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<p>We study families of semidefinite programs (SDPs) that depend nonlinearly on a small number of “external” parameters. Such families appear universally in numerical bootstrap computations. The traditional method for finding an optimal point in parameter space works by first solving an SDP with fixed external parameters, then moving to a new point in parameter space and repeating the process. Instead, we unify solving the SDP and moving in parameter space in a single algorithm that we call “skydiving”. We test skydiving on some representative problems in the conformal bootstrap, finding significant speedups compared to traditional methods.</p>

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Skydiving to bootstrap islands

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年11月4日

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  • Aike Liu,
  • David Simmons-Duffin,
  • Ning Su,
  • Balt C. van Rees

摘要

We study families of semidefinite programs (SDPs) that depend nonlinearly on a small number of “external” parameters. Such families appear universally in numerical bootstrap computations. The traditional method for finding an optimal point in parameter space works by first solving an SDP with fixed external parameters, then moving to a new point in parameter space and repeating the process. Instead, we unify solving the SDP and moving in parameter space in a single algorithm that we call “skydiving”. We test skydiving on some representative problems in the conformal bootstrap, finding significant speedups compared to traditional methods.