Generation of Werner-Like States Via a Two-Qubit System Plunged in A
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Quantum Machine Learning: Benefits and Practical Examples
Quantum Machine Learning: Benefits and Practical Examples Frank Phillipson1[0000-0003-4580-7521] 1 TNO, Anna van Buerenplein 1, 2595 DA Den Haag, The Netherlands [email protected] Abstract. A quantum computer that is useful in practice, is expected to be devel- oped in the next few years. An important application is expected to be machine learning, where benefits are expected on run time, capacity and learning effi- ciency. In this paper, these benefits are presented and for each benefit an example application is presented. A quantum hybrid Helmholtz machine use quantum sampling to improve run time, a quantum Hopfield neural network shows an im- proved capacity and a variational quantum circuit based neural network is ex- pected to deliver a higher learning efficiency. Keywords: Quantum Machine Learning, Quantum Computing, Near Future Quantum Applications. 1 Introduction Quantum computers make use of quantum-mechanical phenomena, such as superposi- tion and entanglement, to perform operations on data [1]. Where classical computers require the data to be encoded into binary digits (bits), each of which is always in one of two definite states (0 or 1), quantum computation uses quantum bits, which can be in superpositions of states. These computers would theoretically be able to solve certain problems much more quickly than any classical computer that use even the best cur- rently known algorithms. Examples are integer factorization using Shor's algorithm or the simulation of quantum many-body systems. This benefit is also called ‘quantum supremacy’ [2], which only recently has been claimed for the first time [3]. There are two different quantum computing paradigms. -
Unconditional Quantum Teleportation
R ESEARCH A RTICLES our experiment achieves Fexp 5 0.58 6 0.02 for the field emerging from Bob’s station, thus Unconditional Quantum demonstrating the nonclassical character of this experimental implementation. Teleportation To describe the infinite-dimensional states of optical fields, it is convenient to introduce a A. Furusawa, J. L. Sørensen, S. L. Braunstein, C. A. Fuchs, pair (x, p) of continuous variables of the electric H. J. Kimble,* E. S. Polzik field, called the quadrature-phase amplitudes (QAs), that are analogous to the canonically Quantum teleportation of optical coherent states was demonstrated experi- conjugate variables of position and momentum mentally using squeezed-state entanglement. The quantum nature of the of a massive particle (15). In terms of this achieved teleportation was verified by the experimentally determined fidelity analogy, the entangled beams shared by Alice Fexp 5 0.58 6 0.02, which describes the match between input and output states. and Bob have nonlocal correlations similar to A fidelity greater than 0.5 is not possible for coherent states without the use those first described by Einstein et al.(16). The of entanglement. This is the first realization of unconditional quantum tele- requisite EPR state is efficiently generated via portation where every state entering the device is actually teleported. the nonlinear optical process of parametric down-conversion previously demonstrated in Quantum teleportation is the disembodied subsystems of infinite-dimensional systems (17). The resulting state corresponds to a transport of an unknown quantum state from where the above advantages can be put to use. squeezed two-mode optical field. -
Explorations in Quantum Neural Networks with Intermediate Measurements
ESANN 2020 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Online event, 2-4 October 2020, i6doc.com publ., ISBN 978-2-87587-074-2. Available from http://www.i6doc.com/en/. Explorations in Quantum Neural Networks with Intermediate Measurements Lukas Franken and Bogdan Georgiev ∗Fraunhofer IAIS - Research Center for ML and ML2R Schloss Birlinghoven - 53757 Sankt Augustin Abstract. In this short note we explore a few quantum circuits with the particular goal of basic image recognition. The models we study are inspired by recent progress in Quantum Convolution Neural Networks (QCNN) [12]. We present a few experimental results, where we attempt to learn basic image patterns motivated by scaling down the MNIST dataset. 1 Introduction The recent demonstration of Quantum Supremacy [1] heralds the advent of the Noisy Intermediate-Scale Quantum (NISQ) [2] technology, where signs of supe- riority of quantum over classical machines in particular tasks may be expected. However, one should keep in mind the limitations of NISQ-devices when study- ing and developing quantum-algorithmic solutions - among other things, these include limits on the number of gates and qubits. At the same time the interaction of quantum computing and machine learn- ing is growing, with a vast amount of literature and new results. To name a few applications, the well-known HHL algorithm [3], quantum phase estimation [5] and inner products speed-up techniques lead to further advances in Support Vector Machines [4] and Principal Component Analysis [6, 7]. Intensive progress and ongoing research has also been made towards quantum analogues of Neural Networks (QNN) [8, 9, 10]. -
Quantum Error Modelling and Correction in Long Distance Teleportation Using Singlet States by Joe Aung
Quantum Error Modelling and Correction in Long Distance Teleportation using Singlet States by Joe Aung Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering and Computer Science at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY May 2002 @ Massachusetts Institute of Technology 2002. All rights reserved. Author ................... " Department of Electrical Engineering and Computer Science May 21, 2002 72-1 14 Certified by.................. .V. ..... ..'P . .. ........ Jeffrey H. Shapiro Ju us . tn Professor of Electrical Engineering Director, Research Laboratory for Electronics Thesis Supervisor Accepted by................I................... ................... Arthur C. Smith Chairman, Department Committee on Graduate Students BARKER MASSACHUSE1TS INSTITUTE OF TECHNOLOGY JUL 3 1 2002 LIBRARIES 2 Quantum Error Modelling and Correction in Long Distance Teleportation using Singlet States by Joe Aung Submitted to the Department of Electrical Engineering and Computer Science on May 21, 2002, in partial fulfillment of the requirements for the degree of Master of Science in Electrical Engineering and Computer Science Abstract Under a multidisciplinary university research initiative (MURI) program, researchers at the Massachusetts Institute of Technology (MIT) and Northwestern University (NU) are devel- oping a long-distance, high-fidelity quantum teleportation system. This system uses a novel ultrabright source of entangled photon pairs and trapped-atom quantum memories. This thesis will investigate the potential teleportation errors involved in the MIT/NU system. A single-photon, Bell-diagonal error model is developed that allows us to restrict possible errors to just four distinct events. The effects of these errors on teleportation, as well as their probabilities of occurrence, are determined. -
Bidirectional Quantum Controlled Teleportation by Using Five-Qubit Entangled State As a Quantum Channel
Bidirectional Quantum Controlled Teleportation by Using Five-qubit Entangled State as a Quantum Channel Moein Sarvaghad-Moghaddam1,*, Ahmed Farouk2, Hussein Abulkasim3 to each other simultaneously. Unfortunately, the proposed Abstract— In this paper, a novel protocol is proposed for protocol required additional quantum and classical resources so implementing BQCT by using five-qubit entangled states as a that the users required two-qubit measurements and applying quantum channel which in the same time, the communicated users global unitary operations. There are many approaches and can teleport each one-qubit state to each other under permission prototypes for the exploitation of quantum principles to secure of controller. The proposed protocol depends on the Controlled- the communication between two parties and multi-parties [18, NOT operation, proper single-qubit unitary operations and single- 19, 20, 21, 22]. While these approaches used different qubit measurement in the Z-basis and X-basis. The results showed that the protocol is more efficient from the perspective such as techniques for achieving a private communication among lower shared qubits and, single qubit measurements compared to authorized users, but most of them depend on the generation of the previous work. Furthermore, the probability of obtaining secret random keys [23, 2]. In this paper, a novel protocol is Charlie’s qubit by eavesdropper is reduced, and supervisor can proposed for implementing BQCT by using five-qubit control one of the users or every two users. Also, we present a new entanglement state as a quantum channel. In this protocol, users method for transmitting n and m-qubits entangled states between may transmit an unknown one-qubit quantum state to each other Alice and Bob using proposed protocol. -
Arxiv:2011.01938V2 [Quant-Ph] 10 Feb 2021 Ample and Complexity-Theoretic Argument Showing How Or Small Polynomial Speedups [8,9]
Power of data in quantum machine learning Hsin-Yuan Huang,1, 2, 3 Michael Broughton,1 Masoud Mohseni,1 Ryan 1 1 1 1, Babbush, Sergio Boixo, Hartmut Neven, and Jarrod R. McClean ∗ 1Google Research, 340 Main Street, Venice, CA 90291, USA 2Institute for Quantum Information and Matter, Caltech, Pasadena, CA, USA 3Department of Computing and Mathematical Sciences, Caltech, Pasadena, CA, USA (Dated: February 12, 2021) The use of quantum computing for machine learning is among the most exciting prospective ap- plications of quantum technologies. However, machine learning tasks where data is provided can be considerably different than commonly studied computational tasks. In this work, we show that some problems that are classically hard to compute can be easily predicted by classical machines learning from data. Using rigorous prediction error bounds as a foundation, we develop a methodology for assessing potential quantum advantage in learning tasks. The bounds are tight asymptotically and empirically predictive for a wide range of learning models. These constructions explain numerical results showing that with the help of data, classical machine learning models can be competitive with quantum models even if they are tailored to quantum problems. We then propose a projected quantum model that provides a simple and rigorous quantum speed-up for a learning problem in the fault-tolerant regime. For near-term implementations, we demonstrate a significant prediction advantage over some classical models on engineered data sets designed to demonstrate a maximal quantum advantage in one of the largest numerical tests for gate-based quantum machine learning to date, up to 30 qubits. -
Arxiv:2009.07590V2 [Quant-Ph] 9 Dec 2020
Emulating quantum teleportation of a Majorana zero mode qubit He-Liang Huang,1, 2, 3 Marek Naro˙zniak,4, 5 Futian Liang,1, 2, 3 Youwei Zhao,1, 2, 3 Anthony D. Castellano,1, 2, 3 Ming Gong,1, 2, 3 Yulin Wu,1, 2, 3 Shiyu Wang,1, 2, 3 Jin Lin,1, 2, 3 Yu Xu,1, 2, 3 Hui Deng,1, 2, 3 Hao Rong,1, 2, 3 6, 7, 8 1, 2, 3 4, 8, 9, 5 1, 2, 3, 1, 2, 3 Jonathan P. Dowling ∗, Cheng-Zhi Peng, Tim Byrnes, Xiaobo Zhu, † and Jian-Wei Pan 1Hefei National Laboratory for Physical Sciences at the Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei 230026, China 2Shanghai Branch, CAS Center for Excellence in Quantum Information and Quantum Physics, University of Science and Technology of China, Shanghai 201315, China 3Shanghai Research Center for Quantum Sciences, Shanghai 201315, China 4New York University Shanghai, 1555 Century Ave, Pudong, Shanghai 200122, China 5Department of Physics, New York University, New York, NY 10003, USA 6Hearne Institute for Theoretical Physics, Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803, USA 7Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei, Anhui 230026, China 8NYU-ECNU Institute of Physics at NYU Shanghai, 3663 Zhongshan Road North, Shanghai 200062, China 9State Key Laboratory of Precision Spectroscopy, School of Physical and Material Sciences, East China Normal University, Shanghai 200062, China (Dated: December 10, 2020) Topological quantum computation based on anyons is a promising approach to achieve fault- tolerant quantum computing. -
Concentric Transmon Qubit Featuring Fast Tunability and an Anisotropic Magnetic Dipole Moment
Concentric transmon qubit featuring fast tunability and an anisotropic magnetic dipole moment Cite as: Appl. Phys. Lett. 108, 032601 (2016); https://doi.org/10.1063/1.4940230 Submitted: 13 October 2015 . Accepted: 07 January 2016 . Published Online: 21 January 2016 Jochen Braumüller, Martin Sandberg, Michael R. Vissers, Andre Schneider, Steffen Schlör, Lukas Grünhaupt, Hannes Rotzinger, Michael Marthaler, Alexander Lukashenko, Amadeus Dieter, Alexey V. Ustinov, Martin Weides, and David P. Pappas ARTICLES YOU MAY BE INTERESTED IN A quantum engineer's guide to superconducting qubits Applied Physics Reviews 6, 021318 (2019); https://doi.org/10.1063/1.5089550 Planar superconducting resonators with internal quality factors above one million Applied Physics Letters 100, 113510 (2012); https://doi.org/10.1063/1.3693409 An argon ion beam milling process for native AlOx layers enabling coherent superconducting contacts Applied Physics Letters 111, 072601 (2017); https://doi.org/10.1063/1.4990491 Appl. Phys. Lett. 108, 032601 (2016); https://doi.org/10.1063/1.4940230 108, 032601 © 2016 AIP Publishing LLC. APPLIED PHYSICS LETTERS 108, 032601 (2016) Concentric transmon qubit featuring fast tunability and an anisotropic magnetic dipole moment Jochen Braumuller,€ 1,a) Martin Sandberg,2 Michael R. Vissers,2 Andre Schneider,1 Steffen Schlor,€ 1 Lukas Grunhaupt,€ 1 Hannes Rotzinger,1 Michael Marthaler,3 Alexander Lukashenko,1 Amadeus Dieter,1 Alexey V. Ustinov,1,4 Martin Weides,1,5 and David P. Pappas2 1Physikalisches Institut, Karlsruhe Institute of Technology, -
Quantum Technology: Advances and Trends
American Journal of Engineering and Applied Sciences Review Quantum Technology: Advances and Trends 1Lidong Wang and 2Cheryl Ann Alexander 1Institute for Systems Engineering Research, Mississippi State University, Vicksburg, Mississippi, USA 2Institute for IT innovation and Smart Health, Vicksburg, Mississippi, USA Article history Abstract: Quantum science and quantum technology have become Received: 30-03-2020 significant areas that have the potential to bring up revolutions in various Revised: 23-04-2020 branches or applications including aeronautics and astronautics, military Accepted: 13-05-2020 and defense, meteorology, brain science, healthcare, advanced manufacturing, cybersecurity, artificial intelligence, etc. In this study, we Corresponding Author: Cheryl Ann Alexander present the advances and trends of quantum technology. Specifically, the Institute for IT innovation and advances and trends cover quantum computers and Quantum Processing Smart Health, Vicksburg, Units (QPUs), quantum computation and quantum machine learning, Mississippi, USA quantum network, Quantum Key Distribution (QKD), quantum Email: [email protected] teleportation and quantum satellites, quantum measurement and quantum sensing, and post-quantum blockchain and quantum blockchain. Some challenges are also introduced. Keywords: Quantum Computer, Quantum Machine Learning, Quantum Network, Quantum Key Distribution, Quantum Teleportation, Quantum Satellite, Quantum Blockchain Introduction information and the computation that is executed throughout a transaction (Humble, 2018). The Tokyo QKD metropolitan area network was There have been advances in developing quantum established in Japan in 2015 through intercontinental equipment, which has been indicated by the number of cooperation. A 650 km QKD network was established successful QKD demonstrations. However, many problems between Washington and Ohio in the USA in 2016; a still need to be fixed though achievements of QKD have plan of a 10000 km QKD backbone network was been showcased. -
Federated Quantum Machine Learning
entropy Article Federated Quantum Machine Learning Samuel Yen-Chi Chen * and Shinjae Yoo Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973, USA; [email protected] * Correspondence: [email protected] Abstract: Distributed training across several quantum computers could significantly improve the training time and if we could share the learned model, not the data, it could potentially improve the data privacy as the training would happen where the data is located. One of the potential schemes to achieve this property is the federated learning (FL), which consists of several clients or local nodes learning on their own data and a central node to aggregate the models collected from those local nodes. However, to the best of our knowledge, no work has been done in quantum machine learning (QML) in federation setting yet. In this work, we present the federated training on hybrid quantum-classical machine learning models although our framework could be generalized to pure quantum machine learning model. Specifically, we consider the quantum neural network (QNN) coupled with classical pre-trained convolutional model. Our distributed federated learning scheme demonstrated almost the same level of trained model accuracies and yet significantly faster distributed training. It demonstrates a promising future research direction for scaling and privacy aspects. Keywords: quantum machine learning; federated learning; quantum neural networks; variational quantum circuits; privacy-preserving AI Citation: Chen, S.Y.-C.; Yoo, S. 1. Introduction Federated Quantum Machine Recently, advances in machine learning (ML), in particular deep learning (DL), have Learning. Entropy 2021, 23, 460. found significant success in a wide variety of challenging tasks such as computer vi- https://doi.org/10.3390/e23040460 sion [1–3], natural language processing [4], and even playing the game of Go with a superhuman performance [5]. -
Deterministic Quantum Teleportation Received 18 February; Accepted 26 April 2004; Doi:10.1038/Nature02600
letters to nature Mars concretion systems. Although the analogue is not a perfect 24. Hoffman, N. White Mars: A new model for Mars’ surface and atmosphere based on CO2. Icarus 146, match in every geologic parameter, the mere presence of these 326–342 (2000). 25. Ferna´ndez-Remolar, D. et al. The Tinto River, an extreme acidic environment under control of iron, as spherical haematite concretions implies significant pore volumes of an analog of the Terra Meridiani hematite site of Mars. Planet. Space Sci. 53, 239–248 (2004). moving subsurface fluids through porous rock. Haematite is one of the few minerals found on Mars that can be Acknowledgements We thank the donors of the American Chemical Society Petroleum Research linked directly to water-related processes. Utah haematite concre- Fund, and the Bureau of Land Management-Grand Staircase Escalante National Monument for partial support of this research (to M.A.C. and W.T.P.). The work by J.O. was supported by the tions are similar to the Mars concretions with spherical mor- Spanish Ministry for Science and Technology and the Ramon y Cajal Program. The work by G.K. phology, haematite composition, and loose, weathered was supported by funding from the Italian Space Agency. accumulations. The abundance of quartz in the Utah example could pose challenges for finding spectral matches to the concre- Competing interests statement The authors declare that they have no competing financial tions. However, the similarities and differences of the Utah and interests. Mars haematite concretions should stimulate further investigations. Correspondence and requests for materials should be addressed to M.A.C. -
Arxiv:2009.06242V1 [Quant-Ph] 14 Sep 2020 Special Type of Highly Entangled State
Quantum teleportation of physical qubits into logical code-spaces Yi-Han Luo,1, 2, ∗ Ming-Cheng Chen,1, 2, ∗ Manuel Erhard,3, 4 Han-Sen Zhong,1, 2 Dian Wu,1, 2 Hao-Yang Tang,1, 2 Qi Zhao,1, 2 Xi-Lin Wang,1, 2 Keisuke Fujii,5 Li Li,1, 2 Nai-Le Liu,1, 2 Kae Nemoto,6, 7 William J. Munro,6, 7 Chao-Yang Lu,1, 2 Anton Zeilinger,3, 4 and Jian-Wei Pan1, 2 1Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei, 230026, China 2CAS Centre for Excellence in Quantum Information and Quantum Physics, Hefei, 230026, China 3Austrian Academy of Sciences, Institute for Quantum Optics and Quantum Information (IQOQI), Boltzmanngasse 3, A-1090 Vienna, Austria 4Vienna Center for Quantum Science and Technology (VCQ), Faculty of Physics, University of Vienna, A-1090 Vienna, Austria 5Graduate School of Engineering Science Division of Advanced Electronics and Optical Science Quantum Computing Group, 1-3 Machikaneyama, Toyonaka, Osaka, 560-8531 6NTT Basic Research Laboratories & NTT Research Center for Theoretical Quantum Physics, NTT Corporation, 3-1 Morinosato-Wakamiya, Atsugi-shi, Kanagawa, 243-0198, Japan 7National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan Quantum error correction is an essential tool for reliably performing tasks for processing quantum informa- tion on a large scale. However, integration into quantum circuits to achieve these tasks is problematic when one realizes that non-transverse operations, which are essential for universal quantum computation, lead to the spread of errors.