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Moline, A., Ibarra, A., & Palomares-Ruiz, S. (2015). Future sensitivity of neutrino telescopes to dark matter annihilations from the cosmic diffuse neutrino signal. J. Cosmol. Astropart. Phys., 06(6), 005–34pp.
Abstract: Cosmological observations and cold dark matter N-body simulations indicate that our Universe is populated by numerous halos, where dark matter particles annihilate, potentially producing Standard Model particles. In this paper we calculate the contribution to the diffuse neutrino background from dark matter annihilations in halos at all redshifts and we estimate the future sensitivity to the annihilation cross section of neutrino telescopes such as IceCube or ANTARES. We consider various parametrizations to describe the internal halo properties and for the halo mass function in order to bracket the theoretical uncertainty in the limits from the modeling of the cosmological annihilation flux. We find that observations of the cosmic diffuse neutrino flux at large angular distances from the galactic center lead to constraints on the dark matter annihilation cross section which are complementary to ( and for some extrapolations of the astrophysical parameters, better than) those stemming from observations of the Milky Way halo, especially for neutrino telescopes not pointing directly to the Milky Way center, as is the case of IceCube.
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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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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.
Keywords: gamma ray experiments; dark matter simulations
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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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de Putter, R., Wagner, C., Mena, O., Verde, L., & Percival, W. J. (2012). Thinking outside the box: effects of modes larger than the survey on matter power spectrum covariance. J. Cosmol. Astropart. Phys., 04(4), 019–31pp.
Abstract: Accurate power spectrum (or correlation function) covariance matrices are a crucial requirement for cosmological parameter estimation from large scale structure surveys. In order to minimize reliance on computationally expensive mock catalogs, it is important to have a solid analytic understanding of the different components that make up a covariance matrix. Considering the matter power spectrum covariance matrix, it has recently been found that there is a potentially dominant effect on mildly non-linear scales due to power in modes of size equal to and larger than the survey volume. This beat coupling effect has been derived analytically in perturbation theory and while it has been tested with simulations, some questions remain unanswered. Moreover, there is an additional effect of these large modes, which has so far not been included in analytic studies, namely the effect on the estimated average density which enters the power spectrum estimate. In this article, we work out analytic, perturbation theory based expressions including both the beat coupling and this local average effect and we show that while, when isolated, beat coupling indeed causes large excess covariance in agreement with the literature, in a realistic scenario this is compensated almost entirely by the local average effect, leaving only similar to 10% of the excess. We test our analytic expressions by comparison to a suite of large N-body simulations, using both full simulation boxes and subboxes thereof to study cases without beat coupling, with beat coupling and with both beat coupling and the local average effect. For the variances, we find excellent agreement with the analytic expressions for k < 0.2 hMpc(-1) at z = 0.5, while the correlation coefficients agree to beyond k = 0.4 hMpc(-1). As expected, the range of agreement increases towards higher redshift and decreases slightly towards z = 0. We finish by including the large-mode effects in a full covariance matrix description for arbitrary survey geometry and confirming its validity using simulations. This may be useful as a stepping stone towards building an actual galaxy (or other tracer's) power spectrum covariance matrix.
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