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Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic Systems Examples Onsager Equation Relaxation kinetics Fluids and Paricles: Doodads and Kinetics Peter Constantin Department of Mathematics The University of Chicago CIME, Cetraro September 2010

Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

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Page 1: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Fluids and Paricles: Doodads and Kinetics

Peter Constantin

Department of MathematicsThe University of Chicago

CIME, Cetraro September 2010

Page 2: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Outline:

1 Equilibrium: Onsager Equation on Metric Spaces

2 Kinetics: Nonlinear Fokker-Planck Equation

3 Gradient System in Metric Spaces

Page 3: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Outline:

1 Equilibrium: Onsager Equation on Metric Spaces

2 Kinetics: Nonlinear Fokker-Planck Equation

3 Gradient System in Metric Spaces

Page 4: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Outline:

1 Equilibrium: Onsager Equation on Metric Spaces

2 Kinetics: Nonlinear Fokker-Planck Equation

3 Gradient System in Metric Spaces

Page 5: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Major Problems

1 Modeling of interactions in the appropriate phase space

2 Relaxation mechanisms in the appropriate phase space

3 Derivation of Micro-Macro coupling

4 PDE existence theory for coupled system

5 Dimension reduction

Page 6: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Major Problems

1 Modeling of interactions in the appropriate phase space

2 Relaxation mechanisms in the appropriate phase space

3 Derivation of Micro-Macro coupling

4 PDE existence theory for coupled system

5 Dimension reduction

Page 7: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Major Problems

1 Modeling of interactions in the appropriate phase space

2 Relaxation mechanisms in the appropriate phase space

3 Derivation of Micro-Macro coupling

4 PDE existence theory for coupled system

5 Dimension reduction

Page 8: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Major Problems

1 Modeling of interactions in the appropriate phase space

2 Relaxation mechanisms in the appropriate phase space

3 Derivation of Micro-Macro coupling

4 PDE existence theory for coupled system

5 Dimension reduction

Page 9: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Major Problems

1 Modeling of interactions in the appropriate phase space

2 Relaxation mechanisms in the appropriate phase space

3 Derivation of Micro-Macro coupling

4 PDE existence theory for coupled system

5 Dimension reduction

Page 10: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

• Configuration space: M = (locally) compact, separable,metric space, d distance. m ∈ M = corpus = doodad.

• Reference measure: dµ – Borel Probability on M.• Corpora state f (m)dµ(m) – Probabililty, AC w.r. dµ.• Interaction kernel k : M ×M → R+,• symmetric: k(m, p) = k(p,m)• uniformly bi-Lipschitz:

|k(m, n)− k(p, n)| ≤ Ld(m, p)

• Potential U[f ](m) =∫M k(m, p)f (p)dµ(p)

• Potential U = micro-micro interaction• Free Energy

E [f ] =

∫Mf log fdµ+

1

2

∫MU[f ]fdµ

• Minima of Free Energy: Onsager Equation

f = Z−1e−U[f ].

Page 11: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

• Configuration space: M = (locally) compact, separable,metric space, d distance. m ∈ M = corpus = doodad.

• Reference measure: dµ – Borel Probability on M.

• Corpora state f (m)dµ(m) – Probabililty, AC w.r. dµ.• Interaction kernel k : M ×M → R+,• symmetric: k(m, p) = k(p,m)• uniformly bi-Lipschitz:

|k(m, n)− k(p, n)| ≤ Ld(m, p)

• Potential U[f ](m) =∫M k(m, p)f (p)dµ(p)

• Potential U = micro-micro interaction• Free Energy

E [f ] =

∫Mf log fdµ+

1

2

∫MU[f ]fdµ

• Minima of Free Energy: Onsager Equation

f = Z−1e−U[f ].

Page 12: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

• Configuration space: M = (locally) compact, separable,metric space, d distance. m ∈ M = corpus = doodad.

• Reference measure: dµ – Borel Probability on M.• Corpora state f (m)dµ(m) – Probabililty, AC w.r. dµ.

• Interaction kernel k : M ×M → R+,• symmetric: k(m, p) = k(p,m)• uniformly bi-Lipschitz:

|k(m, n)− k(p, n)| ≤ Ld(m, p)

• Potential U[f ](m) =∫M k(m, p)f (p)dµ(p)

• Potential U = micro-micro interaction• Free Energy

E [f ] =

∫Mf log fdµ+

1

2

∫MU[f ]fdµ

• Minima of Free Energy: Onsager Equation

f = Z−1e−U[f ].

Page 13: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

• Configuration space: M = (locally) compact, separable,metric space, d distance. m ∈ M = corpus = doodad.

• Reference measure: dµ – Borel Probability on M.• Corpora state f (m)dµ(m) – Probabililty, AC w.r. dµ.• Interaction kernel k : M ×M → R+,

• symmetric: k(m, p) = k(p,m)• uniformly bi-Lipschitz:

|k(m, n)− k(p, n)| ≤ Ld(m, p)

• Potential U[f ](m) =∫M k(m, p)f (p)dµ(p)

• Potential U = micro-micro interaction• Free Energy

E [f ] =

∫Mf log fdµ+

1

2

∫MU[f ]fdµ

• Minima of Free Energy: Onsager Equation

f = Z−1e−U[f ].

Page 14: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

• Configuration space: M = (locally) compact, separable,metric space, d distance. m ∈ M = corpus = doodad.

• Reference measure: dµ – Borel Probability on M.• Corpora state f (m)dµ(m) – Probabililty, AC w.r. dµ.• Interaction kernel k : M ×M → R+,• symmetric: k(m, p) = k(p,m)

• uniformly bi-Lipschitz:

|k(m, n)− k(p, n)| ≤ Ld(m, p)

• Potential U[f ](m) =∫M k(m, p)f (p)dµ(p)

• Potential U = micro-micro interaction• Free Energy

E [f ] =

∫Mf log fdµ+

1

2

∫MU[f ]fdµ

• Minima of Free Energy: Onsager Equation

f = Z−1e−U[f ].

Page 15: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

• Configuration space: M = (locally) compact, separable,metric space, d distance. m ∈ M = corpus = doodad.

• Reference measure: dµ – Borel Probability on M.• Corpora state f (m)dµ(m) – Probabililty, AC w.r. dµ.• Interaction kernel k : M ×M → R+,• symmetric: k(m, p) = k(p,m)• uniformly bi-Lipschitz:

|k(m, n)− k(p, n)| ≤ Ld(m, p)

• Potential U[f ](m) =∫M k(m, p)f (p)dµ(p)

• Potential U = micro-micro interaction• Free Energy

E [f ] =

∫Mf log fdµ+

1

2

∫MU[f ]fdµ

• Minima of Free Energy: Onsager Equation

f = Z−1e−U[f ].

Page 16: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

• Configuration space: M = (locally) compact, separable,metric space, d distance. m ∈ M = corpus = doodad.

• Reference measure: dµ – Borel Probability on M.• Corpora state f (m)dµ(m) – Probabililty, AC w.r. dµ.• Interaction kernel k : M ×M → R+,• symmetric: k(m, p) = k(p,m)• uniformly bi-Lipschitz:

|k(m, n)− k(p, n)| ≤ Ld(m, p)

• Potential U[f ](m) =∫M k(m, p)f (p)dµ(p)

• Potential U = micro-micro interaction• Free Energy

E [f ] =

∫Mf log fdµ+

1

2

∫MU[f ]fdµ

• Minima of Free Energy: Onsager Equation

f = Z−1e−U[f ].

Page 17: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

• Configuration space: M = (locally) compact, separable,metric space, d distance. m ∈ M = corpus = doodad.

• Reference measure: dµ – Borel Probability on M.• Corpora state f (m)dµ(m) – Probabililty, AC w.r. dµ.• Interaction kernel k : M ×M → R+,• symmetric: k(m, p) = k(p,m)• uniformly bi-Lipschitz:

|k(m, n)− k(p, n)| ≤ Ld(m, p)

• Potential U[f ](m) =∫M k(m, p)f (p)dµ(p)

• Potential U = micro-micro interaction

• Free Energy

E [f ] =

∫Mf log fdµ+

1

2

∫MU[f ]fdµ

• Minima of Free Energy: Onsager Equation

f = Z−1e−U[f ].

Page 18: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

• Configuration space: M = (locally) compact, separable,metric space, d distance. m ∈ M = corpus = doodad.

• Reference measure: dµ – Borel Probability on M.• Corpora state f (m)dµ(m) – Probabililty, AC w.r. dµ.• Interaction kernel k : M ×M → R+,• symmetric: k(m, p) = k(p,m)• uniformly bi-Lipschitz:

|k(m, n)− k(p, n)| ≤ Ld(m, p)

• Potential U[f ](m) =∫M k(m, p)f (p)dµ(p)

• Potential U = micro-micro interaction• Free Energy

E [f ] =

∫Mf log fdµ+

1

2

∫MU[f ]fdµ

• Minima of Free Energy: Onsager Equation

f = Z−1e−U[f ].

Page 19: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

• Configuration space: M = (locally) compact, separable,metric space, d distance. m ∈ M = corpus = doodad.

• Reference measure: dµ – Borel Probability on M.• Corpora state f (m)dµ(m) – Probabililty, AC w.r. dµ.• Interaction kernel k : M ×M → R+,• symmetric: k(m, p) = k(p,m)• uniformly bi-Lipschitz:

|k(m, n)− k(p, n)| ≤ Ld(m, p)

• Potential U[f ](m) =∫M k(m, p)f (p)dµ(p)

• Potential U = micro-micro interaction• Free Energy

E [f ] =

∫Mf log fdµ+

1

2

∫MU[f ]fdµ

• Minima of Free Energy: Onsager Equation

f = Z−1e−U[f ].

Page 20: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Examples: packing of soft spheres, low energy many particlequantum systems, ensembles of stick-and-ball models ofmolecules.

m is the system not the particle.

Goals:

1 Existence theory for solutions of Onsager’s equation

2 Classification of high intensity limits

3 Selection mechanisms for high intensity limits

4 Gradient system relaxation

Page 21: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Examples: packing of soft spheres, low energy many particlequantum systems, ensembles of stick-and-ball models ofmolecules. m is the system not the particle.

Goals:

1 Existence theory for solutions of Onsager’s equation

2 Classification of high intensity limits

3 Selection mechanisms for high intensity limits

4 Gradient system relaxation

Page 22: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Examples: packing of soft spheres, low energy many particlequantum systems, ensembles of stick-and-ball models ofmolecules. m is the system not the particle.

Goals:

1 Existence theory for solutions of Onsager’s equation

2 Classification of high intensity limits

3 Selection mechanisms for high intensity limits

4 Gradient system relaxation

Page 23: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Examples: packing of soft spheres, low energy many particlequantum systems, ensembles of stick-and-ball models ofmolecules. m is the system not the particle.

Goals:

1 Existence theory for solutions of Onsager’s equation

2 Classification of high intensity limits

3 Selection mechanisms for high intensity limits

4 Gradient system relaxation

Page 24: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Example: Rods, Maier-Saupe potential

M = Sn−1, dµ = area.

U[f ](p) = −b∫

Sn−1

((p · q)2 − 1

n

)f (q)dµ

b = intensity, inverse temperature.

Page 25: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Dimension Reduction, Maier-Saupe

n × n symmetric, traceless matrix S :

S 7→ Z (S)

Z (S) =

∫Sn−1

eb(Sijmimj )dµ.

fS(m) = (Z (S))−1eb(Sijmimj )

σ(S)ij =

∫Sn−1

(mimj −

δijn

)fS(m)dµ.

TheoremOnsager’s equation with Maier-Saupe potential is equivalent to

σ(S) = S .

Page 26: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Dimension Reduction, Maier-Saupe

n × n symmetric, traceless matrix S :

S 7→ Z (S)

Z (S) =

∫Sn−1

eb(Sijmimj )dµ.

fS(m) = (Z (S))−1eb(Sijmimj )

σ(S)ij =

∫Sn−1

(mimj −

δijn

)fS(m)dµ.

TheoremOnsager’s equation with Maier-Saupe potential is equivalent to

σ(S) = S .

Page 27: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Dimension Reduction, Maier-Saupe

n × n symmetric, traceless matrix S :

S 7→ Z (S)

Z (S) =

∫Sn−1

eb(Sijmimj )dµ.

fS(m) = (Z (S))−1eb(Sijmimj )

σ(S)ij =

∫Sn−1

(mimj −

δijn

)fS(m)dµ.

TheoremOnsager’s equation with Maier-Saupe potential is equivalent to

σ(S) = S .

Page 28: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Dimension Reduction, Maier-Saupe

n × n symmetric, traceless matrix S :

S 7→ Z (S)

Z (S) =

∫Sn−1

eb(Sijmimj )dµ.

fS(m) = (Z (S))−1eb(Sijmimj )

σ(S)ij =

∫Sn−1

(mimj −

δijn

)fS(m)dµ.

TheoremOnsager’s equation with Maier-Saupe potential is equivalent to

σ(S) = S .

Page 29: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Onsager Equation, Maier-Saupe n = 3.

S ij = λiδij

λi ∈ [−13 ,

23 ],

λ1 + λ2 + λ3 = 0.

Let

v1 =1

2(λ1 + λ2), v2 =

1

2(λ1 − λ2).

y1(p) = 1− 3p2

y2(p, t) = (1− p2) cos t

for (p, t) ∈ K = [−1, 1]× [0, 2π].

y = y(p, t) = (y1(p), y2(p, t)), v = (v1, v2).

Page 30: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Onsager Equation, Maier-Saupe n = 3.

S ij = λiδij

λi ∈ [−13 ,

23 ],

λ1 + λ2 + λ3 = 0.

Let

v1 =1

2(λ1 + λ2), v2 =

1

2(λ1 − λ2).

y1(p) = 1− 3p2

y2(p, t) = (1− p2) cos t

for (p, t) ∈ K = [−1, 1]× [0, 2π].

y = y(p, t) = (y1(p), y2(p, t)), v = (v1, v2).

Page 31: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Onsager Equation, Maier-Saupe n = 3.

S ij = λiδij

λi ∈ [−13 ,

23 ],

λ1 + λ2 + λ3 = 0.

Let

v1 =1

2(λ1 + λ2), v2 =

1

2(λ1 − λ2).

y1(p) = 1− 3p2

y2(p, t) = (1− p2) cos t

for (p, t) ∈ K = [−1, 1]× [0, 2π].

y = y(p, t) = (y1(p), y2(p, t)), v = (v1, v2).

Page 32: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

TheoremLet

Z2(v) =

∫K

ebv ·y(p,t)dpdt

F(v) = log(Z2(v))− b(3v21 + v22

).

Onsager’s equation: critical points of F , v ∈ [−13 ,

23 ]× [0, 12 ],

i.e.: 6v1 = [y1](v)2v2 = [y2](v)

where, for any φ : K → R,

[φ](v) = (Z2(v))−1∫Kφ(p, t)ebv ·y(p,t)dpdt

Page 33: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Limit b →∞

[φ] =

∫S2

φ(m)f (m)dµ.

Isotropic:

limb→∞

[φ] =1

∫S2

φ(p)dµ

Oblate:

limb→∞

[φ] =1

∫ 2π

0φ(cosϕ, sinϕ, 0)dϕ

Prolate:limb→∞

[φ] = φ(m), m ∈ S2.

Page 34: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Limit b →∞

[φ] =

∫S2

φ(m)f (m)dµ.

Isotropic:

limb→∞

[φ] =1

∫S2

φ(p)dµ

Oblate:

limb→∞

[φ] =1

∫ 2π

0φ(cosϕ, sinϕ, 0)dϕ

Prolate:limb→∞

[φ] = φ(m), m ∈ S2.

Page 35: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Limit b →∞

[φ] =

∫S2

φ(m)f (m)dµ.

Isotropic:

limb→∞

[φ] =1

∫S2

φ(p)dµ

Oblate:

limb→∞

[φ] =1

∫ 2π

0φ(cosϕ, sinϕ, 0)dϕ

Prolate:limb→∞

[φ] = φ(m), m ∈ S2.

Page 36: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Limit b →∞

[φ] =

∫S2

φ(m)f (m)dµ.

Isotropic:

limb→∞

[φ] =1

∫S2

φ(p)dµ

Oblate:

limb→∞

[φ] =1

∫ 2π

0φ(cosϕ, sinϕ, 0)dϕ

Prolate:limb→∞

[φ] = φ(m), m ∈ S2.

Page 37: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Freely Articulated N-corpora

M = M1 × · · · ×MN , dµ = Πdµj

u(p1, q1, p2, q2, . . . ) =∑i

ui (pi , qi )

U[f ] =N∑i=1

Ui [f ], with

Ui [f ](pi ) =

∫Mui (pi , qi )f (q1, . . . qN)dµ(q)

Onsager Equation f = Z−1e−U f

Z = ΠNj=1Zj , with Zj =

∫Mj

e−Uj [fj ]dµj , fj = (Zj)−1e−Uj [fj ]

f (p1, . . . pN) = f1(p1)f (p2) . . . fN(pN) product measure

Page 38: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Freely Articulated N-corpora

M = M1 × · · · ×MN , dµ = Πdµj

u(p1, q1, p2, q2, . . . ) =∑i

ui (pi , qi )

U[f ] =N∑i=1

Ui [f ], with

Ui [f ](pi ) =

∫Mui (pi , qi )f (q1, . . . qN)dµ(q)

Onsager Equation f = Z−1e−U f

Z = ΠNj=1Zj , with Zj =

∫Mj

e−Uj [fj ]dµj , fj = (Zj)−1e−Uj [fj ]

f (p1, . . . pN) = f1(p1)f (p2) . . . fN(pN) product measure

Page 39: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Freely Articulated N-corpora

M = M1 × · · · ×MN , dµ = Πdµj

u(p1, q1, p2, q2, . . . ) =∑i

ui (pi , qi )

U[f ] =N∑i=1

Ui [f ],

with

Ui [f ](pi ) =

∫Mui (pi , qi )f (q1, . . . qN)dµ(q)

Onsager Equation f = Z−1e−U f

Z = ΠNj=1Zj , with Zj =

∫Mj

e−Uj [fj ]dµj , fj = (Zj)−1e−Uj [fj ]

f (p1, . . . pN) = f1(p1)f (p2) . . . fN(pN) product measure

Page 40: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Freely Articulated N-corpora

M = M1 × · · · ×MN , dµ = Πdµj

u(p1, q1, p2, q2, . . . ) =∑i

ui (pi , qi )

U[f ] =N∑i=1

Ui [f ], with

Ui [f ](pi ) =

∫Mui (pi , qi )f (q1, . . . qN)dµ(q)

Onsager Equation f = Z−1e−U f

Z = ΠNj=1Zj , with Zj =

∫Mj

e−Uj [fj ]dµj , fj = (Zj)−1e−Uj [fj ]

f (p1, . . . pN) = f1(p1)f (p2) . . . fN(pN) product measure

Page 41: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Freely Articulated N-corpora

M = M1 × · · · ×MN , dµ = Πdµj

u(p1, q1, p2, q2, . . . ) =∑i

ui (pi , qi )

U[f ] =N∑i=1

Ui [f ], with

Ui [f ](pi ) =

∫Mui (pi , qi )f (q1, . . . qN)dµ(q)

Onsager Equation f = Z−1e−U f

Z = ΠNj=1Zj , with Zj =

∫Mj

e−Uj [fj ]dµj , fj = (Zj)−1e−Uj [fj ]

f (p1, . . . pN) = f1(p1)f (p2) . . . fN(pN) product measure

Page 42: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Freely Articulated N-corpora

M = M1 × · · · ×MN , dµ = Πdµj

u(p1, q1, p2, q2, . . . ) =∑i

ui (pi , qi )

U[f ] =N∑i=1

Ui [f ], with

Ui [f ](pi ) =

∫Mui (pi , qi )f (q1, . . . qN)dµ(q)

Onsager Equation f = Z−1e−U f

Z = ΠNj=1Zj , with Zj =

∫Mj

e−Uj [fj ]dµj , fj = (Zj)−1e−Uj [fj ]

f (p1, . . . pN) = f1(p1)f (p2) . . . fN(pN) product measure

Page 43: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Freely Articulated N-corpora

M = M1 × · · · ×MN , dµ = Πdµj

u(p1, q1, p2, q2, . . . ) =∑i

ui (pi , qi )

U[f ] =N∑i=1

Ui [f ], with

Ui [f ](pi ) =

∫Mui (pi , qi )f (q1, . . . qN)dµ(q)

Onsager Equation f = Z−1e−U f

Z = ΠNj=1Zj , with Zj =

∫Mj

e−Uj [fj ]dµj , fj = (Zj)−1e−Uj [fj ]

f (p1, . . . pN) = f1(p1)f (p2) . . . fN(pN) product measure

Page 44: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Example of Interacting Corpora

M = S1, M = S1 × S1.

U[f ](p1, p2) =b∫T2 ‖e(p1) ∧ e(p2)− e(q1) ∧ e(q2)‖2f (q1, q2)dq1dq2

with e(p) = (cos p, sin p) if p ∈ [0, 2π].

‖e(p1)∧e(p2)−e(q1)∧e(q2)‖2 = (sin(p1 − p2)− sin(q1 − q2))2

Dimension reduction: Onsager’s equation f = Z−1e−U[f ]

reduces toa = [sin θ](a)

with [φ](a) =

∫ 2π0 φ(θ)g(θ)dθ

g(θ) = Z−1e−b(sin(θ)−a)2

Z =∫ 2π0 e−b(sin(θ)−a)

2dθ

Page 45: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Example of Interacting Corpora

M = S1, M = S1 × S1.

U[f ](p1, p2) =b∫T2 ‖e(p1) ∧ e(p2)− e(q1) ∧ e(q2)‖2f (q1, q2)dq1dq2

with e(p) = (cos p, sin p) if p ∈ [0, 2π].

‖e(p1)∧e(p2)−e(q1)∧e(q2)‖2 = (sin(p1 − p2)− sin(q1 − q2))2

Dimension reduction: Onsager’s equation f = Z−1e−U[f ]

reduces toa = [sin θ](a)

with [φ](a) =

∫ 2π0 φ(θ)g(θ)dθ

g(θ) = Z−1e−b(sin(θ)−a)2

Z =∫ 2π0 e−b(sin(θ)−a)

2dθ

Page 46: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Example of Interacting Corpora

M = S1, M = S1 × S1.

U[f ](p1, p2) =b∫T2 ‖e(p1) ∧ e(p2)− e(q1) ∧ e(q2)‖2f (q1, q2)dq1dq2

with e(p) = (cos p, sin p) if p ∈ [0, 2π].

‖e(p1)∧e(p2)−e(q1)∧e(q2)‖2 = (sin(p1 − p2)− sin(q1 − q2))2

Dimension reduction: Onsager’s equation f = Z−1e−U[f ]

reduces toa = [sin θ](a)

with [φ](a) =

∫ 2π0 φ(θ)g(θ)dθ

g(θ) = Z−1e−b(sin(θ)−a)2

Z =∫ 2π0 e−b(sin(θ)−a)

2dθ

Page 47: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Example of Interacting Corpora

M = S1, M = S1 × S1.

U[f ](p1, p2) =b∫T2 ‖e(p1) ∧ e(p2)− e(q1) ∧ e(q2)‖2f (q1, q2)dq1dq2

with e(p) = (cos p, sin p) if p ∈ [0, 2π].

‖e(p1)∧e(p2)−e(q1)∧e(q2)‖2 = (sin(p1 − p2)− sin(q1 − q2))2

Dimension reduction: Onsager’s equation f = Z−1e−U[f ]

reduces toa = [sin θ](a)

with [φ](a) =

∫ 2π0 φ(θ)g(θ)dθ

g(θ) = Z−1e−b(sin(θ)−a)2

Z =∫ 2π0 e−b(sin(θ)−a)

2dθ

Page 48: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Example of Interacting Corpora

M = S1, M = S1 × S1.

U[f ](p1, p2) =b∫T2 ‖e(p1) ∧ e(p2)− e(q1) ∧ e(q2)‖2f (q1, q2)dq1dq2

with e(p) = (cos p, sin p) if p ∈ [0, 2π].

‖e(p1)∧e(p2)−e(q1)∧e(q2)‖2 = (sin(p1 − p2)− sin(q1 − q2))2

Dimension reduction: Onsager’s equation f = Z−1e−U[f ]

reduces toa = [sin θ](a)

with [φ](a) =

∫ 2π0 φ(θ)g(θ)dθ

g(θ) = Z−1e−b(sin(θ)−a)2

Z =∫ 2π0 e−b(sin(θ)−a)

2dθ

Page 49: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Example of Interacting Corpora

M = S1, M = S1 × S1.

U[f ](p1, p2) =b∫T2 ‖e(p1) ∧ e(p2)− e(q1) ∧ e(q2)‖2f (q1, q2)dq1dq2

with e(p) = (cos p, sin p) if p ∈ [0, 2π].

‖e(p1)∧e(p2)−e(q1)∧e(q2)‖2 = (sin(p1 − p2)− sin(q1 − q2))2

Dimension reduction: Onsager’s equation f = Z−1e−U[f ]

reduces toa = [sin θ](a)

with [φ](a) =

∫ 2π0 φ(θ)g(θ)dθ

g(θ) = Z−1e−b(sin(θ)−a)2

Z =∫ 2π0 e−b(sin(θ)−a)

2dθ

Page 50: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The solution is f (θ1, θ2) = g(θ1 − θ2).

Let

φ(θ, a) = sin θ − a,

and let

[φ](b, a) =

∫ 2π0 φ(θ, a)e−bφ

2(θ,a)dθ∫ 2π0 e−bφ2(θ,a)dθ

.

The Onsager equation is equivalent to

[φ](b, a) = 0.

This determines a, which in turn determines g , f .a = 0 always a solution. It yields

f0(p1, p2) = Z−1e−b sin2(p1−p2).

As b →∞ this tends to δ((p1 − p2)modπ).

Page 51: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The solution is f (θ1, θ2) = g(θ1 − θ2). Let

φ(θ, a) = sin θ − a,

and let

[φ](b, a) =

∫ 2π0 φ(θ, a)e−bφ

2(θ,a)dθ∫ 2π0 e−bφ2(θ,a)dθ

.

The Onsager equation is equivalent to

[φ](b, a) = 0.

This determines a, which in turn determines g , f .a = 0 always a solution. It yields

f0(p1, p2) = Z−1e−b sin2(p1−p2).

As b →∞ this tends to δ((p1 − p2)modπ).

Page 52: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The solution is f (θ1, θ2) = g(θ1 − θ2). Let

φ(θ, a) = sin θ − a,

and let

[φ](b, a) =

∫ 2π0 φ(θ, a)e−bφ

2(θ,a)dθ∫ 2π0 e−bφ2(θ,a)dθ

.

The Onsager equation is equivalent to

[φ](b, a) = 0.

This determines a, which in turn determines g , f .a = 0 always a solution. It yields

f0(p1, p2) = Z−1e−b sin2(p1−p2).

As b →∞ this tends to δ((p1 − p2)modπ).

Page 53: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The solution is f (θ1, θ2) = g(θ1 − θ2). Let

φ(θ, a) = sin θ − a,

and let

[φ](b, a) =

∫ 2π0 φ(θ, a)e−bφ

2(θ,a)dθ∫ 2π0 e−bφ2(θ,a)dθ

.

The Onsager equation is equivalent to

[φ](b, a) = 0.

This determines a, which in turn determines g , f .a = 0 always a solution. It yields

f0(p1, p2) = Z−1e−b sin2(p1−p2).

As b →∞ this tends to δ((p1 − p2)modπ).

Page 54: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The solution is f (θ1, θ2) = g(θ1 − θ2). Let

φ(θ, a) = sin θ − a,

and let

[φ](b, a) =

∫ 2π0 φ(θ, a)e−bφ

2(θ,a)dθ∫ 2π0 e−bφ2(θ,a)dθ

.

The Onsager equation is equivalent to

[φ](b, a) = 0.

This determines a, which in turn determines g , f .

a = 0 always a solution. It yields

f0(p1, p2) = Z−1e−b sin2(p1−p2).

As b →∞ this tends to δ((p1 − p2)modπ).

Page 55: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The solution is f (θ1, θ2) = g(θ1 − θ2). Let

φ(θ, a) = sin θ − a,

and let

[φ](b, a) =

∫ 2π0 φ(θ, a)e−bφ

2(θ,a)dθ∫ 2π0 e−bφ2(θ,a)dθ

.

The Onsager equation is equivalent to

[φ](b, a) = 0.

This determines a, which in turn determines g , f .a = 0 always a solution. It yields

f0(p1, p2) = Z−1e−b sin2(p1−p2).

As b →∞ this tends to δ((p1 − p2)modπ).

Page 56: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The solution is f (θ1, θ2) = g(θ1 − θ2). Let

φ(θ, a) = sin θ − a,

and let

[φ](b, a) =

∫ 2π0 φ(θ, a)e−bφ

2(θ,a)dθ∫ 2π0 e−bφ2(θ,a)dθ

.

The Onsager equation is equivalent to

[φ](b, a) = 0.

This determines a, which in turn determines g , f .a = 0 always a solution. It yields

f0(p1, p2) = Z−1e−b sin2(p1−p2).

As b →∞ this tends to δ((p1 − p2)modπ).

Page 57: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Consider

λ(a, τ) = b12

∫ 2π

0e−b(sin θ−a)

2dθ

with τ = b−1.

Note

[φ] =1

2b

∂aλ

λ

and

∂τλ =1

4∂2aλ

limτ→0

λ(a, τ) = 2√π

1√1− a2

, 0 < a < 1.

Increasing. But things are subtle, ∂λ∂a (1, τ) < 0.

Page 58: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Consider

λ(a, τ) = b12

∫ 2π

0e−b(sin θ−a)

2dθ

with τ = b−1.Note

[φ] =1

2b

∂aλ

λ

and

∂τλ =1

4∂2aλ

limτ→0

λ(a, τ) = 2√π

1√1− a2

, 0 < a < 1.

Increasing. But things are subtle, ∂λ∂a (1, τ) < 0.

Page 59: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Consider

λ(a, τ) = b12

∫ 2π

0e−b(sin θ−a)

2dθ

with τ = b−1.Note

[φ] =1

2b

∂aλ

λ

and

∂τλ =1

4∂2aλ

limτ→0

λ(a, τ) = 2√π

1√1− a2

, 0 < a < 1.

Increasing. But things are subtle, ∂λ∂a (1, τ) < 0.

Page 60: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Consider

λ(a, τ) = b12

∫ 2π

0e−b(sin θ−a)

2dθ

with τ = b−1.Note

[φ] =1

2b

∂aλ

λ

and

∂τλ =1

4∂2aλ

limτ→0

λ(a, τ) = 2√π

1√1− a2

, 0 < a < 1.

Increasing.

But things are subtle, ∂λ∂a (1, τ) < 0.

Page 61: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Consider

λ(a, τ) = b12

∫ 2π

0e−b(sin θ−a)

2dθ

with τ = b−1.Note

[φ] =1

2b

∂aλ

λ

and

∂τλ =1

4∂2aλ

limτ→0

λ(a, τ) = 2√π

1√1− a2

, 0 < a < 1.

Increasing. But things are subtle, ∂λ∂a (1, τ) < 0.

Page 62: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In fact, phase transition at positive τ

∂aλ((a(τ), τ) = 0

and limit limτ→0 a(τ) = 1.

Consider

hb(a) =

∫ 2π

0ue−bu

2dθ

with u(θ, a) = sin θ − a. We seek zeros of hb(a). Clearly,hb(1) < 0. ∃ 0 < a < 1 such that hb(a) > 0: Changingvariables:

hb(a) = 2

∫ 1−a

−1−ae−bu

2 udu√1− (u + a)2

hb(a) = 4∫ 1−a0 e−bu

2u

1√

1−(u+a)2− 1√

1−(a−u)2

du

−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

= 16a∫ 1−a0

e−bu2u2du√(1−(u+a)2)(1−(u−a)2)

(√1−(u−a)2+

√1−(u+a)2

)−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

.

Page 63: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In fact, phase transition at positive τ

∂aλ((a(τ), τ) = 0

and limit limτ→0 a(τ) = 1. Consider

hb(a) =

∫ 2π

0ue−bu

2dθ

with u(θ, a) = sin θ − a.

We seek zeros of hb(a). Clearly,hb(1) < 0. ∃ 0 < a < 1 such that hb(a) > 0: Changingvariables:

hb(a) = 2

∫ 1−a

−1−ae−bu

2 udu√1− (u + a)2

hb(a) = 4∫ 1−a0 e−bu

2u

1√

1−(u+a)2− 1√

1−(a−u)2

du

−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

= 16a∫ 1−a0

e−bu2u2du√(1−(u+a)2)(1−(u−a)2)

(√1−(u−a)2+

√1−(u+a)2

)−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

.

Page 64: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In fact, phase transition at positive τ

∂aλ((a(τ), τ) = 0

and limit limτ→0 a(τ) = 1. Consider

hb(a) =

∫ 2π

0ue−bu

2dθ

with u(θ, a) = sin θ − a. We seek zeros of hb(a).

Clearly,hb(1) < 0. ∃ 0 < a < 1 such that hb(a) > 0: Changingvariables:

hb(a) = 2

∫ 1−a

−1−ae−bu

2 udu√1− (u + a)2

hb(a) = 4∫ 1−a0 e−bu

2u

1√

1−(u+a)2− 1√

1−(a−u)2

du

−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

= 16a∫ 1−a0

e−bu2u2du√(1−(u+a)2)(1−(u−a)2)

(√1−(u−a)2+

√1−(u+a)2

)−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

.

Page 65: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In fact, phase transition at positive τ

∂aλ((a(τ), τ) = 0

and limit limτ→0 a(τ) = 1. Consider

hb(a) =

∫ 2π

0ue−bu

2dθ

with u(θ, a) = sin θ − a. We seek zeros of hb(a). Clearly,hb(1) < 0.

∃ 0 < a < 1 such that hb(a) > 0: Changingvariables:

hb(a) = 2

∫ 1−a

−1−ae−bu

2 udu√1− (u + a)2

hb(a) = 4∫ 1−a0 e−bu

2u

1√

1−(u+a)2− 1√

1−(a−u)2

du

−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

= 16a∫ 1−a0

e−bu2u2du√(1−(u+a)2)(1−(u−a)2)

(√1−(u−a)2+

√1−(u+a)2

)−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

.

Page 66: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In fact, phase transition at positive τ

∂aλ((a(τ), τ) = 0

and limit limτ→0 a(τ) = 1. Consider

hb(a) =

∫ 2π

0ue−bu

2dθ

with u(θ, a) = sin θ − a. We seek zeros of hb(a). Clearly,hb(1) < 0. ∃ 0 < a < 1 such that hb(a) > 0:

Changingvariables:

hb(a) = 2

∫ 1−a

−1−ae−bu

2 udu√1− (u + a)2

hb(a) = 4∫ 1−a0 e−bu

2u

1√

1−(u+a)2− 1√

1−(a−u)2

du

−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

= 16a∫ 1−a0

e−bu2u2du√(1−(u+a)2)(1−(u−a)2)

(√1−(u−a)2+

√1−(u+a)2

)−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

.

Page 67: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In fact, phase transition at positive τ

∂aλ((a(τ), τ) = 0

and limit limτ→0 a(τ) = 1. Consider

hb(a) =

∫ 2π

0ue−bu

2dθ

with u(θ, a) = sin θ − a. We seek zeros of hb(a). Clearly,hb(1) < 0. ∃ 0 < a < 1 such that hb(a) > 0: Changingvariables:

hb(a) = 2

∫ 1−a

−1−ae−bu

2 udu√1− (u + a)2

hb(a) = 4∫ 1−a0 e−bu

2u

1√

1−(u+a)2− 1√

1−(a−u)2

du

−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

= 16a∫ 1−a0

e−bu2u2du√(1−(u+a)2)(1−(u−a)2)

(√1−(u−a)2+

√1−(u+a)2

)−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

.

Page 68: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In fact, phase transition at positive τ

∂aλ((a(τ), τ) = 0

and limit limτ→0 a(τ) = 1. Consider

hb(a) =

∫ 2π

0ue−bu

2dθ

with u(θ, a) = sin θ − a. We seek zeros of hb(a). Clearly,hb(1) < 0. ∃ 0 < a < 1 such that hb(a) > 0: Changingvariables:

hb(a) = 2

∫ 1−a

−1−ae−bu

2 udu√1− (u + a)2

hb(a) = 4∫ 1−a0 e−bu

2u

1√

1−(u+a)2− 1√

1−(a−u)2

du

−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

= 16a∫ 1−a0

e−bu2u2du√(1−(u+a)2)(1−(u−a)2)

(√1−(u−a)2+

√1−(u+a)2

)−2∫ 1+a1−a e−bu

2 udu√1−(a−u)2

.

Page 69: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The last integral is negative but exponentially small as b →∞.

The positive integral is larger than a fixed multiple of∫ δ0 u2e−bu

2du for small fixed δ (depending on a). This integral

asymptotically equals Cb−3/2 with positive C , as b →∞.Thus, for any fixed 0 < a < 1 and b large enough, we havehb(a) > 0. This proves for all large enough b the existence ofa(b) > 0 such that hb(a(b)) = 0. Moreover, because 0 < a < 1was arbitrary, this also proves limb→∞ a(b) = 1 for any sucha(b) > 0.

limb→∞

f (p1 − p2) = δ((

p1 − p2 −π

2

)modπ

)

Page 70: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The last integral is negative but exponentially small as b →∞.The positive integral is larger than a fixed multiple of∫ δ0 u2e−bu

2du for small fixed δ (depending on a).

This integral

asymptotically equals Cb−3/2 with positive C , as b →∞.Thus, for any fixed 0 < a < 1 and b large enough, we havehb(a) > 0. This proves for all large enough b the existence ofa(b) > 0 such that hb(a(b)) = 0. Moreover, because 0 < a < 1was arbitrary, this also proves limb→∞ a(b) = 1 for any sucha(b) > 0.

limb→∞

f (p1 − p2) = δ((

p1 − p2 −π

2

)modπ

)

Page 71: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The last integral is negative but exponentially small as b →∞.The positive integral is larger than a fixed multiple of∫ δ0 u2e−bu

2du for small fixed δ (depending on a). This integral

asymptotically equals Cb−3/2 with positive C , as b →∞.

Thus, for any fixed 0 < a < 1 and b large enough, we havehb(a) > 0. This proves for all large enough b the existence ofa(b) > 0 such that hb(a(b)) = 0. Moreover, because 0 < a < 1was arbitrary, this also proves limb→∞ a(b) = 1 for any sucha(b) > 0.

limb→∞

f (p1 − p2) = δ((

p1 − p2 −π

2

)modπ

)

Page 72: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The last integral is negative but exponentially small as b →∞.The positive integral is larger than a fixed multiple of∫ δ0 u2e−bu

2du for small fixed δ (depending on a). This integral

asymptotically equals Cb−3/2 with positive C , as b →∞.Thus, for any fixed 0 < a < 1 and b large enough, we havehb(a) > 0.

This proves for all large enough b the existence ofa(b) > 0 such that hb(a(b)) = 0. Moreover, because 0 < a < 1was arbitrary, this also proves limb→∞ a(b) = 1 for any sucha(b) > 0.

limb→∞

f (p1 − p2) = δ((

p1 − p2 −π

2

)modπ

)

Page 73: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The last integral is negative but exponentially small as b →∞.The positive integral is larger than a fixed multiple of∫ δ0 u2e−bu

2du for small fixed δ (depending on a). This integral

asymptotically equals Cb−3/2 with positive C , as b →∞.Thus, for any fixed 0 < a < 1 and b large enough, we havehb(a) > 0. This proves for all large enough b the existence ofa(b) > 0 such that hb(a(b)) = 0. Moreover, because 0 < a < 1was arbitrary, this also proves limb→∞ a(b) = 1 for any sucha(b) > 0.

limb→∞

f (p1 − p2) = δ((

p1 − p2 −π

2

)modπ

)

Page 74: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The last integral is negative but exponentially small as b →∞.The positive integral is larger than a fixed multiple of∫ δ0 u2e−bu

2du for small fixed δ (depending on a). This integral

asymptotically equals Cb−3/2 with positive C , as b →∞.Thus, for any fixed 0 < a < 1 and b large enough, we havehb(a) > 0. This proves for all large enough b the existence ofa(b) > 0 such that hb(a(b)) = 0. Moreover, because 0 < a < 1was arbitrary, this also proves limb→∞ a(b) = 1 for any sucha(b) > 0.

limb→∞

f (p1 − p2) = δ((

p1 − p2 −π

2

)modπ

)

Page 75: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

More degrees of freedom

M = [0, L]× [0, L]× [0, π], dµ = 1πL2

dx1dx2dθ.

U[f ](x1, x2, θ) =

∫M

(x1x2 sin(θ)− y1y2 sin(φ))2f (y1, y2, φ)dµ

The solutions of Onsager’s equation are of the form

g(x1, x2, θ) = Z−1e−b(x1x2 sin θ−a)2

with Z determined by the requirement of normalization∫M gdµ = 1, a determined by

a =

∫M

(x1x2 sin θ)g(x1, x2, θ)dµ

Page 76: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

More degrees of freedom

M = [0, L]× [0, L]× [0, π], dµ = 1πL2

dx1dx2dθ.

U[f ](x1, x2, θ) =

∫M

(x1x2 sin(θ)− y1y2 sin(φ))2f (y1, y2, φ)dµ

The solutions of Onsager’s equation are of the form

g(x1, x2, θ) = Z−1e−b(x1x2 sin θ−a)2

with Z determined by the requirement of normalization∫M gdµ = 1, a determined by

a =

∫M

(x1x2 sin θ)g(x1, x2, θ)dµ

Page 77: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

More degrees of freedom

M = [0, L]× [0, L]× [0, π], dµ = 1πL2

dx1dx2dθ.

U[f ](x1, x2, θ) =

∫M

(x1x2 sin(θ)− y1y2 sin(φ))2f (y1, y2, φ)dµ

The solutions of Onsager’s equation are of the form

g(x1, x2, θ) = Z−1e−b(x1x2 sin θ−a)2

with Z determined by the requirement of normalization∫M gdµ = 1, a determined by

a =

∫M

(x1x2 sin θ)g(x1, x2, θ)dµ

Page 78: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

More degrees of freedom

M = [0, L]× [0, L]× [0, π], dµ = 1πL2

dx1dx2dθ.

U[f ](x1, x2, θ) =

∫M

(x1x2 sin(θ)− y1y2 sin(φ))2f (y1, y2, φ)dµ

The solutions of Onsager’s equation are of the form

g(x1, x2, θ) = Z−1e−b(x1x2 sin θ−a)2

with Z determined by the requirement of normalization∫M gdµ = 1,

a determined by

a =

∫M

(x1x2 sin θ)g(x1, x2, θ)dµ

Page 79: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

More degrees of freedom

M = [0, L]× [0, L]× [0, π], dµ = 1πL2

dx1dx2dθ.

U[f ](x1, x2, θ) =

∫M

(x1x2 sin(θ)− y1y2 sin(φ))2f (y1, y2, φ)dµ

The solutions of Onsager’s equation are of the form

g(x1, x2, θ) = Z−1e−b(x1x2 sin θ−a)2

with Z determined by the requirement of normalization∫M gdµ = 1, a determined by

a =

∫M

(x1x2 sin θ)g(x1, x2, θ)dµ

Page 80: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Letφ(x1, x2, θ, a) = x1x2 sin θ − a

[φ] =

∫Mφgdµ

a is determined by [φ] = 0.

λ(a, τ) = τ−1/2∫Me−φ

2/τdµ

obeys the heat equation

∂τλ =1

4∂2aλ

with τ = b−1.

[φ] =1

2b∂a log λ.

a→ 0, as b →∞.

Page 81: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Letφ(x1, x2, θ, a) = x1x2 sin θ − a

[φ] =

∫Mφgdµ

a is determined by [φ] = 0.

λ(a, τ) = τ−1/2∫Me−φ

2/τdµ

obeys the heat equation

∂τλ =1

4∂2aλ

with τ = b−1.

[φ] =1

2b∂a log λ.

a→ 0, as b →∞.

Page 82: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Letφ(x1, x2, θ, a) = x1x2 sin θ − a

[φ] =

∫Mφgdµ

a is determined by [φ] = 0.

λ(a, τ) = τ−1/2∫Me−φ

2/τdµ

obeys the heat equation

∂τλ =1

4∂2aλ

with τ = b−1.

[φ] =1

2b∂a log λ.

a→ 0, as b →∞.

Page 83: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Letφ(x1, x2, θ, a) = x1x2 sin θ − a

[φ] =

∫Mφgdµ

a is determined by [φ] = 0.

λ(a, τ) = τ−1/2∫Me−φ

2/τdµ

obeys the heat equation

∂τλ =1

4∂2aλ

with τ = b−1.

[φ] =1

2b∂a log λ.

a→ 0, as b →∞.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Letφ(x1, x2, θ, a) = x1x2 sin θ − a

[φ] =

∫Mφgdµ

a is determined by [φ] = 0.

λ(a, τ) = τ−1/2∫Me−φ

2/τdµ

obeys the heat equation

∂τλ =1

4∂2aλ

with τ = b−1.

[φ] =1

2b∂a log λ.

a→ 0, as b →∞.

Page 85: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Letφ(x1, x2, θ, a) = x1x2 sin θ − a

[φ] =

∫Mφgdµ

a is determined by [φ] = 0.

λ(a, τ) = τ−1/2∫Me−φ

2/τdµ

obeys the heat equation

∂τλ =1

4∂2aλ

with τ = b−1.

[φ] =1

2b∂a log λ.

a→ 0, as b →∞.

Page 86: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Letφ(x1, x2, θ, a) = x1x2 sin θ − a

[φ] =

∫Mφgdµ

a is determined by [φ] = 0.

λ(a, τ) = τ−1/2∫Me−φ

2/τdµ

obeys the heat equation

∂τλ =1

4∂2aλ

with τ = b−1.

[φ] =1

2b∂a log λ.

a→ 0, as b →∞.

Page 87: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Even More Degrees of Freedom...

V (r) nonnegative, nonincreasing, compactly supported.p = (x1, . . . xN), xi ∈ Ω ⊂ Rn.

Packing energy:

F (p) =∑i<j

V (|xi − xj |).

M = Ω× · · · × Ω ∩ F ≤ F0.

U[f ](p) =

∫M

[|F (p)− F (q)|2 + d2(p, q)

]f (q)dq

Connection to the example of freely articulated 2n doodads,jamming, perhaps...

Page 88: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Even More Degrees of Freedom...

V (r) nonnegative, nonincreasing, compactly supported.p = (x1, . . . xN), xi ∈ Ω ⊂ Rn. Packing energy:

F (p) =∑i<j

V (|xi − xj |).

M = Ω× · · · × Ω ∩ F ≤ F0.

U[f ](p) =

∫M

[|F (p)− F (q)|2 + d2(p, q)

]f (q)dq

Connection to the example of freely articulated 2n doodads,jamming, perhaps...

Page 89: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Even More Degrees of Freedom...

V (r) nonnegative, nonincreasing, compactly supported.p = (x1, . . . xN), xi ∈ Ω ⊂ Rn. Packing energy:

F (p) =∑i<j

V (|xi − xj |).

M = Ω× · · · × Ω ∩ F ≤ F0.

U[f ](p) =

∫M

[|F (p)− F (q)|2 + d2(p, q)

]f (q)dq

Connection to the example of freely articulated 2n doodads,jamming, perhaps...

Page 90: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Even More Degrees of Freedom...

V (r) nonnegative, nonincreasing, compactly supported.p = (x1, . . . xN), xi ∈ Ω ⊂ Rn. Packing energy:

F (p) =∑i<j

V (|xi − xj |).

M = Ω× · · · × Ω ∩ F ≤ F0.

U[f ](p) =

∫M

[|F (p)− F (q)|2 + d2(p, q)

]f (q)dq

Connection to the example of freely articulated 2n doodads,jamming, perhaps...

Page 91: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Even More Degrees of Freedom...

V (r) nonnegative, nonincreasing, compactly supported.p = (x1, . . . xN), xi ∈ Ω ⊂ Rn. Packing energy:

F (p) =∑i<j

V (|xi − xj |).

M = Ω× · · · × Ω ∩ F ≤ F0.

U[f ](p) =

∫M

[|F (p)− F (q)|2 + d2(p, q)

]f (q)dq

Connection to the example of freely articulated 2n doodads,jamming, perhaps...

Page 92: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

TheoremFor any b > 0 there exists a solution g that minimizes theenergy:

E [g ] = minf≥0,

∫M fdµ=1

E [f ]

The function g solves the Onsager equation

g(x) = (Z (b))−1e−bU(x)

with

Z (b) =

∫Me−bU(x)dµ(x)

and

U(x) =

∫Mk(x , y)g(y)dµ(y).

The function g is normalized∫gdµ = 1, strictly positive and

Lipschitz continuous.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

TheoremFor any b > 0 there exists a solution g that minimizes theenergy:

E [g ] = minf≥0,

∫M fdµ=1

E [f ]

The function g solves the Onsager equation

g(x) = (Z (b))−1e−bU(x)

with

Z (b) =

∫Me−bU(x)dµ(x)

and

U(x) =

∫Mk(x , y)g(y)dµ(y).

The function g is normalized∫gdµ = 1, strictly positive and

Lipschitz continuous.

Page 94: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

TheoremFor any b > 0 there exists a solution g that minimizes theenergy:

E [g ] = minf≥0,

∫M fdµ=1

E [f ]

The function g solves the Onsager equation

g(x) = (Z (b))−1e−bU(x)

with

Z (b) =

∫Me−bU(x)dµ(x)

and

U(x) =

∫Mk(x , y)g(y)dµ(y).

The function g is normalized∫gdµ = 1, strictly positive and

Lipschitz continuous.

Page 95: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

TheoremFor any b > 0 there exists a solution g that minimizes theenergy:

E [g ] = minf≥0,

∫M fdµ=1

E [f ]

The function g solves the Onsager equation

g(x) = (Z (b))−1e−bU(x)

with

Z (b) =

∫Me−bU(x)dµ(x)

and

U(x) =

∫Mk(x , y)g(y)dµ(y).

The function g is normalized∫gdµ = 1, strictly positive and

Lipschitz continuous.

Page 96: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

TheoremFor any b > 0 there exists a solution g that minimizes theenergy:

E [g ] = minf≥0,

∫M fdµ=1

E [f ]

The function g solves the Onsager equation

g(x) = (Z (b))−1e−bU(x)

with

Z (b) =

∫Me−bU(x)dµ(x)

and

U(x) =

∫Mk(x , y)g(y)dµ(y).

The function g is normalized∫gdµ = 1, strictly positive and

Lipschitz continuous.

Page 97: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

TheoremFor any b > 0 there exists a solution g that minimizes theenergy:

E [g ] = minf≥0,

∫M fdµ=1

E [f ]

The function g solves the Onsager equation

g(x) = (Z (b))−1e−bU(x)

with

Z (b) =

∫Me−bU(x)dµ(x)

and

U(x) =

∫Mk(x , y)g(y)dµ(y).

The function g is normalized∫gdµ = 1, strictly positive and

Lipschitz continuous.

Page 98: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of Proof0 ≤ U[f ](p) ≤ ‖u‖∞

|U[f ](p)− U[f ](q)| ≤ Ld(p, q)

Jensen, µ(M) = 1⇒ ∫Mf log fdµ ≥ 0.

Consequently:Eb[f ] ≥ 0.

Minimizing sequence fj ,

a = inff≥0,

∫M fdµ=1

Eb[f ] = limj→∞Eb[fj ].

WLOG fjdµ converge weakly to a measure dν. Uj = U[fj ]converge uniformly to a non-negative Lipschitz continuousfunction U. Then it follows that

U(p) =

∫Mk(p, q)dν(q)

Page 99: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of Proof0 ≤ U[f ](p) ≤ ‖u‖∞

|U[f ](p)− U[f ](q)| ≤ Ld(p, q)

Jensen, µ(M) = 1⇒ ∫Mf log fdµ ≥ 0.

Consequently:Eb[f ] ≥ 0.

Minimizing sequence fj ,

a = inff≥0,

∫M fdµ=1

Eb[f ] = limj→∞Eb[fj ].

WLOG fjdµ converge weakly to a measure dν. Uj = U[fj ]converge uniformly to a non-negative Lipschitz continuousfunction U. Then it follows that

U(p) =

∫Mk(p, q)dν(q)

Page 100: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of Proof0 ≤ U[f ](p) ≤ ‖u‖∞

|U[f ](p)− U[f ](q)| ≤ Ld(p, q)

Jensen, µ(M) = 1⇒ ∫Mf log fdµ ≥ 0.

Consequently:Eb[f ] ≥ 0.

Minimizing sequence fj ,

a = inff≥0,

∫M fdµ=1

Eb[f ] = limj→∞Eb[fj ].

WLOG fjdµ converge weakly to a measure dν. Uj = U[fj ]converge uniformly to a non-negative Lipschitz continuousfunction U. Then it follows that

U(p) =

∫Mk(p, q)dν(q)

Page 101: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of Proof0 ≤ U[f ](p) ≤ ‖u‖∞

|U[f ](p)− U[f ](q)| ≤ Ld(p, q)

Jensen, µ(M) = 1⇒ ∫Mf log fdµ ≥ 0.

Consequently:Eb[f ] ≥ 0.

Minimizing sequence fj ,

a = inff≥0,

∫M fdµ=1

Eb[f ] = limj→∞Eb[fj ].

WLOG fjdµ converge weakly to a measure dν. Uj = U[fj ]converge uniformly to a non-negative Lipschitz continuousfunction U. Then it follows that

U(p) =

∫Mk(p, q)dν(q)

Page 102: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of Proof0 ≤ U[f ](p) ≤ ‖u‖∞

|U[f ](p)− U[f ](q)| ≤ Ld(p, q)

Jensen, µ(M) = 1⇒ ∫Mf log fdµ ≥ 0.

Consequently:Eb[f ] ≥ 0.

Minimizing sequence fj ,

a = inff≥0,

∫M fdµ=1

Eb[f ] = limj→∞Eb[fj ].

WLOG fjdµ converge weakly to a measure dν.

Uj = U[fj ]converge uniformly to a non-negative Lipschitz continuousfunction U. Then it follows that

U(p) =

∫Mk(p, q)dν(q)

Page 103: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of Proof0 ≤ U[f ](p) ≤ ‖u‖∞

|U[f ](p)− U[f ](q)| ≤ Ld(p, q)

Jensen, µ(M) = 1⇒ ∫Mf log fdµ ≥ 0.

Consequently:Eb[f ] ≥ 0.

Minimizing sequence fj ,

a = inff≥0,

∫M fdµ=1

Eb[f ] = limj→∞Eb[fj ].

WLOG fjdµ converge weakly to a measure dν. Uj = U[fj ]converge uniformly to a non-negative Lipschitz continuousfunction U. Then it follows that

U(p) =

∫Mk(p, q)dν(q)

Page 104: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

We claim dν AC wr dµ, i.e. dν = gdµ with g ≥ 0 andg ∈ L1(dµ).

Indeed, this is because the sequence fjdµ isuniformly absolutely continuous. The latter is proved usingthe convexity of the function y log y and Jensen’s inequality

µ(A)−1∫Afj log fjdµ ≥ m logm,

where m = m(A, j) = µ(A)−1∫A fjdµ. Thus for all A, j ,

m logm ≤ C

µ(A)

with a fixed C ≥ 1. Let us choose R = R(A) ≥ 1 so thatR logR = C/µ(A). Then m ≤ R and so∫A fjdµ ≤ µ(A)R = C/ logR. This means∫

Afjdµ ≤ δ(µ(A))

with limx→0 δ(x) = 0 and δ(·) independent of A and j . Itfollows that ν is absolutely continuous with respect to dµ.

Page 105: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

We claim dν AC wr dµ, i.e. dν = gdµ with g ≥ 0 andg ∈ L1(dµ). Indeed, this is because the sequence fjdµ isuniformly absolutely continuous.

The latter is proved usingthe convexity of the function y log y and Jensen’s inequality

µ(A)−1∫Afj log fjdµ ≥ m logm,

where m = m(A, j) = µ(A)−1∫A fjdµ. Thus for all A, j ,

m logm ≤ C

µ(A)

with a fixed C ≥ 1. Let us choose R = R(A) ≥ 1 so thatR logR = C/µ(A). Then m ≤ R and so∫A fjdµ ≤ µ(A)R = C/ logR. This means∫

Afjdµ ≤ δ(µ(A))

with limx→0 δ(x) = 0 and δ(·) independent of A and j . Itfollows that ν is absolutely continuous with respect to dµ.

Page 106: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

We claim dν AC wr dµ, i.e. dν = gdµ with g ≥ 0 andg ∈ L1(dµ). Indeed, this is because the sequence fjdµ isuniformly absolutely continuous. The latter is proved usingthe convexity of the function y log y and Jensen’s inequality

µ(A)−1∫Afj log fjdµ ≥ m logm,

where m = m(A, j) = µ(A)−1∫A fjdµ.

Thus for all A, j ,

m logm ≤ C

µ(A)

with a fixed C ≥ 1. Let us choose R = R(A) ≥ 1 so thatR logR = C/µ(A). Then m ≤ R and so∫A fjdµ ≤ µ(A)R = C/ logR. This means∫

Afjdµ ≤ δ(µ(A))

with limx→0 δ(x) = 0 and δ(·) independent of A and j . Itfollows that ν is absolutely continuous with respect to dµ.

Page 107: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

We claim dν AC wr dµ, i.e. dν = gdµ with g ≥ 0 andg ∈ L1(dµ). Indeed, this is because the sequence fjdµ isuniformly absolutely continuous. The latter is proved usingthe convexity of the function y log y and Jensen’s inequality

µ(A)−1∫Afj log fjdµ ≥ m logm,

where m = m(A, j) = µ(A)−1∫A fjdµ. Thus for all A, j ,

m logm ≤ C

µ(A)

with a fixed C ≥ 1.

Let us choose R = R(A) ≥ 1 so thatR logR = C/µ(A). Then m ≤ R and so∫A fjdµ ≤ µ(A)R = C/ logR. This means∫

Afjdµ ≤ δ(µ(A))

with limx→0 δ(x) = 0 and δ(·) independent of A and j . Itfollows that ν is absolutely continuous with respect to dµ.

Page 108: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

We claim dν AC wr dµ, i.e. dν = gdµ with g ≥ 0 andg ∈ L1(dµ). Indeed, this is because the sequence fjdµ isuniformly absolutely continuous. The latter is proved usingthe convexity of the function y log y and Jensen’s inequality

µ(A)−1∫Afj log fjdµ ≥ m logm,

where m = m(A, j) = µ(A)−1∫A fjdµ. Thus for all A, j ,

m logm ≤ C

µ(A)

with a fixed C ≥ 1. Let us choose R = R(A) ≥ 1 so thatR logR = C/µ(A). Then m ≤ R and so∫A fjdµ ≤ µ(A)R = C/ logR. This means∫

Afjdµ ≤ δ(µ(A))

with limx→0 δ(x) = 0 and δ(·) independent of A and j . Itfollows that ν is absolutely continuous with respect to dµ.

Page 109: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In general, weak convergence of measures is not enough toshow lower semicontinuity of nonlinear integrals or almosteverywhere convergence.

We claim however that, in fact, theconvergence fn → g takes place strongly in L1(dµ):

limn→∞

∫M|fn(p)− g(p)|dµ(p) = 0.

In order to prove this, we prove that fn is a Cauchy sequencein L1(dµ). We take ε > 0 and choose N large enough so that

supp∈M

∣∣Un(p)− U(p)∣∣ ≤ ε2

16b,

and

Eb[fn] ≤ a +ε2

16

holds for n ≥ N.

Page 110: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In general, weak convergence of measures is not enough toshow lower semicontinuity of nonlinear integrals or almosteverywhere convergence. We claim however that, in fact, theconvergence fn → g takes place strongly in L1(dµ):

limn→∞

∫M|fn(p)− g(p)|dµ(p) = 0.

In order to prove this, we prove that fn is a Cauchy sequencein L1(dµ). We take ε > 0 and choose N large enough so that

supp∈M

∣∣Un(p)− U(p)∣∣ ≤ ε2

16b,

and

Eb[fn] ≤ a +ε2

16

holds for n ≥ N.

Page 111: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In general, weak convergence of measures is not enough toshow lower semicontinuity of nonlinear integrals or almosteverywhere convergence. We claim however that, in fact, theconvergence fn → g takes place strongly in L1(dµ):

limn→∞

∫M|fn(p)− g(p)|dµ(p) = 0.

In order to prove this, we prove that fn is a Cauchy sequencein L1(dµ).

We take ε > 0 and choose N large enough so that

supp∈M

∣∣Un(p)− U(p)∣∣ ≤ ε2

16b,

and

Eb[fn] ≤ a +ε2

16

holds for n ≥ N.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In general, weak convergence of measures is not enough toshow lower semicontinuity of nonlinear integrals or almosteverywhere convergence. We claim however that, in fact, theconvergence fn → g takes place strongly in L1(dµ):

limn→∞

∫M|fn(p)− g(p)|dµ(p) = 0.

In order to prove this, we prove that fn is a Cauchy sequencein L1(dµ). We take ε > 0 and choose N large enough so that

supp∈M

∣∣Un(p)− U(p)∣∣ ≤ ε2

16b,

and

Eb[fn] ≤ a +ε2

16

holds for n ≥ N.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

In general, weak convergence of measures is not enough toshow lower semicontinuity of nonlinear integrals or almosteverywhere convergence. We claim however that, in fact, theconvergence fn → g takes place strongly in L1(dµ):

limn→∞

∫M|fn(p)− g(p)|dµ(p) = 0.

In order to prove this, we prove that fn is a Cauchy sequencein L1(dµ). We take ε > 0 and choose N large enough so that

supp∈M

∣∣Un(p)− U(p)∣∣ ≤ ε2

16b,

and

Eb[fn] ≤ a +ε2

16

holds for n ≥ N.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Let s(p) = 12(fn(p) + fm(p)) with n,m ≥ N. Then

∫M sdµ = 1,

s ≥ 0, soa ≤ Eb[s].

Therefore1

2Eb[fn] + Eb[fm] − Eb[s] ≤ ε2

16.

On the other hand,∫M

12 (fn log fn + fm log fm)− s log s

≤ 12 Eb[fn] + Eb[fm] − Eb[s] + ε2

16

using U[s] = 12(U[fn] + U[fm]) so,∫

M

1

2(fn log fn + fm log fm)− s log s

dµ ≤ ε2

8.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Let s(p) = 12(fn(p) + fm(p)) with n,m ≥ N. Then

∫M sdµ = 1,

s ≥ 0, soa ≤ Eb[s].

Therefore1

2Eb[fn] + Eb[fm] − Eb[s] ≤ ε2

16.

On the other hand,∫M

12 (fn log fn + fm log fm)− s log s

≤ 12 Eb[fn] + Eb[fm] − Eb[s] + ε2

16

using U[s] = 12(U[fn] + U[fm]) so,∫

M

1

2(fn log fn + fm log fm)− s log s

dµ ≤ ε2

8.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Let s(p) = 12(fn(p) + fm(p)) with n,m ≥ N. Then

∫M sdµ = 1,

s ≥ 0, soa ≤ Eb[s].

Therefore1

2Eb[fn] + Eb[fm] − Eb[s] ≤ ε2

16.

On the other hand,∫M

12 (fn log fn + fm log fm)− s log s

≤ 12 Eb[fn] + Eb[fm] − Eb[s] + ε2

16

using U[s] = 12(U[fn] + U[fm])

so,∫M

1

2(fn log fn + fm log fm)− s log s

dµ ≤ ε2

8.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Let s(p) = 12(fn(p) + fm(p)) with n,m ≥ N. Then

∫M sdµ = 1,

s ≥ 0, soa ≤ Eb[s].

Therefore1

2Eb[fn] + Eb[fm] − Eb[s] ≤ ε2

16.

On the other hand,∫M

12 (fn log fn + fm log fm)− s log s

≤ 12 Eb[fn] + Eb[fm] − Eb[s] + ε2

16

using U[s] = 12(U[fn] + U[fm]) so,∫

M

1

2(fn log fn + fm log fm)− s log s

dµ ≤ ε2

8.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Denote χ = fn−fmfn+fm

and note that −1 ≤ χ ≤ 1 holds µ - a.e.Also, elementary calculations show that

1

2(fn log fn + fm log fm)− s log s

=

s

2G (χ)

holds with

G (χ) = log(1− χ2) + χ log

(1 + χ

1− χ

).

G is even on (−1, 1), G ′(χ) = log(1+χ1−χ

), G (0) = G ′(0) = 0

and G ′′(χ) = 21−χ2 ≥ 2 on (−1, 1). Consequently,

0 ≤ χ2 ≤ G (χ)

holds for −1 ≤ χ ≤ 1.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

It follows that we have∫M

(fn − fm)2

fn + fmdµ ≤ ε2

2

Writing |fn − fm| =√fn + fm

|fn−fm|√fn+fm

and using the Schwartz

inequality we deduce ∫M|fn − fm|dµ ≤ ε.

Therefore the sequence fn is Cauchy in L1(dµ). This provesthat the weak limit fndµ→ gdµ is actually strong fn → g inL1(dµ). By passing to a subsequence if necessary, we mayassume that fn → g holds also µ- a.e. Then from Fatou’sLemma, ∫

Mg log gdµ ≤ lim

j→∞

∫Mfj log fjdµ.

and thus g is a minimizer of Eb with Eb[g ] = a. It also followsthat g ≥ δ where δ > 0 is such that (x log x)′ < −3‖u‖∞ forall x ≤ δ.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The dad-doodad

Let M be a compact metrizable space and let k(x , y) besymmetric, bi-Lipschitz and bounded below.

In addition,assume:

k(x , x) = 0.

Theorem(C-Zlatos) Let ν be any weak limit of a sequence fndµ ofminima of the free energy E corresponding to bn →∞. Thenthere exists m ∈ M such that ν is concentrated on the level setΣ(m) = p | k(m, p) = 0.Explains the selection of prolate states.Pattern recognition example: Rhombi centered at the origin,with k the area of the symmetric difference. The dad-rhombusis the square.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The dad-doodad

Let M be a compact metrizable space and let k(x , y) besymmetric, bi-Lipschitz and bounded below. In addition,assume:

k(x , x) = 0.

Theorem(C-Zlatos) Let ν be any weak limit of a sequence fndµ ofminima of the free energy E corresponding to bn →∞. Thenthere exists m ∈ M such that ν is concentrated on the level setΣ(m) = p | k(m, p) = 0.Explains the selection of prolate states.Pattern recognition example: Rhombi centered at the origin,with k the area of the symmetric difference. The dad-rhombusis the square.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The dad-doodad

Let M be a compact metrizable space and let k(x , y) besymmetric, bi-Lipschitz and bounded below. In addition,assume:

k(x , x) = 0.

Theorem(C-Zlatos) Let ν be any weak limit of a sequence fndµ ofminima of the free energy E corresponding to bn →∞. Thenthere exists m ∈ M such that ν is concentrated on the level setΣ(m) = p | k(m, p) = 0.

Explains the selection of prolate states.Pattern recognition example: Rhombi centered at the origin,with k the area of the symmetric difference. The dad-rhombusis the square.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The dad-doodad

Let M be a compact metrizable space and let k(x , y) besymmetric, bi-Lipschitz and bounded below. In addition,assume:

k(x , x) = 0.

Theorem(C-Zlatos) Let ν be any weak limit of a sequence fndµ ofminima of the free energy E corresponding to bn →∞. Thenthere exists m ∈ M such that ν is concentrated on the level setΣ(m) = p | k(m, p) = 0.Explains the selection of prolate states.

Pattern recognition example: Rhombi centered at the origin,with k the area of the symmetric difference. The dad-rhombusis the square.

Page 124: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The dad-doodad

Let M be a compact metrizable space and let k(x , y) besymmetric, bi-Lipschitz and bounded below. In addition,assume:

k(x , x) = 0.

Theorem(C-Zlatos) Let ν be any weak limit of a sequence fndµ ofminima of the free energy E corresponding to bn →∞. Thenthere exists m ∈ M such that ν is concentrated on the level setΣ(m) = p | k(m, p) = 0.Explains the selection of prolate states.Pattern recognition example: Rhombi centered at the origin,with k the area of the symmetric difference.

The dad-rhombusis the square.

Page 125: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

The dad-doodad

Let M be a compact metrizable space and let k(x , y) besymmetric, bi-Lipschitz and bounded below. In addition,assume:

k(x , x) = 0.

Theorem(C-Zlatos) Let ν be any weak limit of a sequence fndµ ofminima of the free energy E corresponding to bn →∞. Thenthere exists m ∈ M such that ν is concentrated on the level setΣ(m) = p | k(m, p) = 0.Explains the selection of prolate states.Pattern recognition example: Rhombi centered at the origin,with k the area of the symmetric difference. The dad-rhombusis the square.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of proof: First establish

limb→∞

1

b

min

f>0,∫M fdµ=1

E [f ]

= 0

then

ε

∫ ∫k(p,q)≥ε

f (p)dµ(p)f (q)dµ(q) ≤ 2

bE [f ].

if ε2n = 2bnE [fn], 0 < εn → 0, and

Q(p, ε) = q|k(p, q) ≤ ε,

then ∫Mfn(p)

[∫Q(p,εn)

fn(q)dµ(q)

]dµ(p) ≥ 1− εn

∃ pn,∫Q(pn,εn)

fn(q)dµ(q) ≥ 1− 2εn. Pass to subsequencepn → p.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of proof: First establish

limb→∞

1

b

min

f>0,∫M fdµ=1

E [f ]

= 0

then

ε

∫ ∫k(p,q)≥ε

f (p)dµ(p)f (q)dµ(q) ≤ 2

bE [f ].

if ε2n = 2bnE [fn], 0 < εn → 0, and

Q(p, ε) = q|k(p, q) ≤ ε,

then ∫Mfn(p)

[∫Q(p,εn)

fn(q)dµ(q)

]dµ(p) ≥ 1− εn

∃ pn,∫Q(pn,εn)

fn(q)dµ(q) ≥ 1− 2εn. Pass to subsequencepn → p.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of proof: First establish

limb→∞

1

b

min

f>0,∫M fdµ=1

E [f ]

= 0

then

ε

∫ ∫k(p,q)≥ε

f (p)dµ(p)f (q)dµ(q) ≤ 2

bE [f ].

if ε2n = 2bnE [fn], 0 < εn → 0,

and

Q(p, ε) = q|k(p, q) ≤ ε,

then ∫Mfn(p)

[∫Q(p,εn)

fn(q)dµ(q)

]dµ(p) ≥ 1− εn

∃ pn,∫Q(pn,εn)

fn(q)dµ(q) ≥ 1− 2εn. Pass to subsequencepn → p.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of proof: First establish

limb→∞

1

b

min

f>0,∫M fdµ=1

E [f ]

= 0

then

ε

∫ ∫k(p,q)≥ε

f (p)dµ(p)f (q)dµ(q) ≤ 2

bE [f ].

if ε2n = 2bnE [fn], 0 < εn → 0, and

Q(p, ε) = q|k(p, q) ≤ ε,

then ∫Mfn(p)

[∫Q(p,εn)

fn(q)dµ(q)

]dµ(p) ≥ 1− εn

∃ pn,∫Q(pn,εn)

fn(q)dµ(q) ≥ 1− 2εn. Pass to subsequencepn → p.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of proof: First establish

limb→∞

1

b

min

f>0,∫M fdµ=1

E [f ]

= 0

then

ε

∫ ∫k(p,q)≥ε

f (p)dµ(p)f (q)dµ(q) ≤ 2

bE [f ].

if ε2n = 2bnE [fn], 0 < εn → 0, and

Q(p, ε) = q|k(p, q) ≤ ε,

then ∫Mfn(p)

[∫Q(p,εn)

fn(q)dµ(q)

]dµ(p) ≥ 1− εn

∃ pn,∫Q(pn,εn)

fn(q)dµ(q) ≥ 1− 2εn. Pass to subsequencepn → p.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of proof: First establish

limb→∞

1

b

min

f>0,∫M fdµ=1

E [f ]

= 0

then

ε

∫ ∫k(p,q)≥ε

f (p)dµ(p)f (q)dµ(q) ≤ 2

bE [f ].

if ε2n = 2bnE [fn], 0 < εn → 0, and

Q(p, ε) = q|k(p, q) ≤ ε,

then ∫Mfn(p)

[∫Q(p,εn)

fn(q)dµ(q)

]dµ(p) ≥ 1− εn

∃ pn,∫Q(pn,εn)

fn(q)dµ(q) ≥ 1− 2εn.

Pass to subsequencepn → p.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Idea of proof: First establish

limb→∞

1

b

min

f>0,∫M fdµ=1

E [f ]

= 0

then

ε

∫ ∫k(p,q)≥ε

f (p)dµ(p)f (q)dµ(q) ≤ 2

bE [f ].

if ε2n = 2bnE [fn], 0 < εn → 0, and

Q(p, ε) = q|k(p, q) ≤ ε,

then ∫Mfn(p)

[∫Q(p,εn)

fn(q)dµ(q)

]dµ(p) ≥ 1− εn

∃ pn,∫Q(pn,εn)

fn(q)dµ(q) ≥ 1− 2εn. Pass to subsequencepn → p.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Principle: if a µ measure-preserving transformation Texists such that locally around p = p0,k(Tp,Tq) ≤ ck(p, q) with c < 1, then p0 cannot be adad-doodad.

If a local k-preserving transformation around p = p0 hasthe property that µ(T (B)) ≥ Cµ(B) for small balls aroundp0, with C > 1, then p0 cannot be a dad-doodad.

Explains a number of examples with multiple states.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Principle: if a µ measure-preserving transformation Texists such that locally around p = p0,k(Tp,Tq) ≤ ck(p, q) with c < 1, then p0 cannot be adad-doodad.If a local k-preserving transformation around p = p0 hasthe property that µ(T (B)) ≥ Cµ(B) for small balls aroundp0, with C > 1, then p0 cannot be a dad-doodad.

Explains a number of examples with multiple states.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Principle: if a µ measure-preserving transformation Texists such that locally around p = p0,k(Tp,Tq) ≤ ck(p, q) with c < 1, then p0 cannot be adad-doodad.If a local k-preserving transformation around p = p0 hasthe property that µ(T (B)) ≥ Cµ(B) for small balls aroundp0, with C > 1, then p0 cannot be a dad-doodad.

Explains a number of examples with multiple states.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Theorem(Zlatos-C) Let A0,A1 ⊆ M be compacts such that k(p, q) = 0for any p, q ∈ Aj ( j = 0, 1) and letBj(ε) = p ∈ M | d(p,Aj) < ε. Assume that for some εj > 0there is a 1-1 map T : B1(ε1)→ B0(ε0)

such that T ,T−1 aremeasurable and there is c > 1 such that

∀p, q ∈ B1(ε1) : k(T (p),T (q)) ≤ k(p, q)

∀B ⊆ B1(ε1) measurable : µ(T (B)) ≥ cµ(B).

Assume also that for each p ∈ A1, q ∈ M \ B1(ε1) we havek(p, q) > 0.Then ν(A1) < 1 for each measure ν that is a zero temperatureweak limit of minimizers.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Theorem(Zlatos-C) Let A0,A1 ⊆ M be compacts such that k(p, q) = 0for any p, q ∈ Aj ( j = 0, 1) and letBj(ε) = p ∈ M | d(p,Aj) < ε. Assume that for some εj > 0there is a 1-1 map T : B1(ε1)→ B0(ε0) such that T ,T−1 aremeasurable

and there is c > 1 such that

∀p, q ∈ B1(ε1) : k(T (p),T (q)) ≤ k(p, q)

∀B ⊆ B1(ε1) measurable : µ(T (B)) ≥ cµ(B).

Assume also that for each p ∈ A1, q ∈ M \ B1(ε1) we havek(p, q) > 0.Then ν(A1) < 1 for each measure ν that is a zero temperatureweak limit of minimizers.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Theorem(Zlatos-C) Let A0,A1 ⊆ M be compacts such that k(p, q) = 0for any p, q ∈ Aj ( j = 0, 1) and letBj(ε) = p ∈ M | d(p,Aj) < ε. Assume that for some εj > 0there is a 1-1 map T : B1(ε1)→ B0(ε0) such that T ,T−1 aremeasurable and there is c > 1 such that

∀p, q ∈ B1(ε1) : k(T (p),T (q)) ≤ k(p, q)

∀B ⊆ B1(ε1) measurable : µ(T (B)) ≥ cµ(B).

Assume also that for each p ∈ A1, q ∈ M \ B1(ε1) we havek(p, q) > 0.Then ν(A1) < 1 for each measure ν that is a zero temperatureweak limit of minimizers.

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Fluids andParicles:

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PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Theorem(Zlatos-C) Let A0,A1 ⊆ M be compacts such that k(p, q) = 0for any p, q ∈ Aj ( j = 0, 1) and letBj(ε) = p ∈ M | d(p,Aj) < ε. Assume that for some εj > 0there is a 1-1 map T : B1(ε1)→ B0(ε0) such that T ,T−1 aremeasurable and there is c > 1 such that

∀p, q ∈ B1(ε1) : k(T (p),T (q)) ≤ k(p, q)

∀B ⊆ B1(ε1) measurable : µ(T (B)) ≥ cµ(B).

Assume also that for each p ∈ A1, q ∈ M \ B1(ε1) we havek(p, q) > 0.

Then ν(A1) < 1 for each measure ν that is a zero temperatureweak limit of minimizers.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Theorem(Zlatos-C) Let A0,A1 ⊆ M be compacts such that k(p, q) = 0for any p, q ∈ Aj ( j = 0, 1) and letBj(ε) = p ∈ M | d(p,Aj) < ε. Assume that for some εj > 0there is a 1-1 map T : B1(ε1)→ B0(ε0) such that T ,T−1 aremeasurable and there is c > 1 such that

∀p, q ∈ B1(ε1) : k(T (p),T (q)) ≤ k(p, q)

∀B ⊆ B1(ε1) measurable : µ(T (B)) ≥ cµ(B).

Assume also that for each p ∈ A1, q ∈ M \ B1(ε1) we havek(p, q) > 0.Then ν(A1) < 1 for each measure ν that is a zero temperatureweak limit of minimizers.

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Kinetics in Riemannian Setting

M compact, connected Riemannian manifold of dimension d

with metric gαβ, g = det(gαβ), (gαβ) = (gαβ)−1, volumeelement dµ =

√gdφ in local coordinates φ. Generalized

Doi-Smoluchowski equation

∂t f = ∆g f + divg (f∇gU)

∆g Laplace-Beltrami,

divg (f∇gU) =1√g∂α

(√ggαβf ∂βU

).

U[f ](p) =

∫Mk(p, q)f (q)dµ(q)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Kinetics in Riemannian Setting

M compact, connected Riemannian manifold of dimension dwith metric gαβ,

g = det(gαβ), (gαβ) = (gαβ)−1, volumeelement dµ =

√gdφ in local coordinates φ. Generalized

Doi-Smoluchowski equation

∂t f = ∆g f + divg (f∇gU)

∆g Laplace-Beltrami,

divg (f∇gU) =1√g∂α

(√ggαβf ∂βU

).

U[f ](p) =

∫Mk(p, q)f (q)dµ(q)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Kinetics in Riemannian Setting

M compact, connected Riemannian manifold of dimension dwith metric gαβ, g = det(gαβ),

(gαβ) = (gαβ)−1, volumeelement dµ =

√gdφ in local coordinates φ. Generalized

Doi-Smoluchowski equation

∂t f = ∆g f + divg (f∇gU)

∆g Laplace-Beltrami,

divg (f∇gU) =1√g∂α

(√ggαβf ∂βU

).

U[f ](p) =

∫Mk(p, q)f (q)dµ(q)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Kinetics in Riemannian Setting

M compact, connected Riemannian manifold of dimension dwith metric gαβ, g = det(gαβ), (gαβ) = (gαβ)−1,

volumeelement dµ =

√gdφ in local coordinates φ. Generalized

Doi-Smoluchowski equation

∂t f = ∆g f + divg (f∇gU)

∆g Laplace-Beltrami,

divg (f∇gU) =1√g∂α

(√ggαβf ∂βU

).

U[f ](p) =

∫Mk(p, q)f (q)dµ(q)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Kinetics in Riemannian Setting

M compact, connected Riemannian manifold of dimension dwith metric gαβ, g = det(gαβ), (gαβ) = (gαβ)−1, volumeelement dµ =

√gdφ in local coordinates φ.

GeneralizedDoi-Smoluchowski equation

∂t f = ∆g f + divg (f∇gU)

∆g Laplace-Beltrami,

divg (f∇gU) =1√g∂α

(√ggαβf ∂βU

).

U[f ](p) =

∫Mk(p, q)f (q)dµ(q)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Kinetics in Riemannian Setting

M compact, connected Riemannian manifold of dimension dwith metric gαβ, g = det(gαβ), (gαβ) = (gαβ)−1, volumeelement dµ =

√gdφ in local coordinates φ. Generalized

Doi-Smoluchowski equation

∂t f = ∆g f + divg (f∇gU)

∆g Laplace-Beltrami,

divg (f∇gU) =1√g∂α

(√ggαβf ∂βU

).

U[f ](p) =

∫Mk(p, q)f (q)dµ(q)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Kinetics in Riemannian Setting

M compact, connected Riemannian manifold of dimension dwith metric gαβ, g = det(gαβ), (gαβ) = (gαβ)−1, volumeelement dµ =

√gdφ in local coordinates φ. Generalized

Doi-Smoluchowski equation

∂t f = ∆g f + divg (f∇gU)

∆g Laplace-Beltrami,

divg (f∇gU) =1√g∂α

(√ggαβf ∂βU

).

U[f ](p) =

∫Mk(p, q)f (q)dµ(q)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Kinetics in Riemannian Setting

M compact, connected Riemannian manifold of dimension dwith metric gαβ, g = det(gαβ), (gαβ) = (gαβ)−1, volumeelement dµ =

√gdφ in local coordinates φ. Generalized

Doi-Smoluchowski equation

∂t f = ∆g f + divg (f∇gU)

∆g Laplace-Beltrami,

divg (f∇gU) =1√g∂α

(√ggαβf ∂βU

).

U[f ](p) =

∫Mk(p, q)f (q)dµ(q)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Kinetics in Riemannian Setting

M compact, connected Riemannian manifold of dimension dwith metric gαβ, g = det(gαβ), (gαβ) = (gαβ)−1, volumeelement dµ =

√gdφ in local coordinates φ. Generalized

Doi-Smoluchowski equation

∂t f = ∆g f + divg (f∇gU)

∆g Laplace-Beltrami,

divg (f∇gU) =1√g∂α

(√ggαβf ∂βU

).

U[f ](p) =

∫Mk(p, q)f (q)dµ(q)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Kinetics in Riemannian Setting

M compact, connected Riemannian manifold of dimension dwith metric gαβ, g = det(gαβ), (gαβ) = (gαβ)−1, volumeelement dµ =

√gdφ in local coordinates φ. Generalized

Doi-Smoluchowski equation

∂t f = ∆g f + divg (f∇gU)

∆g Laplace-Beltrami,

divg (f∇gU) =1√g∂α

(√ggαβf ∂βU

).

U[f ](p) =

∫Mk(p, q)f (q)dµ(q)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Dissipative Structure

Free Energy:

E [f ] =

∫M

log f +

1

2U[f ]

fdµ

NLFP:

∂t f = divg ·(f∇g

(δE [f ]

δf

))Lyapunov functional:

d

dtE [f ] = −

∫Mf

∣∣∣∣∇g

(δE [f ]

δf

)∣∣∣∣2 dµ

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Dissipative Structure

Free Energy:

E [f ] =

∫M

log f +

1

2U[f ]

fdµ

NLFP:

∂t f = divg ·(f∇g

(δE [f ]

δf

))Lyapunov functional:

d

dtE [f ] = −

∫Mf

∣∣∣∣∇g

(δE [f ]

δf

)∣∣∣∣2 dµ

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Dissipative Structure

Free Energy:

E [f ] =

∫M

log f +

1

2U[f ]

fdµ

NLFP:

∂t f = divg ·(f∇g

(δE [f ]

δf

))Lyapunov functional:

d

dtE [f ] = −

∫Mf

∣∣∣∣∇g

(δE [f ]

δf

)∣∣∣∣2 dµ

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Dissipative Structure

Free Energy:

E [f ] =

∫M

log f +

1

2U[f ]

fdµ

NLFP:

∂t f = divg ·(f∇g

(δE [f ]

δf

))

Lyapunov functional:

d

dtE [f ] = −

∫Mf

∣∣∣∣∇g

(δE [f ]

δf

)∣∣∣∣2 dµ

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Dissipative Structure

Free Energy:

E [f ] =

∫M

log f +

1

2U[f ]

fdµ

NLFP:

∂t f = divg ·(f∇g

(δE [f ]

δf

))Lyapunov functional:

d

dtE [f ] = −

∫Mf

∣∣∣∣∇g

(δE [f ]

δf

)∣∣∣∣2 dµ

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Connection to Onsager’s equation

For Doi-Smoluchowski

δE [f ]

δf= log f + U[f ]

Time independent solutions: Onsager equation:

f = Z−1e−U[f ]

Dynamics: nontrivial. Multiple steady states, gradient system,finite dimensional attractor. Inertial Manifolds: Vukadinovic(2008-9).

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Connection to Onsager’s equation

For Doi-Smoluchowski

δE [f ]

δf= log f + U[f ]

Time independent solutions: Onsager equation:

f = Z−1e−U[f ]

Dynamics: nontrivial. Multiple steady states, gradient system,finite dimensional attractor. Inertial Manifolds: Vukadinovic(2008-9).

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Connection to Onsager’s equation

For Doi-Smoluchowski

δE [f ]

δf= log f + U[f ]

Time independent solutions:

Onsager equation:

f = Z−1e−U[f ]

Dynamics: nontrivial. Multiple steady states, gradient system,finite dimensional attractor. Inertial Manifolds: Vukadinovic(2008-9).

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Connection to Onsager’s equation

For Doi-Smoluchowski

δE [f ]

δf= log f + U[f ]

Time independent solutions: Onsager equation:

f = Z−1e−U[f ]

Dynamics: nontrivial. Multiple steady states, gradient system,finite dimensional attractor. Inertial Manifolds: Vukadinovic(2008-9).

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Connection to Onsager’s equation

For Doi-Smoluchowski

δE [f ]

δf= log f + U[f ]

Time independent solutions: Onsager equation:

f = Z−1e−U[f ]

Dynamics: nontrivial. Multiple steady states, gradient system,finite dimensional attractor.

Inertial Manifolds: Vukadinovic(2008-9).

Page 161: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Connection to Onsager’s equation

For Doi-Smoluchowski

δE [f ]

δf= log f + U[f ]

Time independent solutions: Onsager equation:

f = Z−1e−U[f ]

Dynamics: nontrivial. Multiple steady states, gradient system,finite dimensional attractor. Inertial Manifolds: Vukadinovic(2008-9).

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Gradient System in Metric Space

M metric. Length space:∀m, n ∈ M ∃p ∈ M, d(p,m) = d(p, n) = 1

2d(m, n).P2(M), probability space with the Wasserstein 2 distance (it isa length space if M is).

Problem: define

∂t f = −grad(E [f ])

DeGiorgi, Ambrosio et al: Energy Dissipation Identity (EDI):

d

dtE [f ] ≤ −1

2|f ′(t)|2 − 1

2|∂E [f ]|2

|f ′(t)| = lims→0

d2(f (t + s), f (t))

|s|and descending slope

|∂E [f ]| = lim supg→f

(E [f ]− E [g ])+d2(f , g)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Gradient System in Metric Space

M metric. Length space:∀m, n ∈ M ∃p ∈ M, d(p,m) = d(p, n) = 1

2d(m, n).P2(M), probability space with the Wasserstein 2 distance (it isa length space if M is). Problem: define

∂t f = −grad(E [f ])

DeGiorgi, Ambrosio et al: Energy Dissipation Identity (EDI):

d

dtE [f ] ≤ −1

2|f ′(t)|2 − 1

2|∂E [f ]|2

|f ′(t)| = lims→0

d2(f (t + s), f (t))

|s|and descending slope

|∂E [f ]| = lim supg→f

(E [f ]− E [g ])+d2(f , g)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Gradient System in Metric Space

M metric. Length space:∀m, n ∈ M ∃p ∈ M, d(p,m) = d(p, n) = 1

2d(m, n).P2(M), probability space with the Wasserstein 2 distance (it isa length space if M is). Problem: define

∂t f = −grad(E [f ])

DeGiorgi, Ambrosio et al: Energy Dissipation Identity (EDI):

d

dtE [f ] ≤ −1

2|f ′(t)|2 − 1

2|∂E [f ]|2

|f ′(t)| = lims→0

d2(f (t + s), f (t))

|s|and descending slope

|∂E [f ]| = lim supg→f

(E [f ]− E [g ])+d2(f , g)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Gradient System in Metric Space

M metric. Length space:∀m, n ∈ M ∃p ∈ M, d(p,m) = d(p, n) = 1

2d(m, n).P2(M), probability space with the Wasserstein 2 distance (it isa length space if M is). Problem: define

∂t f = −grad(E [f ])

DeGiorgi, Ambrosio et al: Energy Dissipation Identity (EDI):

d

dtE [f ] ≤ −1

2|f ′(t)|2 − 1

2|∂E [f ]|2

|f ′(t)| = lims→0

d2(f (t + s), f (t))

|s|and descending slope

|∂E [f ]| = lim supg→f

(E [f ]− E [g ])+d2(f , g)

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Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Gradient System in Metric Space

M metric. Length space:∀m, n ∈ M ∃p ∈ M, d(p,m) = d(p, n) = 1

2d(m, n).P2(M), probability space with the Wasserstein 2 distance (it isa length space if M is). Problem: define

∂t f = −grad(E [f ])

DeGiorgi, Ambrosio et al: Energy Dissipation Identity (EDI):

d

dtE [f ] ≤ −1

2|f ′(t)|2 − 1

2|∂E [f ]|2

|f ′(t)| = lims→0

d2(f (t + s), f (t))

|s|and descending slope

|∂E [f ]| = lim supg→f

(E [f ]− E [g ])+d2(f , g)

Page 167: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Gradient System in Metric Space

M metric. Length space:∀m, n ∈ M ∃p ∈ M, d(p,m) = d(p, n) = 1

2d(m, n).P2(M), probability space with the Wasserstein 2 distance (it isa length space if M is). Problem: define

∂t f = −grad(E [f ])

DeGiorgi, Ambrosio et al: Energy Dissipation Identity (EDI):

d

dtE [f ] ≤ −1

2|f ′(t)|2 − 1

2|∂E [f ]|2

|f ′(t)| = lims→0

d2(f (t + s), f (t))

|s|

and descending slope

|∂E [f ]| = lim supg→f

(E [f ]− E [g ])+d2(f , g)

Page 168: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Gradient System in Metric Space

M metric. Length space:∀m, n ∈ M ∃p ∈ M, d(p,m) = d(p, n) = 1

2d(m, n).P2(M), probability space with the Wasserstein 2 distance (it isa length space if M is). Problem: define

∂t f = −grad(E [f ])

DeGiorgi, Ambrosio et al: Energy Dissipation Identity (EDI):

d

dtE [f ] ≤ −1

2|f ′(t)|2 − 1

2|∂E [f ]|2

|f ′(t)| = lims→0

d2(f (t + s), f (t))

|s|and descending slope

|∂E [f ]| = lim supg→f

(E [f ]− E [g ])+d2(f , g)

Page 169: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Gradient System in Metric Space

M metric. Length space:∀m, n ∈ M ∃p ∈ M, d(p,m) = d(p, n) = 1

2d(m, n).P2(M), probability space with the Wasserstein 2 distance (it isa length space if M is). Problem: define

∂t f = −grad(E [f ])

DeGiorgi, Ambrosio et al: Energy Dissipation Identity (EDI):

d

dtE [f ] ≤ −1

2|f ′(t)|2 − 1

2|∂E [f ]|2

|f ′(t)| = lims→0

d2(f (t + s), f (t))

|s|and descending slope

|∂E [f ]| = lim supg→f

(E [f ]− E [g ])+d2(f , g)

Page 170: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Implicit Euler

Piece-wise constant fτ (t) = fk

for t ∈ (kτ, (k + 1)τ ]

fk+1 := argmin

(E [g ] +

1

2τd22 (g , fk)

)

Limits as τ → 0 exist in general, and givegradient flows in the sense of the energy dis-sipation identity EDI.

Motivation for definition:

In metric space, kinetic equation = EDI ofE in P2(M).

Page 171: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Implicit Euler

Piece-wise constant fτ (t) = fk for t ∈ (kτ, (k + 1)τ ]

fk+1 := argmin

(E [g ] +

1

2τd22 (g , fk)

)

Limits as τ → 0 exist in general, and givegradient flows in the sense of the energy dis-sipation identity EDI.

Motivation for definition:

In metric space, kinetic equation = EDI ofE in P2(M).

Page 172: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Implicit Euler

Piece-wise constant fτ (t) = fk for t ∈ (kτ, (k + 1)τ ]

fk+1 := argmin

(E [g ] +

1

2τd22 (g , fk)

)

Limits as τ → 0 exist in general, and givegradient flows in the sense of the energy dis-sipation identity EDI.

Motivation for definition:

In metric space, kinetic equation = EDI ofE in P2(M).

Page 173: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Implicit Euler

Piece-wise constant fτ (t) = fk for t ∈ (kτ, (k + 1)τ ]

fk+1 := argmin

(E [g ] +

1

2τd22 (g , fk)

)

Limits as τ → 0 exist in general, and givegradient flows in the sense of the energy dis-sipation identity EDI.

Motivation for definition:

In metric space, kinetic equation = EDI ofE in P2(M).

Page 174: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Implicit Euler

Piece-wise constant fτ (t) = fk for t ∈ (kτ, (k + 1)τ ]

fk+1 := argmin

(E [g ] +

1

2τd22 (g , fk)

)

Limits as τ → 0 exist in general, and givegradient flows in the sense of the energy dis-sipation identity EDI.

Motivation for definition:

In metric space, kinetic equation = EDI ofE in P2(M).

Page 175: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Implicit Euler

Piece-wise constant fτ (t) = fk for t ∈ (kτ, (k + 1)τ ]

fk+1 := argmin

(E [g ] +

1

2τd22 (g , fk)

)

Limits as τ → 0 exist in general, and givegradient flows in the sense of the energy dis-sipation identity EDI.

Motivation for definition:

In metric space, kinetic equation = EDI ofE in P2(M).

Page 176: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.

Assume E [f ] = E [f ] + Q[f ] with E convex andQ[f ] = 1

2(Lf , f ), with L bounded, selfadjoint in Hilbert spaceH.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 177: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ]

with E convex andQ[f ] = 1

2(Lf , f ), with L bounded, selfadjoint in Hilbert spaceH.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 178: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ] with E convex and

Q[f ] = 12(Lf , f ), with L bounded, selfadjoint in Hilbert space

H.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 179: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ] with E convex andQ[f ] = 1

2(Lf , f ),

with L bounded, selfadjoint in Hilbert spaceH.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 180: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ] with E convex andQ[f ] = 1

2(Lf , f ), with L bounded, selfadjoint

in Hilbert spaceH.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 181: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ] with E convex andQ[f ] = 1

2(Lf , f ), with L bounded, selfadjoint in Hilbert spaceH.

Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 182: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ] with E convex andQ[f ] = 1

2(Lf , f ), with L bounded, selfadjoint in Hilbert spaceH.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 183: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ] with E convex andQ[f ] = 1

2(Lf , f ), with L bounded, selfadjoint in Hilbert spaceH.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0.

Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 184: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ] with E convex andQ[f ] = 1

2(Lf , f ), with L bounded, selfadjoint in Hilbert spaceH.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive.

Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 185: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ] with E convex andQ[f ] = 1

2(Lf , f ), with L bounded, selfadjoint in Hilbert spaceH.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 186: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ] with E convex andQ[f ] = 1

2(Lf , f ), with L bounded, selfadjoint in Hilbert spaceH.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 187: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ] with E convex andQ[f ] = 1

2(Lf , f ), with L bounded, selfadjoint in Hilbert spaceH.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).

Page 188: Fluids and Paricles: Doodads and Kineticsphp.math.unifi.it/users/cime/Courses/2010/04/Talks/...Fluids and Paricles: Doodads and Kinetics Peter Constantin Introduction Complex Microscopic

Fluids andParicles:

Doodads andKinetics

PeterConstantin

Introduction

ComplexMicroscopicSystems

Examples

OnsagerEquation

Relaxationkinetics

Evolutional Variational Inequalities

In the convex energy, Hilbert space case: well understood.Assume E [f ] = E [f ] + Q[f ] with E convex andQ[f ] = 1

2(Lf , f ), with L bounded, selfadjoint in Hilbert spaceH.Definition: Evolutional Variational Inequality (EVI)

1

2

d

dt‖f (t)−g‖2 ≤ E [g ]−E [f (t)]−Q[f (t)−g ], ∀g

recover classical definition for Q = 0. Interesting for L notpositive. Uniqueness of solutions of initial value problem canbe obtained in the non-convex, Hilbert case.

• Open: Define Evolutional Variational Inequality EVI fornon-convex energies in length spaces.

• Open: EDI implies uniqueness of solutions of initial valueproblem in the nonconvex case in length spaces.

• Open: Time asymptotics to Onsager solution, in P2(M).