Dr Grace Lawrence’s PhD thesis focused on dark matter, which comprises 26% of our universe, and is studied through a wide range of observed, simulated and theoretical approaches. An abundance of indirect evidence for dark matter pervades our observations; however, the true nature of dark matter maintains one of astrophysics great mysteries.
An important key to advancing our understanding of dark matter, is through direct detection experiments, searching for a sinusoidally modulating flux of dark matter through the Earth. Detectors search for this energetic signature left when a dark matter particle scatters off of a target detector.
The design, optimisation and predictions for direct detection experiments are based on the Standard Halo Model (SHM), a simplified way to understand galactic halos. Grace and her colleagues study how direct detection predictions change when the SHM is replaced with realistic simulated halos whose complex dark matter structure complicates direct detection predictions. The research was facilitated by a new, innovative count rate approach which re-derived differential rate equations, core to dark matter prediction work, to exclude intrinsic dependencies on the Standard Halo Model. These innovative calculations were developed into an open-source python3 package available on Github, Dark-MaRK.
In recognition of the quality and significance of her research, Dr Grace Lawrence is the First Prize Winner in the Physical Sciences category for the Royal Society of Victoria's Young Scientist Research Prizes in 2023. Grace's presentation has been filmed and published with the support of the Inspiring Victoria program.
