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

Although beam emittance is critical for the performance of high-brightness accelerators, optimization is often time limited as emittance calculations, commonly done via quadrupole scans, are typically slow. Such calculations are a type of multipoint query , i.e. each query requires multiple secondar...

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Vydáno v:Machine learning: science and technology Ročník 5; číslo 1; s. 15004 - 15019
Hlavní autoři: Ayoub Miskovich, Sara, Neiswanger, Willie, Colocho, William, Emma, Claudio, Garrahan, Jacqueline, Maxwell, Timothy, Mayes, Christopher, Ermon, Stefano, Edelen, Auralee, Ratner, Daniel
Médium: Journal Article
Jazyk:angličtina
Vydáno: Bristol IOP Publishing 01.03.2024
Témata:
Algorithms
Bayesian algorithm execution
Bayesian analysis
Bayesian optimization
Black boxes
Coherent light
Emittance
Information theory
Light sources
Linear accelerators
multipoint optimization
online optimization
Optimization
particle accelerator
PARTICLE ACCELERATORS
Quadrupoles
Queries
Tuning
x-ray free electron laser
ISSN:2632-2153, 2632-2153
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Shrnutí:Although beam emittance is critical for the performance of high-brightness accelerators, optimization is often time limited as emittance calculations, commonly done via quadrupole scans, are typically slow. Such calculations are a type of multipoint query , i.e. each query requires multiple secondary measurements. Traditional black-box optimizers such as Bayesian optimization are slow and inefficient when dealing with such objectives as they must acquire the full series of measurements, but return only the emittance, with each query. We propose a new information-theoretic algorithm, Multipoint-BAX , for black-box optimization on multipoint queries, which queries and models individual beam-size measurements using techniques from Bayesian Algorithm Execution (BAX). Our method avoids the slow multipoint query on the accelerator by acquiring points through a virtual objective , i.e. calculating the emittance objective from a fast learned model rather than directly from the accelerator. We use Multipoint-BAX to minimize emittance at the Linac Coherent Light Source (LCLS) and the Facility for Advanced Accelerator Experimental Tests II (FACET-II). In simulation, our method is 20× faster and more robust to noise compared to existing methods. In live tests, it matched the hand-tuned emittance at FACET-II and achieved a 24% lower emittance than hand-tuning at LCLS. Our method represents a conceptual shift for optimizing multipoint queries, and we anticipate that it can be readily adapted to similar problems in particle accelerators and other scientific instruments.
Bibliografie:MLST-101447.R1
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USDOE
USDOE Office of Science (SC), Basic Energy Sciences (BES)
AC02-76SF00515
ISSN:2632-2153
2632-2153
DOI:10.1088/2632-2153/ad169f