Grovers Search Jacob D. Biamonte Portland Quantum Logic Group Jake Biamonte Should be “one in four search”

Slides:



Advertisements
Similar presentations
Quantum Versus Classical Proofs and Advice Scott Aaronson Waterloo MIT Greg Kuperberg UC Davis | x {0,1} n ?
Advertisements

Quantum Software Copy-Protection Scott Aaronson (MIT) |
BQP/qpoly EXP/poly Scott Aaronson UC Berkeley. BQP/qpoly Class of languages recognized by a bounded-error polytime quantum algorithm, with a polysize.
The Equivalence of Sampling and Searching Scott Aaronson MIT.
Quantum walks: Definition and applications
Quantum Computation and Quantum Information – Lecture 3
Quantum Computing MAS 725 Hartmut Klauck NTU
Quantum computing COMP308 Lecture notes based on:
Midterm Exam for Quantum Computing Class Marek Perkowski.
Quantum Speedups DoRon Motter August 14, Introduction Two main approaches are known which produce fast Quantum Algorithms The first, and main approach.
Quantum Computing Ambarish Roy Presentation Flow.
1 Quantum Computing: What’s It Good For? Scott Aaronson Computer Science Department, UC Berkeley January 10,  John.
Grover. Part 2. Components of Grover Loop The Oracle -- O The Hadamard Transforms -- H The Zero State Phase Shift -- Z O is an Oracle H is Hadamards H.
Grover Algorithm Marek Perkowski
An Algebraic Foundation for Quantum Programming Languages Andrew Petersen & Mark Oskin Department of Computer Science The University of Washington.
High-Performance Simulation of Quantum Computation using QuIDDs George F. Viamontes, Manoj Rajagopalan, Igor L. Markov, and John P. Hayes Advanced Computer.
Grover’s Algorithm: Single Solution By Michael Kontz.
Grover. Part 2 Anuj Dawar. Components of Grover Loop The Oracle -- O The Hadamard Transforms -- H The Zero State Phase Shift -- Z.
The Integration Algorithm A quantum computer could integrate a function in less computational time then a classical computer... The integral of a one dimensional.
Boolean Matching in Logic Synthesis. Equivalence of Functions Equivalence of two functions defined under l Negation of input variables l Permutation of.
Quantum Behaviors: synthesis and measurement Martin Lukac Normen Giesecke Sazzad Hossain and Marek Perkowski Department of Electrical Engineering Portland.
CSEP 590tv: Quantum Computing
Quantum Computing Joseph Stelmach.
Quantum Search Algorithms for Multiple Solution Problems EECS 598 Class Presentation Manoj Rajagopalan.
1 Recap (I) n -qubit quantum state: 2 n -dimensional unit vector Unitary op: 2 n  2 n linear operation U such that U † U = I (where U † denotes the conjugate.
Quantum Algorithms II Andrew C. Yao Tsinghua University & Chinese U. of Hong Kong.
Grovers Search Jacob D. Biamonte Portland Quantum Logic Group Jake Biamonte Should be “one in four search”
Grover’s Algorithm in Machine Learning and Optimization Applications
Quantum Algorithms Preliminaria Artur Ekert. Computation INPUT OUTPUT Physics Inside (and outside) THIS IS WHAT OUR LECTURES WILL.
Classical Versus Quantum. Goal: Fast, low-cost implementation of useful algorithms using standard components (gates) and design techniques Classical Logic.
Outline Main result Quantum computation and quantum circuits Feynman’s sum over paths Polynomials QuPol program “Quantum Polynomials” Quantum polynomials.
Generalized Deutsch Algorithms IPQI 5 Jan Background Basic aim : Efficient determination of properties of functions. Efficiency: No complete evaluation.
October 1 & 3, Introduction to Quantum Computing Lecture 2 of 2 Richard Cleve David R. Cheriton School of Computer Science Institute for Quantum.
Quantum Computing MAS 725 Hartmut Klauck NTU TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A.
1 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 467 / Phys 767 C&O 481 / C&O 681 Richard Cleve DC 653 Course.
Lecture note 8: Quantum Algorithms
Algorithms Artur Ekert. Our golden sequence H H Circuit complexity n QUBITS B A A B B B B A # of gates (n) = size of the circuit (n) # of parallel units.
October 1 & 3, Introduction to Quantum Computing Lecture 1 of 2 Introduction to Quantum Computing Lecture 1 of 2
Quantum Computing MAS 725 Hartmut Klauck NTU
So Far……  Clustering basics, necessity for clustering, Usage in various fields : engineering and industrial fields  Properties : hierarchical, flat,
Quantum Computer Simulation Alex Bush Matt Cole James Hancox Richard Inskip Jan Zaucha.
A core Course on Modeling Introduction to Modeling 0LAB0 0LBB0 0LCB0 0LDB0 S.30.
Kuo-Hua Wang, Chung-Ming Chan, Jung-Chang Liu Dept. of CSIE Fu Jen Catholic University Slide: Chih-Fan Lai Simulation and SAT-Based Boolean Matching for.
CSEP 590tv: Quantum Computing Dave Bacon July 20, 2005 Today’s Menu n Qubit registers Begin Quantum Algorithms Administrivia Superdense Coding Finish Teleportation.
Exact quantum algorithms Andris Ambainis University of Latvia.
1 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 667 / Phys 767 C&O 481 / C&O 681 Richard Cleve DC 653 Lecture.
Quantum Computing & Algorithms
Quantum Computing MAS 725 Hartmut Klauck NTU
1 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 467 / Phys 767 C&O 481 / C&O 681 Richard Cleve DC 3524 Course.
Function Tables and Graphs. Function A function is when each input (x-value) corresponds to exactly one output (y- value) In other words, when you substitute.
A new algorithm for directed quantum search Tathagat Tulsi, Lov Grover, Apoorva Patel Vassilina NIKOULINA, M2R III.
1 Introduction to Quantum Information Processing QIC 710 / CS 667 / PH 767 / CO 681 / AM 871 Richard Cleve DC 2117 Lectures
Quantum Computer Simulation Alex Bush Matt Cole James Hancox Richard Inskip Jan Zaucha.
1 An Introduction to Quantum Computing Sabeen Faridi Ph 70 October 23, 2007.
Intro to Quantum Algorithms SUNY Polytechnic Institute Chen-Fu Chiang Fall 2015.
Pattern Recognition Lecture 20: Neural Networks 3 Dr. Richard Spillman Pacific Lutheran University.
Quantum Algorithms Oracles
Fundamental mechanism of the quantum computational speedup
Richard Cleve DC 2117 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 667 / Phys 767 C&O 481 / C&O 681 Lecture.
Fundamental mechanism of the quantum computational speedup
Introduction to Quantum Computing Lecture 1 of 2
A low cost quantum factoring algorithm
Quantum Computation 권민호 Yonsei Univ..
Quantum Computing Dorca Lee.
Grover. Part 2 Anuj Dawar.
Richard Cleve DC 2117 Introduction to Quantum Information Processing CS 667 / PH 767 / CO 681 / AM 871 Lecture 18 (2009) Richard.
Quantum Computing Joseph Stelmach.
Introduction to Quantum Information Processing CS 467 / CS 667 Phys 467 / Phys 767 C&O 481 / C&O 681 Lecture 4 (2005) Richard Cleve DC 653
Presentation transcript:

Grovers Search Jacob D. Biamonte Portland Quantum Logic Group Jake Biamonte Should be “one in four search”

1 in 4 search Why is this important? This presentation shows clearly how to perform a so called 1 in 4 search We start out with the basics

Pick your needle and I will find you a haystack The point of this slide is to show examples of 4 different oracles. Grovers search can tell between these oracles in a single iteration, classically we would need 3 iterations.

Let f : {0,1} 2  {0,1} have the property that there is exactly one x  {0,1} 2 for which f (x) = 1 Goal: find x  {0,1} 2 for which f (x) = 1 Classically: 3 queries are necessary Quantumly: ? Only after 3 tests can we determine with certainty that the oracles is 1 for only a single input value x Properties of the oracle

f x1x1 x2x2 yy x2x2 x1x1  y  f ( x 1,x 2 )  ( ( –1 ) f( 00 )  00  + ( –1 ) f( 01 )  01  + ( –1 ) f( 10 )  10  + ( –1 ) f( 11 )  11  )(  0  –  1  ) Output state: Black box for 1-4 search: Start by creating phases in superposition of all inputs to f : Input state to query: (  00  +  01  +  10  +  11  )(  0  –  1  ) f H H H 11 00 00 A 1-4 search can chose between 4 oracles in one iteration

f H H H 11 00 00 H H H H H X X HH X X M M M Time state = state = state = state = state = state = state = state = state = This slide illustrates how the state of the system is changed as it propagates through the quantum network implementation of Grovers Search algorithm.

 ψ 00  = –  00  +  01  +  10  +  11   ψ 01  = +  00  –  01  +  10  +  11   ψ 10  = +  00  +  01  –  10  +  11   ψ 11  = +  00  +  01  +  10  –  11  f H H H 11 00 00 H H H H H X X HH X X M M M Time The state corresponding to the input to the oracle that has a output result of 1 is ‘tagged’ with a negative 1. After Hadamard the solution is “known” in Hilbert space by having value -1. But it is hidded from us

QuIDDPro Script --- Density states #grover4.qp # state = cb("001")*cb("001")' state = hadamard(3)*state*hadamard(3)' echo("define a needle in a haystack:") ############# # Oracle 1 xi = (1,1) # ---*--- # | # ---*--- # | # --(+)-- ############# oracle = cu_gate(sigma_x(1), "c1c2x3", 3); state = oracle*state*oracle' echo("apply CPS:") state = kron(hadamard(2), identity(1))*state*kron(hadamard(2), identity(1))' state = kron(sigma_x(2), identity(1))*state*kron(sigma_x(2), identity(1))' state = cu_gate(hadamard(1), "x2", 3)*state*cu_gate(hadamard(1), "x2", 3)' state = cu_gate(sigma_x(1), "c1x2", 3)*state*cu_gate(sigma_x(1), "c1x2", 3)' state = cu_gate(hadamard(1), "x2", 3)*state*cu_gate(hadamard(1), "x2", 3)' state = kron(sigma_x(2), identity(1))*state*kron(sigma_x(2), identity(1))' state = hadamard(3)*state*hadamard(3

QuIDDPro Script --- State Vector state = cb("001") state = hadamard(3)*state echo("define a needle in a haystack:") ############# # Oracle 1 xi = (1,1) # ---*--- # | # ---*--- # | # --(+)-- ############# oracle = cu_gate(sigma_x(1), "c1c2x3", 3); state = oracle*state echo("apply CPS:") state = kron(hadamard(2), identity(1))*state state = kron(sigma_x(2), identity(1))*state state = cu_gate(hadamard(1), "x2", 3)*state state = cu_gate(sigma_x(1), "c1x2", 3)*state state = cu_gate(hadamard(1), "x2", 3)*state state = kron(sigma_x(2), identity(1))*state state = hadamard(3)*state

We found Grover!