arXiv subjects

N. Neveu

Publications and source records attributed to N. Neveu.

3 recordsLinked to original sources

arXiv2025

Controls Abstraction Towards Accelerator Physics: A Middle Layer Python Package for Particle Accelerator Control

Control system middle layers act as a co-ordination and communication bridge between end users, including operators, system experts, scientists, and experimental users, and the low-level control system interface. This article describes a Python package -- Controls Abstraction Towards Acclerator Physics (CATAP) -- which aims to build on previous experience and provide a modern Python-based middle layer with explicit abstraction, YAML-based configuration, and procedural code generation. CATAP provides a structured and coherent interface to a control system, allowing researchers and operators to centralize higher-level control logic and device information. This greatly reduces the amount of code that a user must write to perform a task, and codifies system knowledge that is usually anecdotal. The CATAP design has been deployed at two accelerator facilities, and has been developed to produce a procedurally generated facility-specific middle layer package from configuration files to enable its wider dissemination across other machines.

physics.acc-ph↗

arXiv2022

Strategies in Education, Outreach, and Inclusion to Enhance the US Workforce in Accelerator Science and Engineering

We summarize the community-based consensus for improvements concerning education, public outreach, and inclusion in Accelerator Science and Engineering that will enhance the workforce in the USA. The improvements identified reflect the product of discussions held within the 2021-2022 Snowmass community planning process by topical group AF1: Beam Physics and Accelerator Education within the Accelerator Frontier. Although the Snowmass process centers on high-energy physics, this document outlines required improvements for the entire U.S. accelerator science and engineering enterprise because education of those entering and in the field, outreach to the public, and inclusion are inextricably linked.

physics.acc-ph↗

arXiv2013

A Parallel General Purpose Multi-Objective Optimization Framework, with Application to Beam Dynamics

Particle accelerators are invaluable tools for research in the basic and applied sciences, in fields such as materials science, chemistry, the biosciences, particle physics, nuclear physics and medicine. The design, commissioning, and operation of accelerator facilities is a non-trivial task, due to the large number of control parameters and the complex interplay of several conflicting design goals. We propose to tackle this problem by means of multi-objective optimization algorithms which also facilitate a parallel deployment. In order to compute solutions in a meaningful time frame a fast and scalable software framework is required. In this paper, we present the implementation of such a general-purpose framework for simulation-based multi-objective optimization methods that allows the automatic investigation of optimal sets of machine parameters. The implementation is based on a master/slave paradigm, employing several masters that govern a set of slaves executing simulations and performing optimization tasks. Using evolutionary algorithms as the optimizer and OPAL as the forward solver, validation experiments and results of multi-objective optimization problems in the domain of beam dynamics are presented. The high charge beam line at the Argonne Wakefield Accelerator Facility was used as the beam dynamics model. The 3D beam size, transverse momentum, and energy spread were optimized.

physics.acc-ph↗