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We introduce an approach based on mirror descent and sequential Monte Carlo (SMC) to perform joint parameter inference and posterior estimation in latent variable models. This approach is based on minimisation of a functional over the…

Computation · Statistics 2025-11-07 Francesca R. Crucinio

Monte Carlo simulations and finite-size scaling analysis have been carried out to study the critical behavior in a two-dimensional system of particles with two bonding sites that, by decreasing temperature or increasing density, polymerize…

Statistical Mechanics · Physics 2010-10-14 L. G. López , D. H. Linares , A. J. Ramirez-Pastor , S. A. Cannas

A Monte Carlo scheme to sample the screening potential H(r) of Yukawa plasmas notably at short distances is presented. This scheme is based on an importance sampling technique. Comparisons with former results for the Coulombic one-component…

Statistical Mechanics · Physics 2009-11-10 J. -M. Caillol , D. Gilles

Models implicitly defined through a random simulator of a process have become widely used in scientific and industrial applications in recent years. However, simulation-based inference methods for such implicit models, like approximate…

Methodology · Statistics 2025-04-17 Joonha Park

Zero- and two-dimensional crystal defects form in open statistical ensembles, such as the grand canonical, that are usually inaccessible with conventional simulation techniques. This longstanding challenge is overcome with a new Hamiltonian…

Materials Science · Physics 2026-01-16 Flynn Walsh , Babak Sadigh , Joseph T. McKeown , Timofey Frolov

We present a Bayesian approach to the problem of determining parameters for coalescing binary systems observed with laser interferometric detectors. By applying a Markov Chain Monte Carlo (MCMC) algorithm, specifically the Gibbs sampler, we…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Nelson Christensen , Renate Meyer

Bayesian model selection provides a powerful framework for objectively comparing models directly from observed data, without reference to ground truth data. However, Bayesian model selection requires the computation of the marginal…

Methodology · Statistics 2024-01-17 Xiaohao Cai , Jason D. McEwen , Marcelo Pereyra

Although multivariate count data are routinely collected in many application areas, there is surprisingly little work developing flexible models for characterizing their dependence structure. This is particularly true when interest focuses…

Methodology · Statistics 2020-05-19 Arkaprava Roy , David B Dunson

Presented is a description of a Markov chain Monte Carlo (MCMC) parameter estimation routine for use with interferometric gravitational radiational data in searches for binary neutron star inspiral signals. Five parameters associated with…

General Relativity and Quantum Cosmology · Physics 2016-08-16 Christian Röver , Renate Meyer , Nelson Christensen

A simulated annealing algorithm is applied to the reconstruction of two-dimensional porous media with prescribed correlation functions. The experimental correlation function of an isotropic sample of Fontainebleau sandstone and a synthetic…

Materials Science · Physics 2009-10-31 C. Manwart , R. Hilfer

A possible solution of the notorious sign problem preventing direct Monte Carlo calculations for systems with non-zero chemical potential is to deform the integration region in the complex plane to a Lefschetz thimble. We investigate this…

High Energy Physics - Lattice · Physics 2016-01-27 Andrei Alexandru , Gokce Basar , Paulo Bedaque

We present a novel strategy to strongly reduce the severity of the sign problem, using line integrals along paths of changing imaginary action. Highly oscillating regions along these paths cancel out, decreasing their contributions. As a…

High Energy Physics - Lattice · Physics 2023-10-18 Rasmus N. Larsen

We point out that Monte Carlo simulations of theories with severe sign problems can be profitably performed over manifolds in complex space different from the one with fixed imaginary part of the action. We describe a family of such…

High Energy Physics - Lattice · Physics 2016-03-22 Andrei Alexandru , Gokce Basar , Paulo F. Bedaque , Gregory W. Ridgway , Neill C. Warrington

The off-resonant hyperpolarizability is calculated using the dipole-free sum-over-stats expression from a randomly chosen set of energies and transition dipole moments that are forced to be consistent with the sum rules. The process is…

Optics · Physics 2009-11-13 Mark C. Kuzyk , Mark G. Kuzyk

We present an unbiased numerical integration algorithm that handles both low-frequency regions and high frequency details of multidimensional integrals. It combines quadrature and Monte Carlo integration, by using a quadrature-base…

Graphics · Computer Science 2020-08-18 Miguel Crespo , Felix Bernal , Adrian Jarabo , Adolfo Muñoz

Disordered nanostructures with correlations on the scale of visible wavelengths can show angle-independent structural colors. These materials could replace dyes in some applications because the color is tunable and resists photobleaching.…

Optical interferometric imaging enables astronomical observation at extremely high angular resolution. The necessary optical information for imaging, such as the optical path differences and visibilities, is easy to extract from fringes…

We prove that on an atomless probability space, the worst-case mean squared error of the Monte-Carlo estimator is minimal if the random points are chosen independently.

Probability · Mathematics 2019-04-02 Antoine Pinochet Lobos

We put forward a simple procedure for extracting dynamical information from Monte Carlo simulations, by appropriate matching of the short-time diffusion tensor with its infinite-dilution limit counterpart, which is supposed to be known.…

Statistical Mechanics · Physics 2015-06-04 Sara Jabbari-Farouji , Emmanuel Trizac

Computed Tomography (CT) imaging, while essential for diagnostics, exposes patients to ionizing radiation. To accurately quantify radiation dosage, this study introduces MIDSX, a specialized open-source Monte Carlo (MC) photon transport…

Medical Physics · Physics 2023-11-29 John Meneghini