Dr Shahinur Rahman is a past member of RSPE. Contact details and information may no longer be correct.

Dr Shahinur Rahman

Rahman, Shahinur profile
Position Postdoctoral Fellow
Department Materials Physics
Nuclear Physics & Accelerator Applications
Research group
Office phone (02) 612 52083
Skype shahinur.rahman10
Office Cockcroft 3 27
Webpage https://physics.anu.edu.au/people/p...
Curriculum vitae Rahman CV (193KB PDF)
Publication list Rahman publication list (147KB PDF)

Development of a SABRE (Sodium-iodide with Active Background REjection) detector with optimum sensitivity to directly detect dark matter

There is a large and convincing body of astrophysical evidence that most of the matter in the universe is dark (https://arxiv.org/pdf/1006.2483.pdf). Understanding the nature of dark matter is one of the most important problems in modern physics.

The SABRE experiment is a dark matter particle detector that is being constructed in collaboration with researchers in Australia, Europe, and the United States. To reduce the external backgrounds associated with cosmic rays, it will be housed ~1 km underground in a gold mine near Stawell in Victoria, Australia. To reduce the internal backgrounds from naturally occurring radioactive material, the detector will be fabricated from the purest NaI(Tl) scintillator material ever made. The experiment will search for an annually modulating signal due to the Earth's motion around the sun. To avoid confusion between seasonal background effects and a true dark matter signal, SABRE will operate twin detectors in the northern and southern hemisphere. A positive detection from SABRE would be an extremely important physics discovery, on par with the detection of the Higgs boson, gravitational waves, or neutrino oscillations.

A number of experimental measurements are needed to support the SABRE physics program. Measurements at the ANU are focussed on detailed characterisation of the detector components to dark matter-like interactions. This will involve bench measurements and measurements with the ANU 15 MV electrostatic tandem particle accelerator, and compreshensive data analysis.