Information quantique, calcul quantique :

Similar documents
Contents. Contents. 1 Quantum basics 2 Signal detection 3 Signal transmission 4 Signal estimation

Quantum Computing Lecture 3. Principles of Quantum Mechanics. Anuj Dawar

Introduction to Quantum Information Hermann Kampermann

Lecture 4: Postulates of quantum mechanics

Introduction to Quantum Information Processing QIC 710 / CS 768 / PH 767 / CO 681 / AM 871

Fidelity of Quantum Teleportation through Noisy Channels

Quantum Information Types

Ph 219/CS 219. Exercises Due: Friday 20 October 2006

Quantum Information Processing and Diagrams of States

Teleportation of Quantum States (1993; Bennett, Brassard, Crepeau, Jozsa, Peres, Wootters)

Hilbert Space, Entanglement, Quantum Gates, Bell States, Superdense Coding.

Unitary Dynamics and Quantum Circuits

Introduction to Quantum Mechanics

C/CS/Phys 191 Quantum Gates and Universality 9/22/05 Fall 2005 Lecture 8. a b b d. w. Therefore, U preserves norms and angles (up to sign).

1 Readings. 2 Unitary Operators. C/CS/Phys C191 Unitaries and Quantum Gates 9/22/09 Fall 2009 Lecture 8

Introduction to Quantum Computing

An Introduction to Quantum Computation and Quantum Information

Some Introductory Notes on Quantum Computing

PHY305: Notes on Entanglement and the Density Matrix

Quantum Entanglement and Error Correction

Quantum Nonlocality Pt. 4: More on the CHSH Inequality

Seminar 1. Introduction to Quantum Computing

Introduction to Quantum Information Processing QIC 710 / CS 768 / PH 767 / CO 681 / AM 871

DECAY OF SINGLET CONVERSION PROBABILITY IN ONE DIMENSIONAL QUANTUM NETWORKS

Basics on quantum information

Semiconductors: Applications in spintronics and quantum computation. Tatiana G. Rappoport Advanced Summer School Cinvestav 2005

The Postulates of Quantum Mechanics

2.0 Basic Elements of a Quantum Information Processor. 2.1 Classical information processing The carrier of information

Density Operators and Ensembles

Quantum Gates, Circuits & Teleportation

. Here we are using the standard inner-product over C k to define orthogonality. Recall that the inner-product of two vectors φ = i α i.

S.K. Saikin May 22, Lecture 13

SUPERDENSE CODING AND QUANTUM TELEPORTATION

Quantum Computing. Quantum Computing. Sushain Cherivirala. Bits and Qubits

Ensembles and incomplete information

b) (5 points) Give a simple quantum circuit that transforms the state

Instantaneous Nonlocal Measurements

Introduction to Quantum Computing

example: e.g. electron spin in a field: on the Bloch sphere: this is a rotation around the equator with Larmor precession frequency ω

Chapter 5. Density matrix formalism

Quantum Computing 1. Multi-Qubit System. Goutam Biswas. Lect 2

Single qubit + CNOT gates

Basics on quantum information

Introduction to Quantum Computation

2. Introduction to quantum mechanics

Quantum Error Correction Codes-From Qubit to Qudit. Xiaoyi Tang, Paul McGuirk

Introduction to quantum information processing

Lecture 6: Quantum error correction and quantum capacity

Richard Cleve David R. Cheriton School of Computer Science Institute for Quantum Computing University of Waterloo

Unitary evolution: this axiom governs how the state of the quantum system evolves in time.

1. Basic rules of quantum mechanics

MP 472 Quantum Information and Computation

Errata list, Nielsen & Chuang. rrata/errata.html

CS286.2 Lecture 15: Tsirelson s characterization of XOR games

Is Entanglement Sufficient to Enable Quantum Speedup?

Chapter 2 The Density Matrix

Entanglement and Quantum Teleportation

Quantum computing. Jan Černý, FIT, Czech Technical University in Prague. České vysoké učení technické v Praze. Fakulta informačních technologií

Physics 239/139 Spring 2018 Assignment 6

The Principles of Quantum Mechanics: Pt. 1

Introduction to quantum information processing

Short introduction to Quantum Computing

Quantum Statistics -First Steps

Basic Notation and Background

Lecture 14: Quantum information revisited

Quantum Noise. Michael A. Nielsen. University of Queensland

Chapter 10. Quantum algorithms

Quantum Computing: Foundations to Frontier Fall Lecture 3

Introduction to Quantum Algorithms Part I: Quantum Gates and Simon s Algorithm

Quantum Computation: From Quantum Teleportation to the Shor s Algorithm

Lecture Notes on QUANTUM COMPUTING STEFANO OLIVARES. Dipartimento di Fisica - Università degli Studi di Milano. Ver. 2.0

Entanglement Measures and Monotones

Quantum cryptography. Quantum cryptography has a potential to be cryptography of 21 st century. Part XIII

Logical error rate in the Pauli twirling approximation

Short Course in Quantum Information Lecture 2

Tutorial on Quantum Computing. Vwani P. Roychowdhury. Lecture 1: Introduction

Quantum Computation. Alessandra Di Pierro Computational models (Circuits, QTM) Algorithms (QFT, Quantum search)

1 The postulates of quantum mechanics

Lecture 1: Overview of quantum information

What is possible to do with noisy quantum computers?

Introduction to Quantum Information, Quantum Computation, and Its Application to Cryptography. D. J. Guan

An Introduction to Quantum Information and Applications

Quantum Hadamard channels (I)

Quantum Error Correcting Codes and Quantum Cryptography. Peter Shor M.I.T. Cambridge, MA 02139

Discrete Quantum Theories

Quantum information and quantum computing

Any pure quantum state ψ (qubit) of this system can be written, up to a phase, as a superposition (linear combination of the states)

Quantum state discrimination with post-measurement information!

Complex numbers: a quick review. Chapter 10. Quantum algorithms. Definition: where i = 1. Polar form of z = a + b i is z = re iθ, where

INTRODUCTION TO NMR and NMR QIP

Homework 3 - Solutions

Lecture: Quantum Information

Probabilistic exact cloning and probabilistic no-signalling. Abstract

Entropy in Classical and Quantum Information Theory

Quantum Physics II (8.05) Fall 2002 Assignment 3

QUANTUM INFORMATION -THE NO-HIDING THEOREM p.1/36

Introduction to Quantum Computing for Folks

QLang: Qubit Language

Quantum Computers. Todd A. Brun Communication Sciences Institute USC

Planck Constant and the Deutsch-Jozsa Algorithm

Transcription:

Séminaire LARIS, 8 juillet 2014. Information quantique, calcul quantique : des rudiments à la recherche (en 45min!). François Chapeau-Blondeau LARIS, Université d Angers, France. 1/25

Motivations pour le quantique pour le traitement de l information : 1) Quand on utilise des systèmes élémentaires (photons, électrons, atomes, nanodevices,...). 2) Pour bénéficier d effets purement quantiques (parallèlisme, intrication,...). 3) It s fun! 2/25

Quantum system Represented by a state vector ψ in a complex Hilbert space H, with unit norm ψ ψ = ψ 2 = 1. In dimension 2 : the qubit (photon, electron, atom,...) State ψ = α 0 +β 1 in some orthonormal basis { 0, 1 } of H 2, with α 2 + β 2 = 1. [ ] α ψ =, ψ = ψ = [α,β ] = ψ ψ = ψ 2 = α 2 + β 2 scalar. β [ ] [ α αα ψ ψ = [α,β αβ ] ] = β α β ββ = Π ψ orthogonal projector on ψ. 3/25

Measurement of the qubit When a qubit in state ψ = α 0 +β 1 is measured in the orthonormal basis { 0, 1 }, = only 2 possible outcomes (Born rule) : state 0 with probability α 2 = 0 ψ 2, or state 1 with probability β 2 = 1 ψ 2. Measurement : a probabilistic process, as a projection of the state ψ in an orthonormal basis, with statistics evaluable over repeated experiments with same preparation ψ. 4/25

Bloch sphere representation of the qubit Qubit in state ψ = α 0 +β 1 with α 2 + β 2 = 1. ψ = cos(θ/2) 0 +e iϕ sin(θ/2) 1. As a quantum object the qubit has infinitely many degrees of freedom (θ, ϕ), yet when it is measured it can only be found in one of two states (just like a classical bit). 5/25

Multiple qubits A system (a word) of N qubits has a state in H N 2, a tensor-product vector space with dimension 2 N, and orthonormal basis { x 1 x 2 x N } x {0,1} N. Example N = 2 : Generally ψ = α 00 00 +α 01 01 +α 10 10 +α 11 11. Or, as( a special separable ) ( state ) φ = α 1 0 +β 1 1 α 2 0 +β 2 1 = α 1 α 2 00 +α 1 β 2 01 +β 1 α 2 10 +β 1 β 2 11. A multipartite state which is not separable is entangled. 6/25

Entangled states Example of a separable state of two qubits AB : AB = 1 ( 0 + 1 ) 1 ) ( 0 + 1 = 1 ( ) 00 + 01 + 10 + 11. 2 2 2 When measured in the basis { 0, 1 }, each qubit A and B can be found in state 0 or 1 independently with probability 1/2. Example of an entangled state of two qubits AB : AB = 1 ) ( 00 + 11. 2 When measured in the basis { 0, 1 }, each qubit A and B can be found in state 0 or 1 with probability 1/2 (randomly, no predetermination before measure). But if A is found in 0 necessarily B is found in 0, and if A is found in 1 necessarily B is found in 1, no matter how distant the two qubits are before measurement. 7/25

Computation on a qubit Through a unitary operator U on H 2 (a 2 2 matrix) : normalized vector ψ H 2 U ψ normalized vector H 2. quantum gate input ψ U output U ψ Hadamard gate H = 1 [ ] 1 1. Identity gate 1 = 2 1 1 [ ] 1 0. 0 1 [ ] 0 1 [ ] 0 i [ 1 0 ] Pauli gates X = 1 0, Y = i 0, Z = 0 1. {1,X,Y,Z} a basis for operators on H 2. 8/25

Computation on a pair of qubits Through a unitary operator U on H 2 2 (a 4 4 matrix) : normalized vector ψ H 2 2 U ψ normalized vector H 2 2. quantum gate input output (always reversible) ψ U U ψ Controlled-Not gate : CT C,C T 00 00 01 01 10 11 11 10 T CT C C T C,C T C U = 1 0 0 0 0 1 0 0 0 0 0 1 0 0 1 0 9/25

Computation on a system of N qubits Through a unitary operator U on H N 2 (a 2 N 2 N matrix) : normalized vector ψ H N 2 U ψ normalized vector H N 2. quantum gate : N input qubits U N output qubits. Any N-qubit quantum gate may be composed from C-Not gates and single-qubit gates (universatility). This forms the grounding of quantum computation. 10/25

Deutsch-Jozsa algo. (1992) : Parallel evaluation of a function A classical function f( ) {0,1} N {0,1} 2 N values 2 values, can be constant or balanced (equal numbers of 0,1 in output). Classically : Between 2 and 2N 2 +1 evaluations of f( ) to decide. Quantumly : One evaluation of f( ) is enough. ( ) 1/2 1 ( ) ( ) N 1/2 1 ψ = 0 + 1 = x 2 N 2 N 1 x 2 x N x {0,1} N ψ N qubits Quantum circuit f( ) 1 qubit N qubits Decoder 1 cbit 11/25

Deutsch-Jozsa algorithm (Desurvire 2009, Cambridge Univ. Press) 12/25

Superdense coding (Bennett 1992) : exploiting entanglement Alice and Bob share a qubit pair in the entangled state φ = 1 ) ( 00 + 11. 2 Alice chooses two classical bits, pack them into a single qubit. Bob receives this qubit, from which he recovers the two classical bits. Alice 2 cbits 1 X Y Z 1 qbit Bob Decoder 2 cbits φ 2 entangled qubits Teleportation (1993) is the opposite : a shared pair of entangled qubits and two classical bits transmitted from Alice to Bob enable the transfer of an arbitrary quantum state ψ of a qubit. 13/25

Other quantum algorithms Grover quantum search algorithm (1996) : Quantum search in an unsorted database. Finds one item among N in O( N) steps (instead of O(N) classically). Shor factoring algorithm (1997) : Factors any integer in polynomial complexity (instead of exponential classically). 15 = 3 5, with spin-1/2 nuclei (Vandersypen et al., Nature 2001). 21 = 3 7, with photons (Martín-López et al., Nature Photonics 2012). 14/25

Density operator Quantum system in (pure) state ψ j, measured in an orthonormal basis { k } : = probability Pr{ k ψ j } = k ψ j 2 = k ψ j ψ j k. Several possible states ψ j with probabilities p j (with j p j = 1) : = Pr{ k } = ) j p j Pr{ k ψ j } = k ( j p j ψ j ψ j k = k ρ k, with density operator ρ = j p j ψ j ψ j. and Pr{ k } = k ρ k = tr(ρ k k ) = tr(ρπ k ). The quantum system is in a mixed state, corresponding to the statistical ensemble {p j, ψ j }, described by the density operator ρ. Lemma : For any operator A with trace tr(a) = k k A k, one has tr(a ψ ψ ) = k k A ψ ψ k = ( k ψ k k A ψ = ψ k )A ψ k k = ψ A ψ 15/25

Generalized measurement In a Hilbert space H N with dimension N, the state of a quantum system is specified by a Hermitian positive unit-trace density operator ρ. Projective measurement : Defined by a set of N orthogonal projectors k k = Π k, verifying k k k = k Π k = 1, and Pr{ k } = tr(ρπ k ). Moreover k Pr{ k } = 1, ρ k Π k = 1. Generalized measurement : Defined by a set of an arbitrary number of positive operators M m, verifying m M m = 1, and Pr{M m } = tr(ρm m ). Moreover m Pr{M m} = 1, ρ m M m = 1. 16/25

Quantum state discrimination A quantum system can be in one of two alternative states ρ 0 or ρ 1 with prior probabilities P 0 and P 1 = 1 P 0. Question : What is the best measurement {M 0,M 1 } to decide with a maximal probability of success P suc? Answer : One has P suc = P 0 tr(ρ 0 M 0 )+P 1 tr(ρ 1 M 1 ) = P 0 +tr(tm 1 ), with the test operator T = P 1 ρ 1 P 0 ρ 0. Then P suc is maximized by M opt 1 = λ n λ n, λ n >0 the projector on the eigensubspace of T with positive eigenvalues λ n. The optimal measurement {M opt achieves the maximum P max suc = 1 2 1,M opt 0 = 1 M opt 1 } N ) λ n. (Helstrom 1976) ( 1+ n=1 17/25

Discrimination from noisy qubits Quantum noise on a qubit in state ρ can be represented by random applications of (one of) the 4 Pauli operators {1,X,Y,Z} on the qubit, e.g. Bit-flip noise : ρ N(ρ) = (1 p)ρ+pxρx, Depolarizing noise : ρ N(ρ) = (1 p)ρ+ p ) (XρX +YρY +ZρZ. 3 With a noisy qubit, discrimination from N(ρ 0 ) and N(ρ 1 ). Impact of the probability p of action of the quantum noise, on the performance P max suc of the optimal detector, in relation to stochastic resonance and enhancement by noise. (Chapeau-Blondeau, Physics Letters A 2014) 18/25

19/25

Discrimination among M > 2 quantum states A quantum system can be in one of M states ρ m, for m = 1 to M, with prior probabilities P m with M m=1 P m = 1. Problem : What is the best measurement {M m } with M outcomes to decide with a maximal probability of success P suc? = Maximize P suc = M m=1 subject to 0 M m 1 P m tr(ρ m M m ) according to the M operators M m, and M m=1 M m = 1. For M > 2 this problem is only partially solved, in some special cases. (Barnett et al., Adv. Opt. Photon. 2009). Try interval analysis, etc?... 20/25

Error-free discrimination between M = 2 states Two alternative states ρ 0 or ρ 1 of H N, with priors P 0 and P 1 = 1 P 0, are not full-rank in H N, e.g. supp(ρ 0 ) H N [supp(ρ 0 )] { 0}. If S 0 = supp(ρ 0 ) [supp(ρ 1 )] { 0}, error-free discrimination of ρ 0 is possible. If S 1 = supp(ρ 1 ) [supp(ρ 0 )] { 0}, error-free discrimination of ρ 1 is possible. Necessity to find a three-outcome measurement {M 0,M 1,M unc } : = Find M 0 such that 0 M 0 1 and { 0} supp(m 0 ) S 0, and M 1 such that 0 M [ 1 1 and { 0} supp(m 1 ) S 1, ] and M 0 +M 1 1 M 0 +M 1 +M unc = 1 with 0 M unc 1, maximizing P suc = P 0 tr(m 0 ρ 0 )+P 1 tr(m 1 ρ 1 ) ( min P unc = 1 P suc ) This problem is only partially solved, in some special cases, even more so for extension at M > 2. (Kleinmann et al., J. Math. Phys. 2010). 21/25

Quantum feedback control 22/25

System dynamics : Schrödinger equation (for closed systems) d dt ψ = i ( H ψ = ψ(t 2) = exp i ) H(t 2 t 1 ) ψ(t 1 ) = U(t 1,t 2 ) ψ(t 1 ) }{{} unitary U(t 1,t 2 ) Hermitian operator Hamiltonian H = H 0 + H u (control part H u ). d dt ρ = i [H,ρ] = ρ(t 2) = U(t 1,t 2 )ρ(t 1 )U (t 1,t 2 ). Lindblad equation (for open systems) d dt ρ = i [H,ρ] + j ( ) 2L j ρl j {L j L j,ρ}, Lindblad op. L j for interact. with environt. Measurement : Arbitrary operators {E m } such that m E m E m = 1, Pr{m} = tr(e m ρe m ) = tr(ρe m E m) = tr(ρm m ) with M m = E m E m positive, Post-measurement state ρ m = E mρe m tr(e m ρe m ). 23/25

Pour aller plus loin M. Nielsen & I. Chuang E. Desurvire M. Wilde 2000, 676 pages 2009, 691 pages 2013, 655 pages 24/25

Merci de votre attention. Si vous avez compris... c est que je me suis mal exprimé! Nobody really understands quantum mechanics. R. P. Feynman 25/25