调查作为宇宙射线源的超新星残余的 CREDIT 历史

Anton Stall, Chun Khai Loo, Philipp Mertsch
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引用次数: 0

摘要

长期以来,人们一直怀疑超新星剩余物(SNR)是银河宇宙射线的主要来源。在过去的几十年里,人们在粒子加速、磁场放大和SNR逃逸的建模方面取得了长足的进步。然而,尽管已经观测到许多 SNR 在射电、X 射线和伽马射线中的非热辐射,却没有证据表明有任何单个天体对本地观测到的通量做出了贡献。在这里,我们提出了来自单个残余物的特殊光谱特征,这是由于SNR的能量逃逸造成的。对于年轻的和附近的源,我们预测在狭窄的刚性区间内,通量会增强百分之几十;考虑到当代宇宙射线数据的通量不确定性,这种特征应该很容易被探测到。我们用蒙特卡洛方法对源的空间和时间分布以及由此产生的通量分布进行了建模。我们在模拟数据上训练的决策树能够以极高的显著性区分光滑源分布的零假设和单个源的随机分布情况。我们建议在实验搜索中考虑这种宇宙射线能量依赖注入时间(CREDIT)的情况,以确定单个SNR为宇宙射线源。
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Investigating the CREDIT history of supernova remnants as cosmic-ray sources
Supernova remnants (SNRs) have long been suspected to be the primary sources of Galactic cosmic rays. Over the past decades, great strides have been made in the modelling of particle acceleration, magnetic field amplification, and escape from SNRs. Yet, while many SNRs have been observed in non-thermal emission in radio, X-rays, and gamma-rays, there is no evidence for any individual object contributing to the locally observed flux. Here, we propose a particular spectral signature from individual remnants that is due to the energy-dependent escape from SNRs. For young and nearby sources, we predict fluxes enhanced by tens of percent in narrow rigidity intervals; given the percent-level flux uncertainties of contemporary cosmic-ray data, such features should be readily detectable. We model the spatial and temporal distribution of sources and the resulting distribution of fluxes with a Monte Carlo approach. The decision tree that we have trained on simulated data is able to discriminate with very high significance between the null hypothesis of a smooth distribution of sources and the scenario with a stochastic distribution of individual sources. We suggest that this cosmic-ray energy-dependent injection time (CREDIT) scenario be considered in experimental searches to identify individual SNRs as cosmic-ray sources.
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