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High density electromagnetic sandwich calorimeters with high readout granularity are considered for many future collider and fix-target experiments. Optimization of the calorimeter structure from the point of view of the electromagnetic…

High Energy Physics - Experiment · Physics 2024-10-01 Oleksandr Borysov , Shan Huang , Kamil Zembaczyński , Aleksander Filip Żarnecki

The next generation of collider detectors will make full use of Particle Flow Algorithms, requiring high-precision tracking and full imaging calorimeters. The latter, thanks to granularity improvements by two to three orders of magnitude…

Instrumentation and Detectors · Physics 2022-11-15 Roman Pöschl

Granular materials are of critical interest to many robotic tasks in planetary science, construction, and manufacturing. However, the dynamics of granular materials are complex and often computationally very expensive to simulate. We…

Robotics · Computer Science 2023-06-05 David Millard , Daniel Pastor , Joseph Bowkett , Paul Backes , Gaurav S. Sukhatme

Calorimeters with a high granularity are a fundamental requirement of the Particle Flow paradigm. This paper focuses on the prototype of a hadron calorimeter with analog readout, consisting of thirty-eight scintillator layers alternating…

Instrumentation and Detectors · Physics 2014-06-17 C. Adloff , J. Blaha , J. -J. Blaising , C. Drancourt , A. Espargilière , R. Gaglione , N. Geffroy , Y. Karyotakis , J. Prast , G. Vouters , K. Francis , J. Repond , J. Schlereth , J. Smith , L. Xia , E. Baldolemar , J. Li , S. T. Park , M. Sosebee , A. P. White , J. Yu , T. Buanes , G. Eigen , Y. Mikami , N. K. Watson , G. Mavromanolakis , M. A. Thomson , D. R. Ward , W. Yan , D. Benchekroun , A. Hoummada , Y. Khoulaki , J. Apostolakis , A. Dotti , G. Folger , V. Ivantchenko , V. Uzhinskiy , M. Benyamna , C. Cârloganu , F. Fehr , P. Gay , S. Manen , L. Royer , G. C. Blazey , A. Dyshkant , J. G. R. Lima , V. Zutshi , J. -Y. Hostachy , L. Morin , U. Cornett , D. David , G. Falley , K. Gadow , P. Göttlicher , C. Günter , B. Hermberg , S. Karstensen , F. Krivan , A. -I. Lucaci-Timoce , S. Lu , B. Lutz , S. Morozov , V. Morgunov , M. Reinecke , F. Sefkow , P. Smirnov , M. Terwort , A. Vargas-Trevino , N. Feege , E. Garutti , I. Marchesinik , M. Ramilli , P. Eckert , T. Harion , A. Kaplan , H. -Ch. Schultz-Coulon , W. Shen , R. Stamen , B. Bilki , E. Norbeck , Y. Onel , G. W. Wilson , K. Kawagoe , P. D. Dauncey , A. -M. Magnan , V. Bartsch , M. Wing , F. Salvatore , E. Calvo Alamillo , M. -C. Fouz , J. Puerta-Pelayo , B. Bobchenko , M. Chadeeva , M. Danilov , A. Epifantsev , O. Markin , R. Mizuk , E. Novikov , V. Popov , V. Rusinov , E. Tarkovsky , N. Kirikova , V. Kozlov , P. Smirnov , Y. Soloviev , P. Buzhan , A. Ilyin , V. Kantserov , V. Kaplin , A. Karakash , E. Popova , V. Tikhomirov , C. Kiesling , K. Seidel , F. Simon , C. Soldner , M. Szalay , M. Tesar , L. Weuste , M. S. Amjad , J. Bonis , S. Callier , S. Conforti di Lorenzo , P. Cornebise , Ph. Doublet , F. Dulucq , J. Fleury , T. Frisson , N. van der Kolk , H. Li , G. Martin-Chassard , F. Richard , Ch. de la Taille , R. Pöschl , L. Raux , J. Rouëné , N. Seguin-Moreau , M. Anduze , V. Boudry , J-C. Brient , D. Jeans , P. Mora de Freitas , G. Musat , M. Reinhard , M. Ruan , H. Videau , B. Bulanek , J. Zacek , J. Cvach , P. Gallus , M. Havranek , M. Janata , J. Kvasnicka , D. Lednicky , M. Marcisovsky , I. Polak , J. Popule , L. Tomasek , M. Tomasek , P. Ruzicka , P. Sicho , J. Smolik , V. Vrba , J. Zalesak , B. Belhorma , H. Ghazlane , T. Takeshita , S. Uozumi , M. Götze , O. Hartbrich , J. Sauer , S. Weber , C. Zeitnitz

Scalable surrogate models enable efficient emulation of computer models (or simulators), particularly when dealing with large ensembles of runs. While Gaussian process (GP) models are commonly employed for emulation, they face limitations…

Methodology · Statistics 2025-10-07 Grant Hutchings , Derek Bingham , Kellin Rumsey , Earl Lawrence

High-speed flight vehicles, which travel much faster than the speed of sound, are crucial for national defense and space exploration. However, accurately predicting their behavior under numerous, varied flight conditions is a challenge and…

Machine Learning · Computer Science 2024-11-07 Tyler E. Korenyi-Both , Nathan J. Falkiewicz , Matthew C. Jones

Numerical models based on physics represent the state-of-the-art in earth system modeling and comprise our best tools for generating insights and predictions. Despite rapid growth in computational power, the perceived need for higher model…

Machine Learning · Computer Science 2022-01-10 Kate Duffy , Thomas Vandal , Weile Wang , Ramakrishna Nemani , Auroop R. Ganguly

In preparation for Higgs factories and energy-frontier facilities, future colliders are moving toward high-granularity calorimeters to improve reconstruction quality. However, the cost and construction complexity of such detectors is…

High Energy Physics - Experiment · Physics 2025-06-04 Nilotpal Kakati , Etienne Dreyer , Eilam Gross

The fusion research facility ITER is currently being assembled to demonstrate that fusion can be used for industrial energy production, while several other programmes across the world are also moving forward, such as EU-DEMO, CFETR, SPARC…

Climate control of buildings makes up a significant portion of global energy consumption, with groundwater heat pumps providing a suitable alternative. To prevent possibly negative interactions between heat pumps throughout a city, city…

Machine Learning · Computer Science 2022-03-30 Raphael Leiteritz , Kyle Davis , Miriam Schulte , Dirk Pflüger

The lack of freely available standardized datasets represents an aggravating factor during the development and testing the performance of novel computational techniques in exposure assessment and dosimetry research. This hinders progress as…

Medical Physics · Physics 2023-05-04 Ante Kapetanovic , Dragan Poljak , Kun Li

We introduce a particle-based simulation method for granular material in interactive frame rates. We divide the simulation into two decoupled steps. In the first step, a relatively small number of particles is accurately simulated with a…

Graphics · Computer Science 2023-08-04 Alexander Sommer , Ulrich Schwanecke , Elmar Schömer

With the digitalization of power grids, physical equations become insufficient to describe the network's behavior, and realistic but time-consuming simulators must be used. Numerical experiments, such as safety validation, that involve…

Machine Learning · Computer Science 2025-05-01 Pierre Houdouin , Lucas Saludjian

The high-luminosity upgrade of the LHC will come with unprecedented physics and computing challenges. One of these challenges is the accurate reconstruction of particles in events with up to 200 simultaneous proton-proton interactions. The…

Instrumentation and Detectors · Physics 2021-06-04 Shah Rukh Qasim , Kenneth Long , Jan Kieseler , Maurizio Pierini , Raheel Nawaz

Deep generative modeling provides a powerful pathway to overcome data scarcity in energy-related applications where experimental data are often limited, costly, or difficult to obtain. By learning the underlying probability distribution of…

Machine Learning · Computer Science 2025-11-21 Farah Alsafadi , Alexandra Akins , Xu Wu

This paper presents a new C++ framework, DELPHES, performing a fast multipurpose detector response simulation. The simulation includes a tracking system, embedded into a magnetic field, calorimeters and a muon system, and possible very…

High Energy Physics - Phenomenology · Physics 2010-04-12 S. Ovyn , X. Rouby , V. Lemaitre

We introduce ColliderML - a large, open, experiment-agnostic dataset of fully simulated and digitised proton-proton collisions in High-Luminosity Large Hadron Collider conditions ($\sqrt{s}=14$ TeV, mean pile-up $\mu = 200$). ColliderML…

Pions constitute nearly $70\%$ of final state particles in ultra high energy collisions. They act as a probe to understand the statistical properties of Quantum Chromodynamics (QCD) matter i.e. Quark Gluon Plasma (QGP) created in such…

Data Analysis, Statistics and Probability · Physics 2021-03-31 Yogesh Verma , Satyajit Jena

High-fidelity computational fluid dynamics (CFD) simulations are widely used to analyze nuclear reactor transients, but are computationally expensive when exploring large parameter spaces. Multifidelity surrogate models offer an approach to…

Machine Learning · Computer Science 2026-03-17 Meredith Eaheart , Majdi I. Radaideh

As machine learning (ML) is increasingly implemented in hardware to address real-time challenges in scientific applications, the development of advanced toolchains has significantly reduced the time required to iterate on various designs.…