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New Lantern model blends physics with diffusion for LHC calorimeter simulation

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Lantern, a novel physics-guided diffusion model designed to improve the simulation of calorimeter showers for the High-Luminosity LHC. Unlike previous methods, Lantern addresses the statistical nature of diffusion models by incorporating physics-aware auxiliary losses, including a voxel residual loss and a graph Laplacian loss, to ensure physical accuracy. The model utilizes a technique called GradBlend to effectively combine these physics-based objectives with the standard denoising objective, leading to improved performance on the CaloChallenge Dataset 2. AI

IMPACT This research could accelerate high-energy physics simulations, potentially leading to faster and more accurate analysis of experimental data.

RANK_REASON The cluster contains a research paper detailing a new method for physics-guided diffusion models. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Lantern model blends physics with diffusion for LHC calorimeter simulation

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The cluster contains a research paper detailing a new method for physics-guided diffusion models. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Farzana Yasmin Ahmad, Vanamala Venkataswamy, Geoffrey Fox ·

    Lantern: Conflict-Aware Gradient Blending for Physics-Guided Diffusion Models in Calorimeter Simulation

    arXiv:2607.25060v1 Announce Type: cross Abstract: 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 denoising objective is purely statistical, however: a …

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