从探测器水平的散射数据直接进行螺旋度振幅的贝叶斯推断
Direct Bayesian Inference of Helicity Amplitudes from Detector-Level Scattering Data
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中文总结 AI 辅助
该研究提出一种基于分数的扩散模型的贝叶斯推断框架，可从探测器水平散射数据直接提取螺旋度振幅，适用于强相互作用研究的多类实验场景。
中文摘要 AI 辅助
螺旋度振幅是描述强相互作用研究中多种散射反应最完整的物理量，但无法直接测量：实验记录的是螺旋度振幅的双线性组合，并与探测器响应发生卷积，传统分析需通过多个阶段来重建螺旋度振幅，这一过程会引入离散歧义，还需单独提取绝对截面。本文用单一的贝叶斯推断替代上述复杂流程，直接从探测器水平的测量结果中确定实验可识别的振幅参数。基于正向模拟器训练的基于分数的扩散模型，能在每个运动学区间内提供完整的后验分布，正向模型包含探测器响应信息，且参数化方式保证了自旋密度矩阵的正定性。末态粒子电产生中的可观测振幅内容随束流和靶的极化程度增加而提升，这为探测 underlying 相位提供了额外灵敏度。模拟结果显示，该后验分布达到了名义水平或更高的经验覆盖率，能保留角可观测量以及纵向和横向光子的分离贡献及其相关性。该方法无需重新训练即可迁移至训练时未包含的真实探测器响应，且在弱约束的核子螺旋度翻转领域依然可靠，而该领域中按区间进行的似然最大化方法性能会下降。这一成果为一大类逆问题提供了通用框架，相位检索、量子态层析成像和分波分析也是其适用场景。该方法的核心仅需对完整测量过程进行正向模拟，仪器效应在一个统计一致的后验分布内处理，适用于杰斐逊实验室、COMPASS、HERMES以及未来电子离子对撞机的各类排他矢量介子实验项目。
英文摘要
Helicity amplitudes give the most complete description of a variety of scattering reactions used in studies of strong interactions, but they cannot be measured directly: experiments record bilinear combinations of them folded through a detector response, and conventional analyses recover them through multiple stages that introduce discrete ambiguities and require a separate extraction of the absolute cross sections. Here we replace that chain with a single Bayesian inference that determines the experimentally identifiable amplitude parameters directly from detector-level measurements. A score-based diffusion model, trained on a forward simulator, provides the full posterior in each kinematic bin, with the detector response carried by the forward model and positivity of the spin-density matrix guaranteed by the parameterization. The observable amplitude content in electroproduction of final particles grows with polarization of beams and targets, providing additional sensitivity to underlying phases. In simulation, the posterior achieves empirical coverage at or above the nominal level and delivers the angular observables and the separated contributions from longitudinal and transverse photons with their correlations retained. It transfers without retraining to a realistic detector response absent from training and remains reliable in the weakly constrained nucleon-helicity-flip sector, where per-bin likelihood maximization degrades. The result is a general framework for a broad class of inverse problems, phase retrieval, quantum-state tomography, and partial-wave analysis are further instances. Its core requires only a forward simulation of the complete measurement process, instrumental effects are handled within one statistically consistent posterior, applicable across exclusive vector-meson programs at Jefferson Lab, COMPASS, HERMES, and the future Electron-Ion Collider.
