VHE Gamma-ray astronomy with the Cherenkov Telescope Array

Lead Research Organisation: University of Oxford
Department Name: Oxford Physics


The student will contribute to three aspects of CTA design, construction and early science. The aims and objectives of the project are two-fold, having both a technical and an astronomical component. On the technical side student will investigate novel methods for the classification of air showers in Cherenkov telescope images (i.e., whether they are leptonic or hadronic in origin) using machine learning techniques. The scientific side of the project is aimed at investigating the populations of relativistic particles in the so-called "Fermi bubbles" in the Milky Way using a broad-band multi-frequency approach from radio to gamma-rays.

This project lies in the STFC science areas:

D:1. How do the laws of physics work when driven to the extremes?
D:2. How can high energy particles and gravitational waves tell us about the extreme universe?
D:3. How do ultra-compact objects form, what is their nature and how does extreme gravity impact on their surroundings?

Collaborators include the Universities of Liverpool, Leicester and Durham and MPIK Heidelberg. It is envisaged that the student will have a long-term attachment at MPIK.
The machine learning aspects of the project may have impact in application to very-high-speed image classification in areas such as e.g. flame chemistry.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
ST/R505006/1 01/10/2017 30/09/2021
1947714 Studentship ST/R505006/1 01/10/2017 31/03/2021 Samuel Timothy Spencer
Description CTA 
Organisation Cherenkov Telescope Array Consortium
Country Germany 
Sector Academic/University 
PI Contribution Working on new analysis methods for CTA
Collaborator Contribution Pre-construction phase
Impact See website
Description Talk on new machine learning methods at university of Namibia 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Undergraduate students
Results and Impact Gave a talk on 'new machine learning methods in astronomy' at university of Namibia.
Year(s) Of Engagement Activity 2020