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Zeng Lian , Courant Institute KeninG Lu, Brigham Young University. Lyapunov Exponents for Infinite Dimensional Random Dynamical Systems in a Banach Space. International Conference on Random Dynamical Systems Chern Institute of Mathematics, Nankai , June 8-12 2009. Content. - PowerPoint PPT Presentation
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Lyapunov Exponents for Infinite Dimensional Lyapunov Exponents for Infinite Dimensional
Random Dynamical Systems in a Banach SpaceRandom Dynamical Systems in a Banach Space Zeng Lian, Courant Institute Zeng Lian, Courant Institute KeninG Lu, Brigham Young UniversityKeninG Lu, Brigham Young University
International Conference on Random Dynamical SystemsInternational Conference on Random Dynamical Systems Chern Institute of Mathematics, Nankai, June 8-12 2009Chern Institute of Mathematics, Nankai, June 8-12 2009
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ContentContent
1. Random Dynamical Systems2. Basic Problems3. Linear Random Dynamical Systems4. Brief History5. Main Results6. Nonuniform Hyperbolicity
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1. Random Dynamical System1. Random Dynamical Systemss
Example 1: Quasi-period ODE
where is nonlinear
Let be the Haar measure on .
Then
(1) is a probability space and is a DS preserving
(2) Let be the solution of Then
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1. Random Dynamical System1. Random Dynamical Systemss
Example 2. Stochastic Differential Equations
where
•
• is the Brownian motion.
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The classical Wiener Space:
Open compact topology
is the Wiener measure
The dynamical system
is invariant and ergodic under
The solution operator generates RDS
1. Random Dynamical System1. Random Dynamical Systemss
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Example: Random Partial Differential Equation
where -Banach space and is a measurable
dynamical system over probability space
Random dynamical system – solution operator:
1. Random Dynamical System1. Random Dynamical Systemss
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1. Random Dynamical Systems1. Random Dynamical Systems
Metric Dynamical System
Let be a probability space.
Let be a metric dynamical
system:
(i)
(ii)
(iii) preserves the probability measure
Evolution of Noise
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1. Random dynamical systems1. Random dynamical systems
A map
is called a random dynamical system over if
(i) is measurable;
(ii) the mappings form a
cocycle over
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1. Random Dynamical Systems1. Random Dynamical Systems
Time-one map:
Random map generates
the random dynamical system
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2. Basic Problems 2. Basic Problems Mathematical QuestionsMathematical Questions
Two Fundamental Questions:
Mathematical Model
Question 1.
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2. Basic Problems 2. Basic Problems Mathematical QuestionsMathematical Questions
Mathematical Model
Computational Model
Question 2:
Can we trust what we see?
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2. Basic Problems 2. Basic Problems Mathematical QuestionsMathematical Questions
1. Stability
2. Sensitive dependence of initial data
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2. Basic Problems2. Basic Problems
Deterministic Dynamical Systems
Stationary solutions
Eigenvalues
Eigenvectors
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Random Dynamical SystemsRandom Dynamical Systems
Deterministic Dynamical Systems
Periodic Orbits
Floquet exponents
Floquet spaces
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Random Dynamical SystemsRandom Dynamical Systems
Random Dynamical Systems
Orbits
Linearized Systems
Lyapunov exponentsmeasure the average rate of separation of orbits starting from nearby initial points.
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3. 3. Dynamical Behavior of Linear RDSDynamical Behavior of Linear RDS
The Linear random dynamical system generated by S:
Basic Problem:
Find all Lyapunov exponents
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4. Brief History4. Brief History
Finite Dimensional Dynamical SystemsV. Oseledets, 1968 (31 pages)
Existence of Lyapunov exponents
Invarant subspaces,.
Multiplicative Ergodic Theorem
Different ProofsMillionshchikov; Palmer, Johnson, & Sell; Margulis; Kingman;Raghunathan; Ruelle; Mane; Crauel; Ledrappier; Cohen, Kesten, & Newman; Others.
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4.Brief History4.Brief History
Applications: Deterministic Dynamical Systems
Pesin Theory, 1974, 1976, 1977Nonuniform hyperbolicityEntropy formula, chaotic dynamics
Random Dynamical SystemsRuelle inequality, chaotic dynamicsEntropy Formula, Dimension Formula Ruelle, Ladrappia, L-S. Young, …Smooth conjugacyW. Li and K. Lu
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4. Brief History4. Brief History
Infinite Dimensional RDSRuelle, 1982 (Annals of Math)
Random Dynamical Systems in a Separable Hilbert Space.
Multiplicative Ergodic Theorem
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4. Brief History4. Brief History
Basic Problem:
Establish Multiplicative Ergodic Theorem for RDS
Banach space such as
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Brief HistoryBrief History
Infinite Dimensional RDS Mane, 1983
Multiplicative Ergodic Theorem
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4. Brief History4. Brief History
Infinite Dimensional RDS Thieullen, 1987
Multiplicative Ergodic Theorem
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4. Brief History4. Brief History
Infinite Dimensional RDS Flandoli and Schaumlffel, 1991
Multiplicative Ergodic Theorem
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4. Brief History4. Brief History
Infinite Dimensional RDS Schaumlffel, 1991
Multiplicative Ergodic Theorem
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Main ResultsMain Results
Infinite Dimensional RDS Lian & L, Memoirs of AMS 2009
Multiplicative Ergodic Theorem
Difficulties:Random Dynamical Systems No topological structure of the base space Banach Space No inner product structure
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5. Main Results5. Main Results
Settings and Assumptions: --- Separable Banach Space
Measurable metric dynamical system
is strongly measurable map
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5. Main Results5. Main Results
Measure of Noncompactness
Let Kuratowski measure of noncompactness
Index of noncompactness for a map
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5. Main Results5. Main Results
Measure of Noncompactness
If S is a bounded linear operator,
is the radius of essential specrtrum of S
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5. Main Results5. Main Results
Principal Lyapunov Exponent
Exponent of Noncompactness
When LRDS is compact
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5. Main Results5. Main Results
Theorem A (Lian & L, Memoirs of AMS 2009)
Assume that Then, ( -invariant subset of full measure)
(I) there are finitely many Lyapuniv exponents
and invariant splitting
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5. Main Results5. Main Results
such that(1) Invariance:
(2) Lyapunov exponents
for all
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5. Main Results5. Main Results
(3) Exponential decay rate in
and
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5. Main Results5. Main Results
(4) Measurability:
1. are measurable
2. All projections are strongly measurable
(5) All projections are tempered
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5. Main Results5. Main Results
(II) There are many Lyapuniv exponents
and many finite dimensional subpaces
and many infinite dimensional subpaces
such that
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5. Main Results5. Main Results
and(1) Invariance:
(2) Lyapunov exponents
for all
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5. Main Results5. Main Results
(3) Exponential decay rate in
and
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5. Main Results5. Main Results
Theorem B (Lian & L, Memoirs of AMS 2009)
Theorem A holds for continuous time random dynamical systems
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6. 6. Nonuniform HyperbolicityNonuniform Hyperbolicity
Theorem C: There are -invariant random variable >0
and tempered random variable K(¸ 1such that
where are the stable, unstable projections
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7. Random Stable and Unstable Manifolds7. Random Stable and Unstable Manifolds
Theorem D: (Lian & L, Memoirs of AMS 2009)
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7. Random Stable and Unstable Manifolds7. Random Stable and Unstable Manifolds
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88. . ApplicationApplication
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88. . ApplicationApplication
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88. . ApplicationApplication
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99. Outline of Proof. Outline of Proof
• Volume function• Kingman’s additive erogidc theorem• Kato’s space gap • Measurable selection theorem• Measurable Hahn-Banach theorem• Measure theory
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