A. Edelen

发表

arXiv : Opportunities in Machine Learning for Particle Accelerators

R. Ischebeck, D. Ratner, A. Adelmann, 2018 .

Opportunities in Machine Learning for Particle Accelerators

R. Ischebeck, D. Ratner, A. Adelmann, 2018, 1811.03172.

Adaptive model tuning studies for non-invasive diagnostics and feedback control of plasma wakefield acceleration at FACET-II

A. Scheinker, S. Gessner, C. Emma, 2020 .

C$^3$ Demonstration Research and Development Plan

M. Oriunno, J. Frisch, T. Barklow, 2022, 2203.09076.

Compact ring-based X-ray source with on-orbit and on-energy laser-plasma injection

Andrew J. Lajoie, A. Seryi, K. Shih, 2016, 1610.05699.

Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations

D. Ratner, R. Roussel, J. Power, 2022, 2209.04505.

Neural Networks for Modeling and Control of Particle Accelerators

B. Chase, S. Milton, S. Biedron, 2016, IEEE Transactions on Nuclear Science.

Bayesian Algorithm Execution for Tuning Particle Accelerator Emittance with Partial Measurements

S. Ermon, W. Neiswanger, D. Ratner, 2022, ArXiv.

Toward the end-to-end optimization of particle physics instruments with differentiable programming

J. Donini, T. Dorigo, R. R. Austri, 2022, Reviews in Physics.

Bayesian Algorithm Execution for Tuning Particle Accelerator Emittance with a Virtual Objective

S. Ermon, W. Neiswanger, D. Ratner, 2022 .

Efficient Tuning of Particle Accelerator Emittance via Bayesian Algorithm Execution and Virtual Objectives

S. Ermon, W. Neiswanger, D. Ratner, 2022, 2209.04587.

Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems

A. Adelmann, N. Neveu, A. Edelen, 2019, Physical Review Accelerators and Beams.

Physics-informed Gaussian Process for Online Optimization of Particle Accelerators pdf

Adi Hanuka, X. Huang, J. Shtalenkova, 2020, Physical Review Accelerators and Beams.

Bayesian Optimization of a Free-Electron Laser.

S. Ermon, M. McIntire, D. Ratner, 2019, Physical review letters.

Turn-key constrained parameter space exploration for particle accelerators using Bayesian active learning

Young-Kee Kim, Wanming Liu, A. Hanuka, 2021, Nature Communications.

Virtual Diagnostic Suite for Electron Beam Prediction and Control at FACET-II

A. Scheinker, A. Hanuka, B. O'Shea, 2021, Inf..

Multiobjective Bayesian optimization for online accelerator tuning

A. Hanuka, R. Roussel, A. Edelen, 2020, Physical Review Accelerators and Beams.

Machine Learning Models for Optimization and Control of X-ray Free Electron Lasers

D. Ratner, N. Neveu, C. Emma, 2019 .

Machine learning-based longitudinal phase space prediction of particle accelerators

Brendan O'Shea, Mark Hogan, V. Yakimenko, 2018, Physical Review Accelerators and Beams.

Demonstration of Model-Independent Control of the Longitudinal Phase Space of Electron Beams in the Linac-Coherent Light Source with Femtosecond Resolution.

Alexander Scheinker, Claudio Emma, Auralee Edelen, 2018, Physical review letters.

Recovering the phase and amplitude of X-ray FEL pulses using neural networks and differentiable models.

D. Ratner, A. Lutman, J. Cryan, 2021, Optics express.

Improving surrogate model accuracy for the LCLS-II injector frontend using convolutional neural networks and transfer learning

A. Mishra, N. Neveu, A. Edelen, 2021, Mach. Learn. Sci. Technol..

Resonant Frequency Control For the PIP-II Injector Test RFQ: Control Framework and Initial Results

B. Chase, S. Biedron, A. Edelen, 2016, 1612.05659.

Resonant Control for Fermilab's PXIE RFQ

S. G. Biedron, Brian Chase, A. L. Edelen, 2016 .

Beam Commissioning Status and Results of the FNAL PIP2IT Linear Accelerator RFQ

John Staples, M. Hoff, Curtis Baffes, 2017 .

EMITTANCE MEASUREMENTS AT FAST FACILITY *

J. Ruan, A. Lumpkin, R. Thurman-Keup, 2018 .

Observations on Submicropulse Electron-Beam Effects From Short-Range Wakefields in Tesla-Type Superconducting Rf Cavities

F. Zhou, J. Ruan, A. Lumpkin, 2021 .

Direct Observations of Sub-micropulse Electron-beam Effects from Short-range Wakefields in TESLA-type Superconducting RF Cavities

F. Zhou, J. Ruan, A. Lumpkin, 2020 .

Mitigation of Emittance Dilution Due to Wakefields in Accelerator Cavities Using Advanced Diagnostics with Machine Learning Techniques

Nicoleta Baboi, John Power, Alex Lumpkin, 2021 .

DIRECT OBSERVATIONS OF SUBMICROPULSE ELECTRON-BEAM EFFECTS FROM SHORT-RANGE WAKEFIELDS IN TESLA-TYPE SUPERCONDUCTING RF CAVITIES

F. Zhou, J. Ruan, R. Thurman-Keup, 2020 .

Submacropulse electron-beam dynamics correlated with higher-order modes in a Tesla-type cryomodule

F. Zhou, J. Ruan, A. Lumpkin, 2021, Physical Review Accelerators and Beams.

Machine Learning Training for HOM reduction and Emittance Preservation in a TESLA-type Cryomodule at FAST

Alex H. Lumpkin, Dean Edstrom, Jorge Diaz Cruz, 2021 .

Aspiration for Open Science in Accelerator & Beam Physics Modeling

D. Sagan, D. Bruhwiler, M. Bussmann, 2020 .

Develop / integrate data standards & start-to-end workflows for Accelerator Physics ( Letter of Interest to Snowmass 21 , Computational & Accelerator Frontiers )

S. Yoffe, K. Cranmer, D. Sagan, 2020 .

End-to-End Virtual Accelerators ( EVA ) ( Contribution to Snowmass 21 )

J. Qiang, D. Sagan, C. Ng, 2020 .

Online tuning and light source control using a physics-informed Gaussian process Adi pdf

J. Shtalenkova, D. Kennedy, A. Hanuka, 2019, ArXiv.

Temporal power reconstruction for an x-ray free-electron laser using convolutional neural networks

D. Ratner, A. Lutman, T. Maxwell, 2020 .

Aberration Corrector Tuning with Machine-Learning-Based Emittance Measurements and Bayesian Optimization

J. Maxson, A. Hanuka, D. Muller, 2021, Microscopy and Microanalysis.

Using Neural Network Control Policies For Rapid Switching Between Beam Parameters in a Free Electron Laser

Auralee L. Edelen, A. Edelen, 2017 .

Bayesian Optimization for Multi-dimensional Alignment: Tuning Aberration Correctors and Ptychographic Reconstructions

J. Maxson, Y. Shao, A. Hanuka, 2022, Microscopy and Microanalysis.

Applications of Differentiable Physics Simulations in Particle Accelerator Modeling

R. Roussel, A. Edelen, 2022, 2211.09077.

Differentiable Preisach Modeling for Characterization and Optimization of Particle Accelerator Systems with Hysteresis.

R. Roussel, Y. K. Kim, D. Ratner, 2022, Physical review letters.

Status and future plans for C3 R&D

M. Oriunno, J. Duris, P. Bhat, 2023, Journal of Instrumentation.

Plans for End-to-End Optimization of Experiments

T. Dorigo, A. G. Baydin, P. Elmer, 2022 .

Bayesian Optimization Algorithms for Accelerator Physics

W. Neiswanger, M. Streeter, A. F. Pousa, 2023, 2312.05667.

Demonstration of Autonomous Emittance Characterization at the Argonne Wakefield Accelerator

R. Roussel, D. Kennedy, J. Power, 2023, Instruments.

Neural Network Prior Mean for Particle Accelerator Injector Tuning

R. Roussel, A. Edelen, C. Xu, 2022, 2211.09028.

Multipoint-BAX: a new approach for efficiently tuning particle accelerator emittance via virtual objectives

W. Neiswanger, D. Ratner, C. Emma, 2022, Mach. Learn. Sci. Technol..

Phase Space Reconstruction from Accelerator Beam Measurements Using Neural Networks and Differentiable Simulations.

D. Ratner, R. Roussel, J. Power, 2022, Physical Review Letters.

Using a Neural Network Control Policy for Rapid Switching Between Beam Parameters in an FEL

Sandra Biedron, J. P. Edelen, Stephen Milton, 2017 .

Snowmass21 Accelerator Modeling Community White Paper

Hong Zhang, P. Piot, D. Sagan, 2022, 2203.08335.

Multi-Objective Bayesian Active Learning for MeV-ultrafast electron diffraction

Xijie Wang, A. Edelen, S. Miskovich, 2024, 2404.02268.

More Sample-Efficient Tuning of Particle Accelerators with Bayesian Optimization and Prior Mean Models

A. Edelen, Ryan Roussel, Tobias Boltz, 2024, 2403.03225.

Efficient 6-dimensional phase space reconstruction from experimental measurements using generative machine learning

Wanming Liu, E. Wisniewski, A. Edelen, 2024, 2404.10853.

Four-Dimensional Phase-Space Reconstruction of Flat and Magnetized Beams Using Neural Networks and Differentiable Simulations

Wanming Liu, R. Roussel, E. Wisniewski, 2024, 2402.18244.

Neural Network Solver for Coherent Synchrotron Radiation Wakefield Calculations in Accelerator-based Charged Particle Beams

A. Edelen, C. Mayes, 2022, ArXiv.

C$^3$ Demonstration Research and Development Plan

M. Oriunno, J. Frisch, T. Barklow, 2022, 2203.09076.

Machine learning for design optimization of storage ring nonlinear dynamics pdf

Minghao Song, Xiaobiao Huang, Faya Wang, 2019, ArXiv.