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Precise Image Generation on Current Noisy Quantum Computing Devices / Rehm, Florian (CERN ; RWTH Aachen U.) ; Vallecorsa, Sofia (CERN) ; Borras, Kerstin (RWTH Aachen U. ; DESY) ; Krücker, Dirk (DESY) ; Grossi, Michele (CERN) ; Varo, Valle (DESY)
The Quantum Angle Generator (QAG) is a new full Quantum Machine Learning model designed to generate accurate images on current Noise Intermediate Scale (NISQ) Quantum devices. Variational quantum circuits form the core of the QAG model, and various circuit architectures are evaluated. [...]
arXiv:2307.05253.- 2023-10-30 - 22 p. - Published in : Quantum Sci. Technol. 9 (2024) 015009 Fulltext: document - PDF; 2307.05253 - PDF;

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(91)

Precise Quantum Angle Generator Designed for Noisy Quantum Devices / Rehm, Florian (CERN ; DESY) ; Vallecorsa, Sofia (RWTH Aachen U.) ; Borras, Kerstin (DESY) ; Krücker, Dirk (RWTH Aachen U.) ; Grossi, Michele (RWTH Aachen U.) ; Varo, Valle (RWTH Aachen U.)
The Quantum Angle Generator (QAG) is a cutting-edge quantum machine learning model designed to generate precise images on current Noise Intermediate Scale Quantum devices. It utilizes variational quantum circuits and incorporates the MERA-upsampling architecture, achieving exceptional accuracy. [...]
2024 - 8 p. - Published in : EPJ Web Conf. 295 (2024) 12006 Fulltext: PDF;
In : 26th International Conference on Computing in High Energy & Nuclear Physics, Norfolk, Virginia, Us, 8 - 12 May 2023, pp.12006

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(33)

Quantum Angle Generator for Image Generation / Florian, Rehm (CERN ; RWTH Aachen U.) ; Vallecorsa Sofia (CERN) ; Grossi Michele (CERN) ; Kerstin, Borras (DESY ; CERN ; RWTH Aachen U.) ; Krücker Dirk (DESY) ; Schnake Simon (DESY ; RWTH Aachen U.) ; Alexis-Harilaos, Verney-Provatas (DESY ; RWTH Aachen U.)
The Quantum Angle Generator (QAG) is a new generative model for quantum computers. It consists of a parameterized quantum circuit trained with an objective function. [...]
2022 - 5 p. - Published in : 10.1109/SEC54971.2022.00064
In : 2022 IEEE/ACM 7th Symposium on Edge Computing (SEC 2022), Seattle, Washington, United States, 5 - 8 Dec 2022, pp.425-429

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(16)

Quantum Machine Learning for HEP Detector Simulations / Rehm, Florian (CERN ; RWTH Aachen U.) ; Vallecorsa, Sofia (CERN) ; Borras, Kerstin (RWTH Aachen U. ; DESY) ; Krücker, Dirk (DESY)
Quantum Machine Learning (qML) is one of the most promising and very intuitive applications on near-term quantum devices which possess the potential to combat computing resource challenges faster than traditional computers. Classical Machine Learning (ML) is taking up a significant role in particle physics to speed up detector simulations. [...]
2021 - 6 p. - Published in : (2021) , pp. 363-368 Fulltext: PDF;
In : 9th International Conference on Distributed Computing and Grid Technologies in Science and Education (GRID 2021), Dubna, Russian Federation, 5 - 9 Jul 2021, pp.363-368

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(10)

Impact of quantum noise on the training of quantum Generative Adversarial Networks / Borras, Kerstin (DESY, Zeuthen ; RWTH Aachen U.) ; Chang, Su Yeon (CERN ; Ecole Polytechnique, Lausanne) ; Funcke, Lena (MIT, Cambridge, CTP ; IAIFI, Cambridge) ; Grossi, Michele (CERN) ; Hartung, Tobias (Cyprus Inst. ; Bath U.) ; Jansen, Karl (DESY, Zeuthen) ; Kruecker, Dirk (DESY, Zeuthen) ; Kühn, Stefan (Cyprus Inst.) ; Rehm, Florian (CERN ; RWTH Aachen U.) ; Tüysüz, Cenk (DESY, Zeuthen ; Humboldt U., Berlin) et al.
Current noisy intermediate-scale quantum devices suffer from various sources of intrinsic quantum noise. Overcoming the effects of noise is a major challenge, for which different error mitigation and error correction techniques have been proposed. [...]
arXiv:2203.01007; MIT-CTP/5400.- 2023 - 6 p.
- Published in : J. Phys.: Conf. Ser. Fulltext: 2203.01007 - PDF; document - PDF;
In : 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021), Daejeon, Korea, 29 Nov - 3 Dec 2021, pp.012093

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(10)

CaloChallenge 2022: A Community Challenge for Fast Calorimeter Simulation / Krause, Claudius (ed.) (Vienna, OAW ; Heidelberg U.) ; Faucci Giannelli, Michele (ed.) (INFN, Rome2 ; Chalmers U. Tech.) ; Kasieczka, Gregor (ed.) (Hamburg U.) ; Nachman, Benjamin (ed.) (LBNL, Berkeley) ; Salamani, Dalila (ed.) (CERN) ; Shih, David (ed.) (Rutgers U., Piscataway) ; Zaborowska, Anna (ed.) (CERN) ; Amram, Oz (Fermilab) ; Borras, Kerstin (DESY ; Aachen, Tech. Hochsch.) ; Buckley, Matthew R. (Rutgers U., Piscataway) et al.
We present the results of the "Fast Calorimeter Simulation Challenge 2022" - the CaloChallenge. [...]
arXiv:2410.21611 ; HEPHY-ML-24-05 ; FERMILAB-PUB-24-0728-CMS ; TTK-24-43. - 204.
Fermilab Library Server - Fulltext - Fulltext

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(9)

Symmetry Breaking in Geometric Quantum Machine Learning in the Presence of Noise / Tüysüz, Cenk (DESY ; Humboldt U., Berlin) ; Chang, Su Yeon (CERN ; Ecole Polytechnique, Lausanne) ; Demidik, Maria (DESY ; Cyprus Inst.) ; Jansen, Karl (DESY ; Cyprus Inst.) ; Vallecorsa, Sofia (CERN) ; Grossi, Michele (CERN)
Geometric quantum machine learning based on equivariant quantum neural networks (EQNN) recently appeared as a promising direction in quantum machine learning. Despite the encouraging progress, the studies are still limited to theory, and the role of hardware noise in EQNN training has never been explored. [...]
arXiv:2401.10293.- 2024-07-01 - 20 p. - Published in : PRX Quantum 5 (2024) 030314 Fulltext: 2401.10293 - PDF; Publication - PDF;

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Quantum Computing for High-Energy Physics : State of the Art and Challenges / Di Meglio, Alberto (CERN) ; Jansen, Karl (DESY, Zeuthen ; Cyprus Inst.) ; Tavernelli, Ivano (IBM, Zurich) ; Alexandrou, Constantia (Cyprus U. ; Cyprus Inst.) ; Arunachalam, Srinivasan (IBM Watson Res. Ctr.) ; Bauer, Christian W. (LBNL, Berkeley) ; Borras, Kerstin (DESY ; Aachen, Tech. Hochsch.) ; Carrazza, Stefano (Milan U. ; CERN) ; Crippa, Arianna (DESY, Zeuthen ; Humboldt U., Berlin) ; Croft, Vincent (U. Leiden (main)) et al.
Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage, namely a significant (in some cases exponential) speed-up of numerical simulations. The rapid development of hardware devices with various realizations of qubits enables the execution of small scale but representative applications on quantum computers. [...]
arXiv:2307.03236; FERMILAB-PUB-23-468-ETD.- 2024-08-01 - 49 p. - Published in : PRX Quantum 5 (2024) 037001 Fulltext: 2307.03236 - PDF; FERMILAB-PUB-23-468-ETD - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server

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Observation of WW$\gamma $ production and search for H$ \gamma $ production in proton-proton collisions at $ \sqrt{s}= $ 13 TeV / CMS Collaboration
The observation of WW$\gamma $ production in proton-proton collisions at a center-of-mass energy of 13 TeV with an integrated luminosity of 138 fb$ ^{-1} $ is presented. The observed (expected) significance is 5.6 (4.7) standard deviations. [...]
arXiv:2310.05164; CMS-SMP-22-006; CERN-EP-2023-203; CMS-SMP-22-006-003.- Geneva : CERN, 2024-03-19 - 20 p. - Published in : Phys. Rev. Lett. 132 (2024) 121901 Fulltext: FERMILAB-PUB-23-607-CMS - PDF; 2310.05164 - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server

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Measurement of the primary Lund jet plane density in proton-proton collisions at $ \sqrt{\textrm{s}} $ = 13 TeV / CMS Collaboration
A measurement is presented of the primary Lund jet plane (LJP) density in inclusive jet production in proton-proton collisions. The analysis uses 138 fb$ ^{-1} $ of data collected by the CMS experiment at $ \sqrt{s} = $ 13 TeV. [...]
arXiv:2312.16343; CMS-SMP-22-007; CERN-EP-2023-282; CMS-SMP-22-007-003.- Geneva : CERN, 2024-05-10 - 59 p. - Published in : JHEP 2405 (2024) 116 Fulltext: 2312.16343 - PDF; 200411dd73b31f6c7171bd93306c206f - PDF; Fulltext from Publisher: PDF; External link: Fermilab Library Server

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