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Charge collection parameterization of MALTA2, a depleted monolithic active pixel sensor
/ Fasselt, L (DESY ; Humboldt U., Berlin (main)) ; Behera, P (Indian Inst. Tech., Madras) ; Berlea, D V (DESY ; Humboldt U., Berlin (main)) ; Bortoletto, D (U. Oxford (main)) ; Buttar, C (Glasgow U.) ; Chembakan, T (Indian Inst. Tech., Madras) ; Dao, V (Stony Brook U.) ; Dash, G (Indian Inst. Tech., Madras) ; Haberl, S (CERN) ; Inada, T (CERN) et al.
A fast simulation method is presented for a depleted monolithic active pixel sensor, which uses a data driven parameterization of the charge collection and propagation. This approach provides an efficient alternative to TCAD simulations, particularly for sensors whose proprietary process details - such as doping profiles or implant geometries - are unavailable. [...]
arXiv:2602.23139.-
2026 - 7 p.
- Published in : JINST 21 (2026) C04001
Fulltext: 2602.23139 - PDF; document - PDF;
In : Topical Workshop on Electronics for Particle Physics 2025, Rethymno, Crete, Greece, 6 - 10 Oct 2025, pp.C04001
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Automatic Frequency-Domain Modelling of Superconducting Magnets and its Usability to Model General Inductors
/ Wolstrup, Anders Frem (Denmark, Tech. U.) ; Ravaioli, Emmanuele (CERN) ; Zsurzsan, Tiberiu Gabriel (Denmark, Tech. U.) ; Zhang, Zhe (Denmark, Tech. U.)
This paper focuses on the development of a Python dataclass and SWAN notebooks allowing for automatic generation of PSPICE© of the Large Hydron Collider (LHC) superconducting electromagnets and circuits installed at CERN. The models consist of inductors, resistors and capacitors, as well as RL-loops, modelling the behaviour of the magnets and circuits, including eddy-current effects. [...]
2021 - 7 p.
- Published in : IEEE Conf. ECCEAsia 2021 (2021) 1312-1318
In : 12th Energy Conversion Congress & Exposition, Online, 24 - 27 May 2021, pp.1312-1318
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AMS-02 Through a Research-Infrastructure Lens for Space Radiobiology Translation
/ Bartoloni, Alessandro (CERN ; INFN, Rome)
The Alpha Magnetic Spectrometer (AMS-02), operating on the International Space Station since May 2011, is widely recognized for its flagship contributions to astroparticle physics, including precision measurements of cosmic-ray leptons, antiprotons, and nuclei over more than a solar cycle. In this article, I present AMS-02 through the lens of a research infrastructure (RI): a long-lived, globally networked, and continuously evolving capability that produces curated data products, technical documentation, calibration knowledge, and operational experience that remain valuable beyond the original physics drivers. [...]
2026 - 22 p.
- Published in : Comput. Softw. Big Sci. 10 (2026) 7
Fulltext: PDF;
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Top quark pairs in the threshold at the LHC
/ Garzelli, Maria Vittoria (U. Hamburg (main) ; CERN) ; Limatola, Giovanni (U. Hamburg (main)) ; Moch, Sven-Olaf (U. Hamburg (main)) ; Steinhauser, Matthias (KIT, Karlsruhe) ; Zenaiev, Oleksandr (U. Hamburg (main))
We presented updated predictions for top quark-antiquark pair production at the LHC in the threshold region. We presented results for the invariant mass differential distribution of the final state, also accounting for Coulomb resummation within the NRQCD framework..
2026 - 4 p.
- Published in : J. Subatomic Part. Cosmol. 5 (2026) 100368
Fulltext: PDF;
In : 18th International Workshop on Top Quark Physics (TOP2025), Seoul, South Korea, 21 - 26 Sep 2025, pp.100368
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CaloClouds3: Ultra-fast geometry-independent highly-granular calorimeter simulation
/ Buss, Thorsten (DESY ; Hamburg U.) ; Day-Hall, Henry (DESY) ; Gaede, Frank (DESY) ; Kasieczka, Gregor (Hamburg U.) ; Krüger, Katja (DESY) ; Korol, Anatolii (DESY) ; Madlener, Thomas (DESY) ; McKeown, Peter (CERN) ; Mozzanica, Martina (Hamburg U.) ; Valente, Lorenzo (Hamburg U.)
We present CaloClouds3, a model for the fast simulation of photon showers in the barrel of a high granularity detector. This iteration demonstrates for the first time how a pointcloud model can employ angular conditioning to replicate photons at all incident angles. [...]
arXiv:2511.01460; DESY-25-148.-
2026 - 28 p.
- Published in : JINST 21 (2026) P03018
Fulltext: 2511.01460 - PDF; document - PDF;
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Roadmap on fast machine learning for science
/ Summers, Sioni (CERN) ; Tapper, Alex (Imperial Coll., London) ; Årrestad, Thea Klæboe (ETH, Zurich (main)) ; Qin, Chen (Imperial Coll., London) ; Rathsman, Karin (ESS, Lund) ; Streeter, Matthew (Queen's U., Belfast) ; Palmer, Charlotte (Queen's U., Belfast) ; Citrin, Jonathan (Unlisted, UK) ; Zheng, Changgang (U. Oxford (main)) ; Zilberman, Noa (U. Oxford (main)) et al.
The need for microsecond speed machine learning (ML) inference for particle physics experiments has emerged in recent years, in particular for the forthcoming upgrades to the experiments at the Large Hadron Collider at CERN. A community has grown around the need to develop the custom hardware platforms and tools required. [...]
2026 - 30 p.
- Published in : Mach. Learn. Sci. Tech. 7 (2026) 021501
Fulltext: PDF;
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