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CERN Document Server Pronađeno je 9 zapisa  Pretraživanje je potrajalo 1.11 sekundi 
1.
Hybrid actor-critic algorithm for quantum reinforcement learning at CERN beam lines / Schenk, Michael (CERN) ; Combarro, Elías F. (U. Oviedo (main)) ; Grossi, Michele (CERN) ; Kain, Verena (CERN) ; Li, Kevin Shing Bruce (CERN) ; Popa, Mircea-Marian (Bucharest, Polytechnic Inst.) ; Vallecorsa, Sofia (CERN)
Free energy-based reinforcement learning (FERL) with clamped quantum Boltzmann machines (QBM) was shown to significantly improve the learning efficiency compared to classical Q-learning with the restriction, however, to discrete state-action space environments. In this paper, the FERL approach is extended to multi-dimensional continuous state-action space environments to open the doors for a broader range of real-world applications. [...]
arXiv:2209.11044.- 2024-02-21 - 17 p. - Published in : Quantum Sci. Technol. 9 (2024) 025012 Fulltext: Publication - PDF; 2209.11044 - PDF;
2.
Running the Dual-PQC GAN on noisy simulators and real quantum hardware / Chang, Su Yeon (CERN ; Ecole Polytechnique, Lausanne) ; Agnew, Edwin (Cambridge U.) ; Combarro, Elías F (Oviedo U.) ; Grossi, Michele (CERN) ; Herbert, Steven (Cambridge U.) ; Vallecorsa, Sofia (CERN)
In an earlier work, we introduced dual-Parameterized Quantum Circuit (PQC) Generative Adversarial Networks (GAN), an advanced prototype of a quantum GAN. We applied the model on a realistic High-Energy Physics (HEP) use case: the exact theoretical simulation of a calorimeter response with a reduced problem size. [...]
arXiv:2205.15003.- 2023 - 6 p. - Published in : J. Phys. : Conf. Ser.: 2438 (2023) , no. 1, pp. 012062
Fulltext: document - PDF; 2205.15003 - PDF;
In : 20th International Workshop on Advanced Computing and Analysis Techniques in Physics Research (ACAT 2021), Daejeon, Korea, 29 Nov - 3 Dec 2021, pp.012062
3.
A study of the performance of classical minimizers in the Quantum Approximate Optimization Algorithm / Fernández-Pendás, Mario (U. Basque Country, Leioa ; Donostia Intl. Phys. Ctr., San Sebastian) ; Combarro, Elías F (Oviedo U. ; CERN) ; Vallecorsa, Sofia (CERN) ; Ranilla, José (Oviedo U.) ; Rúa, Ignacio F (Oviedo U.)
The Quantum Approximate Optimization Algorithm (QAOA) was proposed as a way of finding good, approximate solutions to hard combinatorial optimization problems. QAOA uses a hybrid approach. [...]
2022 - Published in : J. Comput. Appl. Math. 404 (2022) 113388
4.
On protocols for increasing the uniformity of random bits generated with noisy quantum computers / Combarro, Elías F (CERN ; U. Oviedo (main)) ; Carminati, Federico (CERN) ; Vallecorsa, Sofia (CERN) ; Ranilla, José (U. Oviedo (main)) ; Rúa, Ignacio F (U. Oviedo (main))
Generating random numbers is important for many real-world applications, including cryptography, statistical sampling and Monte Carlo simulations. Quantum systems subject to a measurement produce random results via Born’s rule, and thus it is natural to study the possibility of using such systems in order to generate highquality random numbers. [...]
2021 - 19 p. - Published in : J. Supercomput. 77 (2021) 8063-8081
5.
A report on teaching a series of online lectures on quantum computing from CERN / Combarro, Elías F (CERN ; U. Oviedo (main)) ; Vallecorsa, Sofia (CERN) ; Rodríguez-Muñiz, Luis J (U. Oviedo (main)) ; Aguilar-González, Álvaro (U. Oviedo (main)) ; Ranilla, José (U. Oviedo (main)) ; Di Meglio, Alberto (CERN)
Quantum computing (QC) is one of the most promising new technologies for High Performance Computing. Its potential use in High Energy Physics has lead CERN, one of the top world users of large-scale distributed computing, to start programmes such as the Quantum Technology Initiative (QTI) to further assess and explore the applications of QC. [...]
2021 - 31 p. - Published in : J. Supercomput.: 77 (2021) , no. 12, pp. 14405-14435
- Published in : J. Supercomput.: 77 (2021) , no. 12, pp. 14436-14437
6.
On a poset of quantum exact promise problems / Combarro, Elías F. (Oviedo U. ; CERN) ; Vallecorsa, Sofia (CERN) ; Di Meglio, Alberto (CERN) ; Piñera, Alejandro (Oviedo U.) ; Fernández Rúa, Ignacio (Oviedo U.)
Two of the most well-known quantum algorithms, those introduced by Deutsch–Jozsa and Bernstein–Vazirani, can solve promise problems with just one function query, showing an oracular separation with deterministic classical algorithms. In this work, we generalise those methods to study a family of quantum algorithms that can, with just one query, exactly solve promise problems stated over Boolean functions. [...]
2021 - 17 p. - Published in : Quantum Inf. Process. 20 (2021) 214 Fulltext: PDF;
7.
Higgs analysis with quantum classifiers / Belis, Vasileios (ETH, Zurich (main)) ; González-Castillo, Samuel (Oviedo U.) ; Reissel, Christina (ETH, Zurich (main)) ; Vallecorsa, Sofia (CERN) ; Combarro, Elías F. (Oviedo U.) ; Dissertori, Günther (ETH, Zurich (main)) ; Reiter, Florentin (Zurich, ETH-CSCS/SCSC)
We have developed two quantum classifier models for the tˉtH(bˉb) classification problem, both of which fall into the category of hybrid quantum-classical algorithms for Noisy Intermediate Scale Quantum devices (NISQ). Our results, along with other studies, serve as a proof of concept that Quantum Machine Learning (QML) methods can have similar or better performance, in specific cases of low number of training samples, with respect to conventional ML methods even with a limited number of qubits available in current hardware. [...]
arXiv:2104.07692.- 2021 - 12 p. - Published in : EPJ Web Conf. 251 (2021) 03070 Fulltext: 2104.07692 - PDF; document - PDF;
In : 25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021, pp.03070
8.
Dual-Parameterized Quantum Circuit GAN Model in High Energy Physics / Chang, Su Yeon (CERN ; Ecole Polytechnique, Lausanne) ; Herbert, Steven (Sentec Ltd., Cambridge ; Cambridge U.) ; Vallecorsa, Sofia (CERN) ; Combarro, Elías F. (Oviedo U.) ; Duncan, Ross (Sentec Ltd., Cambridge ; Strathclyde U. ; University Coll. London)
Generative models, and Generative Adversarial Networks (GAN) in particular, are being studied as possible alternatives to Monte Carlo simulations. It has been proposed that, in certain circumstances, simulation using GANs can be sped-up by using quantum GANs (qGANs). [...]
arXiv:2103.15470.- 2021 - 11 p. - Published in : EPJ Web Conf. 251 (2021) 03050 Fulltext: 2103.15470 - PDF; document - PDF;
In : 25th International Conference on Computing in High-Energy and Nuclear Physics (CHEP), Online, Online, 17 - 21 May 2021, pp.03050
9.
Quantum Generative Adversarial Networks in a Continuous-Variable Architecture to Simulate High Energy Physics Detectors / Chang, Su Yeon (CERN ; EPFL, Lausanne, LPPC) ; Vallecorsa, Sofia (CERN) ; Combarro, Elías F. (Oviedo U.) ; Carminati, Federico (CERN)
Deep Neural Networks (DNNs) come into the limelight in High Energy Physics (HEP) in order to manipulate the increasing amount of data encountered in the next generation of accelerators. [...]
arXiv:2101.11132.
- 4 p.
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1 Combarro, E F
6 Combarro, Elías F
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