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

Abstract

The two leading hypotheses for the Galactic Center Excess (GCE) in the $\text{Fermi}$ data are an unresolved population of faint millisecond pulsars (MSPs) and dark-matter (DM) annihilation. The dichotomy between these explanations is typically reflected by modeling them as two separate emission components. However, point-sources (PSs) such as MSPs become statistically degenerate with smooth Poisson emission in the ultra-faint limit (formally where each source is expected to contribute much less than one photon on average), leading to an ambiguity that can render questions such as whether the emission is PS-like or Poissonian in nature ill-defined. We present a conceptually new approach that describes the PS and Poisson emission in a unified manner and only afterwards derives constraints on the Poissonian component from the so obtained results. For the implementation of this approach, we leverage deep learning techniques, centered around a neural network-based method for histogram regression that expresses uncertainties in terms of quantiles. We demonstrate that our method is robust against a number of systematics that have plagued previous approaches, in particular DM / PS misattribution. In the $\text{Fermi}$ data, we find a faint GCE described by a median source-count distribution (SCD) peaked at a flux of $\sim 4\times 10^{-11}\text{counts}{\text{cm}}^{-2}{\text{s}}^{-1}$ (corresponding to $\sim 3-4$ 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 derive the constraint ${\eta }_P\le 66\%$ for the Poissonian fraction of the GCE flux ${\eta }_P$ at 95% confidence, suggesting that a substantial amount of the GCE flux is due to PSs.

36+9 pages, 15+7 figures, main results in Figs. 8 and 12. v2 matches published version in Phys. Rev. D

References in corpus (13)

• Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
• Giant Gamma-ray Bubbles from Fermi-LAT: AGN Activity or Bipolar Galactic Wind?
• Background model systematics for the Fermi GeV excess
• Cosmic Ray Protons in the Inner Galaxy and the Galactic Center Gamma-Ray Excess
• Galactic Center gamma-ray "excess" from an active past of the Galactic Centre?
• Millisecond pulsars and the Galactic Center gamma-ray excess: the importance of luminosity function and secondary emission
• Millisecond pulsar interpretation of the Galactic center gamma-ray excess
• On Detecting Millisecond Pulsars at the Galactic Center
• Distinguishing Dark Matter from Unresolved Point Sources in the Inner Galaxy with Photon Statistics
• Testing the millisecond pulsar scenario of the Galactic center gamma-ray excess with very high energy gamma-rays
• Young Pulsars and the Galactic Center GeV Gamma-ray Excess
• Discovery of a New Galactic Center Excess Consistent with Upscattered Starlight
• Constraining the Reionization History using Bayesian Normalizing Flows

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• Robust inference of the Galactic centre gamma-ray excess spatial properties
• Probing the pulsar explanation of the Galactic-Center GeV excess using continuous gravitational-wave searches
• Mind the gap: The discrepancy between simulation and reality drives interpretations of the Galactic Center Excess
• A New Determination of the Millisecond Pulsar Gamma-Ray Luminosity Function and Implications for the Galactic Center Gamma-Ray Excess
• Multi-Component Imaging of the Fermi Gamma-ray Sky in the Spatio-spectral Domain
• Towards resolving the Galactic center GeV excess with millisecond-pulsar-like sources using machine learning
• Extracting the gamma-ray source-count distribution below the Fermi-LAT detection limit with deep learning
• Applying Simulation-Based Inference to Spectral and Spatial Information from the Galactic Center Gamma-Ray Excess
• Characterizing the Expected Behavior of Non-Poissonian Template Fitting
• Improved Modeling of the Discrete Component of the Galactic Interstellar Gamma-ray Emission and Implications for the Fermi-LAT Galactic Center Excess
• Multiwavelength identification of millisecond pulsar candidates in the Galactic bulge
• Millisecond Pulsars in Globular Clusters and Implications for the Galactic Center Gamma-Ray Excess
• On the Energy Distribution of the Galactic Center Excess' Sources
• High Energy Emission from the Galactic Center
• Assessing the Impact of Hydrogen Absorption on the Characteristics of the Galactic Center Excess