DYNAMICS OF OPEN Q-SYSTES FROM A PERSPECTIVE OF QIT IMS, Imperial College, London, 18 January 2007 Vladimír Bužek Research Center for Quantum Information.

Slides:



Advertisements
Similar presentations
Henry Haselgrove School of Physical Sciences University of Queensland
Advertisements

Strong Monogamy and Genuine Multipartite Entanglement Gerardo Adesso Informal Quantum Information Gathering 2007 The Gaussian Case Quantum Theory group.
Optimizing pointer states for dynamical evolution of quantum correlations under decoherence Bo You,Li-xiang Cen Department of Physics, SiChuan University.
Introduction to Entanglement Allan Solomon, Paris VI.
Chapter 4 Continuous Time Signals Time Response Continuous Time Signals Time Response.
Quantum Computing MAS 725 Hartmut Klauck NTU
Frustration of Decoherence and Entanglement-sharing in the Spin-bath Andrew Hines Christopher Dawson Ross McKenzie Gerard Milburn.
Introduction to Quantum Information Processing CS 467 / CS 667 Phys 467 / Phys 767 C&O 481 / C&O 681 Lecture 11 (2005) Richard Cleve DC 3524
Quantum Information Stephen M. Barnett University of Strathclyde The Wolfson Foundation.
Decoherence Versus Disentanglement for two qubits in a squeezed bath. Facultad de Física Pontificia Universidad Católica de Chile. M.Orszag ; M.Hernandez.
The Postulates of Quantum Mechanics
Emergence of Quantum Mechanics from Classical Statistics.
Corporate Banking and Investment Mathematical issues with volatility modelling Marek Musiela BNP Paribas 25th May 2005.
DENSITY MATRICES, traces, Operators and Measurements
Advanced Computer Architecture Lab University of Michigan Quantum Operations and Quantum Noise Dan Ernst Quantum Noise and Quantum Operations Dan Ernst.
Backward Evolving Quantum State Lev Vaidman 2 March 2006.
Chien Hsing James Wu David Gottesman Andrew Landahl.
Solid state realisation of Werner quantum states via Kondo spins Ross McKenzie Sam Young Cho Reference: S.Y. Cho and R.H.M, Phys. Rev. A 73, (2006)
NMR Quantum Information Processing and Entanglement R.Laflamme, et al. presented by D. Motter.
Quantum fermions from classical statistics. quantum mechanics can be described by classical statistics !
Introduction to Quantum Information Processing Lecture 4 Michele Mosca.
Dirac Notation and Spectral decomposition Michele Mosca.
Quantum Mechanics from Classical Statistics. what is an atom ? quantum mechanics : isolated object quantum mechanics : isolated object quantum field theory.
School of Physics & Astronomy FACULTY OF MATHEMATICAL & PHYSICAL SCIENCE Parallel Transport & Entanglement Mark Williamson 1, Vlatko Vedral 1 and William.
Entanglement Measures in Quantum Computing About distinguishable and indistinguishable particles, entanglement, exchange and correlation Szilvia Nagy Department.
Quantum correlations. Adam W. Majewski. Quantum entanglement. Ghhjhjj Quantum entanglement is a phenomenon that occurs when particles (subsystems) are.
Presented by: Erik Cox, Shannon Hintzman, Mike Miller, Jacquie Otto, Adam Serdar, Lacie Zimmerman.
1 Introduction to Quantum Information Processing CS 667 / PH 767 / CO 681 / AM 871 Richard Cleve DC 2117 Lecture 14 (2009)
Alice and Bob’s Excellent Adventure
Autumn 2008 EEE8013 Revision lecture 1 Ordinary Differential Equations.
From Flipping Qubits to Programmable Quantum Processors Drinking party Budmerice, 1 st May 2003 Vladimír Bužek, Mário Ziman, Mark Hillery, Reinhard Werner,
Quantum measurements: status and problems Michael B. Mensky P.N.Lebedev Physical Institute Moscow, Russia MARKOV READINGS Moscow, May 12, 2005.
Foray into Relativistic Quantum Information Science: Wigner Rotations and Bell States Chopin Soo Laboratory for Quantum Information Science (LQIS) (
Quantum Factoring Michele Mosca The Fifth Canadian Summer School on Quantum Information August 3, 2005.
Degree of polarization in quantum optics UCMUCM Luis L. Sánchez-Soto, E. C. Yustas Universidad Complutense. Madrid. Spain Andrei B. Klimov Universidad.
Quantum entanglement and Quantum state Tomography Zoltán Scherübl Nanophysics Seminar – Lecture BUTE.
1 Introduction to Quantum Information Processing CS 667 / PH 767 / CO 681 / AM 871 Richard Cleve DC 2117 Lecture 20 (2009)
1 Qubits, time and the equations of physics Salomon S. Mizrahi Departamento de Física, CCET, Universidade Federal de São Carlos Time and Matter October.
H ij Entangle- ment flow multipartite systems [1] Numerically computed times assuming saturated rate equations, along with the lower bound (solid line)
1 entanglement-quantum teleportation entanglement-quantum teleportation entanglement (what is it?) quantum teleportation (intuitive & mathematical) ‘ quantum.
Quantum Entanglement and Distillation in Information Processing Shao-Ming Fei
Phase space, decoherence and the Wigner function for finite dimensional systems. James Yearsley Superviser: Prof. JJ Halliwell. See: Gibbons et. al. quant-ph/
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
Quantum info tools & toys for quantum gravity LOOPS `05 Daniel Terno Perimeter Institute.
1 EE571 PART 3 Random Processes Huseyin Bilgekul Eeng571 Probability and astochastic Processes Department of Electrical and Electronic Engineering Eastern.
ECE 8443 – Pattern Recognition EE 3512 – Signals: Continuous and Discrete Objectives: Eigenfunctions Fourier Series of CT Signals Trigonometric Fourier.
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.
Multipartite Entanglement and its Role in Quantum Algorithms Special Seminar: Ph.D. Lecture by Yishai Shimoni.
Liouville Dynamics and Classical Analogues of Information-Related Quantum Impossible Processes A.R. Plastino University of Pretoria, South Africa A.Daffertshofer.
Basic Q.C. One moose, two moose Red moose, blue moose Live moose, dead moose.
Non classical correlations of two interacting qubits coupled to independent reservoirs R. Migliore CNR-INFM, Research Unit CNISM of Palermo Dipartimento.
IPQI-2010-Anu Venugopalan 1 qubits, quantum registers and gates Anu Venugopalan Guru Gobind Singh Indraprastha Univeristy Delhi _______________________________________________.
Colorado Center for Astrodynamics Research The University of Colorado 1 STATISTICAL ORBIT DETERMINATION Kalman Filter with Process Noise Gauss- Markov.
Non completely positive maps in physics Daniel R Terno Karol Życzkowski Hilary Carteret.
Richard Cleve DC 2117 Introduction to Quantum Information Processing QIC 710 / CS 667 / PH 767 / CO 681 / AM 871 Lecture (2011)
Density matrix and its application. Density matrix An alternative of state-vector (ket) representation for a certain set of state-vectors appearing with.
International Scientific Spring 2016
Natsumi Nagata E-ken Journal Club December 21, 2012 Minimal fields of canonical dimensionality are free S. Weinberg, Phys. Rev. D86, (2012) [ ].
Postulates of Quantum Mechanics
M. Stobińska1, F. Töppel2, P. Sekatski3,
Linear Quantum Error Correction
Outline Introduction Signal, random variable, random process and spectra Analog modulation Analog to digital conversion Digital transmission through baseband.
Invitation to Quantum Information III
Quantum mechanics from classical statistics
Quantum One.
Quantum One.
Quantum computation with classical bits
Stability Analysis of Linear Systems
Maths for Signals and Systems Linear Algebra in Engineering Lectures 13 – 14, Tuesday 8th November 2016 DR TANIA STATHAKI READER (ASSOCIATE PROFFESOR)
Computational approaches for quantum many-body systems
Presentation transcript:

DYNAMICS OF OPEN Q-SYSTES FROM A PERSPECTIVE OF QIT IMS, Imperial College, London, 18 January 2007 Vladimír Bužek Research Center for Quantum Information Slovak Academy of Sciences Bratislava, Slovakia Nicolas Gisin, Mario Ziman, Peter Štelmachovič, Valerio Scarani & Mark Hillery

Motivation Information encoded in a state of a quantum system The system interacts with its (large) environment The information “dilutes” into a reservoir (“equilibrates”) Where the original information goes ? Is the process reversible ? Can we recover diluted information ? Can we derive a master equation? What is the role of quantum correlations in reservoir?

Qubit (computer) basis : Poincare sphere – state space

Physics of information transfer System S - a single qubit initially prepared in the unknown state Reservoir R - composed of N qubits all prepared in the state, which is arbitrary but same for all qubits. The state of reservoir is described by the density matrix. Interaction U - a bipartite unitary operator. We assume that at each time step the system qubit interacts with just a single qubit from the reservoir. Moreover, the system qubit can interact with each of the reservoir qubits at most once. R.Alicki & K.Lendi, Quantum Dynamical Semigroups and Applications, Lecture Notes in Physiscs (Springer, Berlin, 1987) U.Weiss, Quantum Dissipative Systems (World Scientific, Singapore, 1999) B.M.Terhal & D.P.diVincenzo, Phys. Rev. A 61, (2001).

Before and After

t = 0s1s 2s 3s 4s Dilution of quantum information

Definition of quantum homogenizer Homogenization is the process in which is some distance defined on the set of all qubit states. At the output the homogenizer all qubits are approximately in a vicinity of the state. Covariance No cloning theorem

Dynamics of homogenization: Partial Swap Transformation satisfying the conditions of homogenization form a one-parametric family where S is the swap operator acting as The partial swap is the only transformation satisfying the homogenization conditions

Dynamics of homogenization: Partial Swap where and. Let with three-dimensional real vector Defining we find that after n steps the density operator reads where is a matrix acting on a four-dimensional vector

Maps Induced by Partial Swap Note that represents a superoperator induced by a map U and the reservoir state. Let is a trace distance. For this distance the transformation is contractive, i.e. for all states with Banach theorem implies that for all states iterations converge to a fixed point of, i.e. to the state

Homogenization of Gaussian states The signal is in a Gaussian state Reservoir states are Gaussian without displacement The signal after k interactions changes according to

Quantum homogenization – squeezed vacuum signal state reservoir state signal after interactions Homogenization of Gaussian states II

signal after interactions signal state reservoir state many Quantum homogenization – squeezed vacuum Homogenization of Gaussian states II

Entanglement due to homogenization t = 0s1s 2s 3s 4s

Measure of Entanglement: Concurrence Measurement of entanglement: 2-qubit concurrence, Von Neumann entropy, … in the standard basis are the square roots of the eigenvalues of in descending order For multipartite pure states we can define the tangle that measures the entanglement between one qubit and the rest of the system where is state of k-th subsystem.

Entanglement: CKW inequality The CKW inequality V.Coffman, J.Kundu, W.K.Wootters, Phys.Rev.A 61, (2000)] Homogenized qubits saturate the CKW inequality Osborn generalization

Where the information goes? Initially we had and reservoir particles in state For large, and all N+1 particles are in the state Moreover all concurrencies vanish in the limit. Therefore, the entanglement between any pair of qubits is zero, i.e. Also the entanglement between a given qubit and rest of the homogenized system, expressed in terms of the function is zero. Information cannot be lost. The process is UNITARY !

Information in correlations Pairwise entanglement in the limit tends to zero. We have infinitely many infinitely small correlations between qubits and it seems that the required information is lost. But, if we sum up all the mutual concurrencies between all pairs of qubits we obtain a finite value The information about the initial state of the system is “hidden” in mutual correlations between qubits of the homogenized system. Can this information be recovered?

Reversibility Perfect recovery can be performed only when the N + 1 qubits of the output state interact, via the inverse of the original partial-swap operation, in the correct order. Classical information has to be kept in order to reverse quantum process

Stochastic homogenization I Example of a stochastic evolution of the system qubits S with 10 qubits in the reservoir. Bipartite interaction : Initial state of the system: Reduced density matrix of the system after n interactions:

Deterministic vs stochastic homogenization: Spin Gas Stochastic evolution of the system qubit S interacting with a reservoir of 100 qubits. The figure shows one particular stochastic evolution of the system S (red line), the deterministic evolution of the system S (blue line) and the average over 1000 different stochastic evolutions of the system S (pink line) Step in deterministic model vs. step in stochastic model Probability of interaction of the system S in:  Deterministic model:  Stochastic model: Necessity of rescaling

a reservoir composed of 100 qubits one particular stochastic evolution of the system S (red line) up to 500 interactions Reversibility Recovery of the initial state “Spontaneous” recurrence - number of steps needed for 90% recovery is

Master equation & dynamical semigroup Standard approach (e.g. Davies) – continuous unitary evolution on extended system (system + reservoir) Reduced dynamics under various approximations – dynamical continuous semigroup From the conditions CP & continuity of -> dynamical semigroup can be written as Evolution can be expressed via the generator Lindblad master equation

Discrete dynamical semigroup Any collision-like model determines one-parametric semigroup of CPTP maps Semigroup property Question: Can we introduce a continuous time version of this discrete dynamical semigroup?

Discrete dynamical semigroup

From discrete to continuous semigroup Discrete dynamics dynamical semigroup We can derive continuous generalization - generator Decoherence time Decay time

Lindblad master equation

Qubit in correlated reservoir Single-qubit reservoir DO Correlated reservoir Reservoir with no correlations

Bell pair in correlated reservoir I

Bell pair in correlated reservoir II

Bell pair in correlated reservoir III

Conclusions: Infodynamics Dilution of quantum information via homogenization Universality & uniqueness of the partial swap operation Physical realization of contractive maps Reversibility and classical information Stochastic vs deterministic models Lindblad master equation Still many open questions – spin gases, stability of reservoirs Related papers: M.Ziman, P.Stelmachovic, V.Buzek, M.Hillery, V.Scarani, & N.Gisin, Phys.Rev.A 65, (2002)] V.Scarani, M.Ziman, P.Stelmachovic, N.Gisin, & V.Buzek, Phys. Rev. Lett. 88, (2002). D.Nagaj, P.Stelmachovic, V.Buzek, & M.S.Kim, Phys. Rev. A 66, (2002) M.Ziman, P.Stelmachovic, & V.Buzek, Open Sys. & Info Dyn. 12, 81 (2005) M.Ziman & V.Buzek, Phys. Rev. A 72, (2005) M.Ziman & V.Buzek, quant-ph (2005).