quantum computing cpsc 321

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Quantum Computing CPSC 321 Andreas Klappenecker

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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 - PowerPoint PPT Presentation

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Page 1: Quantum Computing CPSC 321

Quantum ComputingCPSC 321

Andreas Klappenecker

Page 2: 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?

Page 3: Quantum Computing CPSC 321

Announcements

• Today’s lecture 12:45pm-1:30pm• 12:45pm-1:15pm Basic of QC• 1:15pm-1:30pm Evaluation • Bonfire memorial dedication

Page 4: Quantum Computing CPSC 321

In Memoriam

Page 5: Quantum Computing CPSC 321

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.

Page 6: Quantum Computing CPSC 321

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

Page 7: Quantum Computing CPSC 321

Quantum Bits

Page 8: Quantum Computing CPSC 321

Polarized Light

Page 9: Quantum Computing CPSC 321

Quantum Cryptography

Page 10: Quantum Computing CPSC 321

Quantum Algorithms

• Searching unsorted data• Classical algorithms: linear complexity• Quantum algorithms: O(n1/2)

• Factoring Integers• Classical algorithms: Exponential

complexity• Quantum algorithms: Polynomial

complexity

Page 11: Quantum Computing CPSC 321

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 coNP in polynomial time on a quantum computer?

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

Page 12: Quantum Computing CPSC 321

The Stern-Gerlach Experiment

Page 13: Quantum Computing CPSC 321

Quantum Bits

Page 14: Quantum Computing CPSC 321

Memory

Page 15: Quantum Computing CPSC 321

Quantum Computing in a Nutshell

Page 16: Quantum Computing CPSC 321

Operations on a Quantum Computer

Page 17: Quantum Computing CPSC 321

Example

Page 18: Quantum Computing CPSC 321

Teleportation

Page 19: Quantum Computing CPSC 321

Teleportation – It’s Simple!

Page 20: Quantum Computing CPSC 321

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>)

Page 21: Quantum Computing CPSC 321

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!