English
Related papers

Related papers: Detector and Beamline Simulation for Next-Generati…

200 papers

This roadmap presents the state-of-the-art, current challenges and near future developments anticipated in the thriving field of warm dense matter physics. Originating from strongly coupled plasma physics, high pressure physics and high…

Accelerator-based high-energy physics have been in the forefront of scientific discoveries for more than half a century. The accelerator technology of the colliders has progressed immensely, while the beam energy, luminosity, facility size,…

Accelerator Physics · Physics 2015-06-19 Vladimir Shiltsev

Detector mechanics can play a significant role in a detector's performance, improvements typically require in-depth study of total mass, novel ways to reduce the total mass, as well as more integrated design concepts to save on material…

Instrumentation and Detectors · Physics 2022-03-29 Eric Anderssen , Andreas Werner Jung , Sushrut Karmarkar , Abraham Matthew Koshy

Progress in nuclear physics is driven by the experimental observation that requires state of the art detectors to measure various kinematic properties, such as energy, momentum, position etc. of the particles produced in a nuclear reaction.…

Instrumentation and Detectors · Physics 2018-01-08 T. K. Ghosh

Colliders have been at the forefront of scientic discoveries in high-energy particle physics since the inception of the colliding beams method in the middle of the 20th century. The field of accelerators is very dynamic and many innovative…

Accelerator Physics · Physics 2019-07-03 Vladimir Shiltsev

Since the initial development of charged particle colliders in the middle of the 20th century, these advanced scientific instruments have been at the forefront of scientific discoveries in high energy physics. Collider accelerator…

Accelerator Physics · Physics 2021-03-10 Vladimir Shiltsev , Frank Zimmermann

Machine learning is finding increasingly broad application in the physical sciences. This most often involves building a model relationship between a dependent, measurable output and an associated set of controllable, but complicated,…

Computational Physics · Physics 2018-08-29 Brian K. Spears

As a classical generative modeling approach, energy-based models have the natural advantage of flexibility in the form of the energy function. Recently, energy-based models have achieved great success in modeling high-dimensional data in…

Machine Learning · Computer Science 2024-01-19 Taoli Cheng , Aaron Courville

The physics of high-energy collider experiments asks for delicate comparisons between theoretical predictions and experimental data. Signals and potential backgrounds for new physics have to be predicted at sufficient accuracy. The accuracy…

High Energy Physics - Phenomenology · Physics 2007-05-23 A. van Hameren , C. G. Papadopoulos

After the emergence of quantum mechanics and realising its need for an accurate understanding of physical systems, numerical methods were being used to undergo quantum mechanical treatment. With increasing system correlations and size,…

Physicists at the Large Hadron Collider (LHC) rely on detailed simulations of particle collisions to build expectations of what experimental data may look like under different theory modeling assumptions. Petabytes of simulated data are…

High Energy Physics - Experiment · Physics 2018-02-06 Michela Paganini , Luke de Oliveira , Benjamin Nachman

Our understanding of the Universe critically depends on the fundamental knowledge of particles and fields, which represents a central endeavor of modern high-energy physics. Energy frontier particle colliders - arguably, among the largest,…

Accelerator Physics · Physics 2023-09-29 Vladimir Shiltsev

An overview of computational methods to describe high-dimensional potential energy surfaces suitable for atomistic simulations is given. Particular emphasis is put on accuracy, computability, transferability and extensibility of the methods…

Chemical Physics · Physics 2020-07-08 Oliver T. Unke , Debasish Koner , Sarbani Patra , Silvan Käser , Markus Meuwly

Real-life control tasks involve matters of various substances---rigid or soft bodies, liquid, gas---each with distinct physical behaviors. This poses challenges to traditional rigid-body physics engines. Particle-based simulators have been…

Machine Learning · Computer Science 2019-04-19 Yunzhu Li , Jiajun Wu , Russ Tedrake , Joshua B. Tenenbaum , Antonio Torralba

Neutrino oscillation physics has entered a new precision era, which poses major challenges to the level of control and diagnostics of the neutrino beams. In this paper, we review the design of high-precision beams, their current…

High Energy Physics - Experiment · Physics 2021-03-16 N. Charitonidis , A. Longhin , M. Pari , E. G. Parozzi , F. Terranova

Electromigration, a significant lifetime reliability concern in highperformance integrated circuits, is projected to grow even more important in future heterogeneously integrated systems that will service higher current loads. Today, EM…

Hardware Architecture · Computer Science 2026-03-17 Sachin S. Sapatnekar

There are many astrophysical and laboratory scenarios where kinetic effects play an important role. These range from astrophysical shocks and plasma shell collisions, to high intensity laser-plasma interactions, with applications to fast…

Plasma Physics · Physics 2009-11-13 R. A. Fonseca , S. F. Martins , L. O. Silva , J. W. Tonge , F. S. Tsung , W. B. Mori

The use of machine learning algorithms to predict behaviors of complex systems is booming. However, the key to an effective use of machine learning tools in multi-physics problems, including combustion, is to couple them to physical and…

The synchrotron light source, a cutting-edge large-scale user facility, requires autonomous synchrotron beamline operations, a crucial technique that should enable experiments to be conducted automatically, reliably, and safely with minimum…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Baolu Li , Hongkai Yu , Huiming Sun , Jin Ma , Yuewei Lin , Lu Ma , Yonghua Du

Simulating physical systems is a core component of scientific computing, encompassing a wide range of physical domains and applications. Recently, there has been a surge in data-driven methods to complement traditional numerical simulations…

Machine Learning · Computer Science 2021-08-19 Karl Otness , Arvi Gjoka , Joan Bruna , Daniele Panozzo , Benjamin Peherstorfer , Teseo Schneider , Denis Zorin
‹ Prev 1 3 4 5 6 7 10 Next ›