Classical Versus Quantum. Goal: Fast, low-cost implementation of useful algorithms using standard components (gates) and design techniques Classical Logic.

Slides:



Advertisements
Similar presentations
Department of Computer Science & Engineering University of Washington
Advertisements

Quantum Computation and Quantum Information – Lecture 3
Quantum Circuit Decomposition
University of Queensland
Reversible Gates in various realization technologies
( ( ) quantum bits conventional bit
Quantum Computing MAS 725 Hartmut Klauck NTU
Quantum Logic Marek Perkowski. Sources Mosca, Hayes, Ekert, Lee Spector in collaboration with Herbert J. Bernstein, Howard Barnum, Nikhil Swamy {lspector,
Advanced Computer Architecture Laboratory EECS Fall 2001 Quantum Logic Circuits John P. Hayes EECS Department University of Michigan, Ann Arbor,
Chien Hsing James Wu David Gottesman Andrew Landahl.
Grover. Part 2. Components of Grover Loop The Oracle -- O The Hadamard Transforms -- H The Zero State Phase Shift -- Z O is an Oracle H is Hadamards H.
Quantum Computation and Error Correction Ali Soleimani.
From Quantum Gates to Quantum Learning: recent research and open problems in quantum circuits Marek A. Perkowski, Portland Quantum Logic Group, Department.
University of Queensland
Introduction to Reversible Ckts Igor Markov University of Michigan Electrical Engineering & Computer Science.
Engineering Models and Design Methods for Quantum State Machines.
April 25, A Constructive Group Theory based Algorithm for Reversible Logic Synthesis.
Review of basic quantum and Deutsch-Jozsa. Can we generalize Deutsch-Jozsa algorithm? Marek Perkowski, Department of Electrical Engineering, Portland State.
“Both Toffoli and CNOT need little help to do universal QC” (following a paper by the same title by Yaoyun Shi) paper.
Classical and Quantum Circuit Synthesis An Algorithmic Approach.
Dirac Notation and Spectral decomposition Michele Mosca.
Quantum Behaviors: synthesis and measurement Martin Lukac Normen Giesecke Sazzad Hossain and Marek Perkowski Department of Electrical Engineering Portland.
Anuj Dawar.
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.
An Arbitrary Two-qubit Computation in 23 Elementary Gates or Less Stephen S. Bullock and Igor L. Markov University of Michigan Departments of Mathematics.
Grover’s Algorithm in Machine Learning and Optimization Applications
Lecture 3. Boolean Algebra, Logic Gates
Dirac Notation and Spectral decomposition
Introduction to Quantum logic (2) Yong-woo Choi.
New Approach to Quantum Calculation of Spectral Coefficients Marek Perkowski Department of Electrical Engineering, 2005.
Quantum Algorithms Preliminaria Artur Ekert. Computation INPUT OUTPUT Physics Inside (and outside) THIS IS WHAT OUR LECTURES WILL.
|x1 |x1 (a) |x2 |x2 | x1 x2  y |y |x |x (b) | x  y |y
ROM-based computations: quantum versus classical B.C. Travaglione, M.A.Nielsen, H.M. Wiseman, and A. Ambainis.
Fast Spectral Transforms and Logic Synthesis DoRon Motter August 2, 2001.
Propositional Calculus Math Foundations of Computer Science.
CSEP 590tv: Quantum Computing Dave Bacon June 29, 2005 Today’s Menu Administrivia Complex Numbers Bra’s Ket’s and All That Quantum Circuits.
Quantum Error Correction Jian-Wei Pan Lecture Note 9.
Alice and Bob’s Excellent Adventure
Outline Main result Quantum computation and quantum circuits Feynman’s sum over paths Polynomials QuPol program “Quantum Polynomials” Quantum polynomials.
1 Introduction to Quantum Information Processing QIC 710 / CS 678 / PH 767 / CO 681 / AM 871 Richard Cleve DC 2117 / QNC 3129 Lectures.
Systems Architecture I1 Propositional Calculus Objective: To provide students with the concepts and techniques from propositional calculus so that they.
1 Cost Metrics for Reversible and Quantum Logic Synthesis Dmitri Maslov 1 D. Michael Miller 2 1 Dept. of ECE, McGill University 2 Dept. of CS, University.
Small-Depth Quantum Circuits Frederic Green Department of Math/CS Clark University Worcester, MA.
October 1 & 3, Introduction to Quantum Computing Lecture 1 of 2 Introduction to Quantum Computing Lecture 1 of 2
Short course on quantum computing Andris Ambainis University of Latvia.
Quantum Computing MAS 725 Hartmut Klauck NTU
1 hardware of quantum computer 1. quantum registers 2. quantum gates.
Quantum Computing Reversibility & Quantum Computing.
8.4.2 Quantum process tomography 8.5 Limitations of the quantum operations formalism 量子輪講 2003 年 10 月 16 日 担当:徳本 晋
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.
IPQI-2010-Anu Venugopalan 1 qubits, quantum registers and gates Anu Venugopalan Guru Gobind Singh Indraprastha Univeristy Delhi _______________________________________________.
Quantum Cost Calculation of Reversible Circuit Sajib Mitra MS/ Department of Computer Science and Engineering University of Dhaka
What is a quantum computer? A quantum computer is any device for computation that makes use of quantum mechanical phenomena to perform operations on data,
Quantum Computation Stephen Jordan. Church-Turing Thesis ● Weak Form: Anything we would regard as “computable” can be computed by a Turing machine. ●
LOGIC CIRCUITLOGIC CIRCUIT. Goal To understand how digital a computer can work, at the lowest level. To understand what is possible and the limitations.
1 An Introduction to Quantum Computing Sabeen Faridi Ph 70 October 23, 2007.
Beginner’s Guide to Quantum Computing Graduate Seminar Presentation Oct. 5, 2007.
Quantum gates SALEEL AHAMMAD SALEEL. Introduction.
Richard Cleve DC 3524 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 667 / Phys 767 C&O 481 / C&O 681 Lecture.
Introduction to Quantum Computing Lecture 1 of 2
Lecture on Linear Algebra
Quantum Computing Dorca Lee.
A Ridiculously Brief Overview
Chap 4 Quantum Circuits: p
Introduction to Quantum logic (2)
OSU Quantum Information Seminar
Homework 2 This homework is the first use of quantum gates. In lectures we learned about the following gates: inverter, Feynman (controlled NOT), Toffoli.
Design of new quantum primitives
Quantum Computing Joseph Stelmach.
Presentation transcript:

Classical Versus Quantum

Goal: Fast, low-cost implementation of useful algorithms using standard components (gates) and design techniques Classical Logic Circuits –Circuit behavior is governed implicitly by classical physics –Signal states are simple bit vectors, e.g. X = –Operations are defined by Boolean Algebra –No restrictions exist on copying or measuring signals –Small well-defined sets of universal gate types, e.g. {NAND}, {AND,OR,NOT}, {AND,NOT}, etc. –Well developed CAD methodologies exist –Circuits are easily implemented in fast, scalable and macroscopic technologies such as CMOS Classical vs. Quantum Circuits

Quantum Logic Circuits –Circuit behavior is governed explicitly by quantum mechanics –Signal states are vectors interpreted as a superposition of binary “qubit” vectors with complex-number coefficients –Operations are defined by linear algebra over Hilbert Space and can be represented by unitary matrices with complex elements –Severe restrictions exist on copying and measuring signals –Many universal gate sets exist but the best types are not obvious –Circuits must use microscopic technologies that are slow, fragile, and not yet scalable, e.g., NMR Classical vs. Quantum Circuits

Unitary Operations –Gates and circuits must be reversible (information-lossless) Number of output signal lines = Number of input signal lines The circuit function must be a bijection, implying that output vectors are a permutation of the input vectors –Classical logic behavior can be represented by permutation matrices –Non-classical logic behavior can be represented including state sign (phase) and entanglement Quantum Circuit Characteristics

Quantum Measurement –Measurement yields only one state X of the superposed states –Measurement also makes X the new state and so interferes with computational processes –X is determined with some probability, implying uncertainty in the result –States cannot be copied (“cloned”), implying that signal fanout is not permitted –Environmental interference can cause a measurement-like state collapse (decoherence) Quantum Circuit Characteristics

Classical vs. Quantum Circuits Classical adder

Classical vs. Quantum Circuits Quantum adder Here we use Pauli rotations notation. Controlled σ x is the same as controlled NOT Controlled σ x is the same as Feynman Controlled-controlled σ x is the same as Toffoli

Reversible Circuits

Reversibility was studied around 1980 motivated by power minimization considerations Bennett, Toffoli et al. showed that any classical logic circuit C can be made reversible with modest overhead … …    n inputs Generic Boolean Circuit m outputs    f(i) i …    Reversible Boolean Circuit …    f(i) … … “Junk” i      

How to make a given f reversible –Suppose f :i  f(i) has n inputs m outputs –Introduce n extra outputs and m extra inputs –Replace f by f rev : i, j  i, f(i)  j where  is XOR Example 1: f(a,b) = AND(a,b) This is the well-known Toffoli gate, which realizes AND when c = 0, and NAND when c = 1. Reversible Circuits Reversible AND gate a b f = ab  c a b c a b c a b f

Reversible gate family [Toffoli 1980] Reversible Circuits (Toffoli gate) Every Boolean function has a reversible implementation using Toffoli gates. There is no universal reversible gate with fewer than three inputs

Quantum Gates

One-Input gate: NOT –Input state: c 0  + c 1  –Output state: c 1  + c 0  –Pure states are mapped thus:    and    –Gate operator (matrix) is –As expected: NOT

Quantum Gates One-Input gate: “Square root of NOT” –Some matrix elements are imaginary –Gate operator (matrix): –We find: so    with probability |i/  2| 2 = 1/2 and    with probability |1/  2| 2 = 1/2 Similarly, this gate randomizes input  –But concatenation of two gates eliminates the randomness!

Other variant of square root of not - we do not use complex numbers - only real numbers

Quantum Gates One-Input gate: Hadamard –Maps   1/  2  + 1/  2  and   1/  2  – 1/  2 . –Ignoring the normalization factor 1/  2, we can write x x x–x  x   (-1) x  x  –  –  x  One-Input gate: Phase shift H 

Universal One-Input Gate Sets Requirement: Hadamard and phase-shift gates form a universal gate set of 1-qubit gates, every 1-qubit gate can be built from them. Example: The following circuit generates  = cos   0  + e i  sin   1  up to a global factor Quantum Gates U  Any state    22 HH

Other Quantum Gates

Two-Input Gate: Controlled NOT (CNOT) Quantum Gates xx yy xx  x  y  CNOT –CNOT maps  x    x  x  and  x    x  NOT x  –  x    x  x  looks like cloning, but it’s not. These mappings are valid only for the pure states  and  –Serves as a “non-demolition” measurement gate xx yy xx  x  y 

Polarizing Beam-Splitter CNOT gate from [Cerf,Adami, Kwiat]

3-Input gate: Controlled CNOT (C 2 NOT or Toffoli gate) Quantum Gates bb cc bb  ab  c  aaaa

General controlled gates that control some 1- qubit unitary operation U are useful Quantum Gates U C(U) U C2(U)C2(U) U U etc.

Universal Gate Sets To implement any unitary operation on n qubits exactly requires an infinite number of gate types The (infinite) set of all 2-input gates is universal –Any n-qubit unitary operation can be implemented using  (n 3 4 n ) gates [Reck et al. 1994] CNOT and the (infinite) set of all 1-qubit gates is universal Quantum Gates

Discrete Universal Gate Sets The error on implementing U by V is defined as If U can be implemented by K gates, we can simulate U with a total error less than  with a gate overhead that is polynomial in log(K/  ) A discrete set of gate types G is universal, if we can approximate any U to within any  > 0 using a sequence of gates from G Quantum Gates

Discrete Universal Gate Set Example 1: Four-member “standard” gate set Quantum Gates HS  /8 CNOT Hadamard Phase  /8 (T) gate Example 2: {CNOT, Hadamard, Phase, Toffoli}

Quantum Circuits

A quantum (combinational) circuit is a sequence of quantum gates, linked by “wires” The circuit has fixed “width” corresponding to the number of qubits being processed Logic design (classical and quantum) attempts to find circuit structures for needed operations that are –Functionally correct –Independent of physical technology –Low-cost, e.g., use the minimum number of qubits or gates Quantum logic design is not well developed! Quantum Circuits

Ad hoc designs known for many specific functions and gates Example 1 illustrating a theorem by [Barenco et al. 1995]: Any C 2 (U) gate can be built from CNOTs, C(V), and C(V † ) gates, where V 2 = U Quantum Circuits VV†V† V = U (1+i) (1-i) (1-i) (1+i) 1/2 (1-i) (1+i) (1+i) (1-i) 1/2

Example 1: Simulation Quantum Circuits |0  |1  |x  |0  |1  |x  |0  |1  |x  VV†V† V = U |0  |1  V|x  |0  |1  |0  |1  |x  |0  |1  |0  |1  |x  ?

Quantum Circuits |1  |x  |1  |x  |1  U|x  VV†V† V = U |1  V|x  |1  |0  |1  |0  V|x  |1  U|x  Example 1: Simulation (contd.) ? Exercise: Simulate the two remaining cases

Quantum Circuits Example 1: Algebraic analysis U4U4 U2U2 U3U3 U1U1 U5U5 U0U0 VV†V† V = U ? x1x2x3x1x2x3 Is U 0 (x 1, x 2, x 3 ) = U 5 U 4 U 3 U 2 U 1 (x 1, x 2, x 3 ) = (x 1, x 2, x 1 x 2  U (x 3 ) ) ? We will verify unitary matrix of Toffoli gate Observe that the order of matrices U i is inverted.

Quantum Circuits Example 1 (contd); Kronecker since this is a parallel connection Unitary matrix of a wire Unitary matrix of a controlled V gate (from definition) We calculate the Unitary Matrix U 1 of the first block from left.

Quantum Circuits Example 1 (contd); We calculate the Unitary Matrix U 2 of the second block from left. Unitary matrix of CNOT or Feynman gate with EXOR down As we can check in the schematics, the Unitary Matrices U 2 and U 4 are the same

Quantum Circuits Example 1 (contd);

Quantum Circuits Example 1 (contd); –U 5 is the same as U 1 but has x 1 and x 2 permuted (tricky!) –It remains to evaluate the product of five 8 x 8 matrices U 5 U 4 U 3 U 2 U 1 using the fact that VV † = I and VV = U

Quantum Circuits Example 1 (contd); –We calculate matrix U 3 This is a hermitian matrix, so we transpose and next calculate complex conjugates, we denote complex conjugates by bold symbols v 00 v v 00 v 10 v 01 v v 01 v 11 =

Quantum Circuits Example 1 (contd); –U 5 is the same as U 1 but has x 1 and x 2 permuted because in U 1 black dot is in variable x 2 and in U 5 black dot is in variable x 1 –This can be also checked by definition, see next slide. U 5 =

Quantum Circuits Example 1 (here we explain in detail how to calculate U 5 ). x1x1 x2x2 x3x3 V U5U5 x1x1 x2x2 x3x3 V U1U1. U6U6 U6U6 U 6 is calculated as a Kronecker product of U 7 and I 1 U 7 is a unitary matrix of a swap gate U 5 = U 6 U 1 U 6

Quantum Circuits Example 1 (contd); –It remains to evaluate the product of five 8 x 8 matrices U 5 U 4 U 3 U 2 U 1 using the fact that VV † = I and VV = U U1U1

Quantum Circuits Implementing a Half Adder –Problem: Implement the classical functions sum = x 1  x 0 and carry = x 1 x 0 Generic design: |x 1  U add |x 0  |y 1  |y 0  |x 1  |x 0  |y 1   carry |y 0   sum

Quantum Circuits Half Adder : Generic design (contd.)

Quantum Circuits Half Adder : Specific (reduced) design |x 1  |x 0  |y  |x 1  |y   carry sum C 2 NOT (Toffoli) CNOT