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| URL | https://doi.org/10.18429/JACoW-IPAC2025-WEBN2 |
|---|---|
| Title | A module for fast auto differentiable simulations |
| Authors |
|
| Abstract | The auto differentiable simulation is a type of simulation that outputs of the simulation contain not only the simulation result itself, but also its derivatives with respect to many input parameters. It provides an efficient method to study the sensitivity of the simulation result with respect to the input parameters and can be used in some gradient based optimization methods for fast parameter design optimization. In this paper, we report on the development of a fast auto differentiation module that can be used in many simulation codes. |
| Paper | download: WEBN2.pdf |
| Cite | BibTeX, LaTeX, Text/Word, RIS, EndNote |
| Conference | 16th International Particle Accelerator Conference |
| Series | |
| Location | Taipei, Taiwan |
| Date | 01-06 Jun 2025 |
| Publisher | JACoW Publishing, Geneva, Switzerland |
| Editorial Board | * Ming-Chyuan Lin - National Synchrotron Radiation Research Center * Yoichi Sato - KEK * Jui-Che Huang - National Synchrotron Radiation Research Center * David Button - Australian Nuclear Science and Technology Organisation * Ping-Shun Chuang - National Synchrotron Radiation Research Center |
| Online ISBN | 978-3-95450-248-6 |
| Online ISSN | 2673-5490 |
| Received | 20 May 2025 |
| Revised | 30 May 2025 |
| Accepted | 01 June 2025 |
| Issued | 05 November 2025 |
| DOI | 10.18429/JACoW-IPAC2025-WEBN2 |
| Pages | 1706-1709 |
| Copyright | Published by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |