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Calibration methods have been widely studied in survey sampling over the last decades. Viewing calibration as an inverse problem, we extend the calibration technique by using a maximum entropy method. Finding the optimal weights is achieved…

Methodology · Statistics 2009-09-23 Fabrice Gamboa , Jean-Michel Loubes , Paul Rochet

Particle distributions in weakly collisional environments such as the magnetosphere have been observed to show deviations from the Maxwellian distribution. These can often be reproduced in kinetic simulations, but fluid models, which are…

Space Physics · Physics 2018-08-24 Jonathan Ng , Ammar Hakim , Amitava Bhattacharjee

We present some aspects of high precision calculations in the context of Lattice Quantum Field Theory. This work is a collection of three studies done during my Ph.D. period. First we present how to use the reweighting technique to…

High Energy Physics - Lattice · Physics 2017-10-04 Andrea Bussone

The maximum entropy principle (MEP) apparently allows us to derive, or justify, fundamental results of equilibrium statistical mechanics. Because of this, a school of thought considers the MEP as a powerful and elegant way to make…

Statistical Mechanics · Physics 2015-12-09 Gennaro Auletta , Lamberto Rondoni , Angelo Vulpiani

This work expands on our recently introduced low Mach enthalpy method [1] for simulating the melting and solidification of a phase change material (PCM) alongside (or without) an ambient gas phase. The method captures PCM's volume change…

Fluid Dynamics · Physics 2025-03-11 Ramakrishnan Thirumalaisamy , Amneet Pal Singh Bhalla

Entropy Search (ES) and Predictive Entropy Search (PES) are popular and empirically successful Bayesian Optimization techniques. Both rely on a compelling information-theoretic motivation, and maximize the information gained about the…

Machine Learning · Statistics 2018-08-06 Zi Wang , Stefanie Jegelka

The maximum entropy principle (MEP) is one of the most prominent methods to investigate and model complex systems. Despite its popularity, the standard form of the MEP can only generate Boltzmann-Gibbs distributions, which are ill-suited…

Statistical Mechanics · Physics 2022-03-30 Pablo A. Morales , Fernando E. Rosas

Monte Carlo calculations in the framework of lattice field theory provide non-perturbative access to the equilibrium physics of quantum fields. When applied to certain fermionic systems, or to the calculation of out-of-equilibrium physics,…

High Energy Physics - Lattice · Physics 2020-06-23 Scott Lawrence

The conformational free energy landscape of a system is a fundamental thermodynamic quantity of importance particularly in the study of soft matter and biological systems, in which the entropic contributions play a dominant role. While…

Biological Physics · Physics 2015-10-13 N. Ramakrishnan , Richard W. Tourdot , Ravi Radhakrishnan

Probabilistic reasoning systems combine different probabilistic rules and probabilistic facts to arrive at the desired probability values of consequences. In this paper we describe the MESA-algorithm (Maximum Entropy by Simulated Annealing)…

Artificial Intelligence · Computer Science 2013-03-25 Gerhard Paaß

The Maximum Entropy Modeling Toolkit supports parameter estimation and prediction for statistical language models in the maximum entropy framework. The maximum entropy framework provides a constructive method for obtaining the unique…

cmp-lg · Computer Science 2008-02-03 Eric Sven Ristad

The notorious sign problem severely limits the applicability of quantum Monte Carlo (QMC) simulations, as statistical errors grow exponentially with system size and inverse temperature. A recent proposal of a quantum-computing stochastic…

Quantum Physics · Physics 2026-03-11 Kwai-Kong Ng , Min-Fong Yang

We derive the microcanonical ensemble from the Maximum Entropy Principle (MEP) using the phase space volume entropy of P. Hertz. Maximizing this entropy with respect to the probability distribution with the constraints of normalization and…

Statistical Mechanics · Physics 2008-02-15 Michele Campisi , Donald H. Kobe

Model usage is the central challenge of model-based reinforcement learning. Although dynamics model based on deep neural networks provide good generalization for single step prediction, such ability is over exploited when it is used to…

Machine Learning · Computer Science 2020-06-30 Chi Zhang , Sanmukh Rao Kuppannagari , Viktor K Prasanna

Mapping the relativistic jets emanating from AGN requires the use of a deconvolution algorithm to account for the effects of missing baseline spacings. The CLEAN algorithm is the most commonly used algorithm in VLBI imaging today and is…

Instrumentation and Methods for Astrophysics · Physics 2015-06-17 Colm P. Coughlan , Denise C. Gabuzda

Empirical Mode Decomposition(EMD) is an adaptive data analysis technique for analyzing nonlinear and nonstationary data[1]. EMD decomposes the original data into a number of Intrinsic Mode Functions(IMFs)[1] for giving better physical…

Methodology · Statistics 2016-01-27 Sumit Kumar Ram , Marta Molinas

The most popular methods for self-consistent simulation of fields interacting with charged species is using finite difference time domain (FDTD) methods together with Newton's laws of motion to evolve locations and velocities of particles.…

Computational Physics · Physics 2022-04-29 Zane D. Crawford , O. H. Ramachandran , Scott O'Connor , Daniel L. Dault , John Luginsland , B. Shanker

A novel method combining the ensemble refinement by maximum entropy principle and the force field fitting approach is presented. Its formulation allows to continuously interpolate in between these two methods, which can thus be interpreted…

Chemical Physics · Physics 2024-01-30 Ivan Gilardoni , Thorben Fröhlking , Giovanni Bussi

A new finite element method (FEM) using meshes that do not necessarily align with the interface is developed for two- and three-dimensional anisotropic elliptic interface problems with nonhomogeneous jump conditions. The degrees of freedom…

Numerical Analysis · Mathematics 2025-05-20 Haifeng Ji , Zhilin Li

Herein we propose a new numerical technique for solving field theories: the large momentum frame (LMF). This technique combines several advantages of lattice gauge theory with the simplicity of front form quantisation. We apply the LMF on…

High Energy Physics - Theory · Physics 2007-05-23 Norbert Scheu