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We report on further progress in our programme of understanding confinement in 3d and 4d SU(2) gauge theory in terms of Z(2) monopoles. A sufficient condition for confinement was previously translated into Z(2) monopole correlation…

High Energy Physics - Lattice · Physics 2009-10-28 Tamas G. Kovacs , E. T. Tomboulis

Quantum Monte Carlo is used to investigate the possibility of d_{x^2-y^2} superconductivity in the two-dimensional repulsive Hubbard model. A small energy scale relevant to possible pairing requires a care (i.e., sufficiently small level…

Strongly Correlated Electrons · Physics 2009-10-30 Kazuhiko Kuroki , Hideo Aoki

The Hybrid Monte Carlo algorithm is adapted to the simulation of a system of classical degrees of freedom coupled to non self-interacting lattices fermions. The diagonalization of the Hamiltonian matrix is avoided by introducing a…

Strongly Correlated Electrons · Physics 2009-10-31 J. L. Alonso , L. A. Fernandez , F. Guinea , V. Laliena , V. Martin-Mayor

In parallelized Monte-Carlo simulations, the order of summation is not always the same. When the mean is calculated in running fashion, this may create an artificial randomness in results which ought to be reproducible. This note takes a…

Computational Finance · Quantitative Finance 2022-09-13 Jherek Healy

When properly tuned, Hamiltonian Monte Carlo scales to some of the most challenging high-dimensional problems at the frontiers of applied statistics, but when that tuning is suboptimal the performance leaves much to be desired. In this…

Methodology · Statistics 2016-04-05 Michael Betancourt

Numerical solutions to Newton's equations of motion for chaotic self gravitating systems of more than 2 bodies are often regarded to be irreversible. This is due to the exponential growth of errors introduced by the integration scheme and…

Instrumentation and Methods for Astrophysics · Physics 2018-03-14 Simon Portegies Zwart , Tjarda Boekholt

We test the scaling behaviour of Wilson, hypercube, maximally twisted mass and overlap fermion actions in dynamical simulations of the 2-dimensional massive Schwinger model. We also present possibilities to simulate overlap fermions…

High Energy Physics - Lattice · Physics 2007-05-23 Nils Christian , Karl Jansen , Kei-ichi Nagai , Beatrix Pollakowski

For years limited Monte Carlo simulations have led to the suspicion that the time to failure of hierarchically organized load-transfer models of fracture is non-zero for sets of infinite size. This fact could have a profound significance in…

Statistical Mechanics · Physics 2009-10-31 J. B. Gomez , M. Vazquez-Prada , Y. Moreno , A. F. Pacheco

The EM algorithm is a powerful tool for maximum likelihood estimation with missing data. In practice, the calculations required for the EM algorithm are often intractable. We review numerous methods to circumvent this intractability, all of…

Computation · Statistics 2024-01-03 William Ruth

We propose a modification of the Hybrid Monte Carlo (HMC) algorithm that overcomes the topological freezing of a two-dimensional $U(1)$ gauge theory with and without fermion content. This algorithm includes reversible jumps between…

High Energy Physics - Lattice · Physics 2023-05-09 David Albandea , Pilar Hernández , Alberto Ramos , Fernando Romero-López

Simulations of motion by mean curvature in bounded domains, with applications to bubble motion and grain growth, rely upon boundary conditions that are only approximately compatible with the equation of motion. Three closed form solutions…

Soft Condensed Matter · Physics 2019-01-03 Simon Cox , Gennady Mishuris

The gauge dependence of the conformal anomaly for spin 3/2 and spin 2 fields in non-conformal supergravities has been a long standing puzzle. In this Letter we argue that the `correct' gauge choice is the one that follows from requiring all…

High Energy Physics - Theory · Physics 2017-08-09 Krzysztof A. Meissner , Hermann Nicolai

This paper introduces an open-ended sequential algorithm for computing the p-value of a test using Monte Carlo simulation. It guarantees that the resampling risk, the probability of a different decision than the one based on the theoretical…

Statistics Theory · Mathematics 2013-07-30 Axel Gandy

Algorithmic recourse provides individuals who receive undesirable outcomes from machine learning systems with minimum-cost improvements to achieve a desirable outcome. However, machine learning models often get updated, so the recourse may…

Machine Learning · Computer Science 2026-04-28 Kshitij Kayastha , Vasilis Gkatzelis , Shahin Jabbari

We examine the sources of error in the histogram reweighting method for Monte Carlo data analysis. We demonstrate that, in addition to the standard statistical error which has been studied elsewhere, there are two other sources of error,…

Statistical Mechanics · Physics 2015-06-25 M. E. J. Newman , R. G. Palmer

Recent progress on the theory of variational hypocoercivity established that Randomized Hamiltonian Monte Carlo -- at criticality -- can achieve pronounced acceleration in its convergence and hence sampling performance over diffusive…

Statistics Theory · Mathematics 2025-07-18 Stefan Oberdörster

Markov chain Monte Carlo algorithms are invaluable tools for exploring stationary properties of physical systems, especially in situations where direct sampling is unfeasible. Common implementations of Monte Carlo algorithms employ…

Statistical Mechanics · Physics 2016-04-27 Marija Vucelja

We consider the implementation of a parallel Monte Carlo code for high-performance simulations on PC clusters with MPI. We carry out tests of speedup and efficiency. The code is used for numerical simulations of pure SU(2) lattice gauge…

High Energy Physics - Lattice · Physics 2007-05-23 Attilio Cucchieri , Tereza Mendes , Gonzalo Travieso , Andre R. Taurines

We study an optimal control problem under uncertainty, where the target function is the solution of an elliptic partial differential equation with random coefficients, steered by a control function. The robust formulation of the…

Numerical Analysis · Mathematics 2019-10-23 Philipp A. Guth , Vesa Kaarnioja , Frances Y. Kuo , Claudia Schillings , Ian H. Sloan

Monte Carlo simulations of diffusion processes often introduce bias in the final result, due to time discretization. Using an auxiliary Poisson process, it is possible to run simulations which are unbiased. In this article, we propose such…

Computational Finance · Quantitative Finance 2016-05-09 Louis Paulot