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Bayesian inference provides a principled way of estimating the parameters of a stochastic process that is observed discretely in time. The overdamped Brownian motion of a particle confined in an optical trap is generally modelled by the…

Data Analysis, Statistics and Probability · Physics 2017-02-01 Sudipta Bera , Shuvojit Paul , Rajesh Singh , Dipanjan Ghosh , Avijit Kundu , Ayan Banerjee , R. Adhikari

Carbon-hydrogen plasmas and hydrocarbon materials are of broad interest to laser shock experimentalists, high energy density physicists, and astrophysicists. Accurate equations of state (EOS) of hydrocarbons are valuable for various studies…

Proton radiography combined with X-ray computed tomography (CT) has been proposed to obtain a patient-specific calibration curve and reduce range uncertainties in cancer treatment with charged particles. The main aim of this study was to…

The finely tuned structures of membrane channels allow selective passage of ions through the available aqueous pores. In order to understand channel function, it is crucial to locate the pore and study its physical and chemical properties.…

Soft Condensed Matter · Physics 2007-05-23 Z. Kuang , A. Liu , T. L. Beck

We present an imaging algorithm for polarimetric interferometric data from radio telescopes. It is based on Bayesian statistics and thereby able to provide uncertainties and to incorporate prior information such as positivity of the total…

Instrumentation and Methods for Astrophysics · Physics 2025-04-02 Philipp Arras , Jakob Roth , Martin Reinecke , Richard A. Perley , Andrei Frolov , Rüdiger Westermann , Torsten A. Enßlin

I describe the first continuous space nuclear path integral quantum Monte Carlo method, and calculate the ground state properties of light nuclei including Deuteron, Triton, Helium-3 and Helium-4, using both local chiral interaction up to…

Nuclear Theory · Physics 2022-07-19 Rong Chen

Ion-conducting solid electrolytes are widely used for a variety of purposes. Therefore, designing highly ion-conductive materials is in strongly demand. Because of advancement in computers and enhancement of computational codes, theoretical…

Computational Physics · Physics 2020-03-23 Masayuki Karasuyama , Hiroki Kasugai , Tomoyuki Tamura , Kazuki Shitara

With a Bayesian approach, the linear optics correction algorithm for storage rings is revisited. Starting from the Bayes' theorem, a complete linear optics model is simplified as "likelihood functions" and "prior probability distributions".…

Accelerator Physics · Physics 2019-04-18 Yongjun Li , Robert Rainer , Weixing Cheng

We calculate the hydrogen Hugoniot using ab initio path integral Monte Carlo. We introduce an efficient finite-temperature fixed-node approximation for handling fermions, which includes an optimized mixture of free particle states and…

Materials Science · Physics 2011-08-09 Saad A. Khairallah , J. Shumway , Erik W. Draeger

Recent work has provided the means to rigorously determine properties of super-hadronic matter from experimental data through the application of broad scale modeling of high-energy nuclear collisions within a Bayesian framework. These…

Nuclear Theory · Physics 2016-03-23 Evan Sangaline , Scott Pratt

Attempts to find a quantum-to-classical correspondence in a classically forbidden region leads to non-physical paths, involving, for example, complex time or spatial coordinates. Here, we identify genuine quasi-classical paths for tunneling…

Quantum Physics · Physics 2017-05-31 Charis Anastopoulos , Ntina Savvidou

The results of analytical approximations and extensive calculations based on a path integral Monte Carlo (PIMC) scheme are presented. A new (direct) PIMC method allows for a correct determination of thermodynamic properties such as energy…

Astrophysics · Physics 2007-05-23 V. Filinov , M. Bonitz , D. Kremp , W. -D. Kraeft , V. Fortov

Although Monte Carlo path tracing is a simple and effective algorithm to synthesize photo-realistic images, it is often very slow to converge to noise-free results when involving complex global illumination. One of the most successful…

Finding optimal reaction coordinates and predicting accurate kinetic rates for activated processes are two of the foremost challenges of molecular simulations. We introduce an algorithm that tackles the two problems at once: starting from a…

Statistical Mechanics · Physics 2023-10-30 Line Mouaffac , Karen Palacio-Rodriguez , Fabio Pietrucci

Procedural material models have been gaining traction in many applications thanks to their flexibility, compactness, and easy editability. We explore the inverse rendering problem of procedural material parameter estimation from…

Graphics · Computer Science 2025-04-22 Yu Guo , Milos Hasan , Lingqi Yan , Shuang Zhao

In a geometric inhomogeneous random graph vertices are given by the points of a Poisson process and are equipped with independent weights following a heavy tailed distribution. Any pair of distinct vertices is independently forming an edge…

Probability · Mathematics 2025-09-30 Emmanuel Jacob , Céline Kerriou , Amitai Linker , Peter Mörters

An understanding of how input parameter uncertainty in the numerical simulation of physical models leads to simulation output uncertainty is a challenging task. Common methods for quantifying output uncertainty, such as performing a grid or…

Materials Science · Physics 2023-09-25 Samuel G. McCallum , James E. Lerpiniére , Kjeld O. Jensen , Alison B. Walker

We calculate the photo-ionization cross-section from the ground state of the helium atom, using the complex rotation method and diagonalization of sparse matrices. This produces directly the positions and widths of the doubly excited 1Po…

chao-dyn · Physics 2009-10-31 Benoit Gremaud , Dominique Delande

Multiphoton ionization provides a clear window into the nature of electron correlations in the helium atom. In the present study, the final state energy range extends up to the region near the $N=2$ and $N=3$ ionization thresholds, where…

Atomic Physics · Physics 2021-03-10 Yimeng Wang , Chris H. Greene

Multilevel linear models allow flexible statistical modelling of complex data with different levels of stratification. Identifying the most appropriate model from the large set of possible candidates is a challenging problem. In the…

Methodology · Statistics 2022-11-15 Tom Edinburgh , Ari Ercole , Stephen J. Eglen