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Abstract Identifying the nature of dark matter (DM) has long been a pressing question for particle physics. In the face of ever-more-powerful exclusions and null results from large-exposure searches for TeV-scale DM interacting with nuclei, a significant amount of attention has shifted to lighter (sub-GeV) DM candidates. Direct detection of the light DM in our galaxy by observing DM scattering off a target system requires new approaches compared to prior searches. Lighter DM particles have less available kinetic energy, and achieving a kinematic match between DM and the target mandates the proper treatment of collective excitations in condensed matter systems, such as charged quasiparticles or phonons. In this context, the condensed matter physics of the target material is crucial, necessitating an interdisciplinary approach. In this review, we provide a self-contained introduction to direct detection of keV–GeV DM with condensed matter systems. We give a brief survey of DM models and basics of condensed matter, while the bulk of the review deals with the theoretical treatment of DM-nucleon and DM-electron interactions. We also review recent experimental developments in detector technology, and conclude with an outlook for the field of sub-GeV DM detection over the next decade. 

The local escape velocity provides valuable inputs to the mass profile of the galaxy, and requires understanding the tail of the stellar speed distribution. Following Leonard & Tremaine, various works have since modeled the tail of the stellar speed distribution as$\propto {(v_{\mathrm{esc}}-v)}^k$, wherev_escis the escape velocity, andkis the slope of the distribution. In such studies, however, these two parameters were found to be largely degenerate and often a narrow prior is imposed onkin order to constrainv_esc. Furthermore, the validity of the power-law form can breakdown in the presence of multiple kinematic substructures or other mis-modeled features in the data. In this paper, we introduce a strategy that for the first time takes into account the presence of kinematic substructure. We model the tail of the velocity distribution as a sum of multiple power laws as a way of introducing a more flexible fitting framework. Using mock data and data from FIRE simulations of Milky Way-like galaxies, we show the robustness of this method in the presence of kinematic structure that is similar to the recently discovered Gaia Sausage. In a companion paper, we present the new measurement of the escape velocity and subsequently the mass of the Milky Way using Gaia eDR3 data.

 

Measuring the escape velocity of the Milky Way is critical in obtaining the mass of the Milky Way, understanding the dark matter velocity distribution, and building the dark matter density profile. In Necib & Lin, we introduced a strategy to robustly measure the escape velocity. Our approach takes into account the presence of kinematic substructures by modeling the tail of the stellar distribution with multiple components, including the stellar halo and the debris flow called the Gaia Sausage (Enceladus). In doing so, we can test the robustness of the escape velocity measurement for different definitions of the “tail” of the velocity distribution and the consistency of the data with different underlying models. In this paper, we apply this method to the Gaia eDR3 data release and find that a model with two components is preferred, although results from a single-component fit are also consistent. Based on a fit to retrograde data with two bound components to account for the relaxed halo and the Gaia Sausage, we find the escape velocity of the Milky Way at the solar position to be$v_{\mathrm{esc}}={445}_{-8}^{+25}$km s⁻¹. A fit with a single component to the same data gives$v_{\mathrm{esc}}={472}_{-12}^{+17}$km s⁻¹. Assuming a Navarro−Frenck−White dark matter profile, we find a Milky Way concentration of$c_{200}={19}_{-7}^{+11}$and a mass of$M_{200}={4.6}_{-0.8}^{+1.5}\times {10}^{11}{M}_{\odot }$, which is considerably lighter than previous measurements.