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 limited by a background of neutrinos, which cannot be shielded; this limit is known as 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, a detector capable of inferring directional particle information can search for dark matter against a background of the neutrino fog. Furthermore, even if dark matter is discovered above the neutrino fog, 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.

The ANU plays a leading role in the CYGNUS-Oz collaboration, and we are conducting pilot studies into directional detector technology, with the aim to build a large detector. Eventually such a detector could be located in Australia's new underground physics laboratory at Stawell, Victoria. We are also have an interest in neutron detection for defence and other applications.

Our group hosts Australia's CYGNUS-Oz 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.