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.

Abstract: Cosmological simulations play a pivotal role in understanding the properties of the dark matter (DM) distribution in both galactic and galaxy -cluster environments. The characterization of DM structures is crucial for informing indirect DM searches, aiming at the detection of the annihilation (or decay) products of DM particles. A fundamental quantity in these analyses is the astrophysical J -factor. In the DM phenomenology community, J -factors are typically computed through the semi -analytical modelling of the DM mass distribution, which is affected by large uncertainties. With the scope of addressing and possibly reducing these uncertainties, we present NAJADS, a self-contained framework to derive the DM J -factor directly from the raw simulations data. We show how this framework can be used to compute all -sky maps of the J -factor, automatically accounting for the complex 3D structure of the simulated halos and for the boosting of the signal due to the density fluctuations along the line of sight. After validating our code, we present a proof -of -concept application of NAJADS to a realistic halo from the IllustrisTNG suite, and exploit it to make a thorough comparison between our numerical approach and traditional semi -analytical methods. JCAP02(2024)001

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.

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.

Abstract: Nonzero neutrino masses are required by the existence of flavour oscillations, with values of the order of at least 50 meV. We consider the gravitational clustering of relic neutrinos within the Milky Way, and used the N – one-body simulation technique to compute their density enhancement factor in the neighbourhood of the Earth with respect to the average cosmic density. Compared to previous similar studies, we pushed the simulation down to smaller neutrino masses, and included an improved treatment of the baryonic and dark matter distributions in the Milky Way. Our results are important for future experiments aiming at detecting the cosmic neutrino background, such as the Princeton Tritium Observatory for Light, Early-universe, Massive-neutrino Yield (PTOLEMY) proposal. We calculate the impact of neutrino clustering in the Milky Way on the expected event rate for a PTOLEMY-like experiment. We find that the effect of clustering remains negligible for the minimal normal hierarchy scenario, while it enhances the event rate by 10 to 20% (resp. a factor 1.7 to 2.5) for the minimal inverted hierarchy scenario (resp. a degenerate scenario with 150 meV masses). Finally we compute the impact on the event rate of a possible fourth sterile neutrino with a mass of 1.3 eV.