machine Learning · Computer Science 2013-07-29 Shiliang Sun

Gaussian process (GP) models provide a powerful tool for prediction but are computationally prohibitive using large data sets. In such scenarios, one has to resort to approximate methods. We derive an approximation based on a composite…

Machine Learning · Statistics 2018-02-02 Xiuming Liu , Dave Zachariah , Edith C. H. Ngai

Fractional Gaussian fields provide a rich class of spatial models and have a long history of applications in multiple branches of science. However, estimation and inference for fractional Gaussian fields present significant challenges. This…

Methodology · Statistics 2022-02-22 Somak Dutta , Debashis Mondal

A trial application of the method of Feynman-Kleinert approximants is made to perturbation series arising in connection with the lattice Schwinger model. In extrapolating the lattice strong-coupling series to the weak-coupling continuum…

High Energy Physics - Lattice · Physics 2009-11-10 T. M. R. Byrnes , C. J. Hamer , Zheng Weihong , S. Morrison

An efficient Quantum Monte Carlo algorithm for the simulation of bosonic systems on a lattice in a grand canonical ensemble is proposed. It is based on the mapping of bosonic models to the spin models in the limit of the infinite total spin…

Statistical Mechanics · Physics 2007-05-23 Jurij Smakov , Kenji Harada , Naoki Kawashima

We develop and analyze stochastic inexact Gauss-Newton methods for nonlinear least-squares problems and for nonlinear systems ofequations. Random models are formed using suitable sampling strategies for the matrices involved in the…

Optimization and Control · Mathematics 2024-12-10 Stefania Bellavia , Greta Malaspina , Benedetta Morini

The standard perturbation theory in QFT and lattice models leads to asymptotic expansions. However, an appropriate regularization of the path or lattice integrals allows one to construct convergent series with an infinite radius of the…

High Energy Physics - Lattice · Physics 2016-05-03 V. K. Sazonov
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