English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The two leading hypotheses for the Galactic Center Excess (GCE) in the$\textit{Fermi}$ data are an unresolved population of faint millisecond pulsars(MSPs) and dark-matter (DM) annihilation. The dichotomy between theseexplanations is typically reflected by modeling them as two separate emissioncomponents. However, point-sources (PSs) such as MSPs become statisticallydegenerate with smooth Poisson emission in the ultra-faint limit (formallywhere each source is expected to contribute much less than one photon onaverage), leading to an ambiguity that can render questions such as whether theemission is PS-like or Poissonian in nature ill-defined. We present aconceptually new approach that describes the PS and Poisson emission in aunified manner and only afterwards derives constraints on the Poissoniancomponent from the so obtained results. For the implementation of thisapproach, we leverage deep learning techniques, centered around a neuralnetwork-based method for histogram regression that expresses uncertainties interms of quantiles. We demonstrate that our method is robust against a numberof systematics that have plagued previous approaches, in particular DM / PSmisattribution. In the $\textit{Fermi}$ data, we find a faint GCE described bya median source-count distribution (SCD) peaked at a flux of $\sim4 \times10^{-11} \ \text{counts} \ \text{cm}^{-2} \ \text{s}^{-1}$ (corresponding to$\sim3 - 4$ expected counts per PS), which would require $N \sim\mathcal{O}(10^4)$ sources to explain the entire excess (median value $N =\text{29,300}$ across the sky). Although faint, this SCD allows us to derivethe constraint $\eta_P \leq 66\%$ for the Poissonian fraction of the GCE flux$\eta_P$ at 95% confidence, suggesting that a substantial amount of the GCEflux is due to PSs.

Dim but not entirely dark: Extracting the Galactic Center Excess' source-count distribution with neural nets