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I S R A E L S C I E N C E F O U N D A T I O N Fractals : Spectral properties Statistical physics Course 1 6th Cornell Conference on Analysis, Probability, and Mathematical Physics on Fractals , June 13-17, 2017 Eric Akkermans
92

Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

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Page 1: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

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Fractals : Spectral properties Statistical physics

!

Course 1

6th Cornell Conference on Analysis, Probability, and Mathematical Physics on Fractals, June 13-17, 2017

Eric Akkermans

Page 2: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Benefitted from discussions and collaborations with:

Technion: !Evgeni Gurevich (KLA-Tencor) Dor Gittelman Eli Levy (+ Rafael) Ariane Soret (ENS Cachan) Or Raz (HUJI, Maths) Omrie Ovdat Yaroslav Don !

!

Elsewhere: !Gerald Dunne (UConn.) Alexander Teplyaev (UConn.) Jacqueline Bloch (LPN, Marcoussis) Dimitri Tanese (LPN, Marcoussis) Florent Baboux (LPN, Marcoussis) Alberto Amo (LPN, Marcoussis) Eva Andrei (Rutgers) Jinhai Mao (Rutgers) Arkady Poliakovsky (Maths. BGU)

!!

Rafael: Assaf Barak Amnon Fisher !!

!

Page 3: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Benefitted from discussions and collaborations with:

Technion: !Evgeni Gurevich (KLA-Tencor) Dor Gittelman Eli Levy (+ Rafael) Ariane Soret (ENS Cachan) Or Raz (HUJI, Maths) Omrie Ovdat Yaroslav Don !

!

Elsewhere: !Gerald Dunne (UConn.) Alexander Teplyaev (UConn.) Jacqueline Bloch (LPN, Marcoussis) Dimitri Tanese (LPN, Marcoussis) Florent Baboux (LPN, Marcoussis) Alberto Amo (LPN, Marcoussis) Eva Andrei (Rutgers) Jinhai Mao (Rutgers) Arkady Poliakovsky (Maths. BGU)

!!

Rafael: Assaf Barak Amnon Fisher !!

!

Page 4: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Plan of the 4 talks• Course 1 : Spectral properties of fractals -

Application in statistical physics

• Talk : quantum phase transition - scale anomaly and fractals

• Course 2 : topology and fractals - measuring topological numbers with waves.

• Elaboration : Renormalisation group and Efimov physics

Page 5: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Program for today

• Introduction : spectral properties of self similar fractals.

• Heat kernel - Asymptotic behaviour - Weyl expansion - Spectral volume.

• Thermodynamics of the fractal blackbody.

• Summary - Phase transitions.

Page 6: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Introduction : spectral properties of self similar fractals.

• attractive objects - Bear exotic names

Julia sets

Page 7: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Hofstadter butterfly

Anatomy of the Hofstadter butterfly

Energy levels and wave functions of Bloch electrons in rational and irrational magnetic fields, Douglas Hofstadter, Phys. Rev. B 14 (1976) 2239

0

IMI

0I he

M

OutlineGeneral features ----- square lattice

Half-flux quantum per unit cell ------- Dirac spectrum

Honeycomb lattice, graphene, manipulation of Dirac points

Finite systems, edge states

Hofstadter in other contexts

0

IMI

Anatomy of the Hofstadter butterfly

M. Azbel (1964)

G.H. Wannier

Y. Avron, B. Simon

J. Bellissard, R. Rammal

D. Thouless, Q. Niu

TKNN : Thouless, Kohmoto, Nightingale, den Nijs

Y. Hatsugai

Sierpinski carpet Sierpinski gasket

Page 8: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Figure: Diamond fractals, non-p.c.f., but finitely ramified

Diamond fractals

Convey the idea of highly symmetric objects yet with an unusual type of symmetry and a notion of extreme subdivision

Triadic Cantor set

Page 9: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

! !!!

! !!!!

! !!!!!

Sierpinski gasket

Diamond fractals

Fractal : Iterative graph structure

Figure: Diamond fractals, non-p.c.f., but finitely ramified

n→∞

Page 10: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

! !!!

! !!!!

! !!!!!

Sierpinski gasket

Diamond fractals

Fractal : Iterative graph structure

Figure: Diamond fractals, non-p.c.f., but finitely ramified

n→∞

Page 11: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

As opposed to Euclidean spaces characterised by translation symmetry, fractals possess a

dilatation symmetry.

Fractals are self-similar objects

Page 12: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Fractal ↔ Self-similar

Discrete scaling symmetry

Page 13: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

• But not all fractals are obvious, good faith geometrical objects.!

Sometimes, the fractal structure is not geometrical but it is hidden at a more abstract level.

Exemple : quasi-periodic stack of dielectric layers of 2 types

Fibonacci sequence : F1 = B; F2 = A; Fj≥3 = Fj−2Fj−1⎡⎣ ⎤⎦

A, B

Defines a cavity whose mode spectrum is fractal.

Page 14: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

• But generally, not all fractals are obvious, good faith geometrical objects.!

Sometimes, the fractal structure is not geometrical but it is hidden at a more abstract level.

Exemple : Quasi-periodic chain of layers of 2 types

Fibonacci sequence : F1 = B; F2 = A; Fj≥3 = Fj−2Fj−1⎡⎣ ⎤⎦

A, B

Defines a cavity whose frequency spectrum is fractal.

Page 15: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Density of modes ρ(ω) :

Discrete scaling symmetry

Minicourse 2 - Tomorrow

Page 16: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Operators and fields on fractal manifolds

16

Operators are often expressed by local differential equations relating the space-time behaviour of a field

∂2u∂t 2

= Δu Ex. Wave equation

Such local equations cannot be defined on a fractal

Figure: Diamond fractals, non-p.c.f., but finitely ramified

Page 17: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

But operators are essential quantities for physics!

• Quantum transport in fractal structures :

e.g., networks, waveguides, ...

electrons, photons • Density of states

• Scattering matrix (transmission/reflection)

17

Page 18: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

• Quantum fields on fractals, e.g., fermions (spin 1/2), photons (spin 1) - canonical quantisation (Fourier modes) - path integral quantisation : path integrals, Brownian motion.

!

• “curved space QFT” or quantum gravity

!

• Scaling symmetry (renormalisation group) - critical behaviour.

18

But operators are essential quantities for physics!

Page 19: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

19

Michel Lapidus Bob Strichartz

Jun Kigami

>2000

Recent new ideas

Maths.

Page 20: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Intermezzo : heat and waves

Page 21: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

From classical diffusion to wave propagation

Important relation between classical diffusion and wave propagation on a manifold.

Expresses the idea that it is possible to measure and characterise a manifold using waves (eigenvalue

spectrum of the Laplace operator)

• Generalities on fractals

Many self-similar (fractal) structures in nature and many ways to model them:A random walk in free space or on a periodic lattice etc.

Fractals provide a useful testing ground to investigate properties of disordered classical or quantum systems, renormalization group and phase transitions, gravitational systems and quantum field theory.

Motivation:

geometrycurvaturevolume

dimension

Spectral dataHeat kernel

Zeta function

Differential operator“propagating probe”

physically:Laplacian

How does it look on a fractal ? Even the simplest question, e.g. dimension, are surprisingly different !

Page 22: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

22

Use propagating waves/particles to probe :

• spectral information: density of states, transport,

heat kernel, ...

• geometric information: dimension, volume,

boundaries, shape, ...

Page 23: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Mathematical physics

23

Use propagating waves/particles to probe :

• spectral information: density of states, transport,

heat kernel, ...

• geometric information: dimension, volume,

boundaries, shape, ...

1910 Lorentz: why is the Jeans radiation law only dependent

on the volume ?

1911 Weyl : relation between asymptotic eigenvalues and

dimension/volume.

1966 Kac : can one hear the shape of a drum ?

Page 24: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Important examples

• Heat equation

!

• Wave equation

!

24

i ∂u∂t

= Δu

∂u∂t

= Δu

∂2u∂t 2

= Δu

Schr. equation.

Pt x, y( ) = xe−(i ) !x2 dτ

0

t

x 0( )=x,x t( )=y∫ D Brownian motion

Pt x, y( ) ∼ 1td2

an (x, y)tn

n∑

Pt x, y( ) ∼ #( )geodesics∑ e−(i )Sclassical (x,y,t )

Heat kernel expansion

Gutzwiller - instantons

u x,t( ) = dµ y( )Pt x, y( )u y,0( )∫

Page 25: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Important examples

• Heat equation

!

• Wave equation

!

25

i ∂u∂t

= Δu

∂u∂t

= Δu

∂2u∂t 2

= Δu

Schr. equation.

Pt x, y( ) = xe−(i ) !x2 dτ

0

t

x 0( )=x,x t( )=y∫ D Brownian motion

Pt x, y( ) ∼ 1td2

an (x, y)tn

n∑

Pt x, y( ) ∼ #( )geodesics∑ e−(i )Sclassical (x,y,t )

Heat kernel expansion

Gutzwiller - instantons

u x,t( ) = dµ y( )Pt x, y( )u y,0( )∫u x,t( ) = dµ y( )Pt x, y( )u y,0( )∫

Page 26: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Important examples

• Heat equation

!

• Wave equation

!

26

i ∂u∂t

= Δu

∂u∂t

= Δu

∂2u∂t 2

= Δu

Schr. equation.

Pt x, y( ) = xe−(i ) !x2 dτ

0

t

x 0( )=x,x t( )=y∫ D Brownian motion

Pt x, y( ) ∼ 1td2

an (x, y)tn

n∑

Pt x, y( ) ∼ #( )geodesics∑ e−(i )Sclassical (x,y,t )

Heat kernel expansion

Gutzwiller - instantons

u x,t( ) = dµ y( )Pt x, y( )u y,0( )∫u x,t( ) = dµ y( )Pt x, y( )u y,0( )∫

Pt x, y( ) = xe−(i ) !x2 dτ

0

t

x 0( )=x,x t( )=y∫ D Brownian motion

Pt x, y( ) ∼ 1td2

an (x, y)tn

n∑

Pt x, y( ) ∼ #( )geodesics∑ e−(i )Sclassical (x,y,t )

Heat kernel expansion

Gutzwiller - instantons

Page 27: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Important examples

• Heat equation

!

• Wave equation

!

27

i ∂u∂t

= Δu

∂u∂t

= Δu

∂2u∂t 2

= Δu

Schr. equation.

Pt x, y( ) = xe−(i ) !x2 dτ

0

t

x 0( )=x,x t( )=y∫ D Brownian motion

Pt x, y( ) ∼ 1td2

an (x, y)tn

n∑

Pt x, y( ) ∼ #( )geodesics∑ e−(i )Sclassical (x,y,t )

Heat kernel expansion

Gutzwiller - instantons

u x,t( ) = dµ y( )Pt x, y( )u y,0( )∫u x,t( ) = dµ y( )Pt x, y( )u y,0( )∫

Pt x, y( ) = xe−(i ) !x2 dτ

0

t

x 0( )=x,x t( )=y∫ D Brownian motion

Pt x, y( ) ∼ 1td2

an (x, y)tn

n∑

Pt x, y( ) ∼ #( )geodesics∑ e−(i )Sclassical (x,y,t )

Heat kernel expansion

Gutzwiller - instantons

Page 28: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Spectral functions

28

Small t behaviour of Z(t) poles ofζ Z s( )⇔

Pt x, y( ) = y e−Δt x = ψ λ∗ (y)

λ∑ ψ λ (x)e

−λt

ζ Z s( ) ≡ 1Γ s( ) dtt s−1Z t( )

0

∫ Mellin transform

Heat kernelZ(t) =Tre−Δt = dx x e−Δt x∫ = e−λtλ∑

ζ Z s( ) = Tr 1Δ s =

1λ s

λ∑

Weyl expansion

Page 29: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

29

Small t behaviour of Z(t) poles ofζ Z s( )⇔

Pt x, y( ) = y e−Δt x = ψ λ∗ (y)

λ∑ ψ λ (x)e

−λt

ζ Z s( ) ≡ 1Γ s( ) dtt s−1Z t( )

0

∫ Mellin transform

Heat kernelZ(t) =Tre−Δt = dx x e−Δt x∫ = e−λtλ∑

ζ Z s( ) = Tr 1Δ s =

1λ s

λ∑

Weyl expansion

Spectral functions

Page 30: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

30

Small t behaviour of Z(t) poles ofζ Z s( )⇔

Pt x, y( ) = y e−Δt x = ψ λ∗ (y)

λ∑ ψ λ (x)e

−λt

ζ Z s( ) ≡ 1Γ s( ) dtt s−1Z t( )

0

∫ Mellin transform

Heat kernelZ(t) =Tre−Δt = dx x e−Δt x∫ = e−λtλ∑

ζ Z s( ) = Tr 1Δ s =

1λ s

λ∑

Weyl expansion

Return probability

Spectral functions

Page 31: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

31

Small t behaviour of Z(t) poles ofζ Z s( )⇔

Pt x, y( ) = y e−Δt x = ψ λ∗ (y)

λ∑ ψ λ (x)e

−λt

ζ Z s( ) ≡ 1Γ s( ) dtt s−1Z t( )

0

∫ Mellin transform

Heat kernelZ(t) =Tre−Δt = dx x e−Δt x∫ = e−λtλ∑

ζ Z s( ) = Tr 1Δ s =

1λ s

λ∑

Weyl expansion

Spectral functions

Page 32: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

32

Small t behaviour of Z(t) poles ofζ Z s( )⇔

Pt x, y( ) = y e−Δt x = ψ λ∗ (y)

λ∑ ψ λ (x)e

−λt

ζ Z s( ) ≡ 1Γ s( ) dtt s−1Z t( )

0

∫ Mellin transform

Heat kernelZ(t) =Tre−Δt = dx x e−Δt x∫ = e−λtλ∑

ζ Z s( ) = Tr 1Δ s =

1λ s

λ∑

Spectral functions

Page 33: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

33

Small t behaviour of Z(t) poles ofζ Z s( )⇔

Pt x, y( ) = y e−Δt x = ψ λ∗ (y)

λ∑ ψ λ (x)e

−λt

ζ Z s( ) ≡ 1Γ s( ) dtt s−1Z t( )

0

∫ Mellin transform

Heat kernelZ(t) =Tre−Δt = dx x e−Δt x∫ = e−λtλ∑

ζ Z s( ) = Tr 1Δ s =

1λ s

λ∑

Weyl expansion

Spectral functions

Page 34: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

The heat kernel is related to the density of states of the Laplacian

There are “Laplace transform” of each other:

From the Weyl expansion, it is possible to obtain the density of states. !

Page 35: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Diffusion (heat) equation in d=1

whose spectral solution is

Probability of diffusing from x to y in a time t.!In d space dimensions:

access the volume of the manifold

Pt x, y( ) = 14πDt( )12

e−x−y( )24Dt

Pt x, y( ) = 14πDt( )d 2

e−x−y( )24Dt

Zd t( ) = ddxVol .∫ Pt x, x( )= Volume

4πDt( )d 2

We can characterise the “spatial geometry” by watching how the heat flows. The heat kernel isZd t( )

How does it work ?

Page 36: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

How does it work ?

Diffusion (heat) equation in d=1

whose spectral solution is

Probability of diffusing from x to y in a time t.!In d space dimensions:

access the volume of the manifold

Pt x, y( ) = 14πDt( )12

e−x−y( )24Dt

Pt x, y( ) = 14πDt( )d 2

e−x−y( )24Dt

Zd t( ) = ddxVol .∫ Pt x, x( )= Volume

4πDt( )d 2

We can characterise the “spatial geometry” by watching how the heat flows. The heat kernel isZd t( )

Page 37: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

How does it work ?

Diffusion (heat) equation in d=1

whose spectral solution is

Probability of diffusing from x to y in a time t.!In d space dimensions:

access the volume of the manifold

Pt x, y( ) = 14πDt( )12

e−x−y( )24Dt

Pt x, y( ) = 14πDt( )d 2

e−x−y( )24Dt

Zd t( ) = ddxVol .∫ Pt x, x( )= Volume

4πDt( )d 2

We can characterise the “spatial geometry” by watching how the heat flows. The heat kernel isZd t( )

Page 38: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

How does it work ?

Diffusion (heat) equation in d=1

whose spectral solution is

Probability of diffusing from x to y in a time t.!In d space dimensions:

volume of the manifold

Pt x, y( ) = 14πDt( )12

e−x−y( )24Dt

Pt x, y( ) = 14πDt( )d 2

e−x−y( )24Dt

Zd t( ) = ddxVol .∫ Pt x, x( )= Volume

4πDt( )d 2

We can characterise the “spatial geometry” by watching how the heat flows. The heat kernel isZd t( )

Page 39: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

0 L

Mark Kac (1966)Boundary terms- Hearing the shape of a drum

Page 40: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

0 L

Mark Kac (1966)Boundary terms- Hearing the shape of a drum

Page 41: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

0 L

Mark Kac (1966)Boundary terms- Hearing the shape of a drum

Poisson formula

Page 42: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

0 L

Mark Kac (1966)Boundary terms- Hearing the shape of a drum

Poisson formula

Page 43: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

0 L

Mark Kac (1966)Boundary terms- Hearing the shape of a drum

Poisson formula

Weyl expansion (1d)

Page 44: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

0 L

Weyl expansion (2d) :

Mark Kac (1966)

Zd=2 (t) ∼Vol.4πt

− L4

14πt

+16+…

Boundary terms- Hearing the shape of a drum

Poisson formula

Page 45: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

0 L

Weyl expansion (2d) :

Mark Kac (1966)

bulk

Zd=2 (t) ∼Vol.4πt

− L4

14πt

+16+…

Boundary terms- Hearing the shape of a drum

Poisson formula

Page 46: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

0 L

Weyl expansion (2d) :

Mark Kac (1966)

sensitive to boundarybulk

Zd=2 (t) ∼Vol.4πt

− L4

14πt

+16+…

Boundary terms- Hearing the shape of a drum

Poisson formula

Page 47: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

0 L

Weyl expansion (2d) :

Mark Kac (1966)

sensitive to boundarybulk

integral of bound. curvature

Zd=2 (t) ∼Vol.4πt

− L4

14πt

+16+…

Boundary terms- Hearing the shape of a drum

Poisson formula

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-functionZeta function

has a simple pole at so that,

ζ ζ Z s( ) = Tr 1Δ s =

1λ s

λ∑

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How does it work on a fractal ?

Differently…

No access to the eigenvalue spectrum but we know howto calculate the Heat Kernel.

Z(t) =Tre−Δt = dx x e−Δt x∫ = e−λtλ∑

and thus, the density of states,

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Differently…

No simple access to the eigenvalue spectrum but we know how to calculate the heat kernel.

Z(t) =Tre−Δt = dx x e−Δt x∫ = e−λtλ∑

and thus, the density of states,

How does it work on a fractal ?

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More precisely,

is the total length upon iteration of the elementary step

which has poles at

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Infinite number of complex poles : complex fractal dimensions. They control the behaviour of the heat kernel which exhibits oscillations.

0.00 0.05 0.10 0.15 0.20 0.25t

0.2

0.4

0.6

0.8

1.0K!t"#Kleading!t"

2.10!4

10!3

2.10!3t

0.980

0.985

0.990

0.995

1.000

1.005

dsA new fractal dimension : spectral dimension

⇔ sn =ds2+ 2iπndw lna

Zdiamond t( )Figure: Diamond fractals, non-p.c.f., but finitely ramified

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Notion of spectral volume

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to compare with

s1 =ds2+ 2iπdw lna

≡ ds2+ iδConsider for simplicity , namely n = 1

From the previous expression we obtain Z t( )

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so that

to compare with

s1 =ds2+ 2iπdw lna

≡ ds2+ iδConsider for simplicity , namely n = 1

From the previous expression we obtain Z t( )

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so that

to compare with

s1 =ds2+ 2iπdw lna

≡ ds2+ iδConsider for simplicity , namely n = 1

From the previous expression we obtain Z t( )

Spectral volume

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so that

to compare with

s1 =ds2+ 2iπdw lna

≡ ds2+ iδConsider for simplicity , namely n = 1

From the previous expression we obtain Z t( )

Spectral volume

Zd t( ) = ddxVol .∫ Pt x, x( )= Volume

4πDt( )d 2

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Geometric volume described by the Hausdorff dimension is large

(infinite)

Spectral volume ?

Spectral volume is the finite volume occupied by the

modes

Numerical solution of Maxwell eqs. in the Sierpinski gasket (courtesy of S.F. Liew and H. Cao, Yale)

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Spectral volume is the finite volume occupied by the

modes

Numerical solution of Maxwell eqs. on the Sierpinski gasket

Spectral volume ?

Geometric volume described by the Hausdorff dimension is large

(infinite)

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Physical application : Thermodynamics of photons on fractals

Electromagnetic field in a waveguide fractal structure.

How to measure the spectral volume ?

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physical application: thermodynamics on a fractal

dE

d⇥= V

T

2�2c3⇥2

In an enclosure with a perfectly reflecting surface there can form standing electromagnetic waves analogous to tones of an organ pipe; we shall confine our attention to very high overtones. Jeans asks for the energy in the frequency interval dν ... It is here that there arises the mathematical

problem to prove that the number of sufficiently high overtones that lies in the interval ν to ν+dν is independent of the shape of the enclosure and is simply proportional to its volume.

H. Lorentz, 1910

Akkermans, GD, Teplyaev, 2010

The radiating fractal blackbodyusual approach: count modes in momentum space

thermal equilibrium: equation of state

P V =1d

U

pressure volume internal energy

lnZ(T, V )partition function (generating function)

P =1�

⇥ lnZ⇥V

U = �⇥ lnZ⇥�

� =1T

Equation of state at thermodynamic equilibrium relating pressure, volume and internal energy:

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physical application: thermodynamics on a fractal

dE

d⇥= V

T

2�2c3⇥2

In an enclosure with a perfectly reflecting surface there can form standing electromagnetic waves analogous to tones of an organ pipe; we shall confine our attention to very high overtones. Jeans asks for the energy in the frequency interval dν ... It is here that there arises the mathematical

problem to prove that the number of sufficiently high overtones that lies in the interval ν to ν+dν is independent of the shape of the enclosure and is simply proportional to its volume.

H. Lorentz, 1910

Akkermans, GD, Teplyaev, 2010

usual approach: count modes in momentum space

thermal equilibrium: equation of state

P V =1d

U

pressure volume internal energy

lnZ(T, V )partition function (generating function)

P =1�

⇥ lnZ⇥V

U = �⇥ lnZ⇥�

� =1T

Equation of state at thermodynamic equilibrium relating pressure, volume and internal energy:

Spectral volume ?

The radiating fractal blackbody

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Usual approach : count modes in momentum space

is a dimensionless function

Black-body radiation in a large volume

Mode decomposition of the field:

d-dimensional integer-valued vector-elementary momentum space cells

so that

is the photon thermal wavelength.

Mode decomposition of the field

Calculate the partition (generating) function for a blackbody of !large volume in dimension

z T ,V( )V d

usual approach: count modes in momentum space

thermal equilibrium: equation of state

P V =1d

U

pressure volume internal energy

lnZ(T, V )partition function (generating function)

P =1�

⇥ lnZ⇥V

U = �⇥ lnZ⇥�

� =1T

2π( )dV

is a dimensionless function

Black-body radiation in a large volume

Mode decomposition of the field:

d-dimensional integer-valued vector-elementary momentum space cells

so that

is the photon thermal wavelength.

Lβ ≡ β!cwith

(photon thermal wavelength)β = 1

kBT

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so that

Stefan-Boltzmann is a consequence of

Adiabatic expansion

(The exact expression of Q is unimportant)

Thermodynamics :

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so that

Stefan-Boltzmann is a consequence of

Adiabatic expansion

(The exact expression of Q is unimportant)

Thermodynamics :

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so that

Stefan-Boltzmann is a consequence of

Adiabatic expansion

(The exact expression of Q is unimportant)

Thermodynamics :

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is the “spectral volume”.

On a fractal there is no notion of Fourier mode decomposition.!

Dimensions of momentum and position spaces are usually different : problem with the conventional formulation in terms of

phase space cells.!

Volume of a fractal is usually infinite. !

Nevertheless,

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is the “spectral volume”.

On a fractal there is no notion of Fourier mode decomposition.!

Dimensions of momentum and position spaces are usually different : problem with the conventional formulation in terms of

phase space cells.!

Volume of a fractal is usually infinite. !

Nevertheless,

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is the “spectral volume”.

On a fractal there is no notion of Fourier mode decomposition.!

Dimensions of momentum and position spaces are usually different : problem with the conventional formulation in terms of

phase space cells.!

Volume of a fractal is usually infinite. !

Nevertheless,

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is the “spectral volume”.

On a fractal there is no notion of Fourier mode decomposition.!

Dimensions of momentum and position spaces are usually different : problem with the conventional formulation in terms of

phase space cells.!

Volume of a fractal is usually infinite. !

Nevertheless,

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Re-phrase the thermodynamic problem in terms of heat kernel and zeta function.

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Rescale by Lβ ≡ β!c

ln z T ,V( ) = − 12lnDetM×V

∂2

∂τ 2+ c2Δ⎛

⎝⎜⎞⎠⎟

Looks (almost) like a bona fide wave equation proper time. but

This expression does not rely on mode decomposition.!

Partition function of equilibrium quantum radiation

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Spatial manifold (fractal)

ln z T ,V( ) = − 12lnDetM×V

∂2

∂u2+Lβ

2 Δ⎛⎝⎜

⎞⎠⎟

M Lβ ≡ β!c: circle of radius

Thermal equilibrium of photons on a spatial manifold V at temperature T is described by the (scaled) wave equation on M ×V

Partition function of equilibrium quantum radiation

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can be rewritten

ln z T ,V( ) = − 12lnDetM×V

∂2

∂u2+Lβ

2 Δ⎛⎝⎜

⎞⎠⎟

Z Lβ2 τ( )

Heat kernel

Large volume limit (a high temperature limit)

Weyl expansion:

ln z T ,V( ) = 12

dττf τ( )TrV e−τLβ

2 Δ

0

Z Lβ2 τ( )∼ V

4π Lβ2 τ( )d 2

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can be rewritten

ln z T ,V( ) = − 12lnDetM×V

∂2

∂u2+Lβ

2 Δ⎛⎝⎜

⎞⎠⎟

Large volume limit (a high temperature limit)

Weyl expansion:

ln z T ,V( ) = 12

dττf τ( )TrV e−τLβ

2 Δ

0

Z Lβ2 τ( )∼ V

4π Lβ2 τ( )d 2

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can be rewritten

ln z T ,V( ) = − 12lnDetM×V

∂2

∂u2+Lβ

2 Δ⎛⎝⎜

⎞⎠⎟

Large volume limit (a high temperature limit)

Weyl expansion:

ln z T ,V( ) = 12

dττf τ( )TrV e−τLβ

2 Δ

0

Z Lβ2 τ( )∼ V

4π Lβ2 τ( )d 2

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can be rewritten

ln z T ,V( ) = − 12lnDetM×V

∂2

∂u2+Lβ

2 Δ⎛⎝⎜

⎞⎠⎟

Z Lβ2 τ( )

Heat kernel

Large volume limit (a high temperature limit)

Weyl expansion:

ln z T ,V( ) = 12

dττf τ( )TrV e−τLβ

2 Δ

0

Z Lβ2 τ( )∼ V

4π Lβ2 τ( )d 2

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can be rewritten

ln z T ,V( ) = − 12lnDetM×V

∂2

∂u2+Lβ

2 Δ⎛⎝⎜

⎞⎠⎟

Z Lβ2 τ( )

Heat kernel

Large volume limit (a high temperature limit)

Weyl expansion:

ln z T ,V( ) = 12

dττf τ( )TrV e−τLβ

2 Δ

0

Z Lβ2 τ( )∼ V

4π Lβ2 τ( )d 2

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ln z T ,V( ) = 12

dττf τ( )TrV e−τLβ

2 Δ

0

+ Weyl expansion ln z T ,V( ) ∼ VLβd⇒

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Thermodynamics measures the spectral volume

ln z T ,V( ) = 12

dττf τ( )TrV e−τLβ

2 Δ

0

+ Weyl expansion ln z T ,V( ) ∼ VLβd⇒

so that

Stefan-Boltzmann is a consequence of

Adiabatic expansion

(The exact expression of Q is unimportant)

Thermodynamics :

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Thermodynamics measures the spectral volume

ln z T ,V( ) = 12

dττf τ( )TrV e−τLβ

2 Δ

0

+ Weyl expansion ln z T ,V( ) ∼ VLβd⇒

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On a fractal…

Z Lβ2 τ( )∼ Vs

4π Lβ2 τ( )

ds2f lnτ( )

Thermodynamic equation of state for a fractal manifold

Thermodynamics measures the spectral volume and the spectral dimension.

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Z Lβ2 τ( )∼ Vs

4π Lβ2 τ( )

ds2f lnτ( )

Spectral volume

Thermodynamic equation of state for a fractal manifold

Thermodynamics measures the spectral volume and the spectral dimension.

On a fractal…

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Z Lβ2 τ( )∼ Vs

4π Lβ2 τ( )

ds2f lnτ( )

Spectral dimension

Spectral volume

Thermodynamic equation of state for a fractal manifold

Thermodynamics measures the spectral volume and the spectral dimension.

On a fractal…

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Z Lβ2 τ( )∼ Vs

4π Lβ2 τ( )

ds2f lnτ( )

Spectral dimension

Spectral volume

Thermodynamic equation of state for a fractal manifold

Thermodynamics measures the spectral volume and the spectral dimension.

On a fractal…

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Summary

• Significant progress in understanding and computing the asymptotic behaviour (Weyl) of heat kernels on fractals.

• Thermodynamics is directly related to the heat kernel (partition function) - fractal blackbody - importance of the spectral volume.

• Phase transitions on fractals : scaling/hyperscaling relations are modified on fractals (dependence on distinct fractal dimensions).

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Summary

• Significant progress in understanding and computing the asymptotic behaviour (Weyl) of heat kernels on fractals.

• Thermodynamics is directly related to the heat kernel (partition function) - fractal blackbody - importance of the spectral volume.

• Phase transitions on fractals : scaling/hyperscaling relations are modified on fractals (dependence on distinct fractal dimensions).

Page 88: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

Summary

• Significant progress in understanding and computing the asymptotic behaviour (Weyl) of heat kernels on fractals.

• Thermodynamics is directly related to the heat kernel (partition function) - fractal blackbody - importance of the spectral volume.

• Phase transitions on fractals : scaling/hyperscaling relations are modified on fractals (dependence on distinct fractal dimensions).

Page 89: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

• Non gaussian fixed points (limit cycles) - Harris criterion : fractal geometry is a specific type of disorder similar to quasicrystals.

• Off-diagonal long range order - superfluidity (Mermin, Wagner, Coleman theorem) - Non diagonal Green’s function.

• Applications to other problems : quantum phase transitions - quantum Einstein gravity, …

Page 90: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

• Non gaussian fixed points (limit cycles) - Harris criterion : fractal geometry is a specific type of disorder similar to quasicrystals.

• Off-diagonal long range order - superfluidity (Mermin, Wagner, Coleman theorem) - Non diagonal Green’s function.

• Applications to other problems : quantum phase transitions - quantum Einstein gravity, …

Page 91: Fractals : Spectral properties Statistical physicspi.math.cornell.edu › ~fractals › 6 › slides › Akkermans-course.pdf · Fractals provide a useful testing ground to investigate

• Non gaussian fixed points (limit cycles) - Harris criterion : fractal geometry is a specific type of disorder similar to quasicrystals.

• Off-diagonal long range order - superfluidity (Mermin, Wagner, Coleman theorem) - Non diagonal Green’s function.

• Applications to other problems : quantum phase transitions - quantum Einstein gravity, …

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Thank you for your attention.