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.