29 citations · 41 across the 9 of their papers we have counts for
3 papers · 1 filter
Synthetic Dataset Generation, Physical Consistency and Active Learning for Shape-Informed Surrogate Modeling of Hemodynamics
Francesco Romor, Richard Schussnig, Charles A. Taylor +2
Model order reduction has the potential to enable real-time patient-specific assessment of cardiovascular flows. However, it still faces significant challenges stemming from the ge…
First-Principles Nuclear Modeling for Light Dark Matter Experiments at the Intensity Frontier
Taylor R. Gray, Alberto Scalesi
Accelerator-based experiments at the intensity frontier, in which a high-energy beam impinges on a nuclear target, serve as powerful probes of the light dark matter paradigm. Such…
Light Dark Matter Discovery Potential and Model Selection at LDMX
Adam Berger, Riccardo Catena, Jan Conrad +1
Light dark matter (DM) is a compelling scenario for the observed relic abundance, with accelerator-based searches as a powerful discovery strategy. The upcoming Light Dark Matter e…