:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Ibrahim, Anwar, Derkach, Denis, Petrenko, Alexey, Ratnikov, Fedor, Kaledin, Maxim
Format:	Preprint
Publié:	2025
Sujets:	Accelerator Physics Machine Learning
Accès en ligne:	https://arxiv.org/abs/2503.09665
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Reinforcement Learning for Accelerator Beamline Control: a simulation-based approach
par: Ibrahim, Anwar, et autres
Publié: (2025)

RL-ABC: Reinforcement Learning for Accelerator Beamline Control
par: Ibrahim, Anwar, et autres
Publié: (2026)

Autonomous Pressure Control in MuVacAS via Deep Reinforcement Learning and Deep Learning Surrogate Models
par: Rodriguez-Llorente, Guillermo, et autres
Publié: (2025)

Geoff: The Generic Optimization Framework & Frontend for Particle Accelerator Controls
par: Madysa, Penelope, et autres
Publié: (2025)

Accelerating Cavity Fault Prediction Using Deep Learning at Jefferson Laboratory
par: Rahman, Monibor, et autres
Publié: (2024)

Cheetah: Bridging the Gap Between Machine Learning and Particle Accelerator Physics with High-Speed, Differentiable Simulations
par: Kaiser, Jan, et autres
Publié: (2024)

Robust Errant Beam Prognostics with Conditional Modeling for Particle Accelerators
par: Rajput, Kishansingh, et autres
Publié: (2023)

Beamline Steering Using Deep Learning Models
par: Allen, Dexter, et autres
Publié: (2024)

Beyond PID Controllers: PPO with Neuralized PID Policy for Proton Beam Intensity Control in Mu2e
par: Xu, Chenwei, et autres
Publié: (2023)

Anomaly Detection of Particle Orbit in Accelerator using LSTM Deep Learning Technology
par: Chen, Zhiyuan, et autres
Publié: (2024)

Harnessing Machine Learning for Single-Shot Measurement of Free Electron Laser Pulse Power
par: Korten, Till, et autres
Publié: (2024)

Hybrid Meta-Learning Framework for Anomaly Forecasting in Nonlinear Dynamical Systems via Physics-Inspired Simulation and Deep Ensembles
par: Bereketoglu, Abdullah Burkan
Publié: (2025)

A Supervised Machine Learning Framework for Multipactor Breakdown Prediction in High-Power Radio Frequency Devices and Accelerator Components: A Case Study in Planar Geometry
par: Iqbal, Asif, et autres
Publié: (2025)

Injection Optimization at Particle Accelerators via Reinforcement Learning: From Simulation to Real-World Application
par: Awal, Awal, et autres
Publié: (2024)

Adaptive conditional latent diffusion maps beam loss to 2D phase space projections
par: Scheinker, Alexander, et autres
Publié: (2025)

Efficient Dynamic and Momentum Aperture Optimization for Lattice Design Using Multipoint Bayesian Algorithm Execution
par: Zhang, Z., et autres
Publié: (2025)

PhaseFlow4D: Physically Constrained 4D Beam Reconstruction via Feedback-Guided Latent Diffusion
par: Scheinker, Alexander, et autres
Publié: (2026)

Data-Driven Gradient Optimization for Field Emission Management in a Superconducting Radio-Frequency Linac
par: Goldenberg, Steven, et autres
Publié: (2024)

Adaptable phase retrieval for coherent transition radiation spectroscopy based on differentiable physics information
par: Aguilar, Ritz Ann, et autres
Publié: (2026)

Time-inversion of spatiotemporal beam dynamics using uncertainty-aware latent evolution reversal
par: Rautela, Mahindra, et autres
Publié: (2024)

Advancing accelerator virtual beam diagnostics through latent evolution modeling: an integrated solution to forward, inverse, tuning, and UQ problems
par: Rautela, Mahindra, et autres
Publié: (2026)

Acceleration of Multi-Scale LTS Magnet Simulations with Neural Network Surrogate Models
par: Denis, Louis, et autres
Publié: (2025)

Large Language Models for Human-Machine Collaborative Particle Accelerator Tuning through Natural Language
par: Kaiser, Jan, et autres
Publié: (2024)

AI-Ready Control System for the Fermilab Accelerator Complex
par: Miceli, Tia, et autres
Publié: (2026)

Integration of Machine Learning-Based Plasma Acceleration Simulations into Geant4: A Case Study with the PALLAS Experiment
par: Sytov, A., et autres
Publié: (2025)

Controls Abstraction Towards Accelerator Physics: A Middle Layer Python Package for Particle Accelerator Control
par: King, M., et autres
Publié: (2025)

Machine Learning for Reducing Noise in RF Control Signals at Industrial Accelerators
par: Henderson, M., et autres
Publié: (2024)

A Unified Approach for Coupled Beam Optics in Accelerators
par: Gilanliogullari, Onur, et autres
Publié: (2026)

Design and Numerical Simulation of a SARA-Based RF Accelerator Using the $\mathrm{TE}_{112}$ Mode
par: Carreño, Tomás A., et autres
Publié: (2025)

Physics-Informed Super-Resolution Diffusion for 6D Phase Space Diagnostics
par: Scheinker, Alexander
Publié: (2025)

Advanced Space Mapping Technique Integrating a Shared Coarse Model for Multistate Tuning-Driven Multiphysics Optimization of Tunable Filters
par: Hu, Haitian, et autres
Publié: (2025)

Twinac: A Universal Framework for Virtual Accelerator Controls
par: Miceli, Tia, et autres
Publié: (2025)

Simultaneous Multi-Scale Homogeneous H-Phi Thin-Shell Model for Efficient Simulations of Stacked HTS Coils
par: Denis, Louis, et autres
Publié: (2025)

Modelling Conduction Cooling of Superconducting Accelerator Magnets using a Thermal Thin Shell Approximation
par: Vancayseele, Emma, et autres
Publié: (2026)

Synthesizing Particle-in-Cell Simulations Through Learning and GPU Computing for Hybrid Particle Accelerator Beamlines
par: Sandberg, Ryan T., et autres
Publié: (2024)

Leveraging Trust for Joint Multi-Objective and Multi-Fidelity Optimization
par: Irshad, Faran, et autres
Publié: (2021)

Beam-Plasma Collective Oscillations in Intense Charged-Particle Beams: Dielectric Response Theory, Langmuir Wave Dispersion, and Unsupervised Detection via Prometheus
par: Yee, Brandon, et autres
Publié: (2026)

Evaluating Function-as-a-Service (FaaS) frameworks for the Accelerator Control System
par: Jaikar, A., et autres
Publié: (2025)

Optimisation of integrated luminosity in a circular collider with application to the LHC Run 2
par: Capoani, F., et autres
Publié: (2025)

A conditional latent autoregressive recurrent model for generation and forecasting of beam dynamics in particle accelerators
par: Rautela, Mahindra, et autres
Publié: (2024)