检索结果-内蒙古大学图书馆

Enhancing qubit readout with Bayesian Learning

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Cosco, F. Gullo, N. Lo Quantum Algorithms and Software VTT Technical Research Centre of Finland Ltd Tietotie 3 Espoo02150 Finland Dipartimento di Fisica Università della Calabria Arcavacata CS Rende87036 Italy INFN Sezione LNF Gruppo Collegato di Cosenza Italy

We introduce an efficient and accurate readout measurement scheme for single and multi-qubit states. Our method uses Bayesian inference to build an assignment probability distribution for each qubit state based on a reference characterization of the detector response functions. This allows us to account for system imperfections and thermal noise within the assignment of the computational basis. We benchmark our protocol on a quantum device with five superconducting qubits, testing initial state preparation for single and two-qubit states and an application of the Bernstein-Vazirani algorithm executed on five qubits. Our method shows a substantial reduction of the readout error and promises advantages for near-term and future quantum devices. Copyright © 2023, The Authors. All rights reserved.

关键词： Probability distributions

Random access test as an identifier of nonclassicality*

学校读者我要写书评

暂无评论

JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL 2022年第17期55卷 174003-174003页

作者： Heinosaari, Teiko Leppajarvi, Leevi VTT Tech Res Ctr Finland Ltd Quantum Algorithms & Software Espoo Finland Univ Turku Dept Phys & Astron Turku Finland Slovak Acad Sci RCQI Inst Phys Dubravska Cesta 9 Bratislava 84511 Slovakia

Random access codes (RACs) are an intriguing class of communication tasks that reveal an operational and quantitative difference between classical and quantum information processing. We formulate a natural generalization of RACs and call them random access tests (RATs), defined for any finite collection of measurements in an arbitrary finite dimensional general probabilistic theory. These tests can be used to examine collective properties of collections of measurements. We show that the violation of a classical bound in a RAT is a signature of either measurement incompatibility or super information storability. The polygon theories are exhaustively analysed and a critical difference between even and odd polygon theories is revealed.

关键词： random access code quantum measurement incompatibility joint measurement general probabilistic theory

Bayesian mitigation of measurement errors in multi-qubit experiments

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Cosco, F. Plastina, F. Gullo, N. Lo Quantum algorithms and software VTT Technical Research Centre of Finland Ltd. Tietotie 3 Espoo02150 Finland Dipartimento di Fisica Università della Calabria CS Arcavacata di Rende87036 Italy INFN Sezione LNF Gruppo Collegato di Cosenza United States ICAR Consiglio Nazionale delle Ricerche Italy

We introduce an implementation of Bayesian measurement error mitigation tailored for multiqubit experiments on near-term quantum devices. Our approach leverages complete information from the readout signal, which is available before any binary state assignment of the qubits. We provide a detailed algorithm workflow, from the calibration of detector response functions to the post-processing of measurement outcomes, offering a computationally efficient solution suitable for the output size typical of current quantum computing devices and quantum algorithms. We benchmark our protocol on actual quantum computers with superconducting qubits, where the readout signal encodes the measurement information in the IQ clouds before qubit state assignment. Finally, we compare the performance of our algorithm against other measurement error mitigation methods, such as iterative Bayesian unfolding and noise matrix inversion. Copyright © 2024, The Authors. All rights reserved.

关键词： Qubits

Order preserving maps on quantum measurements

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Heinosaari, Teiko Jivulescu, Maria Anastasia Nechita, Ion Quantum Algorithms and Software VTT Technical Research Centre of Finland Ltd Finland Department of Physics and Astronomy University of Turku Finland Department of Mathematics Politehnica University of Timişoara Romania Laboratoire de Physique Théorique Université de Toulouse CNRS UPS France

We study the partially ordered set of equivalence classes of quantum measurements endowed with the post-processing partial order. The post-processing order is fundamental as it enables to compare measurements by their intrinsic noise and it gives grounds to define the important concept of quantum incompatibility. Our approach is based on mapping this set into a simpler partially ordered set using an order preserving map and investigating the resulting image. The aim is to ignore unnecessary details while keeping the essential structure, thereby simplifying e.g. detection of incompatibility. One possible choice is the map based on Fisher information introduced by Huangjun Zhu, known to be an order morphism taking values in the cone of positive semidefinite matrices. We explore the properties of that construction and improve Zhu's incompatibility criterion by adding a constraint depending on the number of measurement outcomes. We generalize this type of construction to other ordered vector spaces and we show that this map is optimal among all quadratic maps. © 2022, CC BY-NC-ND.

关键词： Equivalence classes

A hybrid classical-quantum approach to speed-up Q-learning

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Sannia, A. Giordano, A. Lo Gullo, N. Mastroianni, C. Plastina, Francesco 87036 Italy ICAR-CNR Rende87036 Italy Quantum algorithms and software VTT Technical Research Centre of Finland Ltd Finland CSC-IT Center for Science P.O. Box 405 EspooFIN-02101 Finland INFN gruppo collegato di Cosenza

We introduce a classical-quantum hybrid approach to computation, allowing for a quadratic performance improvement in the decision process of a learning agent. In particular, a quantum routine is described, which encodes on a quantum register the probability distributions that drive action choices in a reinforcement learning set-up. This routine can be employed by itself in several other contexts where decisions are driven by probabilities. After introducing the algorithm and formally evaluating its performance, in terms of computational complexity and maximum approximation error, we discuss in detail how to exploit it in the Q-learning context. © 2022, CC BY.

关键词： Reinforcement learning

Dispensing of quantum information beyond no-broadcasting theorem - is it possible to broadcast anything genuinely quantum?

学校读者我要写书评

暂无评论

arXiv 2022年

作者： Heinosaari, Teiko Jenčová, Anna Plávala, Martin Quantum Algorithms and Software VTT Technical Research Centre of Finland Ltd Finland Department of Physics and Astronomy University of Turku Turku20014 Finland Mathematical Institute Slovak Academy of Sciences Bratislava Slovakia Naturwissenschaftlich-Technische Fakultät Universität Siegen Siegen57068 Germany

No-broadcasting theorem is one of the most fundamental results in quantum information theory;it guarantees that the simplest attacks on any quantum protocol, based on eavesdropping and copying of quantum information, are impossible. Due to the fundamental importance of the no-broadcasting theorem, it is essential to understand the exact boundaries of this limitation. We generalize the standard definition of broadcasting by restricting the set of states which we want to broadcast and restricting the sets of measurements which we use to test the broadcasting. We show that in some of the investigated cases broadcasting is equivalent to commutativity, while in other cases commutativity is not necessary. Copyright © 2022, The Authors. All rights reserved.

关键词： Broadcasting

A hybrid classical-quantum approach to speed-up Q-learning

学校读者我要写书评

暂无评论

SCIENTIFIC REPORTS 2023年第1期13卷 1-10页

作者： Sannia, A. Giordano, A. Lo Gullo, N. Mastroianni, C. Plastina, F. Univ Calabria Dipartimento Fis I-87036 Arcavacata Di Rende CS Italy UIB CSIC Inst Cross Disciplinary Phys & Complex Syst IFISC Campus Univ Illes Balears Palma De Mallorca 07122 Spain ICAR CNR I-87036 Arcavacata Di Rende Italy INFN Grp Collegato Cosenza Cosenza Italy VTT Tech Res Ctr Finland Ltd Quantum Algorithms & Software Espoo Finland

We introduce a classical-quantum hybrid approach to computation, allowing for a quadratic performance improvement in the decision process of a learning agent. Using the paradigm of quantum accelerators, we introduce a routine that runs on a quantum computer, which allows for the encoding of probability distributions. This quantum routine is then employed, in a reinforcement learning set-up, to encode the distributions that drive action choices. Our routine is well-suited in the case of a large, although finite, number of actions and can be employed in any scenario where a probability distribution with a large support is needed. We describe the routine and assess its performance in terms of computational complexity, needed quantum resource, and accuracy. Finally, we design an algorithm showing how to exploit it in the context of Q-learning.

关键词：

Testing incompatibility of quantum devices with few states

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Heinosaari, Teiko Miyadera, Takayuki Takakura, Ryo Department of Physics and Astronomy University of Turku Finland Quantum Algorithms and Software VTT Technical Research Centre of Finland Ltd Finland Department of Nuclear Engineering Kyoto University Kyoto6158540 Japan

When observations must come from incompatible devices and cannot be produced by compatible devices? This question motivates two integer valued quantifications of incompatibility, called incompatibility dimension and compatibility dimension. The first one quantifies how many states are minimally needed to detect incompatibility if the test states are chosen carefully, whereas the second one quantifies how many states one may have to use if they are randomly chosen. With concrete examples we show that these quantities have unexpected behaviour with respect to noise. Copyright © 2021, The Authors. All rights reserved.

关键词：

Challenges and opportunities in quantum optimization

学校读者我要写书评

暂无评论

NATURE REVIEWS PHYSICS

NATURE REVIEWS PHYSICS 2024年第12期6卷 718-735页

作者： Abbas, Amira Ambainis, Andris Augustino, Brandon Baertschi, Andreas Buhrman, Harry Coffrin, Carleton Cortiana, Giorgio Dunjko, Vedran Egger, Daniel J. Elmegreen, Bruce G. Franco, Nicola Fratini, Filippo Fuller, Bryce Gacon, Julien Gonciulea, Constantin Gribling, Sander Gupta, Swati Hadfield, Stuart Heese, Raoul Kircher, Gerhard Kleinert, Thomas Koch, Thorsten Korpas, Georgios Lenk, Steve Marecek, Jakub Markov, Vanio Mazzola, Guglielmo Mensa, Stefano Mohseni, Naeimeh Nannicini, Giacomo O'Meara, Corey Tapia, Elena Pena Pokutta, Sebastian Proissl, Manuel Rebentrost, Patrick Sahin, Emre Symons, Benjamin C. B. Tornow, Sabine Valls, Victor Woerner, Stefan Wolf-Bauwens, Mira L. Yard, Jon Yarkoni, Sheir Zechiel, Dirk Zhuk, Sergiy Zoufal, Christa Univ Amsterdam Inst Phys Amsterdam Netherlands QuSoft Amsterdam Netherlands Univ Latvia Fac Comp Riga Latvia MIT Sloan Sch Management Cambridge MA USA Los Alamos Natl Lab CCS 3 Informat Sci Los Alamos NM USA Univ Amsterdam Ctr Wiskunde & Informat CWI Amsterdam Netherlands Los Alamos Natl Lab Adv Network Sci Initiat Los Alamos NM USA EON Digital Technol GmbH Hannover Germany Leiden Univ Appl Quantum Algorithms Initiat Leiden Netherlands IBM Res Europe Zurich IBM Quantum Ruschlikon Switzerland IBM TJ Watson Res Ctr IBM Res Yorktown Hts NY USA Fraunhofer Inst Cognit Syst IKS Quantum Enhanced AI Dept D-80686 Munich Germany Erste Grp Bank AG Obere Donaustr 17-19 A-1020 Vienna Austria IBM TJ Watson Res Ctr IBM Quantum Yorktown Hts NY USA Ecole Polytech Fed Lausanne EPFL Inst Phys Lausanne Switzerland Wells Fargo Adv Technol New York NY 10036 USA Tilburg Univ Dept Econometr & Operat Res Tilburg Netherlands NASA Quantum Artificial Intelligence Lab QuAIL Ames Res Ctr Moffett Field CA USA Univ Space Res Assoc USRA Res Inst Adv Comp Sci RIACS Mountain View CA USA Fraunhofer ITWM Optimizat Dept Kaiserslautern Germany Quantagonia GmbH Bad Homburg Germany Zuse Inst Berlin Dept Appl Algorithm Intelligence Methods Berlin Germany Tech Univ Berlin Chair Software & Algorithms Discrete Optimizat Berlin Germany HSBC Holdings HSBC Lab Innovat & Ventures Singapore England Czech Tech Univ Dept Comp Sci & Engn CR-16635 Prague Czech Republic Athena Res & Innovat Ctr Archimedes Res Unit AI Data Sci & Algorithms Maroussi 15125 Greece Fraunhofer Inst Optron Syst Technol & Image Explo Dept Energy Syst Fraunhofer IOSB Ilmenau Germany German Aerosp Ctr DLR Inst Quantum Technol Ulm Germany Univ Zurich Inst Computat Sci Zurich Switzerland UKRI STFC Hartree Ctr Daresbury England Univ Southern Calif Dept Ind & Syst Engn Los Angeles CA USA Zuse Inst Berlin Berlin Germany Tech Univ Berlin Inst Math Berlin Germany Natl Univ Singapore Ctr Quantum Technol

quantum computers have demonstrable ability to solve problems at a scale beyond brute-force classical simulation. Interest in quantum algorithms has developed in many areas, particularly in relation to mathematical optimization - a broad field with links to computer science and physics. In this Review, we aim to give an overview of quantum optimization. Provably exact, provably approximate and heuristic settings are first explained using computational complexity theory, and we highlight where quantum advantage is possible in each context. Then, we outline the core building blocks for quantum optimization algorithms, define prominent problem classes and identify key open questions that should be addressed to advance the field. We underscore the importance of benchmarking by proposing clear metrics alongside suitable optimization problems, for appropriate comparisons with classical optimization techniques, and discuss next steps to accelerate progress towards quantum advantage in optimization. This Review discusses quantum optimization, focusing on the potential of exact, approximate and heuristic methods, core algorithmic building blocks, problem classes and benchmarking metrics. The challenges for quantum optimization are considered, and next steps are suggested for progress towards achieving quantum advantage. quantum computing is advancing rapidly, and quantum optimization is a promising area of *** optimization algorithms - whether provably exact, provably approximate or heuristic - offer opportunities to demonstrate quantum *** benchmarking is crucial to guide research, track progress and further advance understanding of quantum *** research and empirical research using real hardware can complement each other, in the move towards demonstrating quantum advantage.

关键词： quantum computers