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Quantum Computation and Quantum Information Lecture 3

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Title: Quantum Computation and Quantum Information Lecture 3


1
Quantum Computation and Quantum Information
Lecture 3
  • Part 1 of CS406 Research Directions in Computing

Nick Papanikolaou
2
Motivation
  • Quantum computers are built from wires and logic
    gates, just as classical computers are
  • The potential of such devices stems from the
    ability to manipulate superpositions of states
  • Quantum algorithms solve problems which are not
    known to be solvable classically!

3
Lecture 3 Topics
  • Quantum logic gates
  • Simple quantum circuits
  • Quantum teleportation as a circuit
  • Deutschs quantum algorithm

4
Quantum vs. classical gates
  • The simplest boolean gate is NOT, with truth
    table
  • Quantum gates have to be defined not only on the
    equivalents of 0 and 1, but on their
    superpositions too!

5
Quantum NOT gate Linearity
  • Suppose we define a quantum NOT gate as follows
  • The action of the quantum NOT gate on a
    superposition must then be
  • All quantum operations are linear

6
The NOT Gate as a Matrix
  • Because all quantum operations have to be linear,
    we can represent the action of a quantum gate by
    a matrix
  • The quantum NOT, or Pauli-X gate, is written

7
Quantum State Vectors
  • Remember that a quantum state is represented by a
    vector
  • Notation

8
Quantum NOT
  • We can express the NOT operation on a general
    qubit as matrix multiplication

9
Other Single Qubit Gates
  • The Pauli-X gate works on only one qubit
  • Other common single qubit gates are
  • Pauli-Z gate
  • Pauli-Y gate
  • Hadamard gate

10
Summary of Simple Gates
11
Reversibility Requirement
  • All quantum operations have to be reversible
  • Boolean operations are not necessarily so
  • A reversible operation is always given by a
    unitary matrix, i.e. one for which

12
The Controlled NOT Gate
  • The CNOT gate is the standard two-qubit quantum
    gate
  • It is defined like this

13
The Controlled NOT Gate (2)
  • CNOT is a generalisation of the classical XOR
  • The CNOT gate is drawn like this

control qubit
target qubit
14
The Controlled NOT Gate (3)
  • The matrix corresponding to the CNOT gate is
  • The CNOT together with the single qubit gates are
    universal for quantum computing

15
Quantum Circuits
  • Using the conventions for control and target
    qubits, we can build interesting circuits
  • Example A Qubit Swap Circuit

16
Qubit Swap Circuit
17
Features of Quantum Circuits
  • No loops are allowed quantum circuits are
    acyclic
  • Fan-in is not allowed
  • Fan-out is not allowed

18
Generalised Control Gate
  • Any quantum gate U can be converted into a
    controlled gate

One control qubit
n target qubits
U
If the control qubit is high, U is applied to
the targets. CNOT is the Controlled-X gate!
19
Quantum Measurement
  • Measurement in a quantum circuit is drawn as

M
(classical bit representing outcome of
measurement)
M 0 with prob. or M 1 with prob.
If
then
20
A Qubit Cloning Circuit?
  • Using the XOR gate, it is possible to copy a
    classical bit

Can we build a quantum circuit that performs does
this with qubits?
21
A Qubit Cloning Circuit? (2)
OK here
entangled!!
22
A Qubit Cloning Circuit? (3)
It is impossible to clone a qubit! Also note that
unwanted terms!
23
The Bell State Circuit
x
y
24
The Bell State Circuit By Example
?
25
Quantum Teleportation Circuit
M1
H
M2
XM2
ZM1
26
Quantum Teleportation Circuit (2)
M1
H
M2
XM2
ZM1
27
Quantum Teleportation Circuit (3)
M1
H
M2
XM2
ZM1
28
Quantum Teleportation Circuit (4)
M1
H
M2
XM2
ZM1
00, 01, 10 or 11
29
Quantum Teleportation Circuit (5)
30
What have we achieved?
  • The teleportation process makes it possible to
    reproduce a qubit in a different location
  • But the original qubit is destroyed!
  • Next topic Quantum Parallelism and Deutschs
    quantum algorithm

31
Quantum Parallelism
  • Quantum parallelism is that feature of quantum
    computers which makes it possible to evaluate a
    function f(x) on many different values of x
    simultaneously
  • We will look at an example of quantum parallelism
    now how to compute f(0) and f(1) for some
    function f all in one go!

32
Quantum Circuits for Boolean Functions
  • It is known that, for any boolean function
  • it is possible to construct a quantum circuit Uf
    that computes it
  • Specifically, to each binary function f
    corresponds a quantum circuit

binary addition
33
Quantum Circuits for Boolean Functions (2)
  • What can this circuit Uf do? Example

34
Quantum Circuits for Boolean Functions (3)
  • But what if the input is a superposition?

35
Quantum Parallelism Summary
  • So, a superposition of inputs will give a
    superposition of outputs!
  • We can perform many computations simultaneously
  • This is what makes famous quantum algorithms,
    such as Shors algorithm for factoring, or
    Grovers algorithm for searching
  • Simple q. algorithm Deutschs algorithm

36
Deutschs Algorithm
  • David Deutsch famous British physicist
  • Deutschs algorithm allows us to compute, in only
    one step, the value of
  • To do this classically, you would have to
  • compute f(0)
  • compute f(1)
  • add the two results
  • Remember

37
Circuit for Deutschs Algorithm
38
Circuit for Deutschs Algorithm (2)
39
Circuit for Deutschs Algorithm (3)
40
End of Lecture 3
  • Congratulations! If you are still awake, you have
    learned something about
  • quantum gates (X, Y, Z, H, CNOT)
  • quantum circuits (swapping, no-cloning problem)
  • teleportation
  • quantum parallelism
  • and Deutschs algorithm
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