3 research outputs found
-factors for self-interacting dark matter in 20 dwarf spheroidal galaxies
Dwarf spheroidal galaxies are among the most promising targets for indirect
dark matter (DM) searches in -rays. The -ray flux from DM
annihilation in a dwarf spheroidal galaxy is proportional to the -factor of
the source. The -factor of a dwarf spheroidal galaxy is the line-of-sight
integral of the DM mass density squared times , where is the DM annihilation cross-section times relative velocity , angle brackets denote average over , and is the -independent
part of . If is
constant in , -factors only depend on the DM space distribution
in the source. However, if varies with , as in the presence of DM self-interactions, -factors also depend on
the DM velocity distribution, and on the strength and range of the DM
self-interaction. Models for self-interacting DM are increasingly important in
the study of the small scale clustering of DM, and are compatible with current
cosmological observations. Here we derive the -factor of 20 dwarf spheroidal
galaxies from stellar kinematic data under the assumption of Yukawa DM
self-interactions. -factors are derived through a profile Likelihood
approach, assuming either NFW or cored DM profiles. We also compare our results
with -factors derived assuming the same velocity for all DM particles in the
target galaxy. We find that this common approximation overestimates the
-factors by up to one order of magnitude. -factors for a sample of DM
particle masses, self-interaction coupling constants and density profiles are
provided electronically, ready to be used in other projects.Comment: 10 pages, 3 figures and 2 table
Efficacy of SARS-CoV-2 Vaccination in Dialysis Patients: Epidemiological Analysis and Evaluation of the Clinical Progress
This study investigated the impact of the fourth COVID-19 pandemic wave on dialysis patients of Romagna territory, assessing the associations of vaccination status with infection risk, clinical severity and mortality. From November 2021 to February 2022, an epidemiological search was conducted on 829 patients under dialysis treatment for at least one month. The data were then analyzed with reference to the general population of the same area. A temporal comparison was also carried out with the previous pandemic waves (from March 2020 to October 2021). The epidemiological evolution over time in the dialysis population and in Romagna citizens replicated the global trend, as the peak of the fourth wave corresponded to the time of maximum diffusion of omicron variant (B.1.1.529). Of 771 prevalent dialysis patients at the beginning of the study, 109 (14.1%) contracted SARS-CoV-2 infection during the 4-month observation period. Vaccine adherence in the dialysis population of the reference area was above 95%. Compared to fully or partially vaccinated subjects, the unvaccinated ones showed a significantly higher proportion of infections (12.5% vs. 27.0% p = 0.0341), a more frequent need for hospitalization (22.2% vs. 50.0%) and a 3.3-fold increased mortality risk. These findings confirm the effectiveness of COVID-19 vaccines in keeping infectious risk under control and ameliorating clinical outcomes in immunocompromised patients
Dark matter signal normalisation for dwarf spheroidal galaxies : A frequentist analysis of stellar kinematics for indirect Dark Matter searches
Indirect detection strategies of Dark Matter (DM) entail searching for signals of DM annihilation or decay, typically in the form of excess positrons or high-energy photons above the astrophysical background, originating from (inferred) DM-rich environments. Due to their characteristics, dwarf spheroidal satellite galaxies (dSphs) of the Milky Way are considered very promising targets for indirect particle DM identification. To compare model predictions with the observed fluxes of product particles, most analyses of astrophysical data - which are generally performed via frequentist statistics - rely on estimating the abundance of DM by calculating the so-called J-factor. This quantity is usually inferred from the kinematic properties of the stellar population of a dSph, performing a Jeans analysis by means of Bayesian techniques. Previous works have, therefore, combined different statistical methods when analysing astrophysical data from dSphs. This thesis describes the development of a new, fully frequentist approach for constructing the profile likelihood curve for J-factors of dSphs, which can be implemented in indirect DM searches. This method improves upon previous ones by producing data-driven expressions of the likelihood of J, thereby allowing a statistically consistent treatment of the astroparticle and astrometric data from dSphs. Using kinematic data from twenty one satellites of the Milky Way, we derive estimates of their maximum likelihood J-factor and its confidence intervals. The analyses are performed in two different frameworks: the standard scenario of a collisionless DM candidate and the possibility of a self-interacting DM species. In the former case, the obtained J-factors and their uncertainties are consistent with previous, Bayesian-derived values. In the latter, we present prior-less estimates for the Sommerfeld enhanced J-factor of dSphs. In agreement with earlier studies, we find J to be overestimated by several orders of magnitude when DM is allowed is attractively self-interact. In both cases we provide the profile likelihood curves obtained. This technique is validated on a publicly available simulation suite, released by Gaia Challenge, by evaluating its coverage and bias. The results of these tests indicate that the method possesses good statistical properties. Lastly, we discuss the implications of these findings for DM searches, together with future improvements and extensions of this technique.At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.</p