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Strong supremacy of quantum systems as communication resource

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arXiv 2017年

作者： Quadeer, Maria Banik, Manik Ambainis, Andris Rai, Ashutosh Optics and Quantum Information Group Institute of Mathematical Sciences HBNI C.I.T Campus Tharamani Chennai600 113 India Center for Quantum Computer Science Faculty of Computing University of Latvia Raina bulv. 19 Riga LV-1586 Latvia

We investigate the task of d-level random access codes (d-RACs) and consider the possibility of encoding classical strings of d-level symbols (dits) into a quantum system of dimension d0 strictly less than d. We show that the average success probability of recovering one (randomly chosen) dit from the encoded string can be larger than that obtained in the best classical protocol for the task. Our result is intriguing as we know from Holevo's theorem (and more recently from Frenkel-Weiner's result [Commun. Math. Phys. 340, 563 (2015)]) that there exist communication scenarios wherein quantum resources prove to be of no advantage over classical resources. A distinguishing feature of our protocol is that it establishes a stronger quantum advantage in contrast to the existing quantum d-RACs where d-level quantum systems are shown to be advantageous over their classical d-level counterparts. Copyright © 2017, The Authors. All rights reserved.

关键词： quantum optics

Anomalous negative magnetoresistance in quantum-dot Josephson junctions with Kondo correlations

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arXiv 2018年

作者： Deng, M.-T. Yu, C.-L. Huang, G.-Y. López, R. Caroff, P. Ghalamestani, S. Platero, G. Xu, H.Q. Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology NUDT Changsha410073 China NanoLund and Division of Solid State Physics Lund University LundS-22100 Sweden Hefei National Laboratory Hefei230088 China China Greatwall Quantum Laboratory Changsha410006 China Institut de Fisica Interdisciplinària i de Sistemes Complexos IFISC Palma de MallorcaE-07122 Spain Instituto de Ciencia de Materiales de Madrid Madrid28049 Spain NanoLund and Division of Solid State Physics Lund University Box 118 LundS-221 00 Sweden Beijing Key Laboratory of Quantum Devices Key Laboratory for the Physics and Chemistry of Nanodevices Department of Electronics Peking University Beijing100871 China Beijing Academy of Quantum Information Sciences Beijing100193 China

The interplay between superconductivity and the Kondo effect has stimulated significant interest in condensed matter physics. They compete when their critical temperatures are close and can give rise to a quantum phase transition that can mimic Majorana zero modes. Here, we have fabricated and measured Al-InSb nanowire quantum dot-Al devices. In the Kondo regime, a supercurrentinduced zero-bias conductance peak emerges. This zero-bias peak shows an anomalous negative magnetoresistance (NMR) at weak magnetic fields. We attribute this anomalous NMR to quasiparticle trapping at vortices in the superconductor leads as a weak magnetic field is applied. The trapping effect lowers the quasiparticle-caused dissipation and thus enhances the Josephson current. This work connects the vortex physics and the supercurrent tunneling in Kondo regimes and can help further understand the physics of Josephson quantum dot system. Copyright © 2018, The Authors. All rights reserved.

关键词： Vortex flow

The quantum entanglement of measurement

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The quantum entanglement of measurement

Frontiers in Optics, FiO 2017

作者： Yokoyama, Shota Pozza, Nicola Dalla Serikawa, Takahiro Kuntz, Katanya B. Wheatley, Trevor A. Dong, Daoyi Huntington, Elanor H. Yonezawa, Hidehiro School of Engineering and Information Technology The University of New South Wales CanberraACT2600 Australia Centre for Quantum Computation and Communication Technology Australian Research Council Australia Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Research School of Engineering College of Engineering and Computer Science Australian National University CanberraACT2600 Australia

We demonstrate two-mode detector tomography on a detector consisting of two superconducting nanowire single photon detectors. The entangling properties of the detector is verified through a new entanglement measure of... 详细信息

ISBN: (纸本)9781943580330

关键词： quantum entanglement

IDTxl: The information dynamics toolkit xl: A python package for the efficient analysis of multivariate information dynamics in networks

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arXiv 2018年

作者： Wollstadt, Patricia Lizier, Joseph T. Vicente, Raul Finn, Conor Martinez-Zarzuela, Mario Mediano, Pedro Novelli, Leonardo Wibral, Michael MEG Unit Brain Imaging Center Goethe-University Frankfurt Fankfurt am Main Germany Centre for Complex Systems Faculty of Engineering and IT University of Sydney SydneyNSW Australia Computational Neuroscience Lab Institute of Computer Science Tartu Estonia Data61 CSIRO EppingNSW Australia Communications and Signal Theory and Telematics Engineering University of Valladolid Valladolid Spain Computational Neurodynamics Group Department of Computing Imperial College London London United Kingdom Max Planck Institute for Dynamics and Self-Organization Göttingen Germany Campus Institute for Dynamics of Biological Networks Georg-August Universität Göttingen Germany

We present IDTxl (the Information Dynamics Toolkit xl), a new open source Python toolbox for effective network inference from multivariate time series using information theory, available from GitHub (https://***/pwollstadt/IDTxl). Information theory (Cover & Thomas, 2006;MacKay, 2003;Shannon, 1948) is the mathematical theory of information and its transmission over communication channels. Information theory provides quantitative measures of the information content of a single random variable (entropy) and of the information shared between two variables (mutual information). The defined measures build on probability theory and solely depend on the probability distributions of the variables involved. As a consequence, the dependence between two variables can be quantified as the information shared between them, without the need to explicitly model a specific type of dependence. Hence, mutual information is a model-free measure of dependence, which makes it a popular choice for the analysis of systems other than communication channels. Transfer entropy (TE) (Schreiber, 2000) is an extension of mutual information that measures the directed information transfer between time series of a source and a target variable. TE has become popular in many scientific disciplines to infer dependencies and whole networks from data. Notable application domains include neuroscience (Wibral, Vicente, & Lindner, 2014) and dynamical systems analysis (Lizier, Prokopenko, & Zomaya, 2014) (see Bossomaier, Barnett, Harré, & Lizier (2016) for an introduction to TE and a comprehensive discussion of its application). In the majority of the applications, TE is used in a bivariate fashion, where information transfer is quantified between all sourcetarget pairs. In a multivariate setting, however, such a bivariate analysis may infer spurious or redundant interactions, where multiple sources provide the same information about the target. Conversely, bivariate analysis may also miss synergistic

关键词： High level languages

A logician’s view of graph polynomials

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arXiv 2017年

作者： Makowsky, J.A. Ravve, E.V. Kotek, T. Institut für Informationssysteme Technische Universität Wien Vienna Austria Department of Computer Science Technion–IIT Haifa Israel Department of Software Engineering ORT-Braude College Karmiel Israel Simons Institute for the Theory of Computing United States Faculty of Computer Science Technion–IIT Haifa Israel

Graph polynomials are graph parameters invariant under graph isomorphisms which take values in a polynomial ring with a fixed finite number of indeterminates. We study graph polynomials from a model theoretic point of view. In this paper we distinguish between the graph theoretic (semantic) and the algebraic (syntactic) meaning of graph polynomials. Graph polynomials appear in the literature either as generating functions, as generalized chromatic polynomials, or as polynomials derived via determinants of adjacency or Laplacian matrices. We show that these forms are mutually incomparable, and propose a unified framework based on definability in Second Order Logic. We show that this comprises virtually all examples of graph polynomials with a fixed finite set of indeterminates. Finally we show that the location of zeros and stability of graph polynomials is not a semantic property. The paper emphasizes a model theoretic view. It gives a unified exposition of classical results in algebraic combinatorics together with new and some of our previously obtained results scattered in the graph theoretic literature. Copyright © 2017, The Authors. All rights reserved.

关键词： Graph theory

Model checking process scheduling over multi-core computer system with MSVL 5th

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Model checking process scheduling over multi-core computer s...

5th International Workshop on Structured Object-Oriented Formal Language and Method, SOFL+MSVL 2015

作者： Shu, Xinfeng Duan, Zhenhua School of Computer Science Xi’an University of Posts and Communications Xi’an710061 China Institute of Computing Theory and Technology Xidian University Xi’an710071 China

ISBN: (纸本)9783319312194

To solve the problem that software testing cannot meet the verification needs of process scheduling over multi-core computer system, a model checking approach with MSVL is adapted to verify the correctness of process scheduling. Firstly, the grammar of MSVL is briefly introduced;further, a general model supporting the most commonly used scheduling algorithms for multi-core computer is formalized by MSVL program;finally, as a case study, the safeness of the processes scheduler with the earliest deadline first(EDF) scheduling algorithm over a 2-core CPU is verified with MSV toolkit, which indicates the proposed approach can effectively solve the verification problems of process scheduling over multi-core CPU. © Springer International Publishing Switzerland 2016.

关键词： Model checking

On the CNOT-complexity of CNOT-phase circuits

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arXiv 2017年

作者： Amy, Matthew Azimzadeh, Parsiad Mosca, Michele Institute for Quantum Computing University of Waterloo Canada David R. Cheriton School of Computer Science University of Waterloo Canada Department of Combinatorics & Optimization University of Waterloo Canada Perimeter Institute for Theoretical Physics Waterloo Canada Canadian Institute for Advanced Research Toronto Canada

We study the problem of CNOT-optimal quantum circuit synthesis over gate sets consisting of CNOT and Z-basis rotations of arbitrary angles. We show that the circuit-polynomial correspondence relates such circuits to Fourier expansions of pseudo-Boolean functions, and that for certain classes of functions this expansion uniquely determines the minimum CNOT cost of an implementation. As a corollary we prove that CNOT minimization over CNOT and phase gates is at least as hard as synthesizing a CNOT-optimal circuit computing a set of parities of its inputs. We then show that this problem is NP-complete for two restricted cases where all CNOT gates are required to have the same target, and where the circuit inputs are encoded in a larger state space. The latter case has applications to CNOT optimization over more general Clifford+T circuits. We further present an efficient heuristic algorithm for synthesizing circuits over CNOT and Z-basis rotations with small CNOT cost. Our experiments show a 23% reduction of CNOT gates on average across a suite of Clifford+T benchmark circuits, with a maximum reduction of 43%. Copyright © 2017, The Authors. All rights reserved.

关键词： Timing circuits

The Liver Tumor Segmentation Benchmark (LiTS)

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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image computing and computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

Optimizing Adiabatic quantum Program Compilation using a Graph-Theoretic Framework

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arXiv 2017年

作者： Goodrich, Timothy D. Sullivan, Blair D. Humble, Travis S. Department of Computer Science North Carolina State University RaleighNC27606 United States Quantum Computing Institute Oak Ridge National Laboratory 1 Bethel Valley Road Oak RidgeTN37831 United States

Adiabatic quantum computing has evolved in recent years from a theoretical field into an immensely practical area, a change partially sparked by D-Wave System’s quantum annealing hardware. These multimillion-dollar quantum annealers offer the potential to solve optimization problems millions of times faster than classical heuristics, prompting researchers at Google, NASA and Lockheed Martin to study how these computers can be applied to complex real-world problems such as NASA rover missions. Unfortunately, compiling (embedding) an optimization problem into the annealing hardware is itself a difficult optimization problem and a major bottleneck currently preventing widespread adoption. Additionally, while finding a single embedding is difficult, no generalized method is known for tuning embeddings to use minimal hardware resources. To address these barriers, we introduce a graph-theoretic framework for developing structured embedding algorithms. Using this framework, we introduce a biclique virtual hardware layer to provide a simplified interface to the physical hardware. Additionally, we exploit bipartite structure in quantum programs using odd cycle transversal (OCT) decompositions. By coupling an OCT-based embedding algorithm with new, generalized reduction methods, we develop a new baseline for embedding a wide range of optimization problems into fault-free D-Wave annealing hardware. To encourage the reuse and extension of these techniques, we provide an implementation of the framework and embedding algorithms. Copyright © 2017, The Authors. All rights reserved.

关键词： NASA