arXiv subjects

J. Pérez-Romero

Publications and source records attributed to J. Pérez-Romero.

4 recordsLinked to original sources

arXiv2021

Dark Matter search in dwarf irregular galaxies with the Fermi Large Area Telescope

We analyze 11 years of Fermi-LAT data corresponding to the sky regions of 7 dwarf irregular (dIrr) galaxies. DIrrs are dark matter (DM) dominated systems, proposed as interesting targets for the indirect search of DM with gamma rays. The galaxies represent interesting cases with a strong disagreement between the density profiles (core vs. cusp) inferred from observations and numerical simulations. In this work, we addressed the problem by considering two different DM profiles, based on both the fit to the rotation curve (in this case a Burkert cored profile) and results from N-body cosmological simulations (i.e., NFW cuspy profile). We also include halo substructures in our analysis, which is expected to boost the DM signal a factor of ten in halos such as those of dIrrs. For each DM model and dIrr, we create a spatial template of the expected DM-induced gamma-ray signal to be used in the analysis of Fermi-LAT data. No significant emission is detected from any of the targets in our sample. Thus, we compute upper limits on the DM annihilation cross-section versus mass parameter space. Among the 7 dIrrs, we find IC10 and NGC6822 to yield the most stringent individual constraints, independently of the adopted DM profile. We also produce combined DM limits for all objects in the sample, which turn out to be dominated by IC10 for all DM models and annihilation channels, i.e. $b\bar{b}$, $τ^+τ^-$ and $W^+W^-$. The strongest constraints are obtained for $b\bar{b}$ and are at the level of $\langleσv \rangle \sim 7 \times 10^{-26}\text{cm}^{3}\text{s}^{-1}$ at $m_χ\sim 6$ GeV. Though these limits are a factor of 3 higher than the thermal relic cross section at low WIMP masses, they are independent from and complementary to those obtained by means of other targets.

astro-ph.CO↗

arXiv2021

Probing Dark Matter and Fundamental Physics with the Cherenkov Telescope Array

Astrophysical observations provide strong evidence that more than 80% of all matter in the Universe is in the form of dark matter (DM). Two leading candidates of particles beyond the Standard Model that could constitute all or a fraction of the DM content are the so-called Weakly Interacting Massive Particles (WIMPs) and Axion-Like Particles (ALPs). The upcoming Cherenkov Telescope Array, which will observe gamma rays between 20 GeV and 300 TeV with unprecedented sensitivity, will have unique capabilities to search for these DM candidates. A particularly promising target for WIMP searches is the Galactic Center. WIMPs with annihilation cross sections correctly producing the DM relic density will be detectable with CTA, assuming an Einasto-like density profile and WIMP masses between 200 GeV and 10 TeV. Regarding new physics beyond DM, CTA observations will also enable tests of fundamental symmetries of nature such as Lorentz invariance.

astro-ph.HE↗

arXiv2020

MINOT: Modeling the intracluster medium (non-)thermal content and observable prediction tools

In the past decade, the observations of diffuse radio synchrotron emission toward galaxy clusters revealed cosmic-ray (CR) electrons and magnetic fields on megaparsec scales. However, their origin remains poorly understood, and several models have been discussed in the literature. CR protons are also expected to accumulate during the formation of clusters and probably contribute to the production of these high-energy electrons. In order to understand the physics of CRs in clusters, combining of observations at various wavelengths is particularly relevant. The exploitation of such data requires using a self-consistent approach including both the thermal and the nonthermal components, so that it is capable of predicting observables associated with the multiwavelength probes at play, in particular in the radio, millimeter, X-ray, and gamma-ray bands. We develop and describe such a self-consistent modeling framework, called MINOT (modeling the intracluster medium (non-)thermal content and observable prediction tools) and make this tool available to the community. The multiwavelength observables are computed based on the relevant physical process, according to the cluster location, and based on the sampling defined by the user. We describe the implementation of MINOT and how to use it. We also discuss the different assumptions and approximations that are involved and provide various examples regarding the production of output products at different wavelengths. As an illustration, we model the clusters A1795, A2142, and A2255 and compare the MINOT predictions to literature data. MINOT can be used to model the cluster thermal and nonthermal physical processes for a wide variety of datasets in the radio, millimeter, X-ray, and gamma-ray bands, as well as the neutrino emission. [abridged]

astro-ph.HE↗

arXiv2018

Management of Network Slicing in 5G Radio Access Networks: Functional Framework and Information Models

Network slicing is one of the key features for 5G networks to be able to accommodate the anticipated diversity of applications and business actors in a resource-efficient manner. While significant progress has already been achieved at 3GPP specifications level with regard to the system architectural and functional aspects for the realisation of network slicing in 5G networks, management solutions for the exploitation of this feature in the Next Generation Radio Access Network (NG-RAN) are still at a very incipient stage. In this context, this paper presents a framework for the management of network slicing in a NG-RAN infrastructure, identifying the functions, interfaces and information models that are necessary to enable the automation of the RAN slicing provisioning and management processes. Accordingly, a plausible information model intended to describe the manageable characteristics and behaviour of a RAN slice is developed and its applicability discussed in an illustrative neutral host provider scenario.

cs.NI↗