Quantum Information Technology Based on Single Electron Dynamics
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What Is Quantum Information?
What Is Quantum Information? Robert B. Griffiths Carnegie-Mellon University Pittsburgh, Pennsylvania Research supported by the National Science Foundation References (work by R. B. Griffiths) • \Nature and location of quantum information." Ph◦ys. Rev. A 66 (2002) 012311; quant-ph/0203058 \Channel kets, entangled states, and the location of quan◦ tum information," Phys. Rev. A 71 (2005) 042337; quant-ph/0409106 Consistent Quantum Theory (Cambridge 2002) http://quan◦ tum.phys.cmu.edu/ What Is Quantum Information? 01. 100.01.tex Introduction What is quantum information? Precede by: • What is information? ◦ What is classical information theory? ◦ What is information? Example, newspaper • Symbolic representation of some situation ◦ Symbols in newspaper correlated with situation ◦ Information is about that situation ◦ What Is Quantum Information? 04. 100.04.tex Classical Information Theory Shannon: • \Mathematical Theory of Communication" (1948) ◦ One of major scientific developments of 20th century ◦ Proposed quantitative measure of information ◦ Information entropy • H(X) = p log p − X i i i Logarithmic measure of missing information ◦ Probabilistic model: pi are probabilities ◦ Applies to classical (macroscopic)f g signals ◦ Coding theorem: Bound on rate of transmission of information• through noisy channel What Is Quantum Information? 05. 100.05.tex Quantum Information Theory (QIT) Goal of QIT: \Quantize Shannon" • Extend Shannon's ideas to domain where quantum effects◦ are important Find quantum counterpart of H(X) ◦ We live in a quantum world, so • QIT should be the fundamental info theory ◦ Classical theory should emerge from QIT ◦ Analogy: relativity theory Newton for v c ◦ ! What Is Quantum Information? 06. 100.06.tex QIT: Current Status Enormous number of published papers • Does activity = understanding? ◦ Some topics of current interest: • Entanglement ◦ Quantum channels ◦ Error correction ◦ Quantum computation ◦ Decoherence ◦ Unifying principles have yet to emerge • At least, they are not yet widely recognized ◦ What Is Quantum Information? 07. -
Key Concepts for Future QIS Learners Workshop Output Published Online May 13, 2020
Key Concepts for Future QIS Learners Workshop output published online May 13, 2020 Background and Overview On behalf of the Interagency Working Group on Workforce, Industry and Infrastructure, under the NSTC Subcommittee on Quantum Information Science (QIS), the National Science Foundation invited 25 researchers and educators to come together to deliberate on defining a core set of key concepts for future QIS learners that could provide a starting point for further curricular and educator development activities. The deliberative group included university and industry researchers, secondary school and college educators, and representatives from educational and professional organizations. The workshop participants focused on identifying concepts that could, with additional supporting resources, help prepare secondary school students to engage with QIS and provide possible pathways for broader public engagement. This workshop report identifies a set of nine Key Concepts. Each Concept is introduced with a concise overall statement, followed by a few important fundamentals. Connections to current and future technologies are included, providing relevance and context. The first Key Concept defines the field as a whole. Concepts 2-6 introduce ideas that are necessary for building an understanding of quantum information science and its applications. Concepts 7-9 provide short explanations of critical areas of study within QIS: quantum computing, quantum communication and quantum sensing. The Key Concepts are not intended to be an introductory guide to quantum information science, but rather provide a framework for future expansion and adaptation for students at different levels in computer science, mathematics, physics, and chemistry courses. As such, it is expected that educators and other community stakeholders may not yet have a working knowledge of content covered in the Key Concepts. -
Free-Electron Qubits
Free-Electron Qubits Ori Reinhardt†, Chen Mechel†, Morgan Lynch, and Ido Kaminer Department of Electrical Engineering and Solid State Institute, Technion - Israel Institute of Technology, 32000 Haifa, Israel † equal contributors Free-electron interactions with laser-driven nanophotonic nearfields can quantize the electrons’ energy spectrum and provide control over this quantized degree of freedom. We propose to use such interactions to promote free electrons as carriers of quantum information and find how to create a qubit on a free electron. We find how to implement the qubit’s non-commutative spin-algebra, then control and measure the qubit state with a universal set of 1-qubit gates. These gates are within the current capabilities of femtosecond-pulsed laser-driven transmission electron microscopy. Pulsed laser driving promise configurability by the laser intensity, polarizability, pulse duration, and arrival times. Most platforms for quantum computation today rely on light-matter interactions of bound electrons such as in ion traps [1], superconducting circuits [2], and electron spin systems [3,4]. These form a natural choice for implementing 2-level systems with spin algebra. Instead of using bound electrons for quantum information processing, in this letter we propose using free electrons and manipulating them with femtosecond laser pulses in optical frequencies. Compared to bound electrons, free electron systems enable accessing high energy scales and short time scales. Moreover, they possess quantized degrees of freedom that can take unbounded values, such as orbital angular momentum (OAM), which has also been proposed for information encoding [5-10]. Analogously, photons also have the capability to encode information in their OAM [11,12]. -
Quantum Information Science, NIST, and Future Technological Implications National Institute of Standards & Technology Http
Quantum Information Science, NIST, and Future Technological Implications Carl J. Williams, Chief Atomic Physics Division National Institute of Standards & Technology http://qubit.nist.gov NIST – Atomic Physics Division Carl J. Williams, Chief What is Quantum Information? “Quantum information is a radical departure in information technology, more fundamentally different from current technology than the digital computer is from the abacus.” W. D. Phillips, 1997 Nobel Prize Winner in Physics A convergence of two of the 20th Century’s great revolutions A new science! Quantum Mechanics Information Science (i.e. computer science, (i.e. atoms, photons, JJ’s, communications, physics of computation) cryptology) The second quantum revolution NIST – Atomic Physics Division Carl J. Williams, Chief Second Quantum Revolution We are witnessing the second quantum revolution • First quantum revolution (1920’s - 1980’s) – Described how nature works at the quantum level – Weirdness of QM discovered and debated – Wave-particle duality -> Wavefunctions – Spooky action at a distance -> Entanglement – Technology uses semiclassical properties – quantization & wave properties • Second quantum revolution (starts ~1980’s - ) – Exploits how nature works at the quantum level – Interactions are how Nature computes! – Weirdness of QM exploited – Information storage capacity of superposed wavefunctions – Information transmittal accomplished by entanglement, teleportation – Information exchange accomplished by interactions – Technology uses the weird properties of quantum mechanics NIST – Atomic Physics Division Carl J. Williams, Chief Classical Bits vs. Quantum Bits • Classical Bits: two-state systems Classical bits: 0 (off) or 1 (on) (switch) • Quantum Bits are also two-level(state) systems ⎜↑〉 ⎜1〉 Atom ⎜0〉 ⎜↓〉 Internal State Motional State Ö But: Quantum Superpositions are possible Ψ= α|↓〉 + β|↑〉 = α|0〉 + β|1〉 NIST – Atomic Physics Division Carl J. -
Quantum Computation and Complexity Theory
Quantum computation and complexity theory Course given at the Institut fÈurInformationssysteme, Abteilung fÈurDatenbanken und Expertensysteme, University of Technology Vienna, Wintersemester 1994/95 K. Svozil Institut fÈur Theoretische Physik University of Technology Vienna Wiedner Hauptstraûe 8-10/136 A-1040 Vienna, Austria e-mail: [email protected] December 5, 1994 qct.tex Abstract The Hilbert space formalism of quantum mechanics is reviewed with emphasis on applicationsto quantum computing. Standardinterferomeric techniques are used to construct a physical device capable of universal quantum computation. Some consequences for recursion theory and complexity theory are discussed. hep-th/9412047 06 Dec 94 1 Contents 1 The Quantum of action 3 2 Quantum mechanics for the computer scientist 7 2.1 Hilbert space quantum mechanics ..................... 7 2.2 From single to multiple quanta Ð ªsecondº ®eld quantization ...... 15 2.3 Quantum interference ............................ 17 2.4 Hilbert lattices and quantum logic ..................... 22 2.5 Partial algebras ............................... 24 3 Quantum information theory 25 3.1 Information is physical ........................... 25 3.2 Copying and cloning of qbits ........................ 25 3.3 Context dependence of qbits ........................ 26 3.4 Classical versus quantum tautologies .................... 27 4 Elements of quantum computatability and complexity theory 28 4.1 Universal quantum computers ....................... 30 4.2 Universal quantum networks ........................ 31 4.3 Quantum recursion theory ......................... 35 4.4 Factoring .................................. 36 4.5 Travelling salesman ............................. 36 4.6 Will the strong Church-Turing thesis survive? ............... 37 Appendix 39 A Hilbert space 39 B Fundamental constants of physics and their relations 42 B.1 Fundamental constants of physics ..................... 42 B.2 Conversion tables .............................. 43 B.3 Electromagnetic radiation and other wave phenomena ......... -
Quantum Inductive Learning and Quantum Logic Synthesis
Portland State University PDXScholar Dissertations and Theses Dissertations and Theses 2009 Quantum Inductive Learning and Quantum Logic Synthesis Martin Lukac Portland State University Follow this and additional works at: https://pdxscholar.library.pdx.edu/open_access_etds Part of the Electrical and Computer Engineering Commons Let us know how access to this document benefits ou.y Recommended Citation Lukac, Martin, "Quantum Inductive Learning and Quantum Logic Synthesis" (2009). Dissertations and Theses. Paper 2319. https://doi.org/10.15760/etd.2316 This Dissertation is brought to you for free and open access. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of PDXScholar. For more information, please contact [email protected]. QUANTUM INDUCTIVE LEARNING AND QUANTUM LOGIC SYNTHESIS by MARTIN LUKAC A dissertation submitted in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY in ELECTRICAL AND COMPUTER ENGINEERING. Portland State University 2009 DISSERTATION APPROVAL The abstract and dissertation of Martin Lukac for the Doctor of Philosophy in Electrical and Computer Engineering were presented January 9, 2009, and accepted by the dissertation committee and the doctoral program. COMMITTEE APPROVALS: Irek Perkowski, Chair GarrisoH-Xireenwood -George ^Lendaris 5artM ?teven Bleiler Representative of the Office of Graduate Studies DOCTORAL PROGRAM APPROVAL: Malgorza /ska-Jeske7~Director Electrical Computer Engineering Ph.D. Program ABSTRACT An abstract of the dissertation of Martin Lukac for the Doctor of Philosophy in Electrical and Computer Engineering presented January 9, 2009. Title: Quantum Inductive Learning and Quantum Logic Synhesis Since Quantum Computer is almost realizable on large scale and Quantum Technology is one of the main solutions to the Moore Limit, Quantum Logic Synthesis (QLS) has become a required theory and tool for designing Quantum Logic Circuits. -
Models of Quantum Complexity Growth
Models of quantum complexity growth Fernando G.S.L. Brand~ao,a;b;c;d Wissam Chemissany,b Nicholas Hunter-Jones,* e;b Richard Kueng,* b;c John Preskillb;c;d aAmazon Web Services, AWS Center for Quantum Computing, Pasadena, CA bInstitute for Quantum Information and Matter, California Institute of Technology, Pasadena, CA 91125 cDepartment of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, CA 91125 dWalter Burke Institute for Theoretical Physics, California Institute of Technology, Pasadena, CA 91125 ePerimeter Institute for Theoretical Physics, Waterloo, ON N2L 2Y5 *Corresponding authors: [email protected] and [email protected] Abstract: The concept of quantum complexity has far-reaching implications spanning theoretical computer science, quantum many-body physics, and high energy physics. The quantum complexity of a unitary transformation or quantum state is defined as the size of the shortest quantum computation that executes the unitary or prepares the state. It is reasonable to expect that the complexity of a quantum state governed by a chaotic many- body Hamiltonian grows linearly with time for a time that is exponential in the system size; however, because it is hard to rule out a short-cut that improves the efficiency of a computation, it is notoriously difficult to derive lower bounds on quantum complexity for particular unitaries or states without making additional assumptions. To go further, one may study more generic models of complexity growth. We provide a rigorous connection between complexity growth and unitary k-designs, ensembles which capture the randomness of the unitary group. This connection allows us to leverage existing results about design growth to draw conclusions about the growth of complexity. -
Arxiv:Quant-Ph/0002039V2 1 Aug 2000
Methodology for quantum logic gate construction 1,2 3,2 2 Xinlan Zhou ∗, Debbie W. Leung †, and Isaac L. Chuang ‡ 1 Department of Applied Physics, Stanford University, Stanford, California 94305-4090 2 IBM Almaden Research Center, 650 Harry Road, San Jose, California 95120 3 Quantum Entanglement Project, ICORP, JST Edward Ginzton Laboratory, Stanford University, Stanford, California 94305-4085 (October 29, 2018) We present a general method to construct fault-tolerant quantum logic gates with a simple primitive, which is an analog of quantum teleportation. The technique extends previous results based on traditional quantum teleportation (Gottesman and Chuang, Nature 402, 390, 1999) and leads to straightforward and systematic construction of many fault-tolerant encoded operations, including the π/8 and Toffoli gates. The technique can also be applied to the construction of remote quantum operations that cannot be directly performed. I. INTRODUCTION Practical realization of quantum information processing requires specific types of quantum operations that may be difficult to construct. In particular, to perform quantum computation robustly in the presence of noise, one needs fault-tolerant implementation of quantum gates acting on states that are block-encoded using quantum error correcting codes [1–4]. Fault-tolerant quantum gates must prevent propagation of single qubit errors to multiple qubits within any code block so that small correctable errors will not grow to exceed the correction capability of the code. This requirement greatly restricts the types of unitary operations that can be performed on the encoded qubits. Certain fault-tolerant operations can be implemented easily by performing direct transversal operations on the encoded qubits, in which each qubit in a block interacts only with one corresponding qubit, either in another block or in a specialized ancilla. -
Fault-Tolerant Interface Between Quantum Memories and Quantum Processors
ARTICLE DOI: 10.1038/s41467-017-01418-2 OPEN Fault-tolerant interface between quantum memories and quantum processors Hendrik Poulsen Nautrup 1, Nicolai Friis 1,2 & Hans J. Briegel1 Topological error correction codes are promising candidates to protect quantum computa- tions from the deteriorating effects of noise. While some codes provide high noise thresholds suitable for robust quantum memories, others allow straightforward gate implementation 1234567890 needed for data processing. To exploit the particular advantages of different topological codes for fault-tolerant quantum computation, it is necessary to be able to switch between them. Here we propose a practical solution, subsystem lattice surgery, which requires only two-body nearest-neighbor interactions in a fixed layout in addition to the indispensable error correction. This method can be used for the fault-tolerant transfer of quantum information between arbitrary topological subsystem codes in two dimensions and beyond. In particular, it can be employed to create a simple interface, a quantum bus, between noise resilient surface code memories and flexible color code processors. 1 Institute for Theoretical Physics, University of Innsbruck, Technikerstr. 21a, 6020 Innsbruck, Austria. 2 Institute for Quantum Optics and Quantum Information, Austrian Academy of Sciences, Boltzmanngasse 3, 1090 Vienna, Austria. Correspondence and requests for materials should be addressed to H.P.N. (email: [email protected]) NATURE COMMUNICATIONS | 8: 1321 | DOI: 10.1038/s41467-017-01418-2 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-017-01418-2 oise and decoherence can be considered as the major encoding k = n − s qubits. We denote the normalizer of S by Nobstacles for large-scale quantum information processing. -
Realization of the Quantum Toffoli Gate
Realization of the quantum Toffoli gate Realization of the quantum Toffoli gate Based on: Monz, T; Kim, K; Haensel, W; et al Realization of the quantum Toffoli gate with trapped ions Phys. Rev. Lett. 102, 040501 (2009) Lanyon, BP; Barbieri, M; Almeida, MP; et al. Simplifying quantum logic using higher dimensional Hilbert spaces Nat. Phys. 5, 134 (2009) Realization of the quantum Toffoli gate Outline 1. Motivation 2. Principles of the quantum Toffoli gate 3. Implementation with trapped ions 4. Implementation with photons 5. Comparison and conclusion 6. Summary 6. Dezember 2010 Jakob Buhmann Jeffrey Gehrig 1 Realization of the quantum Toffoli gate 1. Motivation • Universal quantum logic gate sets are needed to implement algorithms • Implementation of algorithms is difficult due to the finite fidelity and large amount of gates • Use of other degrees of freedom to store information • Reduction of complexity and runtime 6. Dezember 2010 Jakob Buhmann Jeffrey Gehrig 2 Realization of the quantum Toffoli gate 2. Principles of the Toffoli gate • Three-qubit gate (C1, C2, T) • Logic flip of T depending on (C1 AND C2) Truth table Matrix form Input Output C1 C2 T C1 C2 T 0 0 0 0 0 0 0 0 1 0 0 1 0 1 0 0 1 0 0 1 1 0 1 1 1 0 0 1 0 0 1 0 1 1 0 1 1 1 0 1 1 1 1 1 1 1 1 0 6. Dezember 2010 Jakob Buhmann Jeffrey Gehrig 3 Realization of the quantum Toffoli gate 2. Principles of the Toffoli gate • Qubit Implementation • Qutrit Implementation Qutrit states: and 6. -
Lecture 6: Quantum Error Correction and Quantum Capacity
Lecture 6: Quantum error correction and quantum capacity Mark M. Wilde∗ The quantum capacity theorem is one of the most important theorems in quantum Shannon theory. It is a fundamentally \quantum" theorem in that it demonstrates that a fundamentally quantum information quantity, the coherent information, is an achievable rate for quantum com- munication over a quantum channel. The fact that the coherent information does not have a strong analog in classical Shannon theory truly separates the quantum and classical theories of information. The no-cloning theorem provides the intuition behind quantum error correction. The goal of any quantum communication protocol is for Alice to establish quantum correlations with the receiver Bob. We know well now that every quantum channel has an isometric extension, so that we can think of another receiver, the environment Eve, who is at a second output port of a larger unitary evolution. Were Eve able to learn anything about the quantum information that Alice is attempting to transmit to Bob, then Bob could not be retrieving this information|otherwise, they would violate the no-cloning theorem. Thus, Alice should figure out some subspace of the channel input where she can place her quantum information such that only Bob has access to it, while Eve does not. That the dimensionality of this subspace is exponential in the coherent information is perhaps then unsurprising in light of the above no-cloning reasoning. The coherent information is an entropy difference H(B) − H(E)|a measure of the amount of quantum correlations that Alice can establish with Bob less the amount that Eve can gain. -
Machine Learning for Designing Fast Quantum Gates
University of Calgary PRISM: University of Calgary's Digital Repository Graduate Studies The Vault: Electronic Theses and Dissertations 2016-01-26 Machine Learning for Designing Fast Quantum Gates Zahedinejad, Ehsan Zahedinejad, E. (2016). Machine Learning for Designing Fast Quantum Gates (Unpublished doctoral thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/26805 http://hdl.handle.net/11023/2780 doctoral thesis University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. Downloaded from PRISM: https://prism.ucalgary.ca UNIVERSITY OF CALGARY Machine Learning for Designing Fast Quantum Gates by Ehsan Zahedinejad A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY GRADUATE PROGRAM IN PHYSICS AND ASTRONOMY CALGARY, ALBERTA January, 2016 c Ehsan Zahedinejad 2016 Abstract Fault-tolerant quantum computing requires encoding the quantum information into logical qubits and performing the quantum information processing in a code-space. Quantum error correction codes, then, can be employed to diagnose and remove the possible errors in the quantum information, thereby avoiding the loss of information. Although a series of single- and two-qubit gates can be employed to construct a quan- tum error correcting circuit, however this decomposition approach is not practically desirable because it leads to circuits with long operation times. An alternative ap- proach to designing a fast quantum circuit is to design quantum gates that act on a multi-qubit gate.