There is a large and convincing body of astrophysical evidence indicating that most of the matter in the universe is dark. Understanding the nature of dark matter is one of the most important problems in modern physics.
The search for dark matter has driven fantastic improvements to particle detector technology over the past 20 years, generating improvements to detector sensitivity to dark matter at a rate faster than Moore's law. However, this progress cannot continue forever, as the sensitivity of future dark matter detectors will be stymied by a background of neutrinos, which cannot be shielded; this limit is known as the 'neutrino fog'.
The CYGNUS collaboration is an international group of scientists who are developing a detector technology that is able to infer the direction of dark matter particle interactions. The directional information allows CYGNUS to search for dark matter in the neutrino fog, since the most abundant source of low energy neutrinos is the sun, while the incident dark matter flux comes from the direction of the constellation Cygnus. Even if dark matter is discovered above the neutrino floor, directional detection is a vital tool for confirming a putative signal as dark matter, and to perform dark matter astronomy to discover the properties of the Milky Way's dark matter halo.
Presently CYGNUS is conducting pilot studies into directional detector technology, with the aim to build a large modular detector, with one module to be eventually located in Australia's new underground physics laboratory at Stawell, Victoria.
Our group at the ANU hosts Australia's CYGNUS prototype detector, CYGNUS-1. A number of projects are available for students with an interest in this area:
- Hardware and software development for the CYGNUS-1 prototype
- Directional measurements in the CYGNUS-1 prototype
- Trace element analysis and background assessment
- Analysis and event reconstruction of rich and complex data
- Exploration of sensitivity to the Migdal effect
- Simulation of particle events and electric field modeling
Experience with other experimental projects is useful.
Engineering students with experience in electronics, signal processing, or coding are encouraged to become involved.