Quantum computing cpsc 321
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Quantum Computing CPSC 321. Andreas Klappenecker. Plan. T November 16: Multithreading R November 18: Quantum Computing T November 23: QC + Exam prep R November 25: Thanksgiving M November 29: Review ??? T November 30: Exam R December 02: Summary and Outlook

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Quantum Computing CPSC 321

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Quantum computing cpsc 321

Quantum ComputingCPSC 321

Andreas Klappenecker


Quantum computing cpsc 321

Plan

  • T November 16: Multithreading

  • R November 18: Quantum Computing

  • T November 23: QC + Exam prep

  • R November 25: Thanksgiving

    • M November 29: Review ???

  • T November 30: Exam

  • R December 02: Summary and Outlook

  • T December 07: move to November 29?


Announcements

Announcements

  • Today’s lecture 12:45pm-1:30pm

  • 12:45pm-1:15pm Basic of QC

  • 1:15pm-1:30pm Evaluation

  • Bonfire memorial dedication


In memoriam

In Memoriam


Moore s law

Moore’s Law

Gordon Moore observed in 1965 that the number of transistors per integrated circuit seems to follow an exponential law, and he predicted that future developments will follow this trend.

Remarkably, he made his observation about 4 years after the production of the first integrated circuit.

The number of transistors is supposed to double every 18-24 months.


The end of moore s law

The End of Moore’s Law?

Sometime in 2020-2030, computations will occur at an atomic scale.

We have to deal with quantum effects:

  • Pessimists: Noise

  • Optimists: New computational paradigm


Quantum bits

Quantum Bits


Polarized light

Polarized Light


Quantum cryptography

Quantum Cryptography


Quantum algorithms

Quantum Algorithms

  • Searching unsorted data

    • Classical algorithms: linear complexity

    • Quantum algorithms: O(n1/2)

  • Factoring Integers

    • Classical algorithms: Exponential complexity

    • Quantum algorithms: Polynomial complexity


Complexity questions

Complexity Questions

  • Can quantum algorithms really outperform classical algorithms?

  • Can we solve NP-hard problems in polynomial time on a quantum computer?

  • Can we solve problems in NP O coNP in polynomial time on a quantum computer?

  • Can we solve distributed computing problems with lower message complexity?


The stern gerlach experiment

The Stern-Gerlach Experiment


Quantum bits1

Quantum Bits


Memory

Memory


Quantum computing in a nutshell

Quantum Computing in a Nutshell


Operations on a quantum computer

Operations on a Quantum Computer


Example

Example


Teleportation

Teleportation


Teleportation it s simple

Teleportation – It’s Simple!


Background

Background

  • State of a quantum computer

    • A complex vector of dimension 2n

    • |00>+|11> = (1,0,0,1)

  • Operations

    • Unitary matrices (linear operations)

  • Measurements

    • Probabilistic (amplify quantum effects)

  • Classical Picture

    • Calculate A|00> or A|11>, or both A(|00>+|11>)


Conclusion

Conclusion

  • The basic model is simple

  • Everyone can write a simulator of a quantum computer in a very short time

  • The computational model is different – you need time to absorb that!

  • Numerous potential technologies!


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