Speaker
Description
Sub-GeV, or light, dark matter (DM) remains a compelling candidate for the observed DM in the universe. Its suppressed momentum transfer relative to traditional weakly interacting massive particles motivates accelerator-based missing-momentum searches as a powerful and complementary discovery strategy. Light Dark Matter eXperiment (LDMX) is designed to probe this regime by measuring the energy and transverse momentum spectra of recoil electrons in high-intensity electron–nucleus collisions.
In this talk, I will focus on the discovery potential of LDMX through a detailed statistical analysis of the recoil electron transverse momentum and energy distributions. Using both Bayesian and frequentist likelihood frameworks, we construct multivariate analyses that quantify discovery reach across representative light DM scenarios. We assess the projected sensitivity while consistently including systematic uncertainties, background modelling, and detector resolution effects.
The reliability of these projections and the robustness of any future discovery claim depends not only on the statistical framework, but also on the accuracy of the signal modelling. In fixed-target light DM searches, conventional treatments rely on simple analytic nuclear form factors. I discuss how many-body ab initio methods based on chiral EFT provide a more realistic description of nuclear correlations for DM signal predictions.
Together, likelihood-based statistical methods and state-of-the-art nuclear theory provide a robust and realistic assessment of LDMX’s capability to discover light DM.
| Main Contribution topic | Light Dark Matter |
|---|---|
| Secondary contribution topic | Theory / Phenomenology |