Introduction to Quantum Information Processing CS 467 CS

  • Slides: 16
Download presentation
Introduction to Quantum Information Processing CS 467 / CS 667 Phys 467 / Phys

Introduction to Quantum Information Processing CS 467 / CS 667 Phys 467 / Phys 767 C&O 481 / C&O 681 Lecture 6 (2005) Richard Cleve DC 3524 cleve@cs. uwaterloo. ca Course web site at: http: //www. cs. uwaterloo. ca/~cleve 1

Contents • Phase estimation problem • Algorithm for the phase estimation problem • Order-finding

Contents • Phase estimation problem • Algorithm for the phase estimation problem • Order-finding via phase estimation 2

 • Phase estimation problem • Algorithm for the phase estimation problem • Order-finding

• Phase estimation problem • Algorithm for the phase estimation problem • Order-finding via phase estimation 3

Generalized controlled-U gates a b a U a 1 : am b 1 :

Generalized controlled-U gates a b a U a 1 : am b 1 : bn U a b a 1 : am U U a 1 am b Example: 1101 0101 1101 U 1101 0101 4

Phase estimation problem U is a unitary operation on n qubits is an eigenvector

Phase estimation problem U is a unitary operation on n qubits is an eigenvector of U, with eigenvalue e 2 i (0 ≤ < 1) m qubits Input: black-box for U and a copy of n qubits Output: (m-bit approximation) 5

 • Phase estimation problem • Algorithm for the phase estimation problem • Order-finding

• Phase estimation problem • Algorithm for the phase estimation problem • Order-finding via phase estimation 6

Algorithm for phase estimation (I) Starts off as: 0 0 0 H H H

Algorithm for phase estimation (I) Starts off as: 0 0 0 H H H U 00 … 0 ( 0 + 1 ) … ( 0 + 1 ) a b a U a b = ( 000 + 001 + 010 + 011 + … + 111 ) = ( 0 + 1 + 2 + 3 + … + 2 m 1 ) ( 0 + e 2 i 1 + (e 2 i )2 2 + (e 2 i )3 3 + … + (e 2 i )2 2 m 1 ) m� 1 7

Quantum Fourier transform where = e 2 i/N (for n qubits, N = 2

Quantum Fourier transform where = e 2 i/N (for n qubits, N = 2 n) 8

Computing the QFT (I) Quantum circuit for F 32: H 4 8 4 H

Computing the QFT (I) Quantum circuit for F 32: H 4 8 4 H 16 8 4 H 32 Gates: 16 8 4 H reverse order H H m For F 2 n costs O(n 2) gates 9

Computing the QFT (II) One way on seeing why this circuit works is to

Computing the QFT (II) One way on seeing why this circuit works is to first note that F 2 n a 1 a 2…an = ( 0 + e 2 i (0. an) 1 )…( 0 + e 2 i (0. a 2…an) 1 ) ( 0 + e 2 i (0. a 1 a 2…an) 1 ) It can then be checked that the circuit produces these states (with qubits in reverse order) for all computational basis states a 1 a 2…an Exercise: (a) prove the above equation from the definition of the QFT; (b) confirm that the circuit produces these states 10

Algorithm for phase estimation (II) Note: this is exactly the state generated by our

Algorithm for phase estimation (II) Note: this is exactly the state generated by our preliminary algorithm for phase estimation when = 0. a 1 a 2…am Therefore, if = 0. a 1 a 2…am then applying F† to this state yields a 1 a 2…am (from which can be deduced exactly) What if is not of this nice form? Example: = ⅓ = 0. 01010101… 11

 • Phase estimation problem • Algorithm for the phase estimation problem • Order-finding

• Phase estimation problem • Algorithm for the phase estimation problem • Order-finding via phase estimation 12

Order-finding algorithm (I) Let M be an m-bit integer Def: ZM* = {x {1,

Order-finding algorithm (I) Let M be an m-bit integer Def: ZM* = {x {1, 2, …, M 1} : gcd(x, M ) = 1} ZM* is a group under multiplication modulo M Example: Z 21* = {1, 2, 4, 5, 8, 10, 11, 13, 16, 17, 19, 20} For a ZM*, consider all powers of a : a 0, a 1, a 2, a 3, … Ex: For a = 10, the sequence is: 1, 10, 16, 13, 4, 19, 1, 10, 16, … Def: ord. M (a) is the minimum r > 0 such that ar = 1 (mod M ) Ex: ord 21 (10) = 6 Order-finding problem: given a and M, find ord. M (a) 13

Order-finding algorithm (II) Define: U (an operation on m qubits) as: U y =

Order-finding algorithm (II) Define: U (an operation on m qubits) as: U y = a y mod M Define: Then 14

Order-finding algorithm (III) U 2 n qubits corresponds to the mapping: x y x

Order-finding algorithm (III) U 2 n qubits corresponds to the mapping: x y x ax y mod M n qubits Moreover, this mapping can be implemented with roughly O(n 2) gates The phase estimation algorithm yields a 2 n-bit estimate of 1/r From this, a good estimate of r can be calculated … Problem: how do we construct state 1 to begin with? 15

16

16