Related papers: Accelerator and Beam Physics: Grand Challenges and…
A directed R&D program is presently underway in the U.S. to evaluate the designs and technologies required to provide muon-based high energy physics (HEP) accelerator capabilities. Such capabilities have the potential to provide unique…
The answer to the question in the title is: in search of new physics beyond the Standard Model, for which there are many motivations, including the likely instability of the electroweak vacuum, dark matter, the origin of matter, the masses…
Modern particle physics relies on high energy particle accelerators to provide collisions of various types of elementary particles in order to deduce fundamental laws of physics or properties of individual particles. The only way to…
The investigation of single-particle dynamics in circular particle accelerators can be traced back to pioneering works in the 1950s. Traditionally, the design of new circular accelerators has focused on optimising linear dynamics, striving…
Astrophysical neutrinos allow us to access energies and baselines that cannot be reached by human-made accelerators, offering unique probes of new physics phenomena. This thesis aims to address the challenges currently facing searches for…
Various panel sessions were organized to highlight the activities of the African Strategy for Fundamental and Applied Physics (ASFAP) Working Groups during the second African Conference of Fundamental and Applied Physics (ACP2021) that was…
We briefly give some of the characteristics of the beam-driven, plasma-based particle accelerator known as the plasma wakefield accelerator (PWFA). We also mention some of the major results that have been obtained since the birth of the…
About two generations ago, a large part of AMO science was dominated by experimental high energy collision studies and perturbative theoretical methods. Since then, AMO science has undergone a transition and is now dominated by quantum,…
Over the last dozen of years, the area of accelerating waves has made considerable advances not only in terms of fundamentals and experimental demonstrations but also in connection to a wide range of applications. Starting from the…
Particle accelerators for high energy physics will generate TeV-scale particle beams in large, multi-Km size machines colliding high brightness beams at the interaction point [1-4]. The high luminosity in such machines is achieved by…
Machine learning (ML) is a subfield of artificial intelligence. The term applies broadly to a collection of computational algorithms and techniques that train systems from raw data rather than a priori models. ML techniques are now…
Many applications require that we learn the parameters of a model from data. EM is a method used to learn the parameters of probabilistic models for which the data for some of the variables in the models is either missing or hidden. There…
As the next generation of large accelerator-based facilities are being considered at the Snowmass 2021 study high priority has to be given to environmental sustainability including energy consumption, natural resource use and the…
Considering the difficulty of students in calculating the direct and inverse kinematics of a robotic manipulator using only conventional tools of a classroom, this article proposes the application of Project Based Learning (ABP) through the…
The Continuous Electron Beam Accelerator Facility (CEBAF) and associated experimental equipment at Jefferson Lab comprise a unique facility for experimental nuclear physics. This facility is presently being upgraded, which will enable a new…
These reports present the results of the 2013 Community Summer Study of the APS Division of Particles and Fields ("Snowmass 2013") on the future program of particle physics in the U.S. Chapter 2, on the Intensity Frontier, discusses the…
We discuss recent developments and challenges of beam dynamics in Dielectric Laser Acceleration (DLA), for both high and low energy electron beams. Starting from ultra-low emittance nanotip sources the paper follows the beam path of a…
The performance of high beam power accelerators is strongly dependent on appropriate injection, acceleration and extraction system designs as well as on the way interactions of the beam with machine components are handled. The experience of…
Active Learning (AL) is a family of machine learning (ML) algorithms that predates the current era of artificial intelligence. Unlike traditional approaches that require labeled samples for training, AL iteratively selects unlabeled samples…
Los Alamos is currently developing novel particle accelerator controls and diagnostics algorithms to enable higher quality beams with lower beam losses than is currently possible. The purpose of this workshop was to consider tuning and…