Related papers: Shower Separation in Five Dimensions for Highly Gr…
The hadron energy resolution of a highly granular CALICE analogue scintillator-steel hadronic calorimeter was studied using pion test beam data. The stochastic term contribution to the energy resolution was estimated to be 58%/sqrt(E/GeV).…
For calorimeter applications requiring precise time stamping, the time structure of hadronic showers in the detector is a crucial issue. This applies in particular to detector concepts for CLIC, where a hadronic calorimeter with tungsten…
Recent studies have shown that the electromagnetic shower induced by a high-energy electron, positron or photon incident along the axis of an oriented crystal develops in a space more compact than the ordinary. On the other hand, the…
Calorimeters are a crucial component in modern particle detectors. They are responsible for providing accurate energy measurements of particles produced in high-energy collisions. The demanding requirements set for next-generation collider…
Detector simulations are an exciting application of modern generative networks. Their sparse high-dimensional data combined with the required precision poses a serious challenge. We show how combining Conditional Flow Matching with…
Knowledge of the mass composition of ultra-high-energy cosmic rays is crucial to understanding their origins; however, current approaches have limited event-by-event resolution. With fluorescence telescope measurements of the longitudinal…
We report on the design and the expected performance of a low cost hybrid detection system suitable for operation as an autonomous unit in strong electromagnetic noise environments. The system consists of three particle detectors…
Air shower simulation programs are essential tools for the analysis of data from cosmic ray experiments and for planning the layout of new detectors. They are used to estimate the energy and mass of the primary particle. Unfortunately the…
Efficient and accurate algorithms are necessary to reconstruct particles in the highly granular detectors anticipated at the High-Luminosity Large Hadron Collider and the Future Circular Collider. We study scalable machine learning models…
The High Luminosity LHC (HL-LHC) will integrate 10 times more luminosity than the LHC, posing significant challenges for radiation tolerance and event pileup on detectors, especially for forward calorimetry, and hallmarks the issue for…
The simulation of calorimeter showers presents a significant computational challenge, impacting the efficiency and accuracy of particle physics experiments. While generative ML models have been effective in enhancing and accelerating the…
Intrinsic differences in the processes involved in the development of electromagnetic and hadronic showers in the atmosphere have been evidenced by means of a careful analysis of the event image given by the ARGO-YBJ detector. The images…
Digital Hadronic Calorimeters (DHCAL) were suggested for future Colliders as part of the particle-flow concept. Though studied mainly with Resistive Plate Chambers (RPC), studies focusing on Micro-Pattern Gaseous Detector (MPGD)-based…
Physics-based machine learning blends traditional science with modern data-driven techniques. Rather than relying exclusively on empirical data or predefined equations, this methodology embeds domain knowledge directly into the learning…
In the context of a gas-sampling Digital Hadronic Calorimeter (DHCAL), we explore the potential of using Graph Neural Networks (GNN) for hadron energy reconstruction and Particle Identification (PID) in future collider experiments. For PID,…
In high energy physics experiments, calorimetric data reconstruction requires a suitable clustering technique in order to obtain accurate information about the shower characteristics such as position of the shower and energy deposition.…
Particle filters are a group of algorithms to solve inverse problems through statistical Bayesian methods when the model does not comply with the linear and Gaussian hypothesis. Particle filters are used in domains like data assimilation,…
To search for ultra-high-energy photons in primary cosmic rays, air shower observables are needed that allow a good separation between primary photons and primary hadrons. We present a new observable, $F_\gamma$, which can be extracted from…
The DHCAL collaboration is assembling a large scale prototype Digital Hadron Calorimeter (DHCAL). The calorimeter utilizes Resistive Plate Chambers (RPCs) as active medium and features of the order of 400,000 1 \times 1 cm2 pads with binary…
In particle physics, the demand for rapid and precise simulations is rising. The shift from traditional methods to machine learning-based approaches has led to significant advancements in simulating complex detector responses. CaloShowerGAN…