2 citations · 3 across the 9 of their papers we have counts for
4 papers · 1 filter
Reusable theory representations for colliders: a demonstrator SMEFT foundation model
Supratim Das Bakshi, T. J. Hobbs, Brandon Kriesten
We develop a demonstrator foundation model for collider-scale explorations of the Standard Model Effective Field Theory (SMEFT), constructed from contrastive representations of the…
ArgoLOOM: agentic AI for fundamental physics from quarks to cosmos
S. D. Bakshi, P. Barry, C. Bissolotti +12
Progress in modern physics has been supported by a steadily expanding corpus of numerical analyses and computational frameworks, which in turn form the basis for precision calculat…
Decoding the proton's gluonic density with lattice QCD-informed machine learning
Brandon Kriesten, Alex NieMiera, William Good +2
We present a first machine learning-based decoding of the gluonic structure of the proton from lattice QCD using a variational autoencoder inverse mapper (VAIM). Harnessing the pow…
Quantum entropy as a harbinger of factorizability
Henry Bloss, Brandon Kriesten, T. J. Hobbs
Deeply inelastic scattering (DIS) is a powerful probe for investigating the QCD structure of hadronic matter and testing the standard model (SM). DIS can be described through QCD f…