An Introduction to Quantum Computation Sandy Irani Department of Computer Science University of California, Irvine.

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Presentation transcript:

An Introduction to Quantum Computation Sandy Irani Department of Computer Science University of California, Irvine

“Simulating Physics with Computers” Richard Feynman – Keynote Talk, 1 st Conference on Physics and Computation, MIT, 1981

“Simulating Physics with Computers” Richard Feynman – Keynote Talk, 1 st Conference on Physics and Computation, MIT, 1981 Is it possible to build computers that use the laws of quantum mechanics to compute?

Quantum Superposition √2√2 1 + √2√2 1

√2√2 1 - √2√2 1 -

Implementations of a “Qubit” Energy level of an atom Spin orientation of an electron Polarization of a photon. NMR, Ion traps,…

Information: 1 Bit Example (Schrodinger’s Cat) Classical Information: – A bit is in state 0 or state 1 Classical Information with Uncertainty – Bit is 0 with probability p 0 – Bit is 1 with probability p 1 – State (p 0, p 1 ) Quantum Information – State is a superposition over states 0 and 1 – State is (  0,  1 ) where  0,  1 are complex. X=0 OR X=1

Information: 1 Bit Example (Schrodinger’s Cat) Classical Information: – A bit is in state 0 or state 1 Classical Information with Uncertainty – Bit is 0 with probability p 0 – Bit is 1 with probability p 1 – State (p 0, p 1 ) Quantum Information – State is a superposition over states 0 and 1 – State is (  0,  1 ) where  0,  1 are complex. X=1 with prob p 1 X=0 OR X=0 with prob p 0 X=1

Information: 1 Bit Example (Schrodinger’s Cat) Classical Information: – A bit is in state 0 or state 1 Classical Information with Uncertainty – State (p 0, p 1 ) Quantum Information – State is partly 0 and partly 1 – State is (  0,  1 ) where  0,  1 are complex. X=1 with prob p 1 X=0 OR X=0 with prob p 0 11  0 X=1

Information: n Bit Example Classical Information: – State of n bits specified by a string x in {0,1} n Classical Information with Uncertainty – State described by probability distribution over 2 n possibilities – (p 0, p 1, …., p 2 n -1 ) Quantum Information – State is a superposition over 2 n possibilities – (  0,  1,…,  2 n -1 ), where a is complex X = 011

Information: n Bit Example Classical Information: – State of n bits specified by a string x in {0,1} n Classical Information with Uncertainty – State described by probability distribution over 2 n possibilities – (p 0, p 1, …., p 2 n -1 ) Quantum Information – State is a superposition over 2 n possibilities – (  0,  1,…,  2 n -1 ), where a is complex p 000 p 001 p 010 p 011 p 100 p 101 p 110 p 111

Information: n Bit Example Classical Information: – State of n bits specified by a string x in {0,1} n Classical Information with Uncertainty – State described by probability distribution over 2 n possibilities – (p 0, p 1, …., p 2 n -1 ) Quantum Information – State is a superposition over 2 n possibilities – (  0,  1,…,  2 n -1 ), where a is complex  000  001  010  011  100  101  110  111

A quantum kilobyte of data (8192 qubits) Encodes complex numbers ~ (Number of atoms in the universe ~ 10 82)

State of n qubits (  0,…,  2 n -1 ) stores 2 n complex numbers: Rich in information How to use it? How to access it?

Quantum Measurement State of n qubits (  0,…,  2 n -1 ) If all n qubits are examined: – Outcome is 010 with probability |  010 | 2.  000  001  010  011  100  101  110  111

Quantum Measurement State of n qubits (  0,…,  2 n -1 ) If all n qubits are examined: – Outcome is 010 with probability |  010 | 2. – The measurement causes the state of the system to change: » The state “collapses” to 010

Ingredients in Computation Store information about a problem to be solved Manipulate the information to solve the problem Read out an answer

Computer Circuits AND OR AND OR AND NOT 0/1 Input Output

Quantum Circuits U1U1 U2U2 U3U3 U4U4 U5U5 U6U6 U7U7 U8U8 M Time Input Read the output by measurement

Interference [Image from due to Dr. Glen MacPherson]

[Figure from gwoptics.org]

Quantum Gates: An Example Operation H: H Input:Output: Input:Output:

Qubit measurement Measure: With probability Outcome = With probability Outcome =

Qubit measurement Measure: With probability Outcome = With probability Outcome =

Quantum Interference: An Example |0  + |1  |0  - |1 

Quantum Interference: An Example |0  + |1  |0  - |1  Apply Gate H

Quantum Interference: An Example |0  + |1  |0  - |1  (|0  +|1  ) Apply Gate H

Quantum Interference: An Example |0  + |1  |0  - |1  (|0  +|1  )(|0  -|1  ) + Apply Gate H

Quantum Interference: An Example |0  + |1  |0  - |1  (|0  +|1  )(|0  -|1  ) + Result: |0  Apply Gate H

Quantum Interference: An Example |0  + |1  |0  - |1  (|0  +|1  )(|0  -|1  ) + Result: |0  Apply Gate H Apply Gate H

Quantum Interference: An Example |0  + |1  |0  - |1  (|0  +|1  )(|0  -|1  ) + Result: |0  Apply Gate H Apply Gate H (|0  +|1  )

Quantum Interference: An Example |0  + |1  |0  - |1  (|0  +|1  )(|0  -|1  ) + Result: |0  Apply Gate H Apply Gate H (|0  +|1  )(|0  -|1  ) -

Quantum Interference: An Example |0  + |1  |0  - |1  (|0  +|1  )(|0  -|1  ) + Result: |0  Apply Gate H Apply Gate H (|0  +|1  )(|0  -|1  ) - Result: |1 

Quantum Circuits U1U1 U2U2 U3U3 U4U4 U5U5 U6U6 U7U7 U8U8 M Quantum Algorithms Manipulate data so that negative interference causes wrong answers to have small amplitude and right answers to have high amplitude, so that when we measure output, we are likely to get the right answer.

Factoring Given a positive integer, find its prime factorization. 24 = 2 x 2 x 2 x 3 Input Output

Factoring RSA-210 =

Can Quantum Computers Be Built? Key challenge: prevent decoherence (interaction with the environment). Can factor N=15 on a quantum computer Larger problems will require quantum error correcting codes.

Computer Science Quantum Mechanics Classical Simulation Of Quantum Systems Algorithm Design For Quantum Circuits Physical Implementation Of Quantum Computers Quantum Cryptography Quantum Information Theory Quantum Complexity Theory

Quantum Computers for Simulation in Physics

My Research Design efficient algorithms on a quantum (or classical) computer that will provably compute properties of a quantum system. – For what kinds of systems is this possible? – Or: give mathematical evidence that there is no efficient way to solve this problem.