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物质诱导的CPT破坏与地球密度分层效应在长基线中微子振荡实验中的研究

Matter-Induced CPT Violation and Earth-Density Stratification Effects in Long-Baseline Neutrino Oscillation Experiments

Tia Pandit, Bipin Singh Koranga, Aditya Pant, Vivek Kumar Nautiyal

arXiv 2608.00436首次发表:更新:

发表机构

Chaudhary Charan Singh University; University of Delhi(乔达摩·彻恩·辛格大学; 德里大学)

机构由 AI 辅助整理,请以论文原文为准。

AI 中文总结

该研究将物质诱导的外在CPT破坏与地球密度分层视为关联系统误差,用单一χ²框架分析其对长基线中微子振荡实验CP相位重建的影响,量化了密度不确定性的作用,提出需联合建模两种效应。

AI 中文摘要

我们对长基线(LBL)中微子振荡实验中的两种物质势系统误差进行了统一分析,将物质诱导的外在CPT破坏和地球密度分层视为单一χ²框架内的关联系统误差,研究它们对CP相位重建及质量排序依赖性的联合影响。物质诱导的外在CPT破坏会产生非零不对称性A_{μe}^{CPT}=(P_{μe}-\bar{P}_{μe})/(P_{μe}+\bar{P}_{μe}),通过对T2K、NOνA、DUNE和Hyper-Kamiokande的精确三味矩阵指数计算得到,该不对称性在各峰值能量处范围为0.022至0.180,正常排序与倒置排序间差异最高达9%。DUNE处的A_{μe}^{CPT}(E,δ_{CP})曲面揭示了高L/E区域中外在CPT破坏与内在CP破坏的相互作用,需进行联合统计处理。我们量化了A_{μe}^{CPT}对密度不确定性ρ→ρ(1+ε)(ε=±1%、±2%、±5%)的灵敏度,发现±5%的不确定性在DUNE处引发|ΔA_{CPT}|<0.008。用恒定路径平均密度替代PREM剖面时,L≤5000km的CP相位重建偏差低于0.3°,在7000km时增至17.8°,12000km时达172.2°。由于两种效应源于同一物质哈密顿量,必须结合泊松对数似然χ²与扰动参数约束进行联合建模。

英文摘要

We present a unified analysis of two matter-potential systematics in long-baseline (LBL) neutrino oscillation experiments. Matter-induced extrinsic CPT violation produces a non-zero asymmetry $A_{μe}^{CPT} = (P_{μe} - P_{\barμ\bar{e}})/(P_{μe} + P_{\barμ\bar{e}})$, computed here with exact three-flavour matrix-exponentiation propagators for T2K, NO$ν$A, DUNE, and Hyper-Kamiokande; values range from 0.022 to 0.180 at the respective peak energies and differ by up to 9\% between normal and inverted mass orderings. The three-dimensional surface $A_{μe}^{CPT}(E, δ_{CP})$ at the DUNE baseline reveals an entanglement between extrinsic CPT violation and intrinsic CP violation in the high-$L/E$ regime that requires joint statistical treatment. Concurrently, replacing the Preliminary Reference Earth Model (PREM) with a constant path-averaged density introduces a $δ_{CP}$-reconstruction bias below $0.3^{\circ}$ for $L \leq 5000$ km but growing to $17.8^{\circ}$ at $L = 7000$ km and $172.2^{\circ}$ at $L = 12000$ km. Since both effects share the same matter-potential Hamiltonian they must be modelled jointly; a Poisson log-likelihood $χ^2$ statistic with nuisance-parameter pull terms is used to quantify the bias.

Comments11 pages, 6 figures

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