标题： 基于信息场理论的宇宙射线无线电探测器事件重构 显示英文标题

标题： Information Field Theory based Event Reconstruction for Cosmic Ray Radio Detectors

摘要： 通过无线电天线检测广延空气簇射是宇宙射线物理中一种有吸引力的技术。 然而，由于测量噪声水平较高，目前的重建方法仍有改进空间。 此外，重建工作通常只关注信号的单一方面，例如能量通量或到达时间。 因此，贝叶斯推断是进行整体重建的自然选择，但这个问题将是病态的，因为电场是一个连续量。 信息场理论通过提供一个统计框架来处理连续极限下的离散场，从而解决了这个问题。 我们目前正在开发这种新方法来重建广延空气簇射的模型。 此处描述的模型基于对辐射机制的当前最佳理解：它使用横向信号强度分布、电荷过剩贡献和光谱形状的参数化。 在模型中，阵列间的簇射波动和窄带射频干扰使用高斯过程进行建模。 结合详细的探测器描述，该模型不仅可以推断电场，还可以推算簇射几何结构、电磁能量以及簇射最大位置。 这种方法的另一个重大成就是其能够自然地为重建提供不确定性，这在更传统的方法中已被证明是困难的。 有了这样的开放框架和基于信息场理论的稳健计算方法，未来也很容易纳入新的见解和额外的数据，例如时间分布或粒子探测器数据。 这种方法具有很高的潜力，能够以直接包含领域知识的方式，利用复杂探测器的全部信息内容，并采用严格的统计方法。 显示英文摘要

摘要： Detection of extensive air showers with radio antennas is an appealing technique in cosmic ray physics. However, because of the high level of measurement noise, current reconstruction methods still leave room for improvement. Furthermore, reconstruction efforts typically focus only on a single aspect of the signal, such as the energy fluence or arrival time. Bayesian inference is then a natural choice for a holistic approach to reconstruction, yet, this problem would be ill-posed, since the electric field is a continuous quantity. Information Field Theory provides the solution for this by providing a statistical framework to deal with discretised fields in the continuum limit. We are currently developing models for this novel approach to reconstructing extensive air showers. The model described here is based on the best current understanding of the emission mechanisms: It uses parametrisations of the lateral signal strength distribution, charge-excess contribution and spectral shape. Shower-to-shower fluctuations and narrowband RFI are modelled using Gaussian processes. Combined with a detailed detector description, this model can infer not only the electric field, but also the shower geometry, electromagnetic energy and position of shower maximum. Another big achievement of this approach is its ability to naturally provide uncertainties for the reconstruction, which has been shown to be difficult in more traditional methods. With such an open framework and robust computational methods based in Information Field Theory, it will also be easy to incorporate new insights and additional data, such as timing distributions or particle detector data, in the future. This approach has a high potential to exploit the full information content of a complex detector with rigorous statistical methods, in a way that directly includes domain knowledge.