HGCalVis: Web-Based Importance-Ordered Visualization of CERN’s HGCal Particle Showers

Abstract

The next major upgrade of the Compact Muon Solenoid (CMS) experiment at CERN’s Large Hadron Collider will introduce the High Granularity Calorimeter (HGCal), a new endcap sub-detector designed to cope with the order-of-magnitude increase in collision rates expected from the High-Luminosity LHC. Validating its design relies on Monte Carlo simulations that produce highly cluttered particle shower events: cascades of thousands of trajectories confined within a small detector volume, where physically significant tracks are easily occluded by lower-energy ones. We present a web-based, interactive 3D visualization system for exploring these simulated showers. The system combines a linked 2D hierarchical schematic view, cylinder-shaded lines with screen-space ambient occlusion, multi-attribute filtering, two complementary animation modes and, as our main rendering contribution, an Importance-Ordered Rendering (IOR) algorithm. IOR partitions trajectories into energy-based clusters, renders each into its own G-buffer in a separate pass, and composites them using Gaussian-filtered importance masks so that high-energy tracks remain visible without losing the spatial context provided by low-energy tracks. The system targets restricted graphics environments such as WebGL, where most existing dense-line techniques cannot be used directly. We report a performance evaluation on four production HGCal datasets (1.9k to 22.6k tracks) on both workstation and laptop hardware, a preliminary within-subjects user study (N = 19) that isolates the contribution of each main visual feature, and qualitative feedback from CERN collaborators. In the study, importance-ordered rendering increased the accuracy of identifying the highest-energy trajectory relative to unordered rendering, while energy color-coding alone did not, and the linked schematic view increased recovery of a track’s daughter set.