Entanglement Manipulation
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Superdense Teleportation and Quantum Key Distribution for Space Applications
2015 IEEE International Conference on Space Optical Systems and Applications (ICSOS) Superdense Teleportation and Quantum Key Distribution for Space Applications Trent Graham, Christopher Zeitler, Joseph Chapman, Hamid Javadi Paul Kwiat Submillimeter Wave Advanced Technology Group Department of Physics Jet Propulsion Laboratory, University of Illinois at Urbana-Champaign California Institute of Technology Urbana, USA Pasadena, USA tgraham2@illinois. edu Herbert Bernstein Institute for Science & Interdisciplinary Studies & School of Natural Sciences Hampshire College Amherst, USA Abstract—The transfer of quantum information over long for long periods of time (as would be needed for large scale distances has long been a goal of quantum information science quantum repeaters) and cannot be amplified without and is required for many important quantum communication introducing error [ 6 ] and thus can be very difficult to and computing protocols. When these channels are lossy and distribute over large distances using conventional noisy, it is often impossible to directly transmit quantum states communication techniques. Despite current limitations, some between two distant parties. We use a new technique called quantum communication protocols have already been superdense teleportation to communicate quantum demonstrated over long-distances in terrestrial experiments. information deterministically with greatly reduced resources, Notably, quantum teleportation (a remote quantum state simplified measurements, and decreased classical transfer protocol), -
Superdense Coding Ch.4.4 No Cloning Ch.4.2
C/CS/PhysC191 SuperdenseCoding,NoCloning 9/15/07 Fall 2009 Lecture 6 1 Readings Benenti, Casati, and Strini: Superdense Coding Ch.4.4 No Cloning Ch.4.2 2 Superdense Coding Super dense coding is the less popular sibling of teleportation. It can actually be viewed as the process in reverse. The idea is to transmit two classical bits of information by only sending one quantum bit. The process starts out with an EPR pair that is shared between the sender (Alice) and receiver (Bob). ψ = 1 00 + 11 √2 The first qubit is Alice’s, the second is Bob’s. Alice wants to send a two bit message to Bob, e.g., 00, 01, 10, or 11. She first performs a single qubit operation on her qubit which transforms the EPR pair according to which message she wants to send: • for a message 00: Alice applies I (i.e., does nothing) • for a message 01: Alice applies X • for a message 10: Alice applies Z • for a message 11: Alice applies iY (i.e. both X and Z) + + + This transforms the EPR pair φ into the four Bell (EPR) states φ , φ − , ψ , and ψ− , respec- tively: 1 1 0 0 • 00: 1 00 + 11 1 00 + 11 = 1 0 1 √2 −→ √2 √2 0 1 0 0 1 1 • 01: 1 00 + 11 1 10 + 01 = 1 1 0 √2 −→ √2 √2 1 0 1 1 0 0 • 10: 1 00 + 11 1 00 11 = 1 0 1 √2 −→ √2 − √2 0 − 1 − C/CS/Phys C191, Fall 2009, Lecture 6 1 0 0 i 1 • 11: i − 1 00 + 11 1 01 10 = 1 i 0 √2 −→ √2 − √2 1 − 0 The key to super-dense coding is that these four Bell states are orthonormal and are hence distinguishable by a quantum measurement, in this case a two-qubit measurement made by Bob. -
Introduction to Quantum Information Theory
Introduction to Quantum Information Theory Carlos Palazuelos Instituto de Ciencias Matemáticas (ICMAT) [email protected] Madrid, Spain March 2013 Contents Chapter 1. A comment on these notes 3 Chapter 2. Postulates of quantum mechanics 5 1. Postulate I and Postulate II 5 2. Postulate III 7 3. Postulate IV 9 Chapter 3. Some basic results 13 1. No-cloning theorem 13 2. Quantum teleportation 14 3. Superdense coding 15 Chapter 4. The density operators formalism 17 1. Postulates of quantum mechanics: The density operators formalism 17 2. Partial trace 19 3. The Schmidt decomposition and purifications 20 4. Definition of quantum channel and its classical capacity 21 Chapter 5. Quantum nonlocality 25 1. Bell’s result: Correlations in EPR 25 2. Tsirelson’s theorem and Grothendieck’s theorem 27 Chapter 6. Some notions about classical information theory 33 1. Shannon’s noiseless channel coding theorem 33 2. Conditional entropy and Fano’s inequality 35 3. Shannon’s noisy channel coding theorem: Random coding 38 Chapter 7. Quantum Shannon Theory 45 1. Von Neumann entropy 45 2. Schumacher’s compression theorem 48 3. Accessible Information and Holevo bound 55 4. Classical capacity of a quantum channel 58 5. A final comment about the regularization 61 Bibliography 63 1 CHAPTER 1 A comment on these notes These notes were elaborated during the first semester of 2013, while I was preparing a course on quantum information theory as a subject for the PhD programme: Investigación Matemática at Universidad Complutense de Madrid. The aim of this work is to present an accessible introduction to some topics in the field of quantum information theory for those people who do not have any background on the field. -
Efficient and Exact Quantum Compression
Efficient and Exact Quantum Compression a; ;1 b;2 John H. Reif ∗ , Sukhendu Chakraborty aDepartment of Computer Science, Duke University, Durham, NC 27708-0129 bDepartment of Computer Science, Duke University, Durham, NC 27708-0129 Abstract We present a divide and conquer based algorithm for optimal quantum compression / de- compression, using O(n(log4 n) log log n) elementary quantum operations . Our result pro- vides the first quasi-linear time algorithm for asymptotically optimal (in size and fidelity) quantum compression and decompression. We also outline the quantum gate array model to bring about this compression in a quantum computer. Our method uses various classical algorithmic tools to significantly improve the bound from the previous best known bound of O(n3)(R. Cleve, D. P. DiVincenzo, Schumacher's quantum data compression as a quantum computation, Phys. Rev. A, 54, 1996, 2636-2650) for this operation. Key words: Quantum computing, quantum compression, algorithm 1 Introduction 1.1 Quantum Computation Quantum Computation (QC) is a computing model that applies quantum me- chanics to do computation. (Computations and methods not making use of quantum mechanics will be termed classical). A single molecule (or collection of .particles and/or atoms) may have n degrees of freedom known as qubits. Associated with each fixed setting X of the n qubits to boolean values is a basis state denoted a . Quantum mechanics allows for a linear superposition of these basis states to j i ∗ Corresponding author. Email addresses: [email protected] ( John H. Reif), [email protected] (Sukhendu Chakraborty). 1 The work is supported by NSF EMT Grants CCF-0523555 and CCF-0432038. -
Classical Information Capacity of Superdense Coding
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by CERN Document Server Classical information capacity of superdense coding Garry Bowen∗ Department of Physics, Australian National University, Canberra, A.C.T. 0200, Australia. (February 1, 2001) Classical communication through quantum channels may be enhanced by sharing entanglement. Superdense coding allows the encoding, and transmission, of up to two classical bits of information in a single qubit. In this paper, the maximum classical channel capacity for states that are not maximally entangled is derived. Particular schemes are then shown to attain this capacity, firstly for pairs of qubits, and secondly for pairs of qutrits. 03.67.Hk Quantum information exhibits many features which do ters, then the maximal amount of classical information not have analogues in classical information theory [1]. that may be transferred is given by the Kholevo bound For this reason, when a quantum channel is used for com- [10], munication, there exist a number of different capacities for the different types of information transmitted through C = max S p (U k I )ρ (U k I )y k k A B AB A B the channel [2{5]. fU ;pkg ⊗ ⊗ A " k ! Superdense coding (referred to in this paper simply as X dense coding), first proposed by Bennett and Wiesner [6], k k y pkS (U IB )ρAB(U IB ) : (1) is where the transmission of classical information through − A ⊗ A ⊗ k # a quantum channel is enhanced by shared entanglement X between sender and receiver. The classical information This bound has been shown to be asymptotically attain- capacity for a channel where sender and receiver share able by using product state block coding [8,11]. -
Unitary Decomposition Implemented in the Openql Programming Language for Quantum Computation A.M
Unitary Decomposition Implemented in the OpenQL programming language for quantum computation A.M. Krol September 13th 36 Electrical Engineering, Mathematics and Computer Sciences LB 01.010 Snijderszaal Unitary Decomposition Implemented in the OpenQL programming language for quantum computation by A.M. Krol to obtain the degree of Master of Science at the Delft University of Technology, to be defended publicly on Friday September 13, 2019 at 15:00. Student number: 4292391 Project duration: November 20, 2018 – September 13, 2019 Thesis committee: Prof. dr. ir. K. Bertels, TU Delft, supervisor Dr. I. Ashraf, TU Delft Dr. M. Möller, TU Delft Dr. Z. Al-Ars TU Delft An electronic version of this thesis is available at http://repository.tudelft.nl/. Preface In this thesis, I explain my implementation of Unitary Decomposition in OpenQL. Unitary Decomposition is an algorithm for translating a unitary matrix into many small unitary matrices, which correspond to a circuit that can be executed on a quantum computer. It is implemented in the quantum programming framework of the QCA-group at TU Delft: OpenQL, a library for Python and C++. Unitary Decomposition is a necessary part in Quantum Associative Memory, an algorithm used in Quantum Genome Sequenc- ing. The implementation is faster than other known implementations, and generates 3 ∗ 2 ∗ (2 − 1) rotation gates for an n-qubit input gate. This is not the least-known nor the theoretical minimum amount, and there are some optimizations that can still be done to make it closer to these numbers. I would like to thank my supervisor, Prof. Koen Bertels, for the great supervision and insightful feedback. -
General Overview of the Field
Introduction to quantum computing and simulability General overview of the field Daniel J. Brod Leandro Aolita Ernesto Galvão Outline: General overview of the field • What is quantum computing? • A bit of history; • The rules: the postulates of quantum mechanics; • Information-theoretic-flavoured consequences; • Entanglement; • No-cloning; • Teleportation; • Superdense coding; What is quantum computing? • Computing paradigm where information is processed with the rules of quantum mechanics. • Extremely interdisciplinary research area! • Physics, Computer science, Mathematics; • Engineering (the thing looks nice on paper, but building it is hard!); • Chemistry, biology and others (applications); • Promised speedup on certain computational problems; • New insights into foundations of quantum mechanics and computer science. Let’s begin with some history! Timeline of (classical) computing Charles Babbage Ada Lovelace (1791-1871) (1815-1852) Analytical Engine (1837) First computer program (1843) First proposed general purpose Written by Ada Lovelace for the mechanical computer. Not Analytical engine. Computes completed by lack of money ☹️ Bernoulli numbers. Timeline of (classical) computing Alonzo Church Alan Turing (1903-1995) (1912-1954) 1 0 1 0 0 1 1 0 1 Turing Machine (1936) World War II Abstract model for a universal Colossus, Bombe, Z3/Z4 and others; computing device. - Decryption of secret messages; - Ballistics; Timeline of (classical) computing Intel® 4004 (1971) 2.300 transistors. Intel® Core™ (2010) 560.000.000 transistors. Transistor -
The IBM Quantum Computing Platform
The IBM Quantum Computing Platform Martin Koppenh¨ofer https://www.quantumtheory-bruder.physik.unibas.ch/ Online resources https://www.quantumtheory-bruder.physik.unibas.ch/ people/martin-koppenhoefer/ quantum-computing-and-robotic-science-workshop.html installation guide material for this session slides 2 Outline 1 Recap Overview of quantum-computing platforms Bell states 2 Programming the quantum computer with python The qiskit framework Programming session 1 3 Superdense coding Programming session 2 4 Quantum algorithms Deutsch algorithm Programming session 3 3 Recap spins in large molecules + NMR ions in electromagnetic traps neutral atoms in optical lattices optical quantum computing 31P donor atoms in silicon electron spins in semiconductor quantum dots superconducting electrical circuits flux qubit * charge qubit phase qubit * transmon qubit topological qubits * online access 4 Recap Bell states 1 2 3 x H 1 jβ00i = p (j00i + j11i) |βxy > 2 CNOT 1 y jβ01i = p (j01i + j10i) 2 1 jβ10i = p (j00i − j11i) 1 input state: jxyi = j00i 2 2 apply Hadamard gate 1 jβ i = p (j01i − j10i) 1 1 11 H^ = p1 : 2 2 1 −1 p1 (j00i + j10i) General expression: 2 jβ i = p1 (j0yi + (−1)x j1¯yi) 3 apply CNOT gate: xy 2 p1 (j00i + j11i) = jβ i 2 00 5 Recap Bell states 6 Recap Bell states on a real quantum processor 7 Programming the quantum computer with python The qiskit framework 8 Programming the quantum computer with python The qiskit framework Terra Ignis define quantum algorithms characterize quantum by quantum circuits / pulses hardware adapt quantum -
Quantum Computing
John H. Reif, Quantum Computing. Published in book “Bio-inspired and Nanoscale Integrated Computing”, Chapter 3, pp. 67-110 (edited by Mary Mehrnoosh Eshaghian-Wilner), Publisher: Wiley, Hoboken, NJ, USA, (February 2009). Chapter 3: Quantum Computing John H. Reif Department of Computer Science Duke University ‡ 3.0 Summary Quantum Computation (QC) is a type of computation where unitary and measurement operations are executed on linear superpositions of basis states. This paper provides a brief introduction to QC. We begin with a discussion of basic models for QC such as quantum TMs, quantum gates and circuits and related complexity results. We then discuss a number of topics in quan- tum information theory, including bounds for quantum communication and I/O complexity, methods for quantum data compression. and quantum er- ‡Surface address: Department of Computer Science, Duke University, Durham, NC 27708-0129. E-mail: [email protected]. This work has been supported by grants from NSF CCF-0432038 and CCF-0523555. A postscript preprint of this Chapter is available online at URL: http://www.cs.duke.edu/∼reif/paper/qsurvey/qsurvey.chapter.pdf. ror correction (that is, techniques for decreasing decoherence errors in QC), Furthermore, we enumerate a number of methodologies and technologies for doing QC. Finally, we discuss resource bounds for QC including bonds for processing time, energy and volume, particularly emphasizing challenges in determining volume bounds for observation apperatus. 3.1 Introduction 3.1.1 Reversible Computations Reversible Computations are computations where each state transformation is a reversible function, so that any computation can be reversed without loss of information. -
Supercomputer Simulations of Transmon Quantum Computers Quantum Simulations of Transmon Supercomputer
IAS Series IAS Supercomputer simulations of transmon quantum computers quantum simulations of transmon Supercomputer 45 Supercomputer simulations of transmon quantum computers Dennis Willsch IAS Series IAS Series Band / Volume 45 Band / Volume 45 ISBN 978-3-95806-505-5 ISBN 978-3-95806-505-5 Dennis Willsch Schriften des Forschungszentrums Jülich IAS Series Band / Volume 45 Forschungszentrum Jülich GmbH Institute for Advanced Simulation (IAS) Jülich Supercomputing Centre (JSC) Supercomputer simulations of transmon quantum computers Dennis Willsch Schriften des Forschungszentrums Jülich IAS Series Band / Volume 45 ISSN 1868-8489 ISBN 978-3-95806-505-5 Bibliografsche Information der Deutschen Nationalbibliothek. Die Deutsche Nationalbibliothek verzeichnet diese Publikation in der Deutschen Nationalbibliografe; detaillierte Bibliografsche Daten sind im Internet über http://dnb.d-nb.de abrufbar. Herausgeber Forschungszentrum Jülich GmbH und Vertrieb: Zentralbibliothek, Verlag 52425 Jülich Tel.: +49 2461 61-5368 Fax: +49 2461 61-6103 [email protected] www.fz-juelich.de/zb Umschlaggestaltung: Grafsche Medien, Forschungszentrum Jülich GmbH Titelbild: Quantum Flagship/H.Ritsch Druck: Grafsche Medien, Forschungszentrum Jülich GmbH Copyright: Forschungszentrum Jülich 2020 Schriften des Forschungszentrums Jülich IAS Series, Band / Volume 45 D 82 (Diss. RWTH Aachen University, 2020) ISSN 1868-8489 ISBN 978-3-95806-505-5 Vollständig frei verfügbar über das Publikationsportal des Forschungszentrums Jülich (JuSER) unter www.fz-juelich.de/zb/openaccess. This is an Open Access publication distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract We develop a simulator for quantum computers composed of superconducting transmon qubits. -
Entanglement and Superdense Coding with Linear Optics
International Journal of Quantum Information Vol. 9, Nos. 7 & 8 (2011) 1737À1744 #.c World Scientific Publishing Company DOI: 10.1142/S0219749911008222 ENTANGLEMENT AND SUPERDENSE CODING WITH LINEAR OPTICS MLADEN PAVIČIĆ Chair of Physics, Faculty of Civil Engineering, University of Zagreb, Croatia [email protected] Received 16 May 2011 We discuss a scheme for a full superdense coding of entangled photon states employing only linear optics elements. By using the mixed basis consisting of four states that are unambigu- ously distinguishable by a standard and polarizing beam splitters we can deterministically transfer four messages by manipulating just one of the two entangled photons. The sender achieves the determinism of the transfer either by giving up the control over 50% of sent messages (although known to her) or by discarding 33% of incoming photons. Keywords: Superdense coding; quantum communication; Bell states; mixed basis. 1. Introduction Superdense coding (SC)1 — sending up to two bits of information, i.e. four messages, by manipulating just one of two entangled qubits (two-state quantum systems) — is considered to be a protocol that launched the field of quantum communication.2 Apart from showing how different quantum coding of information is from the classical one — which can encode only two messages in a two-state system — the protocol has also shown how important entanglement of qubits is for their manipulation. Such an entanglement has proven to be a genuine quantum effect that cannot be achieved with the help of two classical bit carriers because we cannot entangle classical systems. To use this advantage of quantum information transfer, it is very important to keep the trade-off of the increased transfer capacity balanced with the technology of implementing the protocol. -
Quantum Information Processing with Superconducting Circuits: a Review
Quantum Information Processing with Superconducting Circuits: a Review G. Wendin Department of Microtechnology and Nanoscience - MC2, Chalmers University of Technology, SE-41296 Gothenburg, Sweden Abstract. During the last ten years, superconducting circuits have passed from being interesting physical devices to becoming contenders for near-future useful and scalable quantum information processing (QIP). Advanced quantum simulation experiments have been shown with up to nine qubits, while a demonstration of Quantum Supremacy with fifty qubits is anticipated in just a few years. Quantum Supremacy means that the quantum system can no longer be simulated by the most powerful classical supercomputers. Integrated classical-quantum computing systems are already emerging that can be used for software development and experimentation, even via web interfaces. Therefore, the time is ripe for describing some of the recent development of super- conducting devices, systems and applications. As such, the discussion of superconduct- ing qubits and circuits is limited to devices that are proven useful for current or near future applications. Consequently, the centre of interest is the practical applications of QIP, such as computation and simulation in Physics and Chemistry. Keywords: superconducting circuits, microwave resonators, Josephson junctions, qubits, quantum computing, simulation, quantum control, quantum error correction, superposition, entanglement arXiv:1610.02208v2 [quant-ph] 8 Oct 2017 Contents 1 Introduction 6 2 Easy and hard problems 8 2.1 Computational complexity . .9 2.2 Hard problems . .9 2.3 Quantum speedup . 10 2.4 Quantum Supremacy . 11 3 Superconducting circuits and systems 12 3.1 The DiVincenzo criteria (DV1-DV7) . 12 3.2 Josephson quantum circuits . 12 3.3 Qubits (DV1) .