Astronomical observations typically provide three-dimensional maps, encoding
the distribution of the observed flux in (1) the two angles of the celestial
sphere and (2) energy/frequency. An important task regarding such maps is to
statistically characterize populations of point sources too dim to be
individually detected. As the properties of a single dim source will be poorly
constrained, instead one commonly studies the population as a whole, inferring
a source-count distribution (SCD) that describes the number density of sources
as a function of their brightness. Statistical and machine learning methods for
recovering SCDs exist; however, they typically entirely neglect spectral
information associated with the energy distribution of the flux. We present a
deep learning framework able to jointly reconstruct the spectra of different
emission components and the SCD of point-source populations. In a
proof-of-concept example, we show that our method accurately extracts even
complex-shaped spectra and SCDs from simulated maps.

天文观测通常提供三维地图，编码观测通量在天球的两个角度和能量 / 频率上的分布。我们提出了一个深度学习框架，能够同时重建不同发射成分的光谱和点源群体的源计数分布，实现了从模拟地图中准确提取复杂形状的光谱和源计数分布的目标。

一种用于在天文学中联合提取光谱和源计数分布的深度学习框架

A deep learning framework for jointly extracting spectra and  source-count distributions in astronomy

The origin of high-energy cosmic rays, atomic nuclei that continuously impact
Earth's atmosphere, has been a mystery for over a century. Due to deflection in
interstellar magnetic fields, cosmic rays from the Milky Way arrive at Earth
from random directions. However, near their sources and during propagation,
cosmic rays interact with matter and produce high-energy neutrinos. We search
for neutrino emission using machine learning techniques applied to ten years of
data from the IceCube Neutrino Observatory. We identify neutrino emission from
the Galactic plane at the 4.5$\sigma$ level of significance, by comparing
diffuse emission models to a background-only hypothesis. The signal is
consistent with modeled diffuse emission from the Galactic plane, but could
also arise from a population of unresolved point sources.

寻找了高能宇宙射线的中微子发射，证实了银河系平面有中微子发射，但这也可能来自未解析的点源。