489 citations · 949 across the 29 of their papers we have counts for
33 papers
Searching for BSM Experimental Signatures with Large Lagrangian Models
Ibrahim Elsharkawy, Victoria Knapp-Perez, Wahid Bhimji +1
The search for physics Beyond the Standard Model (BSM) is generally limited not by the supply of theory descriptions but by the lack of discriminating experimental observations. A…
Hybrid Neural Simulation-Based Inference for Robust Applications and Limited-Budget Scenarios
Sean Benevedes, Mani Dehghan, Aishik Ghosh +1
We develop two hybrid techniques that approach the performance of neural simulation-based inference (NSBI) analyses while substantially reducing the computational cost of inference…
Towards Certificate-Driven Software Porting: A Self-Improving Agentic Harness for Scientific Program Optimization
Piyush Jha, Aishik Ghosh, Vijay Ganesh
The upgrade and rewriting of large scientific codebases has traditionally been a major challenge. While evolutionary search with large language models (LLMs) can port and accelerat…
Learning Scattering Amplitudes with Transformer Reinforcement Learning
Philip Velie, Tianji Cai, Piyush Jha +2
We introduce a transformer reinforcement learning algorithm that learns to solve high loop-level scattering amplitudes in planar N = 4 Super Yang-Mills theory. Our algorithm improv…
CDRL: Certification-Driven Reinforcement Learning for Neutrino Flavor Model Discovery
Piyush Jha, Jake Rudolph, Victoria Knapp-Pérez +3
Many scientific discovery problems require searching combinatorial hypothesis spaces under complex domain constraints. Reinforcement learning (RL) offers a promising approach, but…
Time-dependent signals of new physics at the LHC
Max H. Fieg, Patrick J. Fox, Jinbo Zhang +3
The Large Hadron Collider (LHC) is sensitive to signals of beyond the Standard Model physics through a variety of channels including missing energy and resonance searches. In most…