Mind the gap: The discrepancy between simulation and reality drives interpretations of the Galactic Center Excess

Abstract

The Galactic Center Excess (GCE) in GeV gamma rays has been debated for over a decade, with the possibility that it might be due to dark matter annihilation or undetected point sources such as millisecond pulsars (MSPs). This study investigates how the gamma-ray emission model ($\gamma$EM) used in Galactic center analyses affects the interpretation of the GCE's nature. To address this issue, we construct an ultra-fast and powerful inference pipeline based on convolutional Deep Ensemble Networks. We explore the two main competing hypotheses for the GCE using a set of $\gamma$EMs with increasing parametric freedom. We calculate the fractional contribution ($f_{\mathrm{src}}$) of a dim population of MSPs to the total luminosity of the GCE and analyze its dependence on the complexity of the $\gamma$EM. For the simplest $\gamma$EM, we obtain $f_{\mathrm{src}}=0.10\pm 0.07$, while the most complex model yields $f_{\mathrm{src}}=0.79\pm \mathrm{0.24.}$ In conclusion, we find that the statement about the nature of the GCE (dark matter or not) strongly depends on the assumed $\gamma$EM. The quoted results for $f_{\mathrm{src}}$ do not account for the additional uncertainty arising from the fact that the observed gamma-ray sky is out-of-distribution concerning the investigated $\gamma$EM iterations. We quantify the reality gap between our $\gamma$EMs using deep-learning-based One-Class Deep Support Vector Data Description networks, revealing that all employed $\gamma$EMs have gaps to reality. Our study casts doubt on the validity of previous conclusions regarding the GCE and dark matter, and underscores the urgent need to account for the reality gap and consider previously overlooked ''out of domain'' uncertainties in future interpretations.

56 pages, 25 figures; comments welcome! Accepted for submission to JCAP; text coincides with the published version

References in corpus (21)

• The Parkes multibeam pulsar survey: VI. Discovery and timing of 142 pulsars and a Galactic population analysis
• Background model systematics for the Fermi GeV excess
• Dynamical modelling of the Galactic bulge and bar: the Milky Way's bar pattern speed, stellar, and dark matter mass distribution
• A Tale of Tails: Dark Matter Interpretations of the Fermi GeV Excess in Light of Background Model Systematics
• Possible Evidence For Dark Matter Annihilation In The Inner Milky Way From The Fermi Gamma Ray Space Telescope
• Gamma Ray Signals from Dark Matter: Concepts, Status and Prospects
• GeV excess in the Milky Way: The Role of Diffuse Galactic gamma ray Emission template
• 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?
• The Return of the Templates: Revisiting the Galactic Center Excess with Multi-Messenger Observations
• Rare and Different: Anomaly Scores from a combination of likelihood and out-of-distribution models to detect new physics at the LHC
• A neural simulation-based inference approach for characterizing the Galactic Center $\gamma$-ray excess
• Dissecting the inner Galaxy with $\gamma$-ray pixel count statistics
• Estimating the GeV Emission of Millisecond Pulsars in Dwarf Spheroidal Galaxies
• Dim but not entirely dark: Extracting the Galactic Center Excess' source-count distribution with neural nets
• A stacked analysis of 115 pulsars observed by the Fermi LAT
• Luminosity functions consistent with a pulsar-dominated Galactic Center Excess
• Molecular Clouds as the Origin of the Fermi Gamma-Ray GeV-Excess
• Bayesian inference of three-dimensional gas maps: II. Galactic HI
• Deep Learning Models of the Discrete Component of the Galactic Interstellar Gamma-Ray Emission
• Assessing the Impact of Hydrogen Absorption on the Characteristics of the Galactic Center Excess

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• Robust inference of the Galactic centre gamma-ray excess spatial properties
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• Towards resolving the Galactic center GeV excess with millisecond-pulsar-like sources using machine learning
• AutoSourceID-FeatureExtractor. Optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation
• Search for GeV-scale Dark Matter from the Galactic Center with IceCube-DeepCore
• Millisecond Pulsars in Globular Clusters and Implications for the Galactic Center Gamma-Ray Excess