AI 中文总结
研究宇宙射线反核通量预测因缺乏数据受限的问题，利用归一化流代理拟合质子-质子关联函数，外推到低多重度区域，降低聚结参数不确定性，提高反核产生率预测精度。
AI 中文摘要
宇宙射线反核通量是暗物质的主要标志，其精确预测受限于缺乏反核产生率的数据约束。我们用一种快速、可微的归一化流代理来缓解这一瓶颈，该代理用于快度干涉学源模型（CECA），拟合49个ALICE质子-质子关联函数，并通过标度律外推到与宇宙射线相关的低多重度区域。代理以亚百分比的仿真保真度再现CECA，得到数据约束的源函数，消除了基于聚结的反核产生率中的主要不确定性。聚结参数$B_2$和$B_3$的不确定性分别从10 - 100倍和约1000倍缩小到百分之几和百分之十的水平，$B_{2}$还有约15%的波函数系统误差。
英文摘要
Precise predictions of cosmic-ray antinuclei fluxes, a prime dark matter signature, are limited by the lack of data constraining production rates of antinuclei. We mitigate this bottleneck with a fast, differentiable normalizing-flow surrogate for the femtoscopic source model (CECA), fit to 49 ALICE proton-proton correlation functions, and extrapolated via scaling laws to the low-multiplicity domain relevant for cosmic rays. The surrogate reproduces CECA with sub-percent emulation fidelity, yielding data-constrained source functions that remove the dominant uncertainty in coalescence-based antinuclei production rates. The resulting uncertainties on the coalescence parameters $B_2$ and $B_3$ shrink from factors of 10-100 and ${\sim}$1000 to the few percent and ten-percent level, respectively, with an additional ${\sim}15\%$ wavefunction systematic for $B_{2}$.
