Dissertations
Dissertation

Public defence in Physics: Tomas Bylund

Thesis title:

Seeking the faint extremes - Detection and characterisation of extragalactic soft-spectrum gamma-ray sources and exploring methods to enhance their detection with machine learning in the 50 GeV-50 TeV energy range

Third-cycle subject area:

Physics

Faculty:

Faculty of Technology

Date:

Friday 14 October 2022 at 13:00

Place for thesis:

Weber, House K, Växjö

External reviewer:

Professor Gilles Henri, Université de Grenoble-Alpes, Frankrike

Examining committee:

Dr. Erin O´Sullivan, Uppsala universitet
Docent Roman Pasechnik, Lunds universitet
Professor Marc Pearce, Kungliga tekniska högskolan

Chairperson:

Professor Welf Löwe, Linnéuniversitetet

Supervisor:

Professor Yvonne Becherini, Université Paris Cité, Frankrike

Examiner:

Professor Staffan Carius, Linnéuniversitetet

Spikning:

Friday 23 September 2022 at 13:00 at University Library, Växjö

Abstract

This thesis deals with an observational study of blazars, strong gamma-ray
sources with Very High Energies (VHE) located far outside our Galaxy. Blazars
are a class of galaxies that contain a supermassive black hole that is actively
consuming large quantities of matter, a process that results in the liberation of
tremendous amounts of energy that then powers the emission of huge bulks of charged particles that get accelerated almost to the speed of light.

The details of the extreme processes involved are still very uncertain, and more observational studies are still required to discriminate between the various theories. Because it takes a lot of energy to create VHE gamma-rays, they are tightly coupled to the most energy-rich places in blazars. This means that observations of gamma rays directly probe the central engine responsible for the enormous amounts of radiation we detect.

Direct studies have been carried out with the H.E.S.S. observatory, an Imaging Atmospheric Cherenkov Telescope array which uses our atmosphere as an integral part of its detector and is able to detect gamma-ray photons with energies from over 50 GeV up to tens of TeV . Using H.E.S.S., seven new sources of gamma-rays in the VHE regime were carefully studied in this thesis, significantly expanding the collection of known sources of TeV photons.

Computer studies were also performed exploring the possibility of using deep learning to improve the sensitivity of ALTO, a newly-proposed observatory belonging to an emerging class of gamma-ray instruments, the particle detector arrays.