A5075129347- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Particle Detector Development and Performance
- Computational Physics and Python Applications
- Dark Matter and Cosmic Phenomena
- Neutrino Physics Research
- Cosmology and Gravitation Theories
- Distributed and Parallel Computing Systems
- Astrophysics and Cosmic Phenomena
- Black Holes and Theoretical Physics
- Big Data Technologies and Applications
- Nuclear Physics and Applications
- Radiation Detection and Scintillator Technologies
- Noncommutative and Quantum Gravity Theories
- Atomic and Subatomic Physics Research
- Parallel Computing and Optimization Techniques
- Advanced Data Storage Technologies
- Optical properties and cooling technologies in crystalline materials
- Climate Change Communication and Perception
- Radiation Therapy and Dosimetry
- Sarcoidosis and Beryllium Toxicity Research
- Laser-Plasma Interactions and Diagnostics
- Quantum Mechanics and Applications
- Nuclear reactor physics and engineering
Istituto Nazionale di Fisica Nucleare, Sezione di Padova
2021-2025
University of Padua
2023-2025
University of Trento
2024-2025
University of Antwerp
2024
Institute of High Energy Physics
2023-2024
Istituto Nazionale di Fisica Nucleare
2021-2024
A. Alikhanyan National Laboratory
2024
Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas
2023
European Organization for Nuclear Research
2020
We investigate the psycho-linguistic features of online discourse over climate change, focusing on its modifications throughout years 2017–2019 as a result collective actions emerging and spreading worldwide. seek to understand connection between digital activism psychological processes related social drives. To this end, semantic network is derived from platform Twitter, evolution traced time, tracking textual proxies identity empowerment. Original proposals are made identify communities...
The Compact Muon Solenoid (CMS) experiment prepares its Phase-2 upgrade for the high-luminosity era of LHC operation (HL-LHC). Due to increase occupancy, trigger latency and rates, full electronics CMS Drift Tube (DT) chambers will need be replaced. In new design, time bin digitisation chamber signals around 1~ns, totality forwarded asynchronously service cavern at resolution. backend system in charge building primitives each chamber. These contain information level about muon candidates...
The online reconstruction of muon tracks in High Energy Physics experiments is a highly demanding task, typically performed with programmable logic boards, such as FPGAs. Complex analytical algorithms are executed quasi-real-time environment to identify, select and reconstruct local often noise-rich environments. A novel approach the generation triggers based on an hybrid combination Artificial Neural Networks methods proposed, targeting for drift tube detectors. proposed algorithm exploits...
Abstract The Level-1 trigger scouting system of the CMS experiment aims at intercepting intermediate data produced by L1 processors before final decision. This can be complemented adding raw stream collected from detector front-end, whenever throughput is manageable. In this work, triggerless readout Drift Tubes (DT) presented. realized reading a sector DT which has been equipped with preproduction Phase-2 upgrade front-end boards. A Xilinx VCU118 acts as concentrator demonstrator lpGBT...
Abstract A novel Data Acquisition (DAQ) system, known as Level-1 Scouting (L1DS), is being introduced part of the (L1) trigger CMS experiment. The L1DS system will receive L1 intermediate primitives from Phase-2 on DAQ-800 custom boards, designed for central DAQ. Firmware developed this purpose Xilinx VCU128 board, with features similar to one half DAQ-800, and validated in a demonstrator LHC Run-3. This contribution describes firmware development view target design DAQ-800.
Abstract The CMS experiment 40 MHz data scouting project is aimed at intercepting the produced level of detectors’ front-end without filters induced by hardware-based triggers. A first implementation realized trigger-less reading and processing a fraction Drift Tube (DT) muon detector, equipped with preliminary version so-called Phase-2 Upgrade on-detector electronics boards. are transferred via high-speed optical links to back-end boards independently from central acquisition (DAQ),...
Abstract Several physics experiments are moving towards new acquisition models. In this work some ideas to implement Remote Direct Memory Access (RDMA) directly on the front-end electronics have been explored, part of computing farm's CPU resources could be freed. New simulation techniques introduced understand RDMA over Converged Ethernet (RoCE) firmware block developed at ETH Zürich, including real-time leveraging SystemVerilog's useful features. The ability explore a wider and dynamic...
The CMS detector will undergo a significant upgrade to cope with the HL-LHC instantaneous luminosity and average number of proton–proton collisions per bunch crossing (BX). Phase-2 be equipped new Level-1 (L1) trigger system that have access an unprecedented level information. Advanced reconstruction algorithms deployed directly on L1 FPGA-based processors, producing reconstructed physics primitives quasi-offline quality. latter collected processed by Data Scouting (L1DS) at full rate....
The online reconstruction of muon tracks in High Energy Physics experiments is a highly demanding task, typically performed with programmable logic boards, such as FPGAs. Complex analytical algorithms are executed quasi-real-time environment to identify, select and reconstruct local often noise-rich environments. A novel approach the generation triggers based on an hybrid combination Artificial Neural Networks methods proposed, targeting for drift tube detectors. proposed algorithm exploits...
This work describes an online processing pipeline designed to identify anomalies in a continuous stream of data collected without external triggers from particle detector. The begins with local reconstruction algorithm, employing neural networks on FPGA as its first stage. Subsequent preparation and anomaly detection stages are accelerated using GPGPUs. As practical demonstration detection, we have developed quality monitoring application cosmic muon Its primary objective is detect...
The majority of high energy physics experiments rely on data acquisition and hardware-based trigger systems performing a number stringent selections before storing for offline analysis. online reconstruction selection performed at the level are bound to synchronous nature system, resulting in trade-off between amount collected complexity performed. Exotic processes, such as long-lived slow-moving particles, rarely targeted by triggers they require complex nonstandard reconstruction, usually...