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Markov Chains on Tilings: From Chaos to Order Thomas Fernique CIRM, October 21, 2013

Markov Chains on Tilings: From Chaos to Order

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Page 1: Markov Chains on Tilings: From Chaos to Order

Markov Chains on Tilings:From Chaos to Order

Thomas Fernique

CIRM, October 21, 2013

Page 2: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

1 Order

2 Chaos

3 From chaos to order

Page 3: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

1 Order

2 Chaos

3 From chaos to order

Page 4: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Quasicrystals and tilings

Definition (IUCr, 1992)

Crystal = ordered material = essentially discrete diffraction.

1982: discovery of the first non-periodic crystal ( Nobel in 2011).

The periodic crystals are usually modelled by patterns on lattices.The non-periodic ones have quickly been modelled by tilings.

Definition

Tiling = covering of the plane by non-overlapping compact sets.

Example: digitizations of affine planes in higher dimensional space.

Quasicrystal stability (at low T ): finite range energetic interaction.Modelled on tilings by constraints on the way things locally fit.

Page 5: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Quasicrystals and tilings

Definition (IUCr, 1992)

Crystal = ordered material = essentially discrete diffraction.

1982: discovery of the first non-periodic crystal ( Nobel in 2011).

The periodic crystals are usually modelled by patterns on lattices.The non-periodic ones have quickly been modelled by tilings.

Definition

Tiling = covering of the plane by non-overlapping compact sets.

Example: digitizations of affine planes in higher dimensional space.

Quasicrystal stability (at low T ): finite range energetic interaction.Modelled on tilings by constraints on the way things locally fit.

Page 6: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 1: Dimer tilings

Rows alternate rhombi (between their orientation):

Page 7: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 1: Dimer tilings

Rows alternate rhombi (between their orientation):

Page 8: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 2: Beenker tilings

Rows alternate rhombi, squares are free:

Page 9: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 2: Beenker tilings

Rows alternate rhombi, squares are free:

Page 10: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 2: Beenker tilings

Rows alternate rhombi, squares are free:

Page 11: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 3: generalized Penrose tilings

Rows alternate rhombi of a given type, different types freely mix:

Page 12: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 3: generalized Penrose tilings

Rows alternate rhombi of a given type, different types freely mix:

Page 13: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 3: generalized Penrose tilings

Rows alternate rhombi of a given type, different types freely mix:

Page 14: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Some references

L. S. Levitov, Local rules for quasicrystals, Comm. Math.Phys. Volume 119 (1988)

J. E. S. Socolar, Weak matching rules for quasicrystals,Comm. Math. Phys. 129 (1990)

T. Q. T. Le, Local rules for quasiperiodic tilings in Themathematics long range aperiodic order (1995)

Th. F., M. Sablik, Local rules for computable planar tilings,arXiv:1208.2759 (2012)

N. Bedaride, Th. F., When periodicities enforce aperiodicity,arXiv:1309.3686 (2013)

Page 15: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

1 Order

2 Chaos

3 From chaos to order

Page 16: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Melt and random tilings

First quasicrystals: rapid cooling of the melt (quenching).At high T : stabilization by entropy rather than energy.

Definition (Configurational entropy of a tiling T )

S(T ) := log(nb tilings of the same domain as T )/nb tiles in T .

Maximal entropy tilings? Typical properties? Random sampling?

Page 17: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Melt and random tilings

First quasicrystals: rapid cooling of the melt (quenching).At high T : stabilization by entropy rather than energy.

Definition (Configurational entropy of a tiling T )

S(T ) := log(nb tilings of the same domain as T )/nb tiles in T .

Maximal entropy tilings? Typical properties? Random sampling?

Page 18: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 1: Dimer tilings

Maximal entropy tilings are planar. There are efficiently sampled.

Page 19: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 1: Dimer tilings

Maximal entropy tilings are planar. There are efficiently sampled.

Page 20: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 1: Dimer tilings

Maximal entropy tilings are planar. There are efficiently sampled.

Page 21: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 2: Beenker tilings

Maximal entropy tilings? Typical properties? Random sampling?

Page 22: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 2: Beenker tilings

Maximal entropy tilings? Typical properties? Random sampling?

Page 23: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 3: generalized Penrose tilings

Maximal entropy tilings? Typical properties? Random sampling?

Page 24: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 3: generalized Penrose tilings

Maximal entropy tilings? Typical properties? Random sampling?

Page 25: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Some references

N. Destainville, R. Mosseri, F. Bailly, Configurational entropyof co-dimension one tilings and directed membranes, J. Stat.Phys. 87 (1997)

H. Cohn, M. Larsen, J. Propp, The Shape of a typical boxedplane partition, New-York J. Math. 4 (1998)

H. Cohn, R. Kenyon, J. Propp, A variational principle fordomino tilings, J. Amer. Math. Soc. 14 (2001)

M. Widom, N. Destainville, R. Mosseri, F. Bailly, RandomTilings of High Symmetry: II. Boundary Conditions andNumerical Studies, J. Stat. Phys. 120 (2005)

Page 26: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

1 Order

2 Chaos

3 From chaos to order

Page 27: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Cooling and stochastic flips

Recent quasicrystals: slow cooling of the melt (versus quenching).Energy minimization gradually overcomes entropy maximization.Diffusion mechanism which makes the cooling correct the defects?

Definition

Flip on a vertex x : half-turn a hexagon of three rhombi sharing x .

Diffusion: flips on random vertices with probability exp(−∆E/T ).

This is the Metropolis-Hastings algorithm for the Gibbs distribution

P(tiling) =1

Z (T )exp

(−E (tiling)

T

).

Chaos for high T , order for low T , but what about convergence?

Page 28: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Cooling and stochastic flips

Recent quasicrystals: slow cooling of the melt (versus quenching).Energy minimization gradually overcomes entropy maximization.Diffusion mechanism which makes the cooling correct the defects?

Definition

Flip on a vertex x : half-turn a hexagon of three rhombi sharing x .

Diffusion: flips on random vertices with probability exp(−∆E/T ).

This is the Metropolis-Hastings algorithm for the Gibbs distribution

P(tiling) =1

Z (T )exp

(−E (tiling)

T

).

Chaos for high T , order for low T , but what about convergence?

Page 29: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Cooling and stochastic flips

Recent quasicrystals: slow cooling of the melt (versus quenching).Energy minimization gradually overcomes entropy maximization.Diffusion mechanism which makes the cooling correct the defects?

Definition

Flip on a vertex x : half-turn a hexagon of three rhombi sharing x .

Diffusion: flips on random vertices with probability exp(−∆E/T ).

This is the Metropolis-Hastings algorithm for the Gibbs distribution

P(tiling) =1

Z (T )exp

(−E (tiling)

T

).

Chaos for high T , order for low T , but what about convergence?

Page 30: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 1: Dimer tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, O(n2.5) at T = 0.

Page 31: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 1: Dimer tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 32: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 1: Dimer tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 33: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 1: Dimer tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 34: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 1: Dimer tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 35: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 1: Dimer tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 36: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 2: Beenker tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 37: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 2: Beenker tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 38: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 2: Beenker tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 39: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 2: Beenker tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 40: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 2: Beenker tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 41: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 3: generalized Penrose tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 42: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 3: generalized Penrose tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 43: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 3: generalized Penrose tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 44: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 3: generalized Penrose tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 45: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Example 3: generalized Penrose tilings

Ergodic at T > 0, Θ(n2 ln n) mixing at T =∞, Θ(n2) at T = 0.

Page 46: Markov Chains on Tilings: From Chaos to Order

Order Chaos From chaos to order

Some references

N. Destainville, Flip dynamics in octagonal rhombus tiling sets,Phys. Rev. Lett. 88 (2002)

D. B. Wilson, Mixing times of lozenge tiling and card shufflingMarkov chains, Ann. Appl. Probab. 14 (2004)

O. Bodini, Th. F., D. Regnault, Stochastic flips on two-letterwords, proc. of AnAlCo (2010)

Th. F., D. Regnault, Stochastic flips on dimer tilings, Disc.Math. Theor. Comput. Sci. (2010)

P. Caputo, F. Martinelli, F. Toninelli, Mixing times ofmonotone surfaces and SOS interfaces: a mean curvatureapproach, Comm. Math. Phys. 311 (2012)