1 citations · 1 across the 5 of their papers we have counts for
5 papers
Lantern: Conflict-Aware Gradient Blending for Physics-Guided Diffusion Models in Calorimeter Simulation
Farzana Yasmin Ahmad, Vanamala Venkataswamy, Geoffrey Fox
Monte Carlo simulation of calorimeter showers is a principal bottleneck for the High-Luminosity LHC, and diffusion models have emerged as fast, high-fidelity surrogates. Their deno…
ScatterPrism: convergence for generative simulation and inverse problems in particle and nuclear physics
Zeyu Xia, Tyler Kim, Trevor Reed +3
High-fidelity simulations and complex inverse problems, such as detector modeling and unfolding, are computationally intensive bottlenecks across subatomic physics, yet essential f…
Zephyr quantum-assisted hierarchical Calo4pQVAE for particle-calorimeter interactions
Ian Lu, Hao Jia, Sebastian Gonzalez +10
With the approach of the High Luminosity Large Hadron Collider (HL-LHC) era set to begin particle collisions by the end of this decade, it is evident that the computational demands…
Conditioned quantum-assisted deep generative surrogate for particle-calorimeter interactions
J. Quetzalcoatl Toledo-Marin, Sebastian Gonzalez, Hao Jia +9
Particle collisions at accelerators such as the Large Hadron Collider, recorded and analyzed by experiments such as ATLAS and CMS, enable exquisite measurements of the Standard Mod…
A Comprehensive Evaluation of Generative Models in Calorimeter Shower Simulation
Farzana Yasmin Ahmad, Vanamala Venkataswamy, Geoffrey Fox
The pursuit of understanding fundamental particle interactions has reached unparalleled precision levels. Particle physics detectors play a crucial role in generating low-level obj…