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Local statistics of the abelian sandpile model David B. Wilson

Local statistics of the abelian sandpile model

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Local statistics of the abelian sandpile model. David B. Wilson. TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A. Key ingredients. Bijection between ASM’s and spanning trees: Dhar Majumdar — Dhar Cori—Le Borgne Bernardi Athreya — Jarai - PowerPoint PPT Presentation

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Page 1: Local statistics of the  abelian sandpile  model

Local statistics ofthe abelian sandpile model

David B. Wilson

Page 2: Local statistics of the  abelian sandpile  model

Key ingredients• Bijection between ASM’s and spanning trees:

DharMajumdar—DharCori—Le BorgneBernardiAthreya—Jarai

• Basic properties of spanning treesPemantleBenjamini—Lyons—Peres—Schramm

• Computation of topologically defined events for spanning treesKenyon—Wilson

Page 3: Local statistics of the  abelian sandpile  model

[sandpile demo]

Page 4: Local statistics of the  abelian sandpile  model
Page 5: Local statistics of the  abelian sandpile  model

Infinite volume limit• Infinite volume limit exists (Athreya—Jarai ’04)• Pr[h=0]= (Majumdar—Dhar ’91)• Other one-site probabilities computed by

Priezzhev (’93)

2=¼2 ¡ 4=¼3

Page 6: Local statistics of the  abelian sandpile  model

Priezzhev (’94)

Page 7: Local statistics of the  abelian sandpile  model

Jeng—Piroux—Ruelle (’06)

Page 8: Local statistics of the  abelian sandpile  model

[burning bijection demo]

Page 9: Local statistics of the  abelian sandpile  model

Underlying graph Uniform spanning tree

Page 10: Local statistics of the  abelian sandpile  model

Uniform spanning tree

Uniform spanning tree on infinite grid

Pemantle: limit of UST on large boxes converges as boxes tend to Z^d

Pemantle: limiting process has one tree if d<=4, infinitely many trees if d>4

Page 11: Local statistics of the  abelian sandpile  model

UST and LERW on Z^2

Benjamini-Lyons-Peres-Schramm:UST on Z^d has one end if d>1,i.e., one path to infinity

Page 12: Local statistics of the  abelian sandpile  model

Local statistics of UST

Local statistics of UST can becomputed via determinantsof transfer impedance matrices (Burton—Pemantle)

Why doesn’t this give localstatistics of sandpiles?

Page 13: Local statistics of the  abelian sandpile  model
Page 14: Local statistics of the  abelian sandpile  model
Page 15: Local statistics of the  abelian sandpile  model
Page 16: Local statistics of the  abelian sandpile  model

Sandpile density and LERW

Conjecture: path to infinity visitsneighbor to rightwith probability 5/16(Levine—Peres, Poghosyan—Priezzhev)

Page 17: Local statistics of the  abelian sandpile  model

Sandpile density and LERW

Theorem: path to infinity visitsneighbor to rightwith probability 5/16(Poghosyan-Priezzhev-Ruelle, Kenyon-W)

JPR integral evaluates to ½(Caracciolo—Sportiello)

Page 18: Local statistics of the  abelian sandpile  model

Kenyon—W

Page 19: Local statistics of the  abelian sandpile  model

Kenyon—W

Page 20: Local statistics of the  abelian sandpile  model

Kenyon—W

Page 21: Local statistics of the  abelian sandpile  model

Kenyon—W

Page 22: Local statistics of the  abelian sandpile  model

Joint distribution of heightsat two neighboring vertices

Page 23: Local statistics of the  abelian sandpile  model

Higher dimensional marginals of sandpile heights

Pr[3,2,1,0 in 4x1 rectangle] =

Page 24: Local statistics of the  abelian sandpile  model

Sandpiles on hexagonal lattice

(One-site probabilities also computed by Ruelle)

Page 25: Local statistics of the  abelian sandpile  model

Sandpiles on triangular lattice

Page 26: Local statistics of the  abelian sandpile  model
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Page 29: Local statistics of the  abelian sandpile  model

4

2

1

3

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4

2

1

3

Page 31: Local statistics of the  abelian sandpile  model

4

21

3

Page 32: Local statistics of the  abelian sandpile  model

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

Groves: graph with marked nodes

Page 33: Local statistics of the  abelian sandpile  model

Uniformly random grove

Page 34: Local statistics of the  abelian sandpile  model

5 4

2

1 3

Goal: compute ratios of partition functions in terms of electrical quantities

Page 35: Local statistics of the  abelian sandpile  model

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

5 4

2

1 3

Arbitrary finite graph with two special nodes

Kirchhoff’s formula for resistance

3 spanning trees

5 2-tree forests with nodes 1 and 2 separated

Page 36: Local statistics of the  abelian sandpile  model

5 4

2

1 3Arbitrary finite graph with two special nodes

(Kirchoff)

3

three

Page 37: Local statistics of the  abelian sandpile  model

Arbitrary finite graph with four special nodes?

5

32

1 4 All pairwise resistances are equal

32

1 4 All pairwise resistances are equal

Need more than boundary measurements (pairwise resistances)Need information about internal structure of graph

Page 38: Local statistics of the  abelian sandpile  model

5 4

2

1 3

Planar graphSpecial vertices called nodes on outer faceNodes numbered in counterclockwise order along outer face

Circular planar graphs

5

32

1 4

circular planar circular planar

3

2

1

4

planar,not circular planar

Page 39: Local statistics of the  abelian sandpile  model
Page 40: Local statistics of the  abelian sandpile  model
Page 41: Local statistics of the  abelian sandpile  model

4

21

3

4

2

1

3 4

21

3