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The use of machine learning algorithms is an attractive way to produce very fast detector simulations for scattering reactions that can otherwise be computationally expensive. Here we develop a factorised approach where we deal with each…

Data Analysis, Statistics and Probability · Physics 2022-07-26 D. Darulis , R. Tyson , D. G. Ireland , D. I. Glazier , B. McKinnon , P. Pauli

Spectrometers based on the magnetic adiabatic collimation followed by an electrostatic filter (MAC-E-filter) principle combine high angular acceptance with an excellent energy resolution. These features make MAC-E-filters very valuable for…

Instrumentation and Detectors · Physics 2020-10-20 Alexander Fulst , Alexey Lokhov , Mariia Fedkevych , Nicholas Steinbrink , Christian Weinheimer

We present the implementation of the Particle Flow Algorithm and the result of the muon identification developed at the University of Iowa. We use Monte Carlo samples generated for the benchmark LOI process with the Silicon Detector design…

Instrumentation and Detectors · Physics 2009-01-29 M. J. Charles , U. Mallik , T. J. Kim

Ultracold atomic systems have been of great research interest in the past, with more recent attention being paid to systems of mixed species. In this work we carry out non-perturbative Path Integral Monte Carlo (PIMC) simulations of N…

Quantum Gases · Physics 2017-10-19 William G. Dawkins , Alexandros Gezerlis

Time-Of-Flight (TOF) methods are very effective to detect particles accelerated in laser-plasma interactions, but they shows significant limitations when used in experiments with high energy and intensity lasers, where both high-energy ions…

When tracking a large number of targets, it is often computationally expensive to represent the full joint distribution over target states. In cases where the targets move independently, each target can instead be tracked with a separate…

Artificial Intelligence · Computer Science 2007-05-23 Hedvig Sidenbladh

Tensors are ubiquitous in science and engineering and tensor factorization approaches have become important tools for the characterization of higher order structure. Factorizations includes the outer-product rank Canonical Polyadic…

Machine Learning · Statistics 2023-10-05 Jesper Løve Hinrich , Morten Mørup

The Micro-Pattern Gaseous Detectors offer excellent spatial and temporal resolution in harsh radiation environments of high-luminosity colliders. In this work, an attempt has been made to establish an algorithm for estimating the time…

Instrumentation and Detectors · Physics 2016-05-11 Purba Bhattacharya , Nayana Majumdar , Supratik Mukhopadhyay , Sudeb Bhattacharya

Entanglement is one of the most studied properties of quantum mechanics for its application in quantum information protocols. Nevertheless, detecting the presence of entanglement in large multipartite sates continues to be a great challenge…

Quantum Physics · Physics 2017-06-21 Flavio Baccari , Daniel Cavalcanti , Peter Wittek , Antonio Acín

Multiplicity correlation measurements provide insight into the dynamics of high energy collisions. Models describing these collisions need these correlation measurements to tune the strengths of the underlying QCD processes which influence…

Nuclear Experiment · Physics 2016-04-27 K. Gulbrandsen , C. Soegaard

Analyzing multi-featured time series data is critical for space missions making efficient event detection, potentially onboard, essential for automatic analysis. However, limited onboard computational resources and data downlink constraints…

Machine Learning · Computer Science 2025-10-24 Jonah Ekelund , Savvas Raptis , Vicki Toy-Edens , Wenli Mo , Drew L. Turner , Ian J. Cohen , Stefano Markidis

At the Belle II experiment a Time-of-Propagation (TOP) counter is used for particle identification in the barrel region. This novel type of particle identification device combines the Cherenkov ring imaging technique with the time-of-flight…

High Energy Physics - Experiment · Physics 2023-07-19 Marko Staric

Simulation-guided design represents a fundamental contribution towards the development of modern semiconductor devices aiming to reach high-performance particle detection, identification and tracking, and constitutes a strategic element of…

Instrumentation and Detectors · Physics 2025-05-12 Marco Mandurrino

The many-identical-particle quantum correlations are revisited utilizing the machinery of basic group theory, especially that of the group of permutations. It is done with the purpose to obtain precise definitions of effective distinct…

Quantum Physics · Physics 2007-05-23 Fedor Herbut

We present an efficient machine learning framework for detection and classification of nanoparticles on surfaces that are detected in the far-field with Coherent Fourier Scatterometry (CFS). We study silicon wafers contaminated with…

Optics · Physics 2020-07-15 D. Kolenov , S. F. Pereira

TORCH is a large-area, high-precision time-of-flight (ToF) detector designed to provide charged-particle identification in the 2-20 GeV$/c$ momentum range. Prompt Cherenkov photons emitted by charged hadrons as they traverse a 10mm quartz…

In engineering, accurately modeling nonlinear dynamic systems from data contaminated by noise is both essential and complex. Established Sequential Monte Carlo (SMC) methods, used for the Bayesian identification of these systems, facilitate…

Machine Learning · Statistics 2024-04-25 Joe D. Longbottom , Max D. Champneys , Timothy J. Rogers

A Time Projection Chamber (TPC) is an ideal device for the detection of charged particle tracks in a large volume covering a solid angle of almost $4\pi$. The high density of hits on a given particle track facilitates the task of pattern…

Particle indistinguishability is at the heart of quantum statistics that regulates fundamental phenomena such as the electronic band structure of solids, Bose-Einstein condensation and superconductivity. Moreover, it is necessary in…

Among the main goals in multiple change point problems are the estimation of the number and positions of the change points, as well as the regime structure in the clusters induced by those changes. The product partition model (PPM) is a…

Methodology · Statistics 2021-08-11 Ricardo C. Pedroso , Rosangela H. Loschi , Fernando Andrés Quintana
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