10 citations · 10 across the 2 of their papers we have counts for
3 papers
Building an AI-native Research Ecosystem for Experimental Particle Physics: A Community Vision
Thea Klaeboe Aarrestad, Alaa Abdelhamid, Haider Abidi +457
Experimental particle physics seeks to understand the universe by probing its fundamental particles and forces and exploring how they govern the large-scale processes that shape co…
Equivariant Graph Neural Networks for Charged Particle Tracking
Daniel Murnane, Savannah Thais, Ameya Thete
Graph neural networks (GNNs) have gained traction in high-energy physics (HEP) for their potential to improve accuracy and scalability. However, their resource-intensive nature and…
Realizing the potential of deep neural network for analyzing neutron star observables and dense matter equation of state
Ameya Thete, Kinjal Banerjee, Tuhin Malik
The difficulty in describing the equation of state (EoS) for nuclear matter at densities above the saturation density () has led to the emergence of a multitude of models base…