Amoroso, S., Caron, S., Jueid, A., Ruiz de Austri, R., & Skands, P. (2019). Estimating QCD uncertainties in Monte Carlo event generators for gamma-ray dark matter searches. J. Cosmol. Astropart. Phys., 05(5), 007–44pp.
Abstract: Motivated by the recent galactic center gamma-ray excess identified in the Fermi-LAT data, we perform a detailed study of QCD fragmentation uncertainties in the modeling of the energy spectra of gamma-rays from Dark-Matter (DM) annihilation. When Dark-Matter particles annihilate to coloured final states, either directly or via decays such as W(*) -> qq-', photons are produced from a complex sequence of shower, hadronisation and hadron decays. In phenomenological studies their energy spectra are typically computed using Monte Carlo event generators. These results have however intrinsic uncertainties due to the specific model used and the choice of model parameters, which are difficult to asses and which are typically neglected. We derive a new set of hadronisation parameters (tunes) for the PYTHIA 8.2 Monte Carlo generator from a fit to LEP and SLD data at the Z peak. For the first time we also derive a conservative set of uncertainties on the shower and hadronisation model parameters. Their impact on the gamma-ray energy spectra is evaluated and discussed for a range of DM masses and annihilation channels. The spectra and their uncertainties are also provided in tabulated form for future use. The fragmentation-parameter uncertainties may be useful for collider studies as well.
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Caron, S., Eckner, C., Hendriks, L., Johannesson, G., Ruiz de Austri, R., & Zaharijas, G. (2023). Mind the gap: the discrepancy between simulation and reality drives interpretations of the Galactic Center Excess. J. Cosmol. Astropart. Phys., 06(6), 013–56pp.
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 (-yEM) 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-yEMs with increasing parametric freedom. We calculate the fractional contribution (fsrc) of a dim population of MSPs to the total luminosity of the GCE and analyze its dependence on the complexity of the ryEM. For the simplest ryEM, we obtain fsrc = 0.10 f 0.07, while the most complex model yields fsrc = 0.79 f 0.24. In conclusion, we find that the statement about the nature of the GCE (dark matter or not) strongly depends on the assumed ryEM. The quoted results for fsrc do not account for the additional uncertainty arising from the fact that the observed gamma-ray sky is out-of-distribution concerning the investigated ryEM iterations. We quantify the reality gap between our ryEMs using deep-learning-based One-Class Deep Support Vector Data Description networks, revealing that all employed ryEMs 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.
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Moline, A., Schewtschenko, J. A., Palomares-Ruiz, S., Boehm, C., & Baugh, C. M. (2016). Isotropic extragalactic flux from dark matter annihilations: lessons from interacting dark matter scenarios. J. Cosmol. Astropart. Phys., 08(8), 069–23pp.
Abstract: The extragalactic gamma-ray and neutrino emission may have a contribution from dark matter (DM) annihilations. In the case of discrepancies between observations and standard predictions, one could infer the DM pair annihilation cross section into cosmic rays by studying the shape of the energy spectrum. So far all analyses of the extragalactic DM signal have assumed the standard cosmological model (ACDM) as the underlying theory. However, there are alternative DM scenarios where the number of low-mass objects is significantly suppressed. Therefore the characteristics of the gamma-ray and neutrino emission in these models may differ from ACDM as a result. Here we show that the extragalactic isotropic signal in these alternative models has a similar energy dependence to that in ACDM, but the overall normalisation is reduced. The similarities between the energy spectra combined with the flux suppression could lead one to misinterpret possible evidence for models beyond ACDM as being due to CDM particles annihilating with a much weaker cross section than expected.
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Aoki, M., Toma, T., & Vicente, A. (2015). Non-thermal production of minimal dark matter via right-handed neutrino decay. J. Cosmol. Astropart. Phys., 09(9), 063–19pp.
Abstract: Minimal Dark Matter (MDM) stands as one of the simplest dark matter scenarios. In MDM models, annihilation and co-annihilation processes among the members of the MDM multiplet are usually very efficient, pushing the dark matter mass above O(10) TeV in order to reproduce the observed dark matter relic density. Motivated by this little drawback, in this paper we consider an extension of the MDM scenario by three right-handed neutrinos. Two specific choices for the MDM multiplet are studied: a fermionic SU(2)(L) quintuplet and a scalar SU(2)(L) septuplet. The lightest right-handed neutrino, with tiny Yukawa couplings, never reaches thermal equilibrium in the early universe and is produced by freeze-in. This creates a link between dark matter and neutrino physics: dark matter can be non-thermally produced by the decay of the lightest right-handed neutrino after freeze-out, allowing to lower significantly the dark matter mass. We discuss the phenomenology of the non-thermally produced MDM and, taking into account significant Sommerfeld corrections, we find that the dark matter mass must have some specific values in order not to be in conflict with the current bounds from gamma-ray observations.
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Amerio, A., Cuoco, A., & Fornengo, N. (2023). Extracting the gamma-ray source-count distribution below the Fermi-LAT detection limit with deep learning. J. Cosmol. Astropart. Phys., 09(9), 029–39pp.
Abstract: We reconstruct the extra-galactic gamma-ray source-count distribution, or dN/dS, of resolved and unresolved sources by adopting machine learning techniques. Specifically, we train a convolutional neural network on synthetic 2-dimensional sky-maps, which are built by varying parameters of underlying source-counts models and incorporate the FermiLAT instrumental response functions. The trained neural network is then applied to the Fermi-LAT data, from which we estimate the source count distribution down to flux levels a factor of 50 below the Fermi-LAT threshold. We perform our analysis using 14 years of data collected in the (1, 10) GeV energy range. The results we obtain show a source count distribution which, in the resolved regime, is in excellent agreement with the one derived from cataloged sources, and then extends as dN/dS " S-2 in the unresolved regime, down to fluxes of 5 center dot 10-12 cm-2 s-1. The neural network architecture and the devised methodology have the flexibility to enable future analyses to study the energy dependence of the source-count distribution.
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