Getting the most out of dark matter observations and experiments

by Dr Annika Peter (California Institute of Technology)

Tuesday 27 Apr 2010, 13:15 → 14:15 Europe/Stockholm

FA32

Dark matter, constituting a fifth of the mass-energy in the Universe today, is one of the major "known unknowns" in physics. There are currently four approaches to determining the nature of dark matter, assuming it is composed of at least one new species of particle: 1) creation in collider experiments; 2) indirect detection via its annihilation or decay products; 3) direct detection; and 4) observations sensitive to the gravity of dark matter. For the latter three approaches, event rates are not only sensitive to the "physics" of dark matter (mass, cross sections, and the theory in which the dark matter particles live) but to the "astrophysics" of dark matter as well, namely the phase-space density of dark matter throughout the Milky Way and other galaxies and its evolution through cosmic time. In this talk, I will demonstrate how to get robust constraints on the particle-physics properties of dark matter either by careful modeling the astrophysics properties of dark matter or by elevating the astrophysics properties of dark matter as something to be extracted from future data sets alongside particle-physics parameters, and which approach (modeling vs. empirical) is more useful for given problems. As an example, I will show which aspects of the local dark-matter phase-space density can be understood through modeling and which aspects may be possible to infer empirically, and what the implications are for determining the particle-physics of dark matter from direct and indirect detection. I will conclude with some comments on extensions of some of the techniques to other future dark-matter data sets, and indicate which astrophysical aspects of dark matter are likely to be better understood empirically rather than modeling.