Derivative-Free Optimization of a Rapid-Cycling Synchrotron

TL;DR

This paper presents a derivative-free optimization approach to designing an integrable optics rapid-cycling synchrotron lattice, addressing complex constraints and nondifferentiability issues in accelerator design.

Contribution

It introduces a novel constrained optimization model with a derivative-free manifold sampling algorithm for accelerator lattice design.

Findings

Solutions depend on constraint parameters

Objective function form influences results

The decision space is confirmed to be nonempty

Abstract

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.