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Existing deep learning-based surrogate models facilitate efficient data generation, but fall short in uncertainty quantification, efficient parameter space exploration, and reverse prediction. In our work, we introduce SurroFlow, a novel…

Machine Learning · Computer Science 2024-07-19 Jingyi Shen , Yuhan Duan , Han-Wei Shen

We investigate whether a neural network approach can reproduce and predict the electron-nucleus cross sections in the kinematical domain of present and future accelerator-based neutrino oscillation experiments. For this purpose, we consider…

Nuclear Theory · Physics 2023-06-21 O. Al Hammal , M. Martini , J. Frontera-Pons , T. H. Nguyen , R. Perez-Ramos

PROJET is a parton level Monte Carlo program for the calculation of jet cross sections in deeply inelastic electron proton scattering. In its present version it contains the Born level diagrams for the production of (1+1), (2+1) and (3+1)…

High Energy Physics - Phenomenology · Physics 2009-10-28 Dirk Graudenz

A general purpose, self-adapting, Monte Carlo (MC) event generator (simulator) is described. The high efficiency of the MC, that is small maximum weight or variance of the MC weight is achieved by means of dividing the integration domain…

Computational Physics · Physics 2009-11-07 S. Jadach

We study a phenomenological ansatz for merging next-to-next-to-leading order (NNLO) calculations with Monte Carlo event generators. We reweight them to match bin-integrated NNLO differential distributions. To test this procedure, we study…

High Energy Physics - Phenomenology · Physics 2009-11-11 Giovanna Davatz , Fabian Stoeckli , Charalampos Anastasiou , Guenther Dissertori , Michael Dittmar , Kirill Melnikov , Frank Petriello

Ultra-peripheral heavy-ion collisions (UPCs) provide a distinct environment for high-energy QCD research, focusing on the production of vector mesons. This proceeding details recent advancements in the Sar$t$re Monte Carlo event generator,…

High Energy Physics - Phenomenology · Physics 2025-11-18 Vaidehi Nattoja , Tobias Toll

In light of the recent advancements in machine learning, we propose a novel approach to neutron source distribution estimation through the utilisation of probabilistic generative models. The estimation is based on a Monte Carlo particle…

Instrumentation and Detectors · Physics 2026-05-13 Jose Ignacio Robledo , Norberto Schmidt , Klaus Lieutenant , Jingjing Li , Stefan Kesselheim , Paul Zakalek

This article describes an original approach to analyze simultaneously cross sections and surrogate data measurements using efficient Monte Carlo extended $\mathcal{R}$-matrix theory algorithm based on unique set of nuclear structure…

Nuclear Theory · Physics 2020-01-01 O. Bouland , B. Jurado

Background: At the forefront of the nuclear science, production of new neutron-rich isotopes is continuously pursued at accelerator laboratories all over the world. To explore the currently-unknown territories in the nuclear chart far away…

Nuclear Theory · Physics 2017-07-26 Kazuyuki Sekizawa

In this contribution, we propose a new computationally efficient method to combine Variational Inference (VI) with Markov Chain Monte Carlo (MCMC). This approach can be used with generic MCMC kernels, but is especially well suited to…

We give a brief discussion of the recently developed Constrained-Path Monte Carlo Method. This method is a quantum Monte Carlo technique that eliminates the fermion sign problem plaguing simulations of systems of interacting electrons. The…

Strongly Correlated Electrons · Physics 2009-10-31 J. E. Gubernatis , M. Guerrero

Sampling from complicated probability distributions is a hard computational problem arising in many fields, including statistical physics, optimization, and machine learning. Quantum computers have recently been used to sample from…

We implement a discretization of the one-dimensional branching Brownian motion in the form of a Monte Carlo event generator, designed to efficiently produce ensembles of realizations in which the rightmost lead particle at the final time…

Statistical Mechanics · Physics 2020-06-30 Anh Dung Le , Alfred H. Mueller , Stéphane Munier

A sample of two proton and no pion events selected in the ArgoNeuT neutrino scattering experiment on liquid argon target [Phys. Rev. D90 (2014) 012008] is analyzed with NuWro Monte Carlo event generator. An attempt is made to estimate how…

High Energy Physics - Experiment · Physics 2016-03-23 Kajetan Niewczas , Jan T. Sobczyk

A simple C++ class structure for construction of a Monte Carlo event generators which can produce unweighted events within relativistic phase space is presented. The generator is self-adapting to the provided matrix element and acceptance…

High Energy Physics - Phenomenology · Physics 2018-12-18 R. A. Kycia , J. Chwastowski , R. Staszewski , J. Turnau

Metropolis Monte Carlo simulation is a powerful tool for studying the equilibrium properties of matter. In complex condensed-phase systems, however, it is difficult to design Monte Carlo moves with high acceptance probabilities that also…

Statistical Mechanics · Physics 2014-05-27 Jerome P. Nilmeier , Gavin E. Crooks , David D. L. Minh , John D. Chodera

The fast Monte Carlo procedure of hadron generation developed in our previous work is extended to describe noncentral collisions of nuclei. We consider different possibilities to introduce appropriate asymmetry of the freeze-out…

High Energy Physics - Phenomenology · Physics 2008-11-26 N. S. Amelin , R. Lednicky , I. P. Lokhtin , L. V. Malinina , A. M. Snigirev , Iu. A. Karpenko , Yu. M. Sinyukov , I. Arsene , L. Bravina

Neutrino-oscillation experiments performed in the few-GeV energy region create an urgent demand for a significant improvement in the accuracy of modeling of neutrino interactions with atomic nuclei. Here, we report an updated implementation…

High Energy Physics - Phenomenology · Physics 2025-08-15 Artur M. Ankowski , Rwik Dharmapal Banerjee , Jan T. Sobczyk , José L. Bonilla , Krzysztof M. Graczyk , Beata E. Kowal , Hemant Prasad

The interpretation of the nuclear cross sections measured using accelerator neutrino beams involve severe difficulties, arising primarily from the average over the incoming neutrino flux. The broad energy distribution of the beam particles…

Nuclear Theory · Physics 2021-10-12 Omar Benhar

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
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