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2025-10-22
06:39
Benchmarking massively-parallel Analysis Grand Challenge workflows using Snakemake and REANA / Donadoni, Marco (CERN) ; Feickert, Matthew (U. Wisconsin, Madison (main)) ; Held, Alexander (U. Wisconsin, Madison (main)) ; Povsten, Andrii (Princeton U. (main)) ; Shadura, Oksana (U. Nebraska, Lincoln) ; Šimko, Tibor (CERN)
We have created a Snakemake computational analysis workflow corresponding to the IRIS-HEP Analysis Grand Challenge (AGC) example studying ttbar production channels in the CMS open data. We describe the extensions to the AGC pipeline that allowed porting of the notebook-based analysis to Snakemake. [...]
2025 - 8 p. - Published in : EPJ Web Conf. 337 (2025) 01168 Fulltext: PDF;
In : 27th International Conference on Computing in High Energy & Nuclear Physics (CHEP2024), Kraków, Poland, 19 - 25 Oct 2024, pp.01168

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2025-10-22
06:39
A Pilot Analysis Facility at CERN: Architecture, Implementation and First Evaluation / Castro, Diogo (CERN) ; Delgado Peris, Antonio (CERN) ; García García, Enrique (CERN) ; Guerrieri, Giovanni (CERN) ; Jones, Ben (CERN) ; Schulz, Markus (CERN) ; Sciabà, Andrea (CERN) ; Saavedra, Enric Tejedor (CERN)
Experiment analysis frameworks, physics data formats and expectations of scientists at the LHC have been evolving towards interactive analysis with short turnaround times. In preparation for HL-LHC the experiments are moving to data formats suitable for columnar analysis such as RNTuple. [...]
2025 - 8 p. - Published in : EPJ Web Conf. 337 (2025) 01360 Fulltext: PDF;
In : 27th International Conference on Computing in High Energy & Nuclear Physics (CHEP2024), Kraków, Poland, 19 - 25 Oct 2024, pp.01360

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2025-10-22
06:39
Thoroughly testing and integrating hundreds of Pull Requests per month: ROOT’s new Cost-efficient and Feature Rich GitHub-based CI / Piparo, Danilo (CERN) ; Naumann, Axel (CERN) ; Muzaffar, Shahzad (CERN) ; Morud, Ole (CERN) ; Canal, Philippe (Fermilab) ; Hageböck, Stephan (CERN) ; Vasilev, Vassil (Princeton U. (main))
ROOT is an open source framework, freely available on GitHub, at the heart of data acquisition, processing and analysis of HE(N)P experiments, and beyond. It is developed collaboratively: contributions are not authored only by ROOT team members, but also by the user community at large: developers and scientists from universities, labs as well as the private sector. [...]
2025 - 6 p. - Published in : EPJ Web Conf. 337 (2025) 01006 Fulltext: PDF;
In : 27th International Conference on Computing in High Energy & Nuclear Physics (CHEP2024), Kraków, Poland, 19 - 25 Oct 2024, pp.01006

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2025-10-22
06:39
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

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2025-10-22
06:39
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

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2025-10-22
06:39
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

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2025-10-22
06:39
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

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2025-10-22
06:39
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

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2025-10-22
06:39
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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2025-10-22
06:38
Dijet cross section in pp collisions at s=13TeV with the CMS / Kosmoglou Kioseoglou, Polidamas Georgios (Ioannina U.) /CMS Collaboration
A measurement of the dijet production cross section is reported based on an integrated luminosity of 36.3 fb−1 of proton–proton collision data collected in 2016 at s=13 TeV by the CMS detector [2] at the CERN LHC. Jets are reconstructed with the anti-kT algorithm for distance parameters of R=0.4 and R=0.8 and differential cross sections are measured as a function of the kinematic properties of the two jets with largest transverse momenta pT. [...]
2023 - 4 p. - Published in : Nucl. Part. Phys. Proc. 343 (2024) 3-6
In : 26th High-Energy Physics International Conference in QCD, Montpellier, 10 - 14 Jul 2023, pp.3-6

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