Computability Theory of Closed Timelike Curves
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Quantum Computer: Quantum Model and Reality
Quantum Computer: Quantum Model and Reality Vasil Penchev, [email protected] Bulgarian Academy of Sciences: Institute of Philosophy and Sociology: Dept. of Logical Systems and Models Abstract. Any computer can create a model of reality. The hypothesis that quantum computer can generate such a model designated as quantum, which coincides with the modeled reality, is discussed. Its reasons are the theorems about the absence of “hidden variables” in quantum mechanics. The quantum modeling requires the axiom of choice. The following conclusions are deduced from the hypothesis. A quantum model unlike a classical model can coincide with reality. Reality can be interpreted as a quantum computer. The physical processes represent computations of the quantum computer. Quantum information is the real fundament of the world. The conception of quantum computer unifies physics and mathematics and thus the material and the ideal world. Quantum computer is a non-Turing machine in principle. Any quantum computing can be interpreted as an infinite classical computational process of a Turing machine. Quantum computer introduces the notion of “actually infinite computational process”. The discussed hypothesis is consistent with all quantum mechanics. The conclusions address a form of neo-Pythagoreanism: Unifying the mathematical and physical, quantum computer is situated in an intermediate domain of their mutual transformations. Key words: model, quantum computer, reality, Turing machine Eight questions: There are a few most essential questions about the philosophical interpretation of quantum computer. They refer to the fundamental problems in ontology and epistemology rather than philosophy of science or that of information and computation only. The contemporary development of quantum mechanics and the theory of quantum information generate them. -
Restricted Versions of the Two-Local Hamiltonian Problem
The Pennsylvania State University The Graduate School Eberly College of Science RESTRICTED VERSIONS OF THE TWO-LOCAL HAMILTONIAN PROBLEM A Dissertation in Physics by Sandeep Narayanaswami c 2013 Sandeep Narayanaswami Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy August 2013 The dissertation of Sandeep Narayanaswami was reviewed and approved* by the following: Sean Hallgren Associate Professor of Computer Science and Engineering Dissertation Adviser, Co-Chair of Committee Nitin Samarth Professor of Physics Head of the Department of Physics Co-Chair of Committee David S Weiss Professor of Physics Jason Morton Assistant Professor of Mathematics *Signatures are on file in the Graduate School. Abstract The Hamiltonian of a physical system is its energy operator and determines its dynamics. Un- derstanding the properties of the ground state is crucial to understanding the system. The Local Hamiltonian problem, being an extension of the classical Satisfiability problem, is thus a very well-motivated and natural problem, from both physics and computer science perspectives. In this dissertation, we seek to understand special cases of the Local Hamiltonian problem in terms of algorithms and computational complexity. iii Contents List of Tables vii List of Tables vii Acknowledgments ix 1 Introduction 1 2 Background 6 2.1 Classical Complexity . .6 2.2 Quantum Computation . .9 2.3 Generalizations of SAT . 11 2.3.1 The Ising model . 13 2.3.2 QMA-complete Local Hamiltonians . 13 2.3.3 Projection Hamiltonians, or Quantum k-SAT . 14 2.3.4 Commuting Local Hamiltonians . 14 2.3.5 Other special cases . 15 2.3.6 Approximation Algorithms and Heuristics . -
Quantum Supremacy
Quantum Supremacy Practical QS: perform some computational task on a well-controlled quantum device, which cannot be simulated in a reasonable time by the best-known classical algorithms and hardware. Theoretical QS: perform a computational task efficiently on a quantum device, and prove that task cannot be efficiently classically simulated. Since proving seems to be beyond the capabilities of our current civilization, we lower the standards for theoretical QS. One seeks to provide formal evidence that classical simulation is unlikely. For example: 3-SAT is NP-complete, so it cannot be efficiently classical solved unless P = NP. Theoretical QS: perform a computational task efficiently on a quantum device, and prove that task cannot be efficiently classically simulated unless “the polynomial Heierarchy collapses to the 3nd level.” Quantum Supremacy A common feature of QS arguments is that they consider sampling problems, rather than decision problems. They allow us to characterize the complexity of sampling measurements of quantum states. Which is more difficult: Task A: deciding if a circuit outputs 1 with probability at least 2/3s, or at most 1/3s Task B: sampling from the output of an n-qubit circuit in the computational basis Sampling from distributions is generically more difficult than approximating observables, since we can use samples to estimate observables, but not the other way around. One can imagine quantum systems whose local observables are easy to classically compute, but for which sampling the full state is computationally complex. By moving from decision problems to sampling problems, we make the task of classical simulation much more difficult. -
The Weakness of CTC Qubits and the Power of Approximate Counting
The weakness of CTC qubits and the power of approximate counting Ryan O'Donnell∗ A. C. Cem Sayy April 7, 2015 Abstract We present results in structural complexity theory concerned with the following interre- lated topics: computation with postselection/restarting, closed timelike curves (CTCs), and approximate counting. The first result is a new characterization of the lesser known complexity class BPPpath in terms of more familiar concepts. Precisely, BPPpath is the class of problems that can be efficiently solved with a nonadaptive oracle for the Approximate Counting problem. Similarly, PP equals the class of problems that can be solved efficiently with nonadaptive queries for the related Approximate Difference problem. Another result is concerned with the compu- tational power conferred by CTCs; or equivalently, the computational complexity of finding stationary distributions for quantum channels. Using the above-mentioned characterization of PP, we show that any poly(n)-time quantum computation using a CTC of O(log n) qubits may as well just use a CTC of 1 classical bit. This result essentially amounts to showing that one can find a stationary distribution for a poly(n)-dimensional quantum channel in PP. ∗Department of Computer Science, Carnegie Mellon University. Work performed while the author was at the Bo˘gazi¸ciUniversity Computer Engineering Department, supported by Marie Curie International Incoming Fellowship project number 626373. yBo˘gazi¸ciUniversity Computer Engineering Department. 1 Introduction It is well known that studying \non-realistic" augmentations of computational models can shed a great deal of light on the power of more standard models. The study of nondeterminism and the study of relativization (i.e., oracle computation) are famous examples of this phenomenon. -
STRONGLY UNIVERSAL QUANTUM TURING MACHINES and INVARIANCE of KOLMOGOROV COMPLEXITY (AUGUST 11, 2007) 2 Such That the Aforementioned Halting Conditions Are Satisfied
STRONGLY UNIVERSAL QUANTUM TURING MACHINES AND INVARIANCE OF KOLMOGOROV COMPLEXITY (AUGUST 11, 2007) 1 Strongly Universal Quantum Turing Machines and Invariance of Kolmogorov Complexity Markus M¨uller Abstract—We show that there exists a universal quantum Tur- For a compact presentation of the results by Bernstein ing machine (UQTM) that can simulate every other QTM until and Vazirani, see the book by Gruska [4]. Additional rele- the other QTM has halted and then halt itself with probability one. vant literature includes Ozawa and Nishimura [5], who gave This extends work by Bernstein and Vazirani who have shown that there is a UQTM that can simulate every other QTM for necessary and sufficient conditions that a QTM’s transition an arbitrary, but preassigned number of time steps. function results in unitary time evolution. Benioff [6] has As a corollary to this result, we give a rigorous proof that worked out a slightly different definition which is based on quantum Kolmogorov complexity as defined by Berthiaume et a local Hamiltonian instead of a local transition amplitude. al. is invariant, i.e. depends on the choice of the UQTM only up to an additive constant. Our proof is based on a new mathematical framework for A. Quantum Turing Machines and their Halting Conditions QTMs, including a thorough analysis of their halting behaviour. Our discussion will rely on the definition by Bernstein and We introduce the notion of mutually orthogonal halting spaces and show that the information encoded in an input qubit string Vazirani. We describe their model in detail in Subsection II-B. -
On the Simulation of Quantum Turing Machines
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Theoretical Computer Science 304 (2003) 103–128 www.elsevier.com/locate/tcs On the simulation ofquantum turing machines Marco Carpentieri Universita di Salerno, 84081 Baronissi (SA), Italy Received 20 March 2002; received in revised form 11 December 2002; accepted 12 December 2002 Communicated by G. Ausiello Abstract In this article we shall review several basic deÿnitions and results regarding quantum compu- tation. In particular, after deÿning Quantum Turing Machines and networks the paper contains an exposition on continued fractions and on errors in quantum networks. The topic of simulation ofQuantum Turing Machines by means ofobvious computation is introduced. We give a full discussion ofthe simulation ofmultitape Quantum Turing Machines in a slight generalization of the class introduced by Bernstein and Vazirani. As main result we show that the Fisher-Pippenger technique can be used to give an O(tlogt) simulation ofa multi-tape Quantum Turing Machine by another belonging to the extended Bernstein and Vazirani class. This result, even ifregarding a slightly restricted class ofQuantum Turing Machines improves the simulation results currently known in the literature. c 2003 Published by Elsevier B.V. 1. Introduction Even ifthe present technology does consent realizing only very simple devices based on the principles ofquantum mechanics, many authors considered to be worth it ask- ing whether a theoretical model ofquantum computation could o:er any substantial beneÿts over the correspondent theoretical model based on the assumptions ofclas- sical physics. Recently, this question has received considerable attention because of the growing beliefthat quantum mechanical processes might be able to performcom- putation that traditional computing machines can only perform ine;ciently. -
A Quantum Computer Foundation for the Standard Model and Superstring Theories*
A Quantum Computer Foundation for the Standard Model and SuperString Theories* By Stephen Blaha** * Excerpted from the book Cosmos and Consciousness by Stephen Blaha (1stBooks Library, Bloomington, IN, 2000) available from amazon.com and bn.com. ** Associate of the Harvard University Physics Department. ABSTRACT 1. SuperString Theory can naturally be based on a Quantum Computer foundation. This provides a totally new view of SuperString Theory. 2. The Standard Model of elementary particles can be viewed as defining a Quantum Computer Grammar and language. 3. A Quantum Computer can be represented in part as a second-quantized Fermi field. 4. A Quantum Computer in a certain limit naturally forms a Superspace upon which Supersymmetry rotations can be defined – a Continuum Quantum Computer. 5. A representation of Quantum Computers exists that is similar to Turing Machines - a Quantum Turing Machine. As part of this development we define various types of Quantum Grammars. 6. High level Quantum Computer languages are described for the first time. New linguistic views of the most fundamental theories of Physics, the Standard Model and SuperString Theory are described. In these new linguistic representations particles become literally symbols or letters, and particle interactions become grammar rules. This view is NOT the same as the often-expressed view that Mathematics is the language of Physics. The linguistic representation is a specific new mathematical construct. We show how to create a SuperString Quantum Computer that naturally provides a framework for SuperStrings in general and heterotic SuperStrings in particular. There are also a number of new developments relating to Quantum Computers and Quantum Turing Machines that are of interest to Computer Science. -
Quantum Computing : a Gentle Introduction / Eleanor Rieffel and Wolfgang Polak
QUANTUM COMPUTING A Gentle Introduction Eleanor Rieffel and Wolfgang Polak The MIT Press Cambridge, Massachusetts London, England ©2011 Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher. For information about special quantity discounts, please email [email protected] This book was set in Syntax and Times Roman by Westchester Book Group. Printed and bound in the United States of America. Library of Congress Cataloging-in-Publication Data Rieffel, Eleanor, 1965– Quantum computing : a gentle introduction / Eleanor Rieffel and Wolfgang Polak. p. cm.—(Scientific and engineering computation) Includes bibliographical references and index. ISBN 978-0-262-01506-6 (hardcover : alk. paper) 1. Quantum computers. 2. Quantum theory. I. Polak, Wolfgang, 1950– II. Title. QA76.889.R54 2011 004.1—dc22 2010022682 10987654321 Contents Preface xi 1 Introduction 1 I QUANTUM BUILDING BLOCKS 7 2 Single-Qubit Quantum Systems 9 2.1 The Quantum Mechanics of Photon Polarization 9 2.1.1 A Simple Experiment 10 2.1.2 A Quantum Explanation 11 2.2 Single Quantum Bits 13 2.3 Single-Qubit Measurement 16 2.4 A Quantum Key Distribution Protocol 18 2.5 The State Space of a Single-Qubit System 21 2.5.1 Relative Phases versus Global Phases 21 2.5.2 Geometric Views of the State Space of a Single Qubit 23 2.5.3 Comments on General Quantum State Spaces -
Computational Power of Observed Quantum Turing Machines
Computational Power of Observed Quantum Turing Machines Simon Perdrix PPS, Universit´eParis Diderot & LFCS, University of Edinburgh New Worlds of Computation, January 2009 Quantum Computing Basics State space in a classical world of computation: countable A. inaquantumworld: Hilbertspace CA ket map . : A CA | i → s.t. x , x A is an orthonormal basis of CA {| i ∈ } Arbitrary states Φ = αx x | i x A X∈ 2 s.t. x A αx =1 ∈ | | P Quantum Computing Basics bra map . : A L(CA, C) h | → s.t. x, y A, ∀ ∈ 1 if x = y y x = “ Kronecker ” h | | i (0 otherwise v,t A, v t : CA CA: ∀ ∈ | ih | → v if t = x ( v t ) x = v ( t x )= | i “ v t t v ” | ih | | i | i h | | i (0 otherwise | ih |≈ 7→ Evolution of isolated systems: Linear map U L(CA, CA) ∈ U = ux,y y x | ih | x,y A X∈ which is an isometry (U †U = I). Observation Let Φ = αx x | i x A X∈ (Full) measurement in standard basis: 2 The probability to observe a A is αa . ∈ | | If a A is observed, the state becomes Φa = a . ∈ | i Partial measurement in standard basis: Let K = Kλ, λ Λ be a partition of A. { ∈ } 2 The probability to observe λ Λ is pλ = a Kλ αa ∈ ∈ | | If λ Λ is observed, the state becomes P ∈ 1 1 Φλ = PλΦ = αa a √pλ √pλ | i a Kλ X∈ where Pλ = a Kλ a a . ∈ | ih | P Observation Let Φ = αx x | i x A X∈ (Full) measurement in standard basis: 2 The probability to observe a A is αa . -
Quantum Computational Complexity Theory Is to Un- Derstand the Implications of Quantum Physics to Computational Complexity Theory
Quantum Computational Complexity John Watrous Institute for Quantum Computing and School of Computer Science University of Waterloo, Waterloo, Ontario, Canada. Article outline I. Definition of the subject and its importance II. Introduction III. The quantum circuit model IV. Polynomial-time quantum computations V. Quantum proofs VI. Quantum interactive proof systems VII. Other selected notions in quantum complexity VIII. Future directions IX. References Glossary Quantum circuit. A quantum circuit is an acyclic network of quantum gates connected by wires: the gates represent quantum operations and the wires represent the qubits on which these operations are performed. The quantum circuit model is the most commonly studied model of quantum computation. Quantum complexity class. A quantum complexity class is a collection of computational problems that are solvable by a cho- sen quantum computational model that obeys certain resource constraints. For example, BQP is the quantum complexity class of all decision problems that can be solved in polynomial time by a arXiv:0804.3401v1 [quant-ph] 21 Apr 2008 quantum computer. Quantum proof. A quantum proof is a quantum state that plays the role of a witness or certificate to a quan- tum computer that runs a verification procedure. The quantum complexity class QMA is defined by this notion: it includes all decision problems whose yes-instances are efficiently verifiable by means of quantum proofs. Quantum interactive proof system. A quantum interactive proof system is an interaction between a verifier and one or more provers, involving the processing and exchange of quantum information, whereby the provers attempt to convince the verifier of the answer to some computational problem. -
Models of Quantum Computation and Quantum Programming Languages
Models of quantum computation and quantum programming languages Jaros law Adam MISZCZAK Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Ba ltycka 5, 44-100 Gliwice, Poland The goal of the presented paper is to provide an introduction to the basic computational mod- els used in quantum information theory. We review various models of quantum Turing machine, quantum circuits and quantum random access machine (QRAM) along with their classical counter- parts. We also provide an introduction to quantum programming languages, which are developed using the QRAM model. We review the syntax of several existing quantum programming languages and discuss their features and limitations. I. INTRODUCTION of existing models of quantum computation is biased towards the models interesting for the development of Computational process must be studied using the fixed quantum programming languages. Thus we neglect some model of computational device. This paper introduces models which are not directly related to this area (e.g. the basic models of computation used in quantum in- quantum automata or topological quantum computa- formation theory. We show how these models are defined tion). by extending classical models. We start by introducing some basic facts about clas- A. Quantum information theory sical and quantum Turing machines. These models help to understand how useful quantum computing can be. It can be also used to discuss the difference between Quantum information theory is a new, fascinating field quantum and classical computation. For the sake of com- of research which aims to use quantum mechanical de- pleteness we also give a brief introduction to the main res- scription of the system to perform computational tasks. -
Complexity Theory and Its Applications in Linear Quantum
Louisiana State University LSU Digital Commons LSU Doctoral Dissertations Graduate School 2016 Complexity Theory and its Applications in Linear Quantum Optics Jonathan Olson Louisiana State University and Agricultural and Mechanical College, [email protected] Follow this and additional works at: https://digitalcommons.lsu.edu/gradschool_dissertations Part of the Physical Sciences and Mathematics Commons Recommended Citation Olson, Jonathan, "Complexity Theory and its Applications in Linear Quantum Optics" (2016). LSU Doctoral Dissertations. 2302. https://digitalcommons.lsu.edu/gradschool_dissertations/2302 This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Doctoral Dissertations by an authorized graduate school editor of LSU Digital Commons. For more information, please [email protected]. COMPLEXITY THEORY AND ITS APPLICATIONS IN LINEAR QUANTUM OPTICS A Dissertation Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Doctor of Philosophy in The Department of Physics and Astronomy by Jonathan P. Olson M.S., University of Idaho, 2012 August 2016 Acknowledgments My advisor, Jonathan Dowling, is apt to say, \those who take my take my advice do well, and those who don't do less well." I always took his advice (sometimes even against my own judgement) and I find myself doing well. He talked me out of a high-paying, boring career, and for that I owe him a debt I will never be able to adequately repay. My mentor, Mark Wilde, inspired me to work hard without saying a word about what I \should" be doing, and instead leading by example.