Derivative-free optimization of a rapid-cycling synchrotron

Eldred, Jeffrey S.; Larson, Jeffrey; Padidar, Misha; Stern, Eric; Wild, Stefan M.

doi:10.1007/s11081-022-09733-4

Title: Derivative-free optimization of a rapid-cycling synchrotron

Journal Article · 15 June 2022 · Optimization and Engineering

DOI: https://doi.org/10.1007/s11081-022-09733-4 · OSTI ID:1831981

Eldred, Jeffrey S. ^[1]; Larson, Jeffrey ^[2]; Padidar, Misha ^[3]; Stern, Eric ^[1]; Wild, Stefan M. ^[2]

Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Argonne National Lab. (ANL), Argonne, IL (United States)
Argonne National Lab. (ANL), Argonne, IL (United States); Cornell Univ., Ithaca, NY (United States)

Here, we develop and solve a constrained optimization model to identify an integrable optics rapid-cycling synchrotron lattice design that performs well in several capacities. Our model encodes the design criteria into 78 linear and nonlinear constraints, as well as a single nonsmooth objective, where the objective and some constraints are defined from the output of Synergia, an accelerator simulator. We detail the difficulties of the 23-dimensional simulation-constrained decision space and establish that the space is nonempty. We use a derivative-free manifold sampling algorithm to account for structured nondifferentiability in the objective function. Our numerical results quantify the dependence of solutions on constraint parameters and the effect of the form of objective function.

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Research Organization:: Argonne National Laboratory (ANL), Argonne, IL (United States); Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); USDOE Office of Science (SC), High Energy Physics (HEP)

Grant/Contract Number:: AC02-05CH11231; AC02-06CH11357; AC02-07CH11359

OSTI ID:: 1831981

Report Number(s):: FERMILAB-PUB--21-353-AD-SCD; arXiv:2108.04774; oai:inspirehep.net:1903184

Journal Information:: Optimization and Engineering, Journal Name: Optimization and Engineering Journal Issue: 2 Vol. 23; ISSN 1389-4420

Publisher:: SpringerCopyright Statement

Country of Publication:: United States

Language:: English

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