Cosmic dust as a dark matter discriminator

Zoom Recording Passcode: Fjd0AS=$

I will explore dust as a novel discriminator between cold and warm dark matter, using hydro zoom-in simulations of Milky Way-mass haloes. I'll motivate the CDM/WDM problem through current observational tensions, highlighting the need for new galaxy-scale tests beyond traditional substructure studies. Using our simulations, I'll demonstrate that CDM and WDM produce observably different dust populations. CDM, having more substructure, requires higher supernova efficiency to match observed satellite numbers; this creates distinct dust masses and spatial distributions that I'll quantify with maps and profiles. I'll discuss whether observatories like JWST and ALMA could detect these differences, outlining the signatures we would predict. Finally, I'll show how AI techniques enable systematic exploration of the feedback parameter space, extending this dust discriminator approach to test additional dark matter scenarios and galactic physics.