Quantum Computing CPSC 321 Andreas Klappenecker. Plan T November 16: Multithreading R November 18: Quantum Computing T November 23: QC + Exam prep R November.

Slides:

Advertisements

Similar presentations

New Evidence That Quantum Mechanics Is Hard to Simulate on Classical Computers Scott Aaronson Parts based on joint work with Alex Arkhipov.

Advertisements

Solving Hard Problems With Light Scott Aaronson (Assoc. Prof., EECS) Joint work with Alex Arkhipov vs.

Quantum Computation and Quantum Information – Lecture 3

Block LU Factorization Lecture 24 MA471 Fall 2003.

Parallel Programming Henri Bal Rob van Nieuwpoort Vrije Universiteit Amsterdam Faculty of Sciences.

Nanoscale structures in Integrated Circuits By Edward Mulimba.

CS 501: Software Engineering Fall 2000 Lecture 19 Performance of Computer Systems.

Multithreading and Dataflow Architectures CPSC 321 Andreas Klappenecker.

University of Queensland

 States that the number of transistors on a microprocessor will double every two years.  Current technology is approaching physical limitations. The.

Matthew Guidry. The Fundamentals of Cryptography  One of the fundamentals of cryptography is that keys selected for various protocols that are computationally.

Quantum Computing II CPSC 321 Andreas Klappenecker.

1 Recap (I) n -qubit quantum state: 2 n -dimensional unit vector Unitary op: 2 n  2 n linear operation U such that U † U = I (where U † denotes the conjugate.

Moore’s Law By: Avery A, David D, David G, Donovan R and Katie F.

Quantum Information Processing

Quantum Complexity Classes By: Larisse D. Voufo On: November 28 th, 2006

Christina Cuervo, Kenny Roth, and Daniel Merrill.

Quantum Computing MAS 725 Hartmut Klauck NTU

Debasis Sadhukhan M.Sc. Physics, IIT Bombay. 1. Basics of Quantum Computation. 2. Quantum Circuits 3. Quantum Fourier Transform and it’s applications.

Dominique Unruh 3 September 2012 Quantum Cryptography Dominique Unruh.

Quantum Algorithms for Neural Networks Daniel Shumow.

Alice and Bob’s Excellent Adventure

Chapter Complexity of Algorithms –Time Complexity –Understanding the complexity of Algorithms 1.

Exponential Functions and Equations. Water Temperature – Time vs. Hours The following table shows the time, in hours, before the body of a scuba diver,

Quantum Computers. Overview Brief History Computing – (generations) Current technology Limitations Theory of Quantum Computing How it Works? Applications.

1 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 667 / Phys 767 C&O 481 / C&O 681 Richard Cleve DC 2117 Lecture.

History of Integrated Circuits  In 1961 the first commercially available integrated circuits came from the Fairchild Semiconductor Corporation.  The.

1 Dr. Michael D. Featherstone Introduction to e-Commerce Laws of the Web.

Very Large Scale Integrated chips (VLSI) The complexity of the digital computation chips is increasing in line with Moore’s law.The complexity of the digital.

Limits and Horizon of Computing Post silicon computing.

October 1 & 3, Introduction to Quantum Computing Lecture 1 of 2 Introduction to Quantum Computing Lecture 1 of 2

1 Lecture 16 Quantum computing Ubiquitous Internet Services The client server paradigm DNS Electronic Mail World Wide Web.

Integrated electronic optical switches in future chip ion trap Shu, Gang 5/24/2006.

Quantum Computing Paola Cappellaro

A brief introduction to Quantum computer

Lecture 8 Overview. Analysis of Algorithms Algorithms – Time Complexity – Space Complexity An algorithm whose time complexity is bounded by a polynomial.

Quantum Computers by Ran Li.

Quantum Processing Simulation

Is This the Dawn of the Quantum Information Age? Discovering Physics, Nov. 5, 2003.

Quantum Computing and Quantum Programming Language

Cove: A Practical Quantum Computer Programming Framework Matt Purkeypile (DCS3) Winter 2009.

1 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 467 / Phys 767 C&O 481 / C&O 681 Richard Cleve DC 3524 Course.

1 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 667 / Phys 767 C&O 481 / C&O 681 Richard Cleve DC 653 Lecture.

The Kind of Stuff I Think About Scott Aaronson (MIT) LIDS Lunch, October 29, 2013 Abridged version of plenary talk at NIPS’2012.

Chapter VI What should I know about the sizes and speeds of computers?

Capabilities and limitations of quantum computers Michele Mosca 1 November 1999 ECC ’99.

Introduction Why Study Algorithms? Design and Analysis of Algorithms I.

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

1 Introduction to Quantum Information Processing QIC 710 / CS 667 / PH 767 / CO 681 / AM 871 Richard Cleve DC 2117 Lectures

Quantum Computers By Ryan Orvosh.

Intel’s 3D Transistor BENJAMIN BAKER. Where we are headed  What is a transistor?  What it is and what does it do?  Moore’s Law  Who is Moore and what.

Quantum Computing Are We There Yet?

Quantum Computing: An Introduction

Babbage’s Difference Engine #2 Ed Lazowska Bill & Melinda Gates Chair in Computer Science & Engineering University of Washington August 2011.

Quantum Computers TAUKI TAHMID BRAC UNIVERSITY ID:

Attendance Syllabus Textbook (hardcopy or electronics) Groups s First-time meeting.

Integration Lower sums Upper sums

Quantum Bits (qubit) 1 qubit probabilistically represents 2 states

Richard Cleve DC 3524 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 667 / Phys 767 C&O 481 / C&O 681 Lecture.

VLSI Tarik Booker.

Introduction to Quantum Computing Lecture 1 of 2

Limits and Horizon of Computing

By Nealesh Ragoodial - Security Capstone

Technology Forecasting: Moore’s Law

A Ridiculously Brief Overview

OSU Quantum Information Seminar

Quantum Computing Hakem Alazmi Jhilakshi Sharma Linda Vu.

Vrije Universiteit Amsterdam

Presentation transcript:

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 T December 07: move to November 29?

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

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 months.

The End of Moore’s Law? Sometime in , computations will occur at an atomic scale. We have to deal with quantum effects: - Pessimists: Noise - Optimists: New computational paradigm

Quantum Bits

Polarized Light

Quantum Cryptography

Quantum Algorithms Searching unsorted data Classical algorithms: linear complexity Quantum algorithms: O(n 1/2 ) Factoring Integers Classical algorithms: Exponential complexity Quantum algorithms: Polynomial complexity

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

Quantum Bits

Memory

Quantum Computing in a Nutshell

Operations on a Quantum Computer

Example

Teleportation

Teleportation – It’s Simple!

Background State of a quantum computer A complex vector of dimension 2 n |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 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!