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The configuration-interaction shell model approach provides an attractive framework for the calculation of nuclear level densities in the presence of correlations, but the large dimensionality of the model space has hindered its application…

Nuclear Theory · Physics 2016-01-05 Y. Alhassid , G. F. Bertsch , C. N. Gilbreth , H. Nakada , C. Özen

Kernel density estimation on a finite interval poses an outstanding challenge because of the well-recognized bias at the boundaries of the interval. Motivated by an application in cancer research, we consider a boundary constraint linking…

Statistics Theory · Mathematics 2020-12-01 Matthew J. Colbrook , Zdravko I. Botev , Karsten Kuritz , Shev MacNamara

Intractable generative models are models for which the likelihood is unavailable but sampling is possible. Most approaches to parameter inference in this setting require the computation of some discrepancy between the data and the…

Computation · Statistics 2022-07-05 Ziang Niu , Johanna Meier , François-Xavier Briol

Markov chain Monte Carlo samplers produce dependent streams of variates drawn from the limiting distribution of the Markov chain. With this as motivation, we introduce novel univariate kernel density estimators which are appropriate for the…

Methodology · Statistics 2016-07-29 Hang J. Kim , Steven N. MacEachern , Yoonsuh Jung

We introduce a guided stochastic sampling method that augments sampling from diffusion models with physics-based guidance derived from partial differential equation (PDE) residuals and observational constraints, ensuring generated samples…

Machine Learning · Computer Science 2026-05-28 Andrew Millard , Fredrik Lindsten , Zheng Zhao

This work studies distributed (probability) density estimation of large-scale systems. Such problems are motivated by many density-based distributed control tasks in which the real-time density of the swarm is used as feedback information,…

Systems and Control · Electrical Eng. & Systems 2021-06-03 Tongjia Zheng , Hai Lin

To better understand the capture process by a nanopore, we introduce an efficient Kinetic Monte Carlo (KMC) algorithm that can simulate long times and large system sizes by mapping the dynamic of a point-like particle in a 3D spherically…

Biological Physics · Physics 2021-03-22 Le Qiao , Maxime Ignacio , Gary W. Slater

Tuning of measurement models is challenging in real-world applications of sequential Monte Carlo methods. Recent advances in differentiable particle filters have led to various efforts to learn measurement models through neural networks.…

Artificial Intelligence · Computer Science 2022-03-17 Xiongjie Chen , Yunpeng Li

Because of properties of QED, the bremsstrahlung corrections to decays of particles or resonances can be calculated, with a good precision, separately from other effects. Thanks to the widespread use of event records such calculations can…

High Energy Physics - Phenomenology · Physics 2008-11-07 Z. Was , P. Golonka , G. Nanava

We present a new method for multiclass thresholding of a histogram which is based on the nonparametric Kernel Density (KD) estimation, where the unknown parameters of the KD estimate are defined using the Expectation-Maximization (EM)…

Image and Video Processing · Electrical Eng. & Systems 2022-02-11 S. Korneev , J. Gilles , I. Battiato

This study proposes multivariate kernel density estimation by stagewise minimization algorithm based on $U$-divergence and a simple dictionary. The dictionary consists of an appropriate scalar bandwidth matrix and a part of the original…

Machine Learning · Statistics 2021-08-11 Kiheiji Nishida , Kanta Naito

MCViNE (Monte-Carlo VIrtual Neutron Experiment) is a versatile Monte Carlo (MC) neutron ray-tracing program that provides researchers with tools for performing computer modeling and simulations that mirror real neutron scattering…

We present a new combinatorial method for the calculation of the nuclear level density. It is based on a Monte Carlo technique, in order to avoid a direct counting procedure which is generally impracticable for high-A nuclei. The Monte…

Nuclear Theory · Physics 2008-11-26 N. Cerf

The iterative Quasi-Monte Carlo (iQMC) method is a recently proposed method for multigroup neutron transport simulations. iQMC can be viewed as a hybrid between deterministic iterative techniques, Monte Carlo simulation, and Quasi-Monte…

Computational Physics · Physics 2024-01-09 Samuel Pasmann , Ilham Variansyah , C. T. Kelley , Ryan G. McClarren

When nonlinear measures are estimated from sampled temporal signals with finite-length, a radius parameter must be carefully selected to avoid a poor estimation. These measures are generally derived from the correlation integral which…

Methodology · Statistics 2024-01-09 Johan Medrano , Abderrahmane Kheddar , Annick Lesne , Sofiane Ramdani

A recent reformulation [1] of the problem of Coulomb gases in the presence of a dynamical dielectric medium showed that finite temperature simulations of such systems can be accomplished on the basis of completely local Hamiltonians on a…

Soft Condensed Matter · Physics 2009-11-11 A. Duncan , R. D. Sedgewick

Proton radiography is used in various high-energy-density (HED) plasma experiments. In this paper, we describe a Monte Carlo and ray-tracing simulation tool called MPRAD that can be used for modeling the deflection of proton beams in…

Plasma Physics · Physics 2020-01-08 Yingchao Lu , Hui Li , Kirk A. Flippo , Kwyntero Kelso , Andy Liao , Shengtai Li , Edison Liang

A compact photoneutron source (PNS), based on an electron linac was designed and constructed to provide required nuclear data for the design of Thorium Molten Salt Reactor (TMSR). Many local shielding are built to reduce the background of…

The validation, verification, and uncertainty quantification of computationally expensive theoretical models of quantum many-body systems require the construction of fast and accurate emulators. In this work, we develop emulators for…

In this paper, Kernel Density Estimation (KDE) as a non-parametric estimation method is used to investigate statistical properties of nuclear spectra. The deviation to regular or chaotic dynamics, is exhibited by closer distances to Poisson…

Nuclear Theory · Physics 2011-12-13 M. A. Jafarizadeh , N. Fouladi , H. Sabri , B. Rashidian Maleki
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