Doctor of Philosophy

dissertationOne of the greatest mysteries in modern-day astrophysics is that of the nature and composition of dark matter. Numerous lines of research have sought to detect and characterize this unknown material. Cosmological simulations in particular have proven very successful at re-creating observed large scale structure given a few simple assumptions about dark matter. These simulations, however, become discrepant with observations on smaller scales. Tension between simulations and observations still exists in the predicted abundance of dark matter subhalos: small, gravitationally-bound dark matter halos. These subhalos are believed to host dwarf galaxies in the Milky Way. The observed abundance of dwarf galaxies, however, is too low by an order of magnitude. This thesis describes an observational program to address this tension. Strong gravitational lensing has been demonstrated to have the ability to detect dark matter substructure and empirically test cosmological simulations across large regions of the universe. We propose an extension of current results using a particular class of lensed galaxies known as Lyman-a Emitters (LAEs) to achieve lower mass detection thresholds. Our sample of high-resolution HST images holds the greatest substructure detection power of any to date. We develop the statistical framework to measure the mass fraction and slope of the subhalo mass function (SHMF). Our preliminary results suggest a substructure mass fraction f = 0.0020+0.0027 0.0013 which is lower than previous studies, but consistent with both observational results and theoretical predictions. For the slope we find a = 0.968+0.485 0.524 which is significantly lower than cosmological predictions. Given this tension, we suspect that we are less sensitive to low-mass substructure than high-mass substructure. We propose an alternative analysis that may definitively determine whether this apparent difference is real or an artifact introduced in data reduction. We also discuss the implications for warm dark matter (WDM) if our results hold