arXiv subjects

Lorenzo Pezzotti

Publications and source records attributed to Lorenzo Pezzotti.

3 recordsLinked to original sources

arXiv2025

A new method for structural diagnostics with muon tomography and deep learning

This work investigates the production of high-resolution images of typical support elements in concrete structures by means of muon tomography (muography). By exploiting detailed Monte Carlo radiation-matter simulations, we demonstrate the feasibility of reconstructing 1 cm-thick iron bars inside 30 cm-deep concrete blocks, regarded as an important testbed within the structural diagnostics community. In addition, we present a new method for integrating simulated data with advanced deep learning techniques in order to improve the muon imaging of concrete structures. Through deep learning enhancement techniques, this results in a dramatic improvement in image quality and a significant reduction in data acquisition time, which are two critical limitations within the usual practice of muography for civil engineering diagnostics.

hep-ex↗

arXiv2025

Energy Response and Resolution to Positrons in a Capillary-Tube Dual-Readout Calorimeter

We present the results of a test beam campaign on a capillary-tube fibre-based dual-readout calorimeter, designed for precise hadronic and electromagnetic energy measurements in future collider experiments. The calorimeter prototype consists of nine modules, each composed of brass capillary tubes housing scintillating and Cherenkov optical fibres, read out using silicon photomultipliers for the central module and photomultiplier tubes for the outer modules. The performance of the detector was assessed using a positron beam with energies ranging from 10 to 120 GeV at the CERN SPS H8 beamline. The prototype is characterised in terms of the linearity and resolution of its energy response to positrons. The results confirm the feasibility of the capillary-tube mechanical design for large-scale dual-readout calorimetry and provide a benchmark for future detector development within the HiDRa project.

physics.ins-det↗

arXiv2022

Particle Flow with a Hybrid Segmented Crystal and Fiber Dual-Readout Calorimeter

In the reconstruction of physics events at future e$^+$e$^-$ colliders the calorimeter design has a crucial role in the overall detector performance. The reconstruction of events with many jets in their final state sets stringent requirements on the jet energy and angular resolutions. The energy resolution for jets with energy of about 45 GeV is required to be at the 4-5\% level to enable an efficient separation of the W and Z boson invariant masses. We demonstrate in this paper how such a performance can be achieved by exploiting a particle flow algorithm tailored for a hybrid dual-readout calorimeter made of segmented crystals and fibers. The excellent energy resolution and linearity of such calorimeter for both photons and neutral hadrons ($3\%/\sqrt{E}$ and $26\%/\sqrt{E}$, respectively), inherent to the homogeneous crystals and dual-readout technological choices, provides a powerful handle for the development of a new approach for particle identification and jet reconstruction. While the dual-readout particle flow algorithm (DR-PFA) presented in this paper is at its early stage of development, it already demonstrates the potential of a hybrid dual-readout calorimeter for jet reconstruction by improving the jet energy resolution with respect to a calorimeter-only reconstruction from 6.0\% to about 4.5\% for 45 GeV jets.

hep-ex↗