Quantum Computer Algorithms: basics

Similar documents
An Introduction to Quantum Computation and Quantum Information

Quantum Computation. Michael A. Nielsen. University of Queensland

Problem Set # 5 Solutions

Introduction to Quantum Algorithms Part I: Quantum Gates and Simon s Algorithm

QUANTUM COMPUTATION. Exercise sheet 1. Ashley Montanaro, University of Bristol H Z U = 1 2

Simulation of quantum computers with probabilistic models

6.896 Quantum Complexity Theory September 18, Lecture 5

Introduction into Quantum Computations Alexei Ashikhmin Bell Labs

Quantum Circuits and Algorithms

Lecture 2: From Classical to Quantum Model of Computation

8. BOOLEAN ALGEBRAS x x

Introduction to Quantum Computing

X row 1 X row 2, X row 2 X row 3, Z col 1 Z col 2, Z col 2 Z col 3,

Deutsch Algorithm on Classical Circuits

Single qubit + CNOT gates

2.2 Classical circuit model of computation

Quantum Algorithms Lecture #2. Stephen Jordan

Lecture 4: Elementary Quantum Algorithms

Week 3 September 5-7.

Chapter 2. Basic Principles of Quantum mechanics

Introduction to Quantum Computation

Boolean State Transformation

Chapter 10. Quantum algorithms

Quantum Computing: Foundations to Frontier Fall Lecture 3

The Maze Generation Problem is NP-complete

2.0 Basic Elements of a Quantum Information Processor. 2.1 Classical information processing The carrier of information

Toda s Theorem: PH P #P

Quantum Phase Estimation using Multivalued Logic

hydrogen atom: center-of-mass and relative

C/CS/Phys C191 Grover s Quantum Search Algorithm 11/06/07 Fall 2007 Lecture 21

Complex numbers: a quick review. Chapter 10. Quantum algorithms. Definition: where i = 1. Polar form of z = a + b i is z = re iθ, where

Fourier Sampling & Simon s Algorithm

C/CS/Phys C191 Quantum Gates, Universality and Solovay-Kitaev 9/25/07 Fall 2007 Lecture 9

*WILEY- Quantum Computing. Joachim Stolze and Dieter Suter. A Short Course from Theory to Experiment. WILEY-VCH Verlag GmbH & Co.

An Introduction to Quantum Information and Applications

Lecture 5. Equations of Lines and Planes. Dan Nichols MATH 233, Spring 2018 University of Massachusetts.

Quantum Entanglement and the Bell Matrix

Quantum Computing Lecture 6. Quantum Search

Quantum Algorithms Lecture #3. Stephen Jordan

1 Bernstein-Vazirani Algorithm

6.080/6.089 GITCS May 6-8, Lecture 22/23. α 0 + β 1. α 2 + β 2 = 1

11.4 Polar Coordinates

Introduction to Quantum Information Processing

RELATIONS AND FUNCTIONS through

Mathematics of Cryptography Part I

Some Introductory Notes on Quantum Computing

Quantum Computing. Joachim Stolze and Dieter Suter. A Short Course from Theory to Experiment. WILEY-VCH Verlag GmbH & Co. KGaA

Discrete Quantum Theories

The Force Table Introduction: Theory:

Quantum gate. Contents. Commonly used gates

Cartesian coordinates in space (Sect. 12.1).

Introduction to Quantum Computing

Ph 219b/CS 219b. Exercises Due: Wednesday 20 November 2013

You don't have to be a mathematician to have a feel for numbers. John Forbes Nash, Jr.

Introduction to Quantum Logic. Chris Heunen

Quantum Complexity Theory and Adiabatic Computation

Quantum Recursion and Second Quantisation

Review: critical point or equivalently f a,

Quantum computing! quantum gates! Fisica dell Energia!

Short Course in Quantum Information Lecture 5

Seminar 1. Introduction to Quantum Computing

Systems of Linear Equations: Solving by Graphing

Simulating classical circuits with quantum circuits. The complexity class Reversible-P. Universal gate set for reversible circuits P = Reversible-P

MATH Line integrals III Fall The fundamental theorem of line integrals. In general C

Hilbert Space, Entanglement, Quantum Gates, Bell States, Superdense Coding.

( 7, 3) means x = 7 and y = 3. ( 7, 3) works in both equations so. Section 5 1: Solving a System of Linear Equations by Graphing

Section 1.5 Formal definitions of limits

ES.182A Topic 41 Notes Jeremy Orloff. 41 Extensions and applications of Green s theorem

The Deutsch-Josza Algorithm in NMR

TRANSFORMATIONS OF f(x) = x Example 1

Errata list, Nielsen & Chuang. rrata/errata.html

5. Zeros. We deduce that the graph crosses the x-axis at the points x = 0, 1, 2 and 4, and nowhere else. And that s exactly what we see in the graph.

1 Quantum Computing Simulation using the Auxiliary Field Decomposition

Mathematics 309 Conic sections and their applicationsn. Chapter 2. Quadric figures. ai,j x i x j + b i x i + c =0. 1. Coordinate changes

Foundations of Databases

Ph 219b/CS 219b. Exercises Due: Wednesday 4 December 2013

The Distance Formula & The Midpoint Formula

Lecture 3: Constructing a Quantum Model

Projects about Quantum adder circuits Final examination June 2018 Quirk Simulator

Polynomial approximation and Splines

6. Quantum error correcting codes

QLang: Qubit Language

Teleportation of Quantum States (1993; Bennett, Brassard, Crepeau, Jozsa, Peres, Wootters)

Compute the Fourier transform on the first register to get x {0,1} n x 0.

Gates for Adiabatic Quantum Computing

15. Eigenvalues, Eigenvectors

ROM-BASED COMPUTATION: QUANTUM VERSUS CLASSICAL

Ch 3 Alg 2 Note Sheet.doc 3.1 Graphing Systems of Equations

Physics Gravitational force. 2. Strong or color force. 3. Electroweak force

Quantum Computing Lecture Notes, Extra Chapter. Hidden Subgroup Problem

Richard Cleve David R. Cheriton School of Computer Science Institute for Quantum Computing University of Waterloo

Calculating with the square root of NOT

An Information Theory For Preferences

Realization of Quantum Hadamard Gate by Applying Optimal Control Fields to a Spin Qubit

Eigenvectors and Eigenvalues 1

Relations. Functions. Bijection and counting.

Chapter 4 Page 1 of 16. Lecture Guide. Math College Algebra Chapter 4. to accompany. College Algebra by Julie Miller

3.0 PROBABILITY, RANDOM VARIABLES AND RANDOM PROCESSES

Quantum Computation CMU BB, Fall Week 6 work: Oct. 11 Oct hour week Obligatory problems are marked with [ ]

TROPICAL SCHEME THEORY

Transcription:

Quantum Computer Algorithms: basics Michele Mosca Canada Research Chair in Quantum Computation SQUINT Summer School on Quantum Information Processing June 3

Overview A quantum computing model Basis changes Eigenvalue kick-back Some simple algorithms

A QUANTUM COMPUTING MODEL

Classical logic gates A gate is a function from m bits to n bits, for some fied numbers m and n AND NOT a b a b a a

Classical circuits We glue gates together to make circuits (or arras of gates ) which compute Boolean functions

Universal sets of logic gates A set B of gates is universal if, for an Boolean function F, there is a circuit composed of gates in B that computes F E.g. B = { NOT } is not universal E.g B = { AND } is not universal E.g. B = {NOT, AND, FANOUT } is universal

eample A circuit made from gates from set A = {,, }

Universal sets of logic gates If B is universal B = {,, } then e.g. = C C C

Universal sets of logic gates We can eactl simulate the circuit with gates from A with a circuit with gates from B C C C C

Making irreversible gates reversible Note that irreversible gates are reall just reversible gates where we hardwire some inputs and/or throw awa some outputs a a b b a b a b a b

Making irreversible circuits reversible a b c d Replace irreversible gates with their reversible counterparts a b c d

New gates and notation X X -gate or NOT-gate X controlled-not gate b b b b

A Classical Computing Model Acclic circuits of reversible gates

Eample phsical realization NOT (negligible coupling to the environment)

More logic gates (negligible coupling to the environment)

A classical computation

Aside: Is this realistic? We do have a theor of classical linear error correction. But before we worr about stabilizing this sstem, let s push forward its capabilities.

A quantum gate i NOT + i NOT +

A simple quantum circuit i + NOT NOT i

Linear Algebra notation NOT NOT i i i i i i =

Notation = = = = = = =

A quantum computation NOT i + NOT I i + CNOT i +

A quantum computation NOT I + i + i c NOT I i i i i

A Quantum Computing Model Acclic circuits of unitar gates (from a finite universal set ) and von Neumann measurements in the computational basis? = {,} a n

Universalit A set B of quantum gates is universal if, for an positive integer n, an unitar operator ( n U S U ) on n qubits and for an e >, there is a finite circuit in those gates that implements satisfing U ~ U ~ U < e where A = min?? = A?

In other words A set B of quantum gates is universal if, for an positive integer n, the gates of B acting on n qubits span a dense subset of S U ( n ). Wh not demand eact implementation of all operators? Eact universalit would require an infinite set of gates B and/or infinite sized circuits.

Some universal sets {C-NOT, all -qubit gates} {C-NOT, H, P} most -qubit gates are universal

BASIS CHANGES

Distinguishing orthogonal states Given a state {??, }? B =,?, K N?? = i j d i j we can in principle determine which state we have b performing a Von Neumann measurement with respect to the basis B

Distinguishing orthogonal states We can implement this measurement efficientl if we can efficientl implement the unitar transformation A? j = j? j A A t? j j

In general We can measure an state wrt the basis B in this wa j a j? j A A t? j j a j j j with probabilit a j

The Hadamard basis change H H H + + H

The Hadamard transformation: summar b H + ( ) b

The Hadamard transformation: circuit notation b b H + ( )

The Hadamard transformation on several bits H + ( ) H + ( ) H 3 + ( ) 3

The Hadamard transformation: global view H 3 H {, } 3 ( ) 8 3 H

The Hadamard transformation: global view 3 H H H {, } 3 ( ) 8 3

The Hadamard transformation: global view H H H 3 = {,} 3 ( ) 8 3

The Hadamard transformation on several bits + ( ) H + ( ) H 3 + ( ) H 3

The Hadamard transformation: global view H {, } 3 ( ) 3 H 3 H

The Hadamard transformation: global view {, } 3 ( ) 3 H H H 3

Looking at NOT and CNOT in Hadamard bases Consider appling a NOT (or X ) gate to the following states + X + X ( ) In other words: X = H Z H Z =

e.g. Now consider appling a controlled-not gate to the following states ( ) C N O T + ( + ) ( ) C N O T + ( + ) ( ) C N O T ( ) ( ) C N O T ( )

e.g. Now consider appling a controlled-not gate to the following states ( )( ) C N O T + + ( + )( + ) ( )( ) C N O T + ( )( + ) ( )( ) C N O T + ( )( ) ( )( ) C N O T ( + )( )

Eigenvalue kick-back

Computing functions into the phase Suppose we know how to compute a function f : {,} {,} c U f a c f ( ) ( ) ( ) a ( ) f ( )

Generalization: Eigenvalue kick-back Suppose we know how to compute an operator U? = Then the controlled-u gives us e if? c U? =? c U? = e if? ( ) (? e if )? c U + = +

How do we implement c-u? Replace ever gate G in the circuit for with a c-g. For eample, =

SOME SIMPLE ALGORITHMS

Deutsch s problem Compute ( ) f ( ) using U onl once f f H H f

Deutsch algorithm H f () H ( ) f () f () f = ) f ( ) f ( ( ) + ( ) )( ) f ( ) ( ) ) ( f ( ) f ( + ( ) )( )

Deutsch-Jozsa problem f : {,} n {,} Suppose promise that f is either constant or balanced. Decide if f is constant or balanced. with the Equivalentl, determine ( ) n f ( )

Deutsch-Jozsa problem H H H H {,} 3 ( ) 3 f ( ) + H H Probabilit of measuring f is ( ) i.e. we measure iff f is constant 3 f ( )

Bernstein-Vazirani problem Suppose f ( ) = a f : {,} n for some {,} a {, } is of the form n Given determine c U a f c f ( ) a = a a K a n

Bernstein-Vazirani problem H H H H H H a a a 3 f {,} 3 3 {,} 3 ( ) 3 a

Another propert of Hadamard transformation Consider n Z S + = + S s s S S Let Then = + S t t n t S S H ) ( { } S s t s Z t t S n = =, :

e.g. Consider }, { s S = s S + = + Then ( ) = + = + S t n t t n t s t n t n t t t S H ) ( ) ( ) (