From the 1 of 4 linked papers with an AI index.
4 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
The paper introduces ScatterPrism, a generative surrogate that exposes shortcomings of the standard Conditional Flow Matching loss in particle‑physics simulations and proposes mult…
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…
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…