Confronting self-interacting dark matter with observational data
Dwarf galaxies are dark matter (DM) dominated systems, and therefore provide ideal laboratories to study not only the DM halo and galaxy structure, but also the nature of DM. It has been proposed that DM particles experience collisions against each other, and to further constrain the rate of these collisions, recent studies (e.g. Valli & Yu 2018) have derived a semi-analytic approach for describing self-interacting DM halo profiles, called the Jeans model. This approach is only valid in the regime where the mean free path is larger than the typical size of the collisional region (corresponding to a small collision cross section). A recent study (Correa 2020), however, is predicting that the dwarf galaxies that orbit around the Milky Way are in gravothermal core-collapse, a state where DM-DM collisions increase the density in the central regions. This scenario invalidates the Jeans model analysis of these systems, as well as the current upper limits of the DM collision cross sections.
The goals of this research project are to derive an alternative model for describing self-interacting DM halo profiles under gravothermal collapse, use the latest observational data from the local dwarfs to constrain their density profile and provide new upper limits to the DM collision cross sections. During the first part of the project the student will study the density profile of self-interacting DM haloes using cosmological simulations of galaxy formation.
By carrying out this project, the student will learn about the observations of galaxies from the local group, cosmological simulations of galaxy formation, as well as the theory of structure formation.
Valli & Yu (2018) Correa (2020)
Galactic clues to the nature of dark matter
Understanding the nature of dark matter (DM) has become one of the most pressing questions in modern physics and cosmology. Evidence for its existence is exclusively based on its gravitational interactions, as we still know very little about its particle properties. Recent studies are investigating the possibility that DM particles experience collisions against each other. The rate of such collisions can be constrained from observed galaxy density profiles, spanning from dwarf galaxy scales (e.g. Correa 2020) to cluster scales (e.g. Sagunski et al. 2020).
However, a theoretical model for the DM particle interactions, that connects the recent observational estimations at various galaxy scales, is still missing. The goals of this research project are to derive such model arguing that DM exists in a ‘hidden sector’, where forces between DM particles are mediated by analogues to electroweak or strong forces. The following steps will be to implement the model in a numerical simulation of galaxy formation, produce simulation runs using the supercomputer cartesius, and investigate observational signatures of self-interacting DM.
Numerical simulations have become an almost indispensable tool in astrophysical research. By carrying out this project, the student will learn about cosmological simulations of galaxy formation, parallelisation and high-performance computing. The student will also connect particle physics modelling with cosmology while building a solid understanding of structure formation.
Higher order statistics of the gamma-ray data
In recent years, discussions on statistical properties of the all-sky gamma-ray data have been found very efficient to constrain properties of astrophysical sources and dark matter that can contribute to the gamma-ray background. Thus far, however, people argued only up to a second-order moment, i.e., variance or the angular power spectrum, of the distribution of the photon counts. There is however no need to stop there, and therefore, it is natural to question what extra information the next third-order moment, skewness, would bring on top of what has been achieved. Maybe using the skewness or the angular bi-spectrum will be essential in revealing the nature of particle dark matter still hidden in the existing data. Master student will explore this.
Understanding the high energy emission mechanisms in globular clusters of the Milky Way
With the increased sensitivity of gamma-ray detectors such as Fermi-LAT the number of presently known gamma-ray globular clusters has grown by a factor of ~2 in the last year. The new detections are beginning to provide clues about the origin of the high-energy radiation in the form of emerging patterns and correlations among observed quantities such as gamma-ray luminosity, stellar mass and interstellar radiation energy density. But there are still many questions about the mechanisms of emission and intracluster environmental properties. This project will re-examine these emerging patterns and correlations by carefully studying the population of currently undetected globular clusters.
The Hubble Tension
One of the fundamental cosmological parameters is the Hubble constant, which is related to the age of the universe. A way to determine the Hubble constant is to measure the expansion rate of the universe using supernova explosions. Unfortunately, these measurements don’t quite agree with the value of the Hubble constant inferred from the cosmic microwave background. To reconcile these measurements might require a change of the standard model of cosmology.
In this thesis, you will first study the observations that led to the Hubble tension and then explore possible resolutions due to new physics.
Searching for dark matter with gravitational waves
The discovery of gravitational waves has opened new exciting opportunities for fundamental physics. One of the most intriguing aspects of this new “window in the universe” is the possibility to study in unprecedented detail the environment around black holes, and a team of GRAPPA researchers has recently shown that these observations can set extraordinarily stringent constraints on the mysterious dark matter that appears to permeate the universe at all scales. In this project we will explore the interplay between gravitational waves, black holes and dark matter. We will focus in particular on the possibility to probe the fundamental nature of dark matter by looking at how it clusters around black holes, and on its subtle impact on the gravitational waveform produced in the merger of black hole binaries. The project will involve both analytical and numerical work, and will be conducted under supervision of G. Bertone, and in collaboration with other GRAPPA staff and postdocs.
A realistic assessment of CTA sensitivities to dark matter and millisecond pulsars in the Andromeda Galaxy
Future gamma-ray telescopes such as CTA will allow comparative studies of cosmic rays (CRs) and high-energy objects in the Milky Way (MW) and in other, external galaxies such as Andromeda. Measurements with the Fermi-LAT telescope revealed that the flux from Andromeda is confined to the inner regions of the galaxy and does not fill its galactic disk or extend far from it. The gamma-ray signal is not correlated with regions rich in gas or star-formation activity suggesting that the emission is not interstellar in origin. Alternative and nonexclusive interpretations are that the emission results from a population of millisecond pulsars dispersed in the bulge and disk of Andromeda by disrupted globular clusters or from the decay or annihilation of dark matter particles. This project will estimate the sensitivity of the upcoming CTA gamma-ray telescope to DM annihilation and MSPs at the Andromeda Galaxy. We will introduce a statistical framework for including systematic errors and estimate the consequent degradation in sensitivity. The morphology of the signal at very high energies might allow to distinguish the DM from MSPs hypothesis in the Andromeda galaxy.
XENON1T Data Analysis
The XENON collaboration has used the XENON1T detector to achieve the world’s most sensitive direct detection dark matter results and is currently building the XENONnT successor experiment. The detectors operate at the Gran Sasso underground laboratory and consist of so-called dual-phase xenon time-projection chambers filled with ultra-pure xenon. Our group has an opening for a motivated MSc student to do analysis with the data from the XENON1T detector.
The work will consist of understanding the detector signals and applying machine learning tools such as deep neutral networks to improve the reconstruction performance in our Python-based analysis tool, following the approach described in arXiv:1804.09641. The final goal is to improve the energy and position reconstruction uncertainties for the dark matter search. There will also be opportunity to do data-taking shifts at the Gran Sasso underground laboratory in Italy.