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Dynamics in near-threshold J/ψ photoproduction

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arXiv 2023年

作者： Winney, D. Fernández-Ramírez, C. Pilloni, A. Blin, A.N. Hiller Albaladejo, M. Bibrzycki, L. Hammoud, N. Liao, J. Mathieu, V. Montaña, G. Perry, R.J. Shastry, V. Smith, W.A. Szczepaniak, A.P. Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangzhou510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangzhou510006 China MadridE-28040 Spain Instituto de Ciencias Nucleares Universidad Nacional Autónoma de México Ciudad de México04510 Mexico Dipartimento di Scienze Matematiche e Informatiche Scienze Fisiche e Scienze della Terra Università degli Studi di Messina MessinaI-98166 Italy INFN Sezione di Catania CataniaI-95123 Italy Institute for Theoretical Physics Regensburg University RegensburgD-93040 Germany Institute for Theoretical Physics Tübingen University TübingenD-72076 Germany Centro Mixto CSIC-Universidad de Valencia ValenciaE-46071 Spain AGH University of Krakow Faculty of Physics and Applied Computer Science KrakówPL-30-059 Poland Institute of Nuclear Physics Polish Academy of Sciences Kraków31-342 Poland Center for Exploration of Energy and Matter Indiana University BloomingtonIN47403 United States Department of Physics Indiana University BloomingtonIN47405 United States Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona E-08028 Spain Departamento de Física Teórica Universidad Complutense de Madrid IPARCOS MadridE-28040 Spain Theory Center Thomas Jefferson National Accelerator Facility Newport NewsVA23606 United States Institute of Physics Jan Kochanowski University KielcePL-25-406 Poland

The study of J/ψ photoproduction at low energies has consequences for the understanding of multiple aspects of nonperturbative QCD, ranging from mechanical properties of the proton, to the binding inside nuclei, and the existence of hidden-charm pentaquarks. Factorization of the photon-cc¯ and nucleon dynamics or Vector Meson Dominance are often invoked to justify these studies. Alternatively, open-charm intermediate states have been proposed as the dominant mechanism underlying J/ψ photoproduction. As the latter violates this factorization, it is important to estimate the relevance of such contributions. We analyse the latest differential and integrated photoproduction cross sections from the GlueX and J/ψ–007 experiments. We show that the data can be adequately described by a small number of partial waves, which we parameterize with generic models enforcing low-energy unitarity. The results suggest a nonnegligible contribution from open-charm intermediate states. Furthermore, most of the models present an elastic scattering length incompatible with previous extractions based on Vector Meson Dominance, and thus call into question its applicability to heavy mesons. Our results indicate a wide array of physics possibilities that are compatible with present data and need to be disentangled. Copyright © 2023, The Authors. All rights reserved.

关键词： Factorization

Building Bulk Geometry from the Tensor Radon Transform

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arXiv 2020年

作者： Cao, ChunJun Qi, Xiao-Liang Swingle, Brian Tang, Eugene Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States Stanford Institute for Theoretical Physics Stanford University StanfordCA94305 United States Condensed Matter Theory Center University of Maryland College ParkMD20742 United States Institute for Quantum Information and Matter California Institute of Technology PasadenaCA91125 United States

Using the tensor Radon transform and related numerical methods, we study how bulk geometries can be explicitly reconstructed from boundary entanglement entropies in the specific case of AdS3/CFT2. We find that, given the boundary entanglement entropies of a 2d CFT, this framework provides a quantitative measure that detects whether the bulk dual is geometric in the perturbative (near AdS) limit. In the case where a well-defined bulk geometry exists, we explicitly reconstruct the unique bulk metric tensor once a gauge choice is made. We then examine the emergent bulk geometries for static and dynamical scenarios in holography and in many-body systems. Apart from the physics results, our work demonstrates that numerical methods are feasible and effective in the study of bulk reconstruction in AdS/CFT. Copyright © 2020, The Authors. All rights reserved.

关键词： Geometry

quantum Games and Interactive Tools for quantum Technologies Outreach and Education

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arXiv 2022年

作者： Seskir, Zeki C. Migdal, Piotr Weidner, Carrie Anupam, Aditya Case, Nicky Davis, Noah Decaroli, Chiara Ercan, İlke Foti, Caterina Gora, Pawel Jankiewicz, Klementyna La Cour, Brian R. Malo, Jorge Yago Maniscalco, Sabrina Naeemi, Azad Nita, Laurentiu Parvin, Nassim Scafirimuto, Fabio Sherson, Jacob F. Surer, Elif Wootton, James Yeh, Lia Zabello, Olga Chiofalo, Marilù Karlsruhe Institute of Technology ITAS Karlstraße 11 Karlsruhe76133 Germany Quantum Flytrap ul. Ceglowska 29 Warsaw01-809 Poland Quantum Engineering Technology Laboratories H.H. Wills Physics Laboratory Department of Electrical and Electronic Engineering University of Bristol BristolBS8 1FD United Kingdom Georgia Institute of Technology School of Literature Media and Communication 686 Cherry St NW AtlantaGA30313 United States The University of Texas at Austin Center for Quantum Research Applied Research Laboratories 10000 Burnet Rd AustinTX78758 United States National Quantum Computing Center Oxfordshire DidcotOX11 0GD United Kingdom TU Delft Department of Microelectronics Mekelweg 4 Delft2628 CD Netherlands QPlayLearn Aalto University InstituteQ - The Finnish Quantum Institute Department of Applied Physics AaltoFI-00076 11000 Finland Quantum AI Foundation Sanocka 9/103 Warsaw02-110 Poland University of Pisa Department of Physics Largo Bruno Pontecorvo 3 PisaI-56126 Italy University of Helsinki InstituteQ - The Finnish Quantum Institute Department of Physics Helsinki Finland Georgia Institute of Technology School of Electrical and Computer Engineering 777 Atlantic Drive NW AtlantaGA30332 United States Quarks Interactive Strada Bailor 93a Miercurea-Ciuc Harghita4500 Romania IBM Quantum IBM Research - Zurich Säumerstrasse 4 Rüschlikon8803 Switzerland ScienceAtHome Fuglesangs Allé 4 Aarhus8210 Denmark Aarhus University Institute for Physics and Astronomy Ny Munkegade 120 Aarhus8000 Denmark Middle East Technical University Graduate School of Informatics Department of Modeling and Simulation Üniversiteler Mah. Dumlupınar Blv. No:1 Ankara06800 Turkey University of Oxford Department of Computer Science Wolfson Building Parks Road OxfordOX1 3QD United Kingdom IBM Quantum IBM T. J. Watson Research Center Yorktown HeightsNY10598 United States Offenburg University of Applied Sciences Department of Business and Industrial Eng

In this article, we provide an extensive overview of a wide range of quantum games and interactive tools that have been employed by the community in recent years. The paper presents selected tools, as described by their developers. The list includes Hello quantum, Hello Qiskit, Particle in a Box, Psi and Delta, QPlayLearn, Virtual Lab by quantum Flytrap, quantum Odyssey, scienceAtHome, and The Virtual quantum Optics Laboratory. Additionally, we present events for quantum game development: hackathons, game jams, and semester projects. Furthermore, we discuss the quantum Technologies Education for Everyone (QUTE4E) pilot project, which illustrates an effective integration of these interactive tools with quantum outreach and education activities. Finally, we aim at providing guidelines for incorporating quantum games and interactive tools in pedagogic materials to make quantum technologies more accessible for a wider population. Copyright © 2022, The Authors. All rights reserved.

关键词： quantum optics

A Memory-efficient Simulation Method of Grover’s Search Algorithm

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computers, Materials & Continua 2018年第11期57卷 307-319页

作者： Xuwei Tang Juan Xu Bojia Duan College of Computer Science and Technology Nanjing University of Aeronautics and AstronauticsNanjingChina Institute for Quantum Computing University of WaterlooCanada Key Laboratory of Computer Network and Information Integration(Southeast University) Ministry of EducationChina

Grover’s search algorithm is one of the most significant quantum algorithms,which can obtain quadratic speedup of the extensive search *** Grover's search algorithm cannot be implemented on a real quantum computer at present,its quantum simulation is regarded as an effective method to study the search *** simulating the Grover's algorithm,the storage space required is exponential,which makes it difficult to simulate the high-qubit Grover’s *** this end,we deeply study the storage problem of probability amplitude,which is the core of the Grover simulation *** propose a novel memory-efficient method via amplitudes compression,and validate the effectiveness of the method by theoretical analysis and simulation *** results demonstrate that our compressed simulation search algorithm can help to save nearly 87.5%of the storage space than the uncompressed *** under the same hardware conditions,our method can dramatically reduce the required computing nodes,and at the same time,it can simulate at least 3 qubits more than the uncompressed ***,our memory-efficient simulation method can also be used to simulate other quantum algorithms to effectively reduce the storage costs required in simulation.

关键词： Grover’s search algorithm probability amplitude quantum simulation memory compression

Generalization in quantum machine learning from few training data

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arXiv 2021年

作者： Caro, Matthias C. Huang, Hsin-Yuan Cerezo, M. Sharma, Kunal Sornborger, Andrew Cincio, Lukasz Coles, Patrick J. Department of Mathematics Technical University of Munich Garching Germany Munich Germany Institute for Quantum Information and Matter Caltech PasadenaCA United States Department of Computing and Mathematical Sciences Caltech PasadenaCA United States Information Sciences Los Alamos National Laboratory Los AlamosNM87545 United States Center for Nonlinear Studies Los Alamos National Laboratory Los AlamosNM87545 United States Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD20742 United States Quantum Science Center Oak RidgeTN37931 United States Theoretical Division Los Alamos National Laboratory Los AlamosNM87545 United States

Modern quantum machine learning (QML) methods involve variationally optimizing a parameterized quantum circuit on a training data set, and subsequently making predictions on a testing data set (i.e., generalizing). In this work, we provide a comprehensive study of generalization performance in QML after training on a limited number N of training data points. We show that the generalization error of a quantum machine learning model with T trainable gates scales at worst as √T/N. When only K T gates have undergone substantial change in the optimization process, we prove that the generalization error improves to √K/N. Our results imply that the compiling of unitaries into a polynomial number of native gates, a crucial application for the quantum computing industry that typically uses exponential-size training data, can be sped up significantly. We also show that classification of quantum states across a phase transition with a quantum convolutional neural network requires only a very small training data set. Other potential applications include learning quantum error correcting codes or quantum dynamical simulation. Our work injects new hope into the field of QML, as good generalization is guaranteed from few training data. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

QPSO-CD: quantum-behaved particle swarm optimization algorithm with Cauchy distribution

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arXiv 2020年

作者： Bhatia, Amandeep Singh Saggi, Mandeep Kaur Zheng, Shenggen Nayak, Soumya Ranjan Chitkara University Institute of Engineering & Technology Chitkara University Punjab India Department of Computer Science Thapar Institute of Engineering & Technology India Center for Quantum Computing Peng Cheng Laboratory Shenzhen China Amity School Of Engineering & Technology Amity University Uttar Pradesh Noida India

Motivated by the particle swarm optimization (PSO) and quantum computing theory, we have presented a quantum variant of PSO (QPSO) mutated with Cauchy operator and natural selection mechanism (QPSO-CD) from evolutionary computations. The performance of proposed hybrid quantum-behaved particle swarm optimization with Cauchy distribution (QPSO-CD) is investigated and compared with its counterparts based on a set of benchmark problems. Moreover, QPSO-CD is employed in well-studied constrained engineering problems to investigate its applicability. Further, the correctness and time complexity of QPSO-CD are analysed and compared with the classical PSO. It has been proved that QPSO-CD handles such real-life problems efficiently and can attain superior solutions in most of the problems. The experimental results shown that QPSO associated with Cauchy distribution and natural selection strategy outperforms other variants in context of stability and convergence. Copyright © 2020, The Authors. All rights reserved.

关键词： Particle swarm optimization (PSO)

Semi-device-independent random number generation with flexible assumptions

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arXiv 2020年

作者： Pivoluska, Matej Plesch, Martin Farkas, Máté Ružičková, Natália Flegel, Clara Valencia, Natalia Herrera McCutcheon, Will Malik, Mehul Aguilar, Edgar A. Institute of Physics Slovak Academy of Sciences Bratislava845 11 Slovakia Institute of Computer Science Masaryk University Brno602 00 Czech Republic ICFO-Institut de Ciencies Fotoniques Barcelona Institute of Science and Technology Castelldefels08860 Spain Institute of Theoretical Physics and Astrophysics National Quantum Information Centre Faculty of Mathematics Physics and Informatics University of Gdansk Gdansk80-952 Poland International Centre for Theory of Quantum Technologies University of Gdansk Gdansk80-308 Poland Institute of Science and Technology Klosterneuburg3400 Austria Institute of Photonics and Quantum Sciences Heriot-Watt University EdinburghEH14 4AS United Kingdom Institute of Quantum Optics and Quantum Information Austrian Academy of Sciences Vienna1090 Austria Ait Austrian Institute of Technology GmbH Vienna1210 Austria

Our ability to trust that a random number is truly random is essential for fields as diverse as cryptography and fundamental tests of quantum mechanics. Existing solutions both come with drawbacks - device-independent quantum random number generators (QRNGs) are highly impractical and standard semi-device-independent QRNGs are limited to a specific physical implementation and level of trust. Here we propose a new framework for semi-deviceindependent randomness certification, using a source of trusted vacuum in the form of a signal shutter. It employs a flexible set of assumptions and levels of trust, allowing it to be applied in a wide range of physical scenarios involving both quantum and classical entropy sources. We experimentally demonstrate our protocol with a photonic setup and generate secure random bits under three different assumptions with varying degrees of security and resulting data rates. Copyright © 2020, The Authors. All rights reserved.

关键词： Random number generation

Doubly-efficient pseudo-deterministic proofs

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arXiv 2019年

作者： Goemans, Michel Goldwasser, Shafi Holden, Dhiraj Department of Mathematics MIT Simons Institute for the Theory of Computing UC Berkeley Department of Electrical Engineering and Computer Science MIT

In [20] Goldwasser, Grossman and Holden introduced pseudo-deterministic interactive proofs for search problems where a powerful prover can convince a probabilistic polynomial time verifier that a solution to a search problem is canonical. They studied search problems for which polynomial time algorithms are not known and for which many solutions are possible. They showed that whereas there exists a constant round pseudo deterministic proof for graph isomorphism where the canonical solution is the lexicographically smallest isomorphism, the existence of pseudo-deterministic interactive proofs for NP-hard problems would imply the collapse of the polynomial time hierarchy. Copyright © 2019, The Authors. All rights reserved.

关键词： Polynomial approximation

Hot QCD at finite isospin density: Confronting SU(3) Nambu-Jona-Lasinio model with recent lattice data

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arXiv 2021年

作者： Lopes, Bruno S. Avancini, Sidney S. Bandyopadhyay, Aritra Duarte, Dyana C. Farias, Ricardo L.S. Departamento de Física Universidade Federal de Santa Maria Santa Maria RS97105-900 Brazil Departamento de Física Universidade Federal de Santa Catarina Florianópolis Santa Catarina88040-900 Brazil Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangzhou510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangzhou510006 China Institute for Nuclear Theory University of Washington SeattleWA98195 United States Departamento de Física Instituto Tecnológico de Aeronáutica São José dos Campos SP12228-900 Brazil

Extending our recently published SU(2) results for zero temperature we now compute the QCD equation of state for finite isospin density within the three flavor Nambu-Jona-Lasinio model in the mean field approximation, motivated by the recently obtained Lattice QCD results for both zero and finite temperatures. Like our previous study, here also we have considered both the commonly used Traditional cutoff Regularization Scheme and the Medium Separation Scheme. Our results are compared with recent high-precision lattice simulations as well as previously obtained results in two-flavor Nambu-Jona-Lasinio model. The agreement between the lattice results and the predictions from three-flavor NJL model is very good for low values of µI (for both zero and finite temperatures). For larger values of µI, the agreement between lattice data and the two-flavor NJL predictions is surprisingly good and better than with the three-flavor predictions. © 2021, CC BY.

关键词： Forecasting