Enhanced KAN architecture for experimental data processing in high-energy physics

IF 3.4 2区物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computer Physics Communications Pub Date : 2025-08-06 DOI:10.1016/j.cpc.2025.109801

Yauheni Talochka, Gennady Ososkov, Nikolay Voytishin

引用次数: 0

Abstract

An enhanced Kolmogorov-Arnold Network (KAN) compatible with the Adam optimizer is developed and applied to the deconvolution problem of multi-Gaussian signals and the fitting problem of the 3D distribution of the magnetic field in the BM@N (Baryonic Matter at Nuclotron) spectrometer of the Nuclotron-based Ion Collider fAcilit (NICA). Stable training dynamics and rapid convergence with the Adam algorithm, closely matching those of the computationally intensive LBFGS method, are achieved by implementing activation functions as a superposition of asymmetric super-Gaussian components and initializing their weights close to zero. The proposed KANs exhibit high accuracy (

> 90 %

) in the deconvolution of overlapping Gaussian signals with an unknown number of components as well as in the modeling of complex magnetic field geometries.

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高能物理实验数据处理的增强KAN架构

提出了一种与Adam优化器兼容的增强型Kolmogorov-Arnold网络（KAN），并将其应用于多高斯信号的反褶积问题和中子离子对撞机（NICA） BM@N（中子重子物质）光谱仪中磁场三维分布的拟合问题。通过将激活函数实现为非对称超高斯分量的叠加，并初始化它们的权值接近于零，Adam算法实现了稳定的训练动态和快速收敛，与计算密集型的LBFGS方法非常接近。所提出的KANs在具有未知分量的重叠高斯信号的反卷积以及复杂磁场几何形状的建模中表现出很高的精度（>90%）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computer Physics Communications 物理-计算机：跨学科应用

CiteScore

12.10

自引率

3.20%

发文量

287

审稿时长

5.3 months

期刊介绍： The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper. Computer Programs in Physics (CPiP) These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged. Computational Physics Papers (CP) These are research papers in, but are not limited to, the following themes across computational physics and related disciplines. mathematical and numerical methods and algorithms; computational models including those associated with the design, control and analysis of experiments; and algebraic computation. Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.