计算含物质效应的长基线中微子振荡概率的快速准确算法：NuFast
Fast and Accurate Algorithm for Calculating Long-Baseline Neutrino Oscillation Probabilities with Matter Effects: NuFast
AI总结：
本文提出了一种名为NuFast的快速精确算法，用于计算含物质效应的长基线中微子振荡概率，并提供C++和Fortran代码以支持DUNE等精确时代实验的大规模Monte Carlo模拟需求。
摘要：
随着DUNE、HK和JUNO等高统计量实验的出现，中微子振荡实验将在未来十年进入精确时代。为了从数据中正确估计振荡参数的置信区间，需要涉及多次计算物质中振荡概率的超大Monte Carlo数据集。本文利用以往工作，提出了一种新的快速、精确的用于计算物质中中微子振荡概率的技术，该技术针对地球地壳中的长基线中微子振荡进行了优化，涵盖加速器和反应堆实验。为方便理论家和实验学家使用，我们提供了快速的C++和Fortran代码。
英文摘要：
Neutrino oscillation experiments will be entering the precision era in the next decade with the advent of high statistics experiments like DUNE, HK, and JUNO. Correctly estimating the confidence intervals from data for the oscillation parameters requires very large Monte Carlo data sets involving calculating the oscillation probabilities in matter many, many times. In this paper, we leverage past work to present a new, fast, precise technique for calculating neutrino oscillation probabilities in matter optimized for long-baseline neutrino oscillations in the Earth's crust including both accelerator and reactor experiments. For ease of use by theorists and experimentalists, we provide fast c++ and fortran codes.
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