High-performance statistical methods for reactor neutrino oscillations.

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Bibliographic Details
Title: High-performance statistical methods for reactor neutrino oscillations.
Authors: Xue, Jingqin1,2 (AUTHOR) xuejingqin@ihep.ac.cn, Zhang, Han1,2 (AUTHOR), Shen, Hongfang1 (AUTHOR), Sun, Guangbao1,3 (AUTHOR), Li, Dian1,2 (AUTHOR), Fan, Liangqianjin1,2 (AUTHOR), Yao, Haifeng1,2 (AUTHOR), Zhan, Liang1,2 (AUTHOR), Zhou, Xiang3 (AUTHOR), Ding, Xuefeng1,2 (AUTHOR) dingxf@ihep.ac.cn
Source: European Physical Journal C -- Particles & Fields. Dec2025, Vol. 85 Issue 12, p1-10. 10p.
Subjects: Neutrino oscillation, Software frameworks, Mathematical statistics, Neutrino interactions, Spectrum analysis instruments, Sensitivity analysis, Neutrinos
Abstract: We present a PyTorch-based framework for forward folded reactor neutrino spectrum fitting that accelerates the two main bottlenecks: IBD mapping and detector response, using (i) result caching, (ii) banded sparse matrices, and (iii) blocked construction of the response. On an Intel Xeon Gold 6338 CPU, these techniques reduce per-fit walltime by ≈ 7 × (median over 5 runs) relative to a dense, unoptimized implementation, with < 10 - 6 relative spectral error versus a double-precision baseline. The framework has been applied to reactor-neutrino oscillation analyses and is reusable in other neutrino experiments that rely on forward-folded energy spectra, enabling practical Feldman–Cousins coverage studies and large parameter scans at substantially lower computational cost. [ABSTRACT FROM AUTHOR]
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Abstract:We present a PyTorch-based framework for forward folded reactor neutrino spectrum fitting that accelerates the two main bottlenecks: IBD mapping and detector response, using (i) result caching, (ii) banded sparse matrices, and (iii) blocked construction of the response. On an Intel Xeon Gold 6338 CPU, these techniques reduce per-fit walltime by ≈ 7 × (median over 5 runs) relative to a dense, unoptimized implementation, with < 10 - 6 relative spectral error versus a double-precision baseline. The framework has been applied to reactor-neutrino oscillation analyses and is reusable in other neutrino experiments that rely on forward-folded energy spectra, enabling practical Feldman–Cousins coverage studies and large parameter scans at substantially lower computational cost. [ABSTRACT FROM AUTHOR]
ISSN:14346044
DOI:10.1140/epjc/s10052-025-15164-z