JuTrack, a Julia-based auto-differentiable accelerator simulation code for advanced dynamics, scientific machine learning and optimization

JuTrack is a high-performance accelerator modeling and particle tracking package developed in the Julia programming language. With compiler-level automatic differentiation (AD), JuTrack enables fast and precise derivative computations for arbitrary differentiable simulation functions. It supports efficient modeling of complex collective effects such as space-charge forces, wakefields, and beam-beam interactions. Beyond conventional tracking simulations, JuTrack also incorporates a machine learning–based module for self-field modeling and convenience interface that brings data-driven and physics-driven model together. In this paper, we demonstrate the capability and performance of JuTrack through a broad set of beam dynamics applications and optimization across various accelerator types, including a synchrotron light source, a heavy-ion linear accelerator, and the colliders. Built on Julia’s high-performance architecture and user-friendly syntax, JuTrack provides a powerful tool for beam dynamics studies and accelerator design optimization.

Authors

Publication Details

Journal
JACOW
Published
2026-01-29
DOI
https://doi.org/10.18429/jacow-napac2025-tup056
Primary Topic
Particle Accelerators and Free-Electron Lasers
Type
article
Field-Weighted Citation Impact
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article

JuTrack, a Julia-based auto-differentiable accelerator simulation code for advanced dynamics, scientific machine learning and optimization

Yue Hao, Jinyu Wan, Christian Ratcliff, Yue Hao et al.
JACOW
Particle Accelerators and Free-Electron Lasers
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JuTrack, a Julia-based auto-differentiable accelerator simulation code for advanced dynamics, scientific machine learning and optimization

Yue Hao, Jinyu Wan, Christian Ratcliff, Yue Hao, Ji Qiang
article en

Abstract

JuTrack is a high-performance accelerator modeling and particle tracking package developed in the Julia programming language. With compiler-level automatic differentiation (AD), JuTrack enables fast and precise derivative computations for arbitrary differentiable simulation functions. It supports efficient modeling of complex collective effects such as space-charge forces, wakefields, and beam-beam interactions. Beyond conventional tracking simulations, JuTrack also incorporates a machine learning–based module for self-field modeling and convenience interface that brings data-driven and physics-driven model together. In this paper, we demonstrate the capability and performance of JuTrack through a broad set of beam dynamics applications and optimization across various accelerator types, including a synchrotron light source, a heavy-ion linear accelerator, and the colliders. Built on Julia’s high-performance architecture and user-friendly syntax, JuTrack provides a powerful tool for beam dynamics studies and accelerator design optimization.

JACOW
Industry, innovation and infrastructure
Openalex Percentile: Top 74%
Particle Accelerators and Free-Electron Lasers
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