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Study of the Galactic Center region and searches for dark matter signals with gamma-rays

Grant number: 21/02027-0
Support Opportunities:Scholarships in Brazil - Doctorate (Direct)
Effective date (Start): May 01, 2021
Field of knowledge:Physical Sciences and Mathematics - Physics - Elementary Particle Physics and Fields
Principal Investigator:Aion da Escóssia Melo Viana
Grantee:Igor Reis
Host Institution: Instituto de Física de São Carlos (IFSC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated research grant:19/14893-3 - Extreme phenomena of the Galactic Center and indirect searches of dark matter with gamma rays, AP.JP


The study of gamma-ray astrophysical observations is essential to the understanding of non-thermal phenomena in the universe in their most extreme and violent forms. Their study allow scientists to answer persistent questions across a broad range of topics, including supermassive black-hole systems, pulsars, the origin of cosmic rays, and searches for signals of new physics. Among all the high-energy environments of our galaxy, the Galactic Center (GC) region is definitely the richest. It harbours a large amount of high-energy emitters, including the closest supermassive black hole, a cosmic Pevatron, dense molecular clouds, strong starforming activity, multiple supernova remnants and pulsar wind nebulae, arc-like radio structures, as well as the base of what may be largescale galactic outflows. It stands out as one of the most studied regions of the sky in nearly every wavelength, and has some of the deepest exposures with high-energy observatories (GALÁXIA.E.S.S., Fermi-LAT, Chandra, XMM, INTEGRAL), which have provided an enormous amount of scientific results. Moreover, this region is also expected to be the brightest source of Dark Matter (DM) annihilations in the gamma-ray sky by several orders of magnitude. Even considering the contamination from standard astrophysical sources, it is one of the most promising targets to detect the presence of new massive particles. This project aims to understand the high-energy gamma-ray astrophysics and astroparticle physics of the Galactic Centre region and its relationship to diffuse emissions in other wavelengths and at different scales in the galaxy. Special attention will be given to the use of advanced astronomical softwares to handle gamma-ray data, such as Astropy, Gammapy, CTools, and numerical libraries that can generate non-thermal radiation from a population of relativistic particle, such as Naima or Gamera. These softwares will be used to analyze real data from observations of the Galactic Center region by the Fermi-LAT and GALÁXIA.E.S.S. telescopes. In particular, the student will work on the implementation of a multi-dimensional template (or cube) analysis, where models of spatial and energy distribution of the emission are used to disentangle overlapping sources in complex regions. This will allow the deep study of the astrophysics of known gamma-ray source in this region, such as SgrA*, the Galactic Ridge, J1745-303 and G+0.9-0.1, as well as to search for new sources of very-high-energy gamma-rays, such as the Inner Fermi Bubble and DM annihilation in the GC halo. In the case of no detection of a DM annihilation signal, constraints to theoretical models of DM particle will be derived. Similar procedure may be applied to the search of DM signals in other high-density environments of the universe, such as dwarf galaxies and galaxy clusters. Finally, the sensitivity of future observatories, such as the Southern Wide field-of-view Gamma-ray Observatory (SWGO) and the Cherenkov Telescope Array (CTA), to study the astrophysics of the GC region, as well as to detect DM annihilation signals from the most promising targets in the universe will be performed. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
VALERIANO, JOAO PEDRO; CINTRA, PEDRO HENRIQUE; LIBOTTE, GUSTAVO; REIS, IGOR; FONTINELE, FELIPE; SILVA, RENATO; MALTA, SANDRA. Sequential time-window learning with approximate Bayesian computation: an application to epidemic forecasting. NONLINEAR DYNAMICS, v. 111, n. 1, p. 10-pg., . (21/02027-0, 20/14169-0)

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