Machine Learning Enables Real-Time Waveform Decomposition for Dual-Readout Calorimetry
ML-based waveform decomposition enables real-time Cherenkov/scintillation separation in dual-readout crystal calorimeters with reduced sampling requirements and FPGA-compatible latency.
Apr 28, 2026
Phenomenological Detector Design and Optimization in Vertically-Integrated Differentiable Full Simulations with Agentic-AI
First demonstration of agentic-AI driven detector optimization using vertically-integrated bilevel framework for dual-readout calorimeters.
Apr 23, 2026
Edge Machine Learning for Cluster Counting in Next-Generation Drift Chambers
A demonstration of ML-based cluster counting for drift chambers is presented.
Nov 13, 2025
eFPGA Technology
Machine Learning At-source
Oct 10, 2025
Developing Digital Silicon Photomultiplier (dSiPM) Specifications for a High-Granularity Calorimeter with Simulations
dSiPM R&D
Oct 8, 2025
Embedded ML Solutions for Real-time Processing in Future Drift Chambers
Online Data Compression
Oct 6, 2025
5D Calorimetry
5D Calorimetry R&D
Mar 28, 2025
On the resolution of dual readout calorimeters
In this paper, we present a simple formula for the resolution of a dual readout calorimeter, which we verify with a toy simulation and with full simulation results. This formula can help those new to dual readout calorimetry understand its strengths and limitations.
Jan 29, 2025
Geant4 simulations of sampling and homogeneous hadronic calorimeters with dual readout for future colliders
Our simulations demonstrates the effect of inclusion of Cherenkov light in the reconstruction of energies for sampling and homogeneous calorimeters.
Jan 6, 2025
Design and experimental application of a radon diffusion chamber for determining diffusion coefficients in membrane materials
We designed a detector for the quantitative assessment of membrane materials’ radon blocking capabilities.
Oct 8, 2024