Physical Fluctuomatics (Tohoku University) 1 Physical Fluctuomatics 13th Quantum-mechanical extensions of probabilistic information processing Kazuyuki.

Slides:



Advertisements
Similar presentations
3 March, 2003University of Glasgow1 Statistical-Mechanical Approach to Probabilistic Inference --- Cluster Variation Method and Generalized Loopy Belief.
Advertisements

Graduate School of Information Sciences, Tohoku University
1 Bayesian Image Modeling by Generalized Sparse Markov Random Fields and Loopy Belief Propagation Kazuyuki Tanaka GSIS, Tohoku University, Sendai, Japan.
Conditional Random Fields
Code and Decoder Design of LDPC Codes for Gbps Systems Jeremy Thorpe Presented to: Microsoft Research
Belief Propagation Kai Ju Liu March 9, Statistical Problems Medicine Finance Internet Computer vision.
24 November, 2011National Tsin Hua University, Taiwan1 Mathematical Structures of Belief Propagation Algorithms in Probabilistic Information Processing.
Physics Fluctuomatics (Tohoku University) 1 Physical Fluctuomatics 2nd Mathematical Preparations (1): Probability and statistics Kazuyuki Tanaka Graduate.
1 物理フラクチュオマティクス論 Physical Fluctuomatics 応用確率過程論 Applied Stochastic Process 第 5 回グラフィカルモデルによる確率的情報処理 5th Probabilistic information processing by means of.
Physics Fluctuomatics / Applied Stochastic Process (Tohoku University) 1 Physical Fluctuomatics Applied Stochastic Process 7th “More is different” and.
Physics Fluctuomatics (Tohoku University) 1 Physical Fluctuomatics 7th~10th Belief propagation Appendix Kazuyuki Tanaka Graduate School of Information.
1 October, 2007 ALT&DS2007 (Sendai, Japan ) 1 Introduction to Probabilistic Image Processing and Bayesian Networks Kazuyuki Tanaka Graduate School of Information.
1 Physical Fluctuomatics 5th and 6th Probabilistic information processing by Gaussian graphical model Kazuyuki Tanaka Graduate School of Information Sciences,
3 September, 2009 SSP2009, Cardiff, UK 1 Probabilistic Image Processing by Extended Gauss-Markov Random Fields Kazuyuki Tanaka Kazuyuki Tanaka, Muneki.
Physics Fluctuomatics / Applied Stochastic Process (Tohoku University) 1 Physical Fluctuomatics Applied Stochastic Process 2nd Probability and its fundamental.
Bayesian Macromodeling for Circuit Level QCA Design Saket Srivastava and Sanjukta Bhanja Department of Electrical Engineering University of South Florida,
Physics Fluctuomatics / Applied Stochastic Process (Tohoku University) 1 Physical Fluctuomatics Applied Stochastic Process 9th Belief propagation Kazuyuki.
28 February, 2003University of Glasgow1 Cluster Variation Method and Probabilistic Image Processing -- Loopy Belief Propagation -- Kazuyuki Tanaka Graduate.
Physical Fuctuomatics (Tohoku University) 1 Physical Fluctuomatics Applied Stochastic Process 1st Review of probabilistic information processing Kazuyuki.
10 December, 2008 CIMCA2008 (Vienna) 1 Statistical Inferences by Gaussian Markov Random Fields on Complex Networks Kazuyuki Tanaka, Takafumi Usui, Muneki.
September 2007 IW-SMI2007, Kyoto 1 A Quantum-Statistical-Mechanical Extension of Gaussian Mixture Model Kazuyuki Tanaka Graduate School of Information.
Tokyo Institute of Technology, Japan Yu Nishiyama and Sumio Watanabe Theoretical Analysis of Accuracy of Gaussian Belief Propagation.
Physics Fluctuomatics (Tohoku University) 1 Physical Fluctuomatics 12th Bayesian network and belief propagation in statistical inference Kazuyuki Tanaka.
14 October, 2010LRI Seminar 2010 (Univ. Paris-Sud)1 Statistical performance analysis by loopy belief propagation in probabilistic image processing Kazuyuki.
29 December, 2008 National Tsing Hua University, Taiwan 1 Introduction to Probabilistic Image Processing and Bayesian Networks Kazuyuki Tanaka Graduate.
Physics Fluctuomatics/Applied Stochastic Process (Tohoku University) 1 Physical Fluctuomatics Applied Stochastic Process 3rd Random variable, probability.
Physics Fluctuomatics (Tohoku University) 1 Physical Fluctuomatics 7th~10th Belief propagation Kazuyuki Tanaka Graduate School of Information Sciences,
General ideas to communicate Dynamic model Noise Propagation of uncertainty Covariance matrices Correlations and dependencs.
Phisical Fluctuomatics (Tohoku University) 1 Physical Fluctuomatics 4th Maximum likelihood estimation and EM algorithm Kazuyuki Tanaka Graduate School.
Physics Fluctuomatics (Tohoku University) 1 Physical Fluctuomatics 3rd Random variable, probability distribution and probability density function Kazuyuki.
Physical Fuctuomatics (Tohoku University) 1 Physical Fluctuomatics 1st Review of probabilistic information processing Kazuyuki Tanaka Graduate School of.
Belief Propagation and its Generalizations Shane Oldenburger.
PHY 520 Introduction Christopher Crawford
Graduate School of Information Sciences, Tohoku University
Daphne Koller Overview Conditional Probability Queries Probabilistic Graphical Models Inference.
Physics Fluctuomatics (Tohoku University) 1 Physical Fluctuomatics 2nd Probability and its fundamental properties Kazuyuki Tanaka Graduate School of Information.
30 November, 2005 CIMCA2005, Vienna 1 Statistical Learning Procedure in Loopy Belief Propagation for Probabilistic Image Processing Kazuyuki Tanaka Graduate.
ICPR2004 (24 July, 2004, Cambridge) 1 Probabilistic image processing based on the Q-Ising model by means of the mean- field method and loopy belief propagation.
10 October, 2007 University of Glasgow 1 EM Algorithm with Markov Chain Monte Carlo Method for Bayesian Image Analysis Kazuyuki Tanaka Graduate School.
Graduate School of Information Sciences, Tohoku University
マルコフ確率場の統計的機械学習の数理と データサイエンスへの展開 Statistical Machine Learning in Markov Random Field and Expansion to Data Sciences 田中和之 東北大学大学院情報科学研究科 Kazuyuki Tanaka.
Physical Fluctuomatics 13th Quantum-mechanical extensions of probabilistic information processing Kazuyuki Tanaka Graduate School of Information Sciences,
Statistical-Mechanical Approach to Probabilistic Image Processing -- Loopy Belief Propagation and Advanced Mean-Field Method -- Kazuyuki Tanaka and Noriko.
Graduate School of Information Sciences, Tohoku University
Graduate School of Information Sciences, Tohoku University
Graduate School of Information Sciences, Tohoku University
Sublinear Computational Time Modeling in Statistical Machine Learning Theory for Markov Random Fields Kazuyuki Tanaka GSIS, Tohoku University, Sendai,
Graduate School of Information Sciences, Tohoku University
Graduate School of Information Sciences, Tohoku University, Japan
Graduate School of Information Sciences, Tohoku University
Graduate School of Information Sciences, Tohoku University
Graduate School of Information Sciences Tohoku University, Japan
量子情報処理にむけての クラスター変分法と確率伝搬法の定式化
Graduate School of Information Sciences, Tohoku University
一般化された確率伝搬法の数学的構造 東北大学大学院情報科学研究科 田中和之
Cluster Variation Method for Correlation Function of Probabilistic Model with Loopy Graphical Structure Kazuyuki Tanaka Graduate School of Information.
Graduate School of Information Sciences, Tohoku University
Physical Fluctuomatics 7th~10th Belief propagation
Expectation-Maximization & Belief Propagation
Graduate School of Information Sciences, Tohoku University
Advanced Mean Field Methods in Quantum Probabilistic Inference
Probabilistic image processing and Bayesian network
Probabilistic image processing and Bayesian network
Graduate School of Information Sciences, Tohoku University
Cluster Variation Method for Correlation Function of Probabilistic Model with Loopy Graphical Structure Kazuyuki Tanaka Graduate School of Information.
Graduate School of Information Sciences, Tohoku University
Graduate School of Information Sciences, Tohoku University
Graduate School of Information Sciences, Tohoku University
Kazuyuki Tanaka Graduate School of Information Sciences
Presentation transcript:

Physical Fluctuomatics (Tohoku University) 1 Physical Fluctuomatics 13th Quantum-mechanical extensions of probabilistic information processing Kazuyuki Tanaka Graduate School of Information Sciences, Tohoku University

Contents 1. Introduction 2. Quantum System and Density Matrix 3. Transformation between Density Matrix and Probability Distribution by using Suzuki-Trotter Formula 4. Quantum Belief Propagation 5. Summary Physical Fluctuomatics (Tohoku University)2

3 Probability Distribution: 2 N - tuple summation Probability Distribution and Density Matrix Density Matrix: Diagonalization of 2 N × 2 N Matrix

Physical Fluctuomatics (Tohoku University)4 Mathematical Framework of Probabilistic Information Processing Such computations are difficult in quantum systems. For any matrices A and B, it is not always valid that

Contents 1. Introduction 2. Quantum System and Density Matrix 3. Transformation between Density Matrix and Probability Distribution by using Suzuki-Trotter Formula 4. Quantum Belief Propagation 5. Summary Physical Fluctuomatics (Tohoku University)5

6 Quantum State of One Node All the possible states in classical Systems are two as follows: Two vectors in two-dimensional space

Physical Fluctuomatics (Tohoku University)7 Quantum State of One Node 10 0 Quantum states are expressed in terms of superpositions of two classical states Quantum states are expressed in terms of any position vectors on unit circle. Classical States are expressed in terms of two position vectors The coefficients can take complex numbers as well as real numbers.

Physical Fluctuomatics (Tohoku University)8 Probability Distribution

Physical Fluctuomatics (Tohoku University)9 Density Matrix

Physical Fluctuomatics (Tohoku University)10 Quantum State of One Node and Pauli Spin Matrices

Physical Fluctuomatics (Tohoku University)11 Quantum State of One Node and Pauli Spin Matrices

Physical Fluctuomatics (Tohoku University)12 Quantum State of One Node and Pauli Spin Matrices

Physical Fluctuomatics (Tohoku University)13 Quantum State of Two Nodes 12

Physical Fluctuomatics (Tohoku University)14 Transition Matrix of Two Nodes Inner Product of same states provides a diagonal element. Inner Product of different states provides an off-diagonal element. 12

Physical Fluctuomatics (Tohoku University)15 Hamiltonian and Density Matrix Hamiltonian Density Matrix 12

Physical Fluctuomatics (Tohoku University)16 Density Matrix and Probability Distribution Probability Distribution P(x 1,x 2 ) H is a diagonal matrix and each diagonal element is defined by ln P(x 1,x 2 ) 12

Physical Fluctuomatics (Tohoku University)17 Computation of Density Matrix Statistical quantities of the density matrix can be calculated by diagonalising the Hamiltonian H. 12

Physical Fluctuomatics (Tohoku University)18 Probability Distribution and Density Matrix Each state and it corresponding probability Classical State Quantum State 21

Physical Fluctuomatics (Tohoku University)19 Marginal Probability Distribution and Reduced Density Matrix Marginal Probability Distribution Reduced Density Matrix Sum of random variables of all the nodes except the node i Partial trace for the freedom of all the nodes except the node i

Physical Fluctuomatics (Tohoku University)20 Reduced Density Matrix Partial trace under fixed state at node 1 1 2

Physical Fluctuomatics (Tohoku University)21 Reduced Density Matrix Partial trace under fixed state at node 2 12

Physical Fluctuomatics (Tohoku University)22 Quantum Heisenberg Model with Two Nodes 12

Physical Fluctuomatics (Tohoku University)23 Quantum Heisenberg Model with Two Nodes 12

Physical Fluctuomatics (Tohoku University)24 Eigen States of Quantum Heisenberg Model with Two Nodes 12

Physical Fluctuomatics (Tohoku University)25 Computation of Density Matrix of Quantum Heisenberg Model with Two Nodes 12

Physical Fluctuomatics (Tohoku University)26 Representationon of Ising Model with Two Nodes by Density Matrix Diagonal Elements correspond to Probability Distribution of Ising Model. Probability Distribution of Ising Model Density Matrix 12

Physical Fluctuomatics (Tohoku University)27 Transverse Ising Model Density Matrix 12

Physical Fluctuomatics (Tohoku University)28 Density Matrix of Three Nodes 2 3 x2 3 Matrix = +

Physical Fluctuomatics (Tohoku University)29 Density Matrix of Three Nodes 12 3

Physical Fluctuomatics (Tohoku University)30 Density Matrix of Three Nodes 1 23

Contents 1. Introduction 2. Quantum System and Density Matrix 3. Transformation between Density Matrix and Probability Distribution by using Suzuki-Trotter Formula 4. Quantum Belief Propagation 5. Summary Physical Fluctuomatics (Tohoku University)31

Difficulty of Quantum Systems Addition and Subtraction Formula of Exponential Function is not always valid. 32Physical Fluctuomatics (Tohoku University)

Suzuki-Trotter Formula n: Trotter number 33Physical Fluctuomatics (Tohoku University)

Suzuki-Trotter Formula n: Trotter number Density Matrix ST Formula Σ Probability Distribution 34Physical Fluctuomatics (Tohoku University)

Suzuki-Trotter Formula Density Matrix ST Formula Σ Probability Distribution Statistical quantities can be computed by using belief propagation of graphical model on 3×n ladder graph Quantum System on Chain Graph with Three Nodes 35Physical Fluctuomatics (Tohoku University)

Contents 1. Introduction 2. Quantum System and Density Matrix 3. Transformation between Density Matrix and Probability Distribution by using Suzuki-Trotter Formula 4. Quantum Belief Propagation 5. Summary Physical Fluctuomatics (Tohoku University)36

Physical Fluctuomatics (Tohoku University)37 Density Matrix and Reduced Density Matrix 1 H {i,j} is a 2 9 ×2 9 matrix.

Physical Fluctuomatics (Tohoku University)38 Density Matrix and Reduced Density Matrix Reduced Density Matrix Reducibility Condition

Physical Fluctuomatics (Tohoku University)39 Approximate Expressions of Reduced Density Matrices in Quantum Belief Propagation j i j i i ij

Physical Fluctuomatics (Tohoku University)40 Message Passing Rule of Quantum Belief Propagation Message Passing Rule j i Output

Contents 1. Introduction 2. Quantum System and Density Matrix 3. Transformation between Density Matrix and Probability Distribution by using Suzuki-Trotter Formula 4. Quantum Belief Propagation 5. Summary Physical Fluctuomatics (Tohoku University)41

Physical Fluctuomatics (Tohoku University)42 Summary Probability Distribution and Density Matrix Reduced Density Matrix Quantum Heisenberg Model Suzuki Trotter Formula Quantum Belief Propagation

Physical Fluctuomatics (Tohoku University)43 My works of Information Processing by using in Quantum Probabilistic Model and Quantum Belief Propagation K. Tanaka and T. Horiguchi: Quantum Statistical-Mechanical Iterative Method in Image Restoration, IEICE Transactions (A), vol.J80-A, no.12, pp , December 1997 (in Japanese); translated in Electronics and Communications in Japan, Part 3: Fundamental Electronic Science, vol.83, no.3, pp.84-94, March K. Tanaka: Image Restorations by using Compound Gauss- Markov Random Field Model with Quantized Line Fields, IEICE Transactions (D-II), vol.J84-D-II, no.4, pp , April 2001 (in Japanese); see also Section 5.2 in K. Tanaka, Journal of Physics A: Mathematical and General, vol.35, no.37, pp.R81- R150, September K. Tanaka: Mathematical Structures of Loopy Belief Propagation and Cluster Variation Method, Journal of Physics: Conference Series, vol.143, article no , pp.1-18, January 2009