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Field experiments are often difficult and expensive to make. To bypass these issues, industrial companies have developed computational codes. These codes intend to be representative of the physical system, but come with a certain amount of…

Computation · Statistics 2019-03-26 Mathieu Carmassi , Pierre Barbillon , Merlin Keller , Eric Parent , Matthieu Chiodetti

Nonlinear mixed effects models have become a standard platform for analysis when data is in the form of continuous and repeated measurements of subjects from a population of interest, while temporal profiles of subjects commonly follow a…

Methodology · Statistics 2022-03-04 Se Yoon Lee

A method for the extraction of an effective meson-meson potential from Green functions, which can be obtained from a lattice simulation, is presented. Simulations are carried out for compact QED and QCD in four dimensions using the quenched…

High Energy Physics - Lattice · Physics 2009-10-28 H. R. Fiebig , H. Markum , A. Mihály , K. Rabitsch , W. Sakuler , C. Starkjohann

Quantum Bayesian Computation (QBC) is an emerging field that levers the computational gains available from quantum computers to provide an exponential speed-up in Bayesian computation. Our paper adds to the literature in two ways. First, we…

Machine Learning · Statistics 2023-03-07 Nick Polson , Vadim Sokolov , Jianeng Xu

A framework for probabilistic forecasting of vessel motion is developed and validated for a semisubmersible operating in long period swell. Bayesian statistical methods are applied to predictions of the heave response from a physics model…

Other Statistics · Statistics 2026-03-30 Ian Milne , Lachlan Astfalck , Matthew Zed , Jack Lee-Kopij , Edward Cripps

This article discusses applications of Bayesian machine learning for quantum molecular dynamics. One particular formulation of quantum dynamics advocated here is in the form of a machine learning simulator of the Schr\"{o}dinger equation.…

Chemical Physics · Physics 2019-07-24 R. V. Krems

Almost all fields of science rely upon statistical inference to estimate unknown parameters in theoretical and computational models. While the performance of modern computer hardware continues to grow, the computational requirements for the…

Computation · Statistics 2022-10-25 David J. Warne , Ruth E. Baker , Matthew J. Simpson

Fluctuations of conserved quantities in heavy-ion collisions have been argued to be diagnostic tools for the nature of the produced phase. These can be related to the predictions of quark number susceptibilities (QNS) from lattice QCD.…

High Energy Physics - Phenomenology · Physics 2009-11-11 Rajiv V. Gavai , Sourendu Gupta

Breakjunction experiments allow investigating electronic and spintronic properties at the atomic and molecular scale. These experiments generate by their very nature broad and asymmetric distributions of the observables of interest, and…

Mesoscale and Nanoscale Physics · Physics 2023-09-20 Dylan Dyer , Oliver L. A. Monti

The successful quasi-particle model is compared with recent lattice data of the coefficients in the Taylor series expansion of the excess pressure at finite temperature and baryon density. A chain of approximations, starting from QCD to…

High Energy Physics - Phenomenology · Physics 2009-11-10 M. Bluhm , B. Kampfer , G. Soff

We discuss recent progress made studies of bulk thermodynamics of strongly interacting matter through lattice simulations of QCD with an almost physical light and strange quark mass spectrum. We present results on the QCD equation of state…

High Energy Physics - Lattice · Physics 2008-11-26 Frithjof Karsch

The PID problem in high energy physics experiments is analysed with Bayesian technique. The corresponding applicable method is presented.

Data Analysis, Statistics and Probability · Physics 2007-05-23 Ding Tian

A century of coherent experimental and theoretical investigations have uncovered the laws of nature that underly nuclear physics. The standard model of strong and electroweak interactions, with its modest number of input parameters,…

Nuclear Theory · Physics 2013-09-19 Martin J. Savage

In recent years, machine learning has emerged as a powerful computational tool and novel problem-solving perspective for physics, offering new avenues for studying strongly interacting QCD matter properties under extreme conditions. This…

High Energy Physics - Phenomenology · Physics 2023-12-05 Kai Zhou , Lingxiao Wang , Long-Gang Pang , Shuzhe Shi

The effective residual interaction for a system of hadrons has a long tradition in theoretical physics. It has been mostly addressed in terms of boson exchange models. The aim of this review is to describe approaches based on lattice field…

High Energy Physics - Lattice · Physics 2007-05-23 H. Rudolf Fiebig , Harald Markum

A comprehensive artificial intelligence system needs to not only perceive the environment with different `senses' (e.g., seeing and hearing) but also infer the world's conditional (or even causal) relations and corresponding uncertainty.…

Machine Learning · Statistics 2021-01-07 Hao Wang , Dit-Yan Yeung

Ultrarelativistic heavy-ion collisions are considered ideal environments for exploring the QCD phase diagram and probing the properties of the QGP as functions of temperature and baryon chemical potential. At the highest energies, such as…

High Energy Physics - Experiment · Physics 2025-10-13 Mesut Arslandok

We review the theoretical aspects relevant in the description of high energy heavy ion collisions, with an emphasis on the learnings about the underlying QCD phenomena that have emerged from these collisions.

High Energy Physics - Phenomenology · Physics 2022-08-31 Francois Gelis

This work presents a Bayesian inference study for relativistic heavy-ion collisions in the Beam Energy Scan program at the Relativistic Heavy-Ion Collider. The theoretical model simulates event-by-event (3+1)D collision dynamics using…

Nuclear Theory · Physics 2026-02-03 Syed Afrid Jahan , Hendrik Roch , Chun Shen

The quantum statistical parton distributions approach proposed more than one decade ago is revisited by considering a larger set of recent and accurate Deep Inelastic Scattering experimental results. It enables us to improve the description…

High Energy Physics - Phenomenology · Physics 2015-12-09 Claude Bourrely , Jacques Soffer
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