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Beginner

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Quantum Computation and Quantum Information by Nielsen and ... An Introduction to Quantum Computing for Non-Physicists ACM Computing Surveys, Sept. 2000 ... – PowerPoint PPT presentation

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Title: Beginner


1
Beginners Guide to Quantum Computing
  • Graduate Seminar Presentation
  • Oct. 5, 2007

2
Introduction
  • Quantum Computation and Quantum Information by
    Nielsen and Chuang
  • Answer Guide Tech Report
  • An Introduction to Quantum Computing for
    Non-Physicists ACM Computing Surveys, Sept.
    2000
  • Quantum Mechanics Demo

3
Qubits
  • Representation of basic physical property
  • Spin of atom
  • Orientation of photon
  • Computational Basis
  • Ket notation
  • 0gt 1gt

4
Qubit State
  • Other states
  • Complex probabilities
  • x yi i is square root of -1
  • Sum of square of absolute values of probabilities
    1
  • Absolute value of complex number is distance from
    origin in complex plane
  • abs(xyi) (x2 y2)0.5

5
Example Qubits
  • (1/2)0.50gt (1/2)0.51gt
  • (1/2)0.5 (0gt 1gt)
  • (1/2)0.5,(1/2)0.5
  • (1/2)0.5i/2,i/2
  • sin(x),cos(x)
  • sin(x)cos(x)i,0

6
Qubit Systems
  • Two qubits (q0, q1) gt Four probabilities
  • 00gt, 01gt, 10gt, 11gt
  • Tensor product
  • a,b c,d ac, ad, bc, bd
  • N qubits gt 2N probabilities
  • Exponential growth!

7
Measurement
  • Reduces qubit to classical bit
  • 1,0 (0gt) or 0, 1 (1gt)
  • Can measure 1 qubit and leave rest alone

8
Entangled States
  • Cannot be represented as tensor product of two
    qubits
  • (1/2)0.5, 0, 0, (1/2)0.5 (Bell state)
  • Measure 1 qubit, fixes other qubit!

9
Unitary Operators
  • 1-qubit ops
  • effect both complex probabilities
  • 2x2 matrix of complex numbers
  • UUT I (reversible)
  • Examples
  • THISXYZ
  • T1 00 (1i)/(20.5)

10
(Walsh)-Hadamard Gate
  • H (1/2)0.5, (1/2)0.5
    (1/2)0.5, -(1/2)0.5
  • Applying to N qubits generates superposition
    2N possibilities equally likely
  • True random number generator

11
Review
  • Benefits
  • Massive parallelism
  • Exponential state space growth
  • Problems
  • Measurement collapses state
  • Reversible computation
  • No copying

12
Shors Algorithm
  • Finding prime factors (RSA)
  • Input N (integer) in binary (e.g., 128-bit)
  • Randomly choose x, 1ltxltN
  • Find smallest r such that xr N 1
  • If r is even and x(r/2) N ! N-1
  • Factors are at least one of gcd(x(r/2)-1,N)
    gcd(x(r/2)1,N)

13
Factoring 15
  • Randomly pick 8
  • 84 15 1
  • gcd(82-1,15) 3
  • gcd(821,15) 5

14
Shors Algorithm Quantum Part
  • Finding r
  • Superposition N qubits
  • Apply xr N on all qubits
  • Effectively calculates r for all values from 0 to
    N-1
  • Find minimum value (1)

15
Shors Algorithm - Analysis
  • Benefits
  • Uses O(log N)3 time
  • Uses O(log N) space
  • Implemented on 7 qubit machine
  • Cons
  • Probabilistic est. 25 failure rate
  • More qubits required than bits

16
Grovers Algorithm
  • Unordered search O(N)
  • Quantum results O(N0.5)
  • Search matrix
  • e.g., identity with -1 at desired location
  • Rotation matrix
  • Applied N0.5 times yields minimal failure rate
  • Optimal for quantum

17
Phase Estimation
  • Unitary op has eigenvalue e(2PIiX)
  • Estimate X
  • Basis for Grovers algorithm and Shors algorithm
  • Shors algorithm achieves exponential speed-up
  • Grovers algorithm quadratic

18
Simulation
  • Java using dense matrices
  • 12-qubit op requires 5-25 seconds
  • 12-qubit Inverse QFT requires 2 minutes
  • 10-qubit ripple carry adder requires 2 min
  • Allows combination quantum and classical

19
Future
  • Quantum algorithm other than phase estimation?
  • Quantum computer larger than 16 qubits?
  • Quantum data structures?
  • Quantum subprocessor?

20
Questions?
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