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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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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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XENON Collaboration(Aprile, E. et al), & Orrigo, S. E. A. (2016). Physics reach of the XENON1T dark matter experiment. J. Cosmol. Astropart. Phys., 04(4), 027–37pp.
Abstract: The XENON1T experiment is currently in the commissioning phase at the Laboratori Nazionali del Gran Sasso, Italy. In this article we study the experiment's expected sensitivity to the spin-independent WIMP-nucleon interaction cross section, based on Monte Carlo predictions of the electronic and nuclear recoil backgrounds. The total electronic recoil background in 1 tonne fiducial volume and (1, 12) keV electronic recoil equivalent energy region, before applying any selection to discriminate between electronic and nuclear recoils, is (1.80+/-0.15) . 10(-4) (kg.day.keV)(-1), mainly due to the decay of Rn-222 daughters inside the xenon target. The nuclear recoil background in the corresponding nuclear recoil equivalent energy region (4, 50) keV, is composed of (0.6 +/- 0.1) (t.y)(-1) from radiogenic neutrons, (1.8+/-0.3) . 10(-2) (t.y)(-1) from coherent scattering of neutrinos, and less than 0.01 (t.y)(-1) from muon-induced neutrons. The sensitivity of XENON1T is calculated with the Pro file Likelihood Ratio method, after converting the deposited energy of electronic and nuclear recoils into the scintillation and ionization signals seen in the detector. We take into account the systematic uncertainties on the photon and electron emission model, and on the estimation of the backgrounds, treated as nuisance parameters. The main contribution comes from the relative scintillation efficiency L-eff, which affects both the signal from WIMPs and the nuclear recoil backgrounds. After a 2 y measurement in 1 tonne fiducial volume, the sensitivity reaches a minimum cross section of 1.6 . 10(-47) cm(2) at m(chi) = 50 GeV/c(2).
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De Romeri, V., Majumdar, A., Papoulias, D. K., & Srivastava, R. (2024). XENONnT and LUX-ZEPLIN constraints on DSNB-boosted dark matter. J. Cosmol. Astropart. Phys., 03(3), 028–34pp.
Abstract: We consider a scenario in which dark matter particles are accelerated to semirelativistic velocities through their scattering with the Diffuse Supernova Neutrino Background. Such a subdominant, but more energetic dark matter component can be then detected via its scattering on the electrons and nucleons inside direct detection experiments. This opens up the possibility to probe the sub -GeV mass range, a region of parameter space that is usually not accessible at such facilities. We analyze current data from the XENONnT and LUX-ZEPLIN experiments and we obtain novel constraints on the scattering cross sections of sub -GeV boosted dark matter with both nucleons and electrons. We also highlight the importance of carefully taking into account Earth's attenuation effects as well as the finite nuclear size into the analysis. By comparing our results to other existing constraints, we show that these effects lead to improved and more robust constraints.
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Kuo, J. L., Lattanzi, M., Cheung, K., & Valle, J. W. F. (2018). Decaying warm dark matter and structure formation. J. Cosmol. Astropart. Phys., 12(12), 026–24pp.
Abstract: We examine the cosmology of warm dark matter (WDM), both stable and decaying, from the point of view of structure formation. We compare the matter power spectrum associated to WDM masses of 1.5 keV and 0.158 keV, with that expected for the stable cold dark matter ACDM Xi SCDM paradigm, taken as our reference model. We scrutinize the effects associated to the warm nature of dark matter, as well as the fact that it decays. The decaying warm dark matter (DWDM) scenario is well-motivated, emerging in a broad class of particle physics theories where neutrino masses arise from the spontaneous breaking of a continuous global lepton number symmetry. The majoron arises as a Nambu-Goldstone boson, and picks up a mass from gravitational effects, that explicitly violate global symmetries. The majoron necessarily decays to neutrinos, with an amplitude proportional to their tiny mass, which typically gives it cosmologically long lifetimes. Using N-body simulations we show that our DWDM picture leads to a viable alternative to the ACDM scenario, with predictions that can differ substantially on small scales.
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Caron, S., Gomez-Vargas, G. A., Hendriks, L., & Ruiz de Austri, R. (2018). Analyzing gamma rays of the Galactic Center with deep learning. J. Cosmol. Astropart. Phys., 05(5), 058–24pp.
Abstract: We present the application of convolutional neural networks to a particular problem in gamma ray astronomy. Explicitly, we use this method to investigate the origin of an excess emission of GeV gamma rays in the direction of the Galactic Center, reported by several groups by analyzing Fermi-LAT data. Interpretations of this excess include gamma rays created by the annihilation of dark matter particles and gamma rays originating from a collection of unresolved point sources, such as millisecond pulsars. We train and test convolutional neural networks with simulated Fermi-LAT images based on point and diffuse emission models of the Galactic Center tuned to measured gamma ray data. Our new method allows precise measurements of the contribution and properties of an unresolved population of gamma ray point sources in the interstellar diffuse emission model. The current model predicts the fraction of unresolved point sources with an error of up to 10% and this is expected to decrease with future work.
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