CERN Accelerating science

CERN Document Server Pronađeno je 518,758 zapisa  početakprethodni621 - 630slijedećikraj  idi na zapis: Pretraživanje je potrajalo 0.98 sekundi 
621.
Beam-beam / Buffat, Xavier (CERN)
The interaction of the two beams in a collider leads to a variety of effects that may limit the performance of the machine. [...]
arXiv:2510.14056.
- 2025 - 15.
Fulltext
622.
Quantum computing for heavy-ion physics: near-term status and future prospects / Barata, João (CERN)
We discuss recent advances in applying Quantum Information Science to problems in high-energy nuclear physics. [...]
arXiv:2510.04207.
- 2025
Fulltext
623.
FPGA-RICH: A low-latency, high-throughput online partial particle identification system for the NA62 experiment / Perticaroli, Pierpaolo (INFN, Rome) ; Ammendola, Roberto (U. Rome 2, Tor Vergata (main)) ; Biagioni, Andrea (INFN, Rome) ; Chiarini, Carlotta (INFN, Rome) ; Ciardiello, Andrea (U. Rome La Sapienza (main) ; INFN, Rome) ; Cretaro, Paolo (INFN, Rome) ; Frezza, Ottorino (INFN, Rome) ; Lo Cicero, Francesca (INFN, Rome) ; Martinelli, Michele (INFN, Rome) ; Piandani, Roberto (San Luis Potosi U.) et al.
FPGA-RICH is an FPGA-based online partial particle identification system for the NA62 experiment utilizing Artificial Intelligence (AI) techniques. Integrated between the readout of the Ring Imaging Cherenkov detector (RICH) and the low-level trigger processor (L0TP+), FPGA-RICH implements a fast pipeline to process in real-time the RICH raw hit data stream, producing trigger-primitives containing elaborate physics information, such as the number of charged particles in a physics event, that L0TP+ can use to improve trigger decision selectivity. [...]
2025 - 7 p. - Published in : EPJ Web Conf. 337 (2025) 01280 Fulltext: PDF;
In : 27th International Conference on Computing in High Energy & Nuclear Physics (CHEP2024), Kraków, Poland, 19 - 25 Oct 2024, pp.01280
624.
Effects of Neutron Radiation on the Current Transfer Ratio of GaAsP and AlGaAs Optocouplers / Martín-Holgado, Pedro (Seville U.) ; Romero-Maestre, Amor (Seville U.) ; De-Martín-Hernández, José (Seville U.) ; González-Luján, José J (Seville U.) ; Jalón, María Ángeles (Seville U.) ; Ricca-Soaje, Álvaro (Seville U.) ; Domínguez, Manuel (Seville U.) ; Ferraro, Rudy (CERN) ; Alía, Rubén García (CERN) ; Morilla, Yolanda (Seville U.)
This work presents the degradation of the GaAsP and AlGaAs optocouplers as a result of the displacement damage produced by neutron radiation. [...]
2023
625.
H11(0) end cells for a 750 MHz IH structure / Moreno, Gabriela (Madrid, CIEMAT) ; Giner Navarro, Jorge (Madrid, CIEMAT) ; Gavela, Daniel (Madrid, CIEMAT) ; Calvo, Pedro (Madrid, CIEMAT) ; Leon Lopez, Miguel (Madrid, CIEMAT) ; Rodriguez Paramo, Angel (Madrid, CIEMAT) ; Oliver, Concepcion (Madrid, CIEMAT) ; Perez Morales, Jose (Madrid, CIEMAT) ; Carmona, José Miguel (Unlisted, ES) ; Alvarado Martin, Maria (Unlisted, ES) et al.
This article presents a study on the H11(0) end cell of an IH-DTL prototype for accelerating carbon ion beams from 5 to 5.5 MeV/u, which is designed for a hadron therapy linac injector. The voltage across the first and last gap in a drift tube linac tends to drop from a typical uniform voltage distribution along the inner cells. [...]
2023 - 4 p. - Published in : JACoW IPAC 2023 (2023) TUPA171 Fulltext: PDF;
In : 14th International Particle Accelerator Conference (IPAC 2023), Venice, Italy, 7 - 12 May 2023, pp.TUPA171
626.
Analytic derivative of orbit response matrix and dispersion with thick error sources and thick steerers implemented in python / Franchi, Andrea (ESRF, Grenoble) ; Liuzzo, Simone (ESRF, Grenoble) ; Martí, Zeus (ESRF, Grenoble)
While large circular colliders rely upon analysis of turn-by-turn beam trajectory data to infer and correct magnetic lattice imperfection and beam optics parameters, historically storage-ring based light sources have been exploiting orbit distortion, via the orbit response matrix. However, even large collider usually benefit of the orbit analysis during the design phase, in order to evaluate and define tolerances, correction layouts and expected performances. [...]
2023 - 3 p. - Published in : JACoW IPAC 2023 (2023) MOPL069 Fulltext: PDF;
In : 14th International Particle Accelerator Conference (IPAC 2023), Venice, Italy, 7 - 12 May 2023, pp.MOPL069
627.
Monitoring particle accelerators with wireless IoT / Sierra, Rodrigo (CERN) ; Cosmed, Xoán (CERN) ; Danzeca, Salvatore (CERN)
Deployment of a private LoRaWAN® network at CERN started in 2019 to complement the sitewide Wi-Fi network and to meet a demand from our community of technologically advanced users. In addition to indoor coverage in our many buildings, we also provide coverage over around 60 km2 of the surrounding area via outdoor gateways strategically positioned within the campus. [...]
2025 - 4 p. - Published in : EPJ Web Conf. 337 (2025) 01303 Fulltext: PDF;
In : 27th International Conference on Computing in High Energy & Nuclear Physics (CHEP2024), Kraków, Poland, 19 - 25 Oct 2024, pp.01303
628.
Introduction to Optics Design / Sterbini, Guido (CERN)
This lecture provides an overview of the principles and methodologies involved in linear optics design. [...]
arXiv:2510.13346.
- 2025 - 23.
Fulltext
629.
Performance study of novel micro-Resistive WELL ($\mu$-RWELL) detector in different gas mixtures / Chakraborty, S (York U., England ; TRIUMF) ; Laird, A M (York U., England) ; Lynch, W (York U., England) ; Bencivenni, G (Frascati) ; De Oliveira, R (CERN) ; Joshi, P (York U., England) ; Hide, B (York U., England) ; Raspino, D (Rutherford) ; Martin, L (TRIUMF) ; Ruiz, C (TRIUMF) et al.
Versatility of micro-pattern gaseous detectors (MPGD) make them suitable for the use in various fields of study, e.g. nuclear physics, particle physics, dark matter physics along with a wide range of medical and security applications. [...]
2023 - 4 p. - Published in : JINST 18 (2023) C06006 Fulltext: PDF;
In : 7th International Conference on Micro Pattern Gaseous Detectors 2022 (MPGD 2022), Rehovot, Israel, 11 - 16 Dec 2022, pp.C06006
630.
Classification with Integrated Quantum and Spiking Neural Networks / Pasquali, Dominic (UC, Santa Cruz ; CERN) ; Grossi, Michele (CERN) ; Vallecorsa, Sofia (CERN)
Spiking neural networks are rapidly gaining interest in analogue computation. So far little work has been conducted in blending quantum and spiking neural network methods into machine learning models. [...]
2023 - 2 p. - Published in : 10.1109/QCE57702.2023.10251
In : 2023 International Conference on Quantum Computing and Engineering (QCE23), Bellevue, United States, 17 - 22 Sep 2023, pp.298-299

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