SlideShare a Scribd company logo
Journ´ees Cartes,
Jun. 20, 2013
From planar maps to
spatial topology change in 2d gravity
Timothy Budd
(joint work with J. Ambjørn)
Niels Bohr Institute, Copenhagen.
budd@nbi.dk
http://www.nbi.dk/~budd/
Outline
Introduction to the (generalized) CDT model of 2d gravity
Bijection between labeled quadrangulations and labeled planar maps
Generalized CDT solved in terms of labeled trees
Two-point functions
Bijection between pointed quadrangulations and pointed planar maps
Loop identity of generalized CDT
Causal Dynamical Triangulations (CDT) [Ambjørn, Loll, ’98]
CDT in 2d is a statistical system with partition function
ZCDT =
T
1
CT
gN(T )
ZCDT (g) is a generating function for the number of causal
triangulations T of S2
with N triangles.
Causal Dynamical Triangulations (CDT) [Ambjørn, Loll, ’98]
CDT in 2d is a statistical system with partition function
ZCDT =
T
1
CT
gN(T )
ZCDT (g) is a generating function for the number of causal
triangulations T of S2
with N triangles.
The triangulations have a foliated
structure
t
Causal Dynamical Triangulations (CDT) [Ambjørn, Loll, ’98]
CDT in 2d is a statistical system with partition function
ZCDT =
T
1
CT
gN(T )
ZCDT (g) is a generating function for the number of causal
triangulations T of S2
with N triangles.
The triangulations have a foliated
structure
May as well view them as causal
quadrangulations with a unique
local maximum of the distance
function from the origin.
t
Causal Dynamical Triangulations (CDT) [Ambjørn, Loll, ’98]
CDT in 2d is a statistical system with partition function
ZCDT =
T
1
CT
gN(T )
ZCDT (g) is a generating function for the number of causal
triangulations T of S2
with N triangles.
The triangulations have a foliated
structure
May as well view them as causal
quadrangulations with a unique
local maximum of the distance
function from the origin.
What if we allow more than one
local maximum?
t
Generalized CDT
Allow spatial topology to change in time.
Assign a coupling gs to each baby universe.
Generalized CDT
Allow spatial topology to change in time.
Assign a coupling gs to each baby universe.
The model was solved in the continuum by
gluing together chunks of CDT. [Ambjørn,
Loll, Westra, Zohren ’07]
Generalized CDT
Allow spatial topology to change in time.
Assign a coupling gs to each baby universe.
The model was solved in the continuum by
gluing together chunks of CDT. [Ambjørn,
Loll, Westra, Zohren ’07]
Can we understand the geometry in more
detail by obtaining generalized CDT as a
scaling limit of a discrete model?
Generalized CDT
Allow spatial topology to change in time.
Assign a coupling gs to each baby universe.
The model was solved in the continuum by
gluing together chunks of CDT. [Ambjørn,
Loll, Westra, Zohren ’07]
Can we understand the geometry in more
detail by obtaining generalized CDT as a
scaling limit of a discrete model?
Generalized CDT partition function
Z(g, g) =
Q
1
CQ
gN
gNmax
,
sum over quadrangulations Q with
N faces, a marked origin, and Nmax
local maxima of the distance to the
origin.
Generalized CDT
Allow spatial topology to change in time.
Assign a coupling gs to each baby universe.
The model was solved in the continuum by
gluing together chunks of CDT. [Ambjørn,
Loll, Westra, Zohren ’07]
Can we understand the geometry in more
detail by obtaining generalized CDT as a
scaling limit of a discrete model?
Generalized CDT partition function
Z(g, g) =
Q
1
CQ
gN
gNmax
,
sum over quadrangulations Q with
N faces, a marked origin, and Nmax
local maxima of the distance to the
origin.
−→
N = 2000, g = 0, Nmax = 1
N = 5000, g = 0.00007, Nmax = 12
N = 7000, g = 0.0002, Nmax = 38
N = 7000, g = 0.004, Nmax = 221
N = 4000, g = 0.02, Nmax = 362
N = 2500, g = 1, Nmax = 1216
Causal triangulations and trees
Causal triangulations and trees
Union of all left-most geodesics
running away from the origin.
Causal triangulations and trees
Union of all left-most geodesics
running away from the origin.
Simple enumeration of planar trees:
#
N
= C(N), C(N) =
1
N + 1
2N
N
[Malyshev, Yambartsev, Zamyatin ’01]
[Krikun, Yambartsev ’08]
[Durhuus, Jonsson, Wheater ’09]
Causal triangulations and trees
Union of all left-most geodesics
running away from the origin.
Simple enumeration of planar trees:
#
N
= C(N), C(N) =
1
N + 1
2N
N
[Malyshev, Yambartsev, Zamyatin ’01]
[Krikun, Yambartsev ’08]
[Durhuus, Jonsson, Wheater ’09]
Union of all left-most geodesics
running towards the origin.
Causal triangulations and trees
Union of all left-most geodesics
running away from the origin.
Simple enumeration of planar trees:
#
N
= C(N), C(N) =
1
N + 1
2N
N
[Malyshev, Yambartsev, Zamyatin ’01]
[Krikun, Yambartsev ’08]
[Durhuus, Jonsson, Wheater ’09]
Union of all left-most geodesics
running towards the origin.
Both generalize to generalized CDT
leading to different representations.
Causal triangulations and trees
Causal triangulations and trees
Labeled planar trees: Schaeffer’s bijection.
Causal triangulations and trees
Labeled planar trees: Schaeffer’s bijection.
Unlabeled planar maps (one face per local
maximum).
Labeled quadrangulations
Q(l)
= {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
Labeled quadrangulations
Q(l)
= {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
Labeled quadrangulations
Q(l)
= {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q
rooted on an edge
with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q
rooted on an edge
with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q
rooted on an edge
with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M w
rooted on a corner
ith labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
t t
t +1
t - 1
t t
t +1
t +1
Labeled quadrangulations
Q(l)
= {quadrangulations Q
rooted on an edge
with labels : {v} → Z, s.t. | (v1) − (v2)| = 1}
M(l)
= {planar maps M w
rooted on a corner
ith labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1}
Schaeffer’s rules define a map Ψ : Q(l)
→ M(l)
:
→
Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB]
The map Ψ : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local minima of Q} = #{faces of Ψ(Q)}
#{local maxima of Q} = #{local maxima of Ψ(Q)}
Max label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q) minus 1
Maximal label on Q = maximal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB]
The map Ψ : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local minima of Q} = #{faces of Ψ(Q)}
#{local maxima of Q} = #{local maxima of Ψ(Q)}
Max label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q) minus 1
Maximal label on Q = maximal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB]
The map Ψ : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local minima of Q} = #{faces of Ψ(Q)}
#{local maxima of Q} = #{local maxima of Ψ(Q)}
Max label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q) minus 1
Maximal label on Q = maximal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB]
The map Ψ : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local minima of Q} = #{faces of Ψ(Q)}
#{local maxima of Q} = #{local maxima of Ψ(Q)}
Max label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q) minus 1
Maximal label on Q = maximal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB]
The map Ψ : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local minima of Q} = #{faces of Ψ(Q)}
#{local maxima of Q} = #{local maxima of Ψ(Q)}
Max label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q) minus 1
Maximal label on Q = maximal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB]
The map Ψ : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local minima of Q} = #{faces of Ψ(Q)}
#{local maxima of Q} = #{local maxima of Ψ(Q)}
Max label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q) minus 1
Maximal label on Q = maximal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB]
The map Ψ : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local minima of Q} = #{faces of Ψ(Q)}
#{local maxima of Q} = #{local maxima of Ψ(Q)}
Max label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q) minus 1
Maximal label on Q = maximal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB]
The map Ψ : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local minima of Q} = #{faces of Ψ(Q)}
#{local maxima of Q} = #{local maxima of Ψ(Q)}
Max label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q) minus 1
Maximal label on Q = maximal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB]
The map Ψ : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local minima of Q} = #{faces of Ψ(Q)}
#{local maxima of Q} = #{local maxima of Ψ(Q)}
Max label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q) minus 1
Maximal label on Q = maximal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB]
The map Ψ : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local minima of Q} = #{faces of Ψ(Q)}
#{local maxima of Q} = #{local maxima of Ψ(Q)}
Max label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q) minus 1
Maximal label on Q = maximal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Theorem 1−
The map Ψ− : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local maxima of Q} = #{faces of Ψ(Q)}
#{local minima of Q} = #{local minima of Ψ(Q)}
Min label on root edge of Q = label on root of Ψ(Q)
Maximal label on Q = maximal label on Ψ(Q) plus 1
Minimal label on Q = minimal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98]
Restrict to Q with single local minimum and minimal label 0.
Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98]
Restrict to Q with single local minimum and minimal label 0.
Labeling on Q is a distance to a distinguished vertex.
Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98]
Restrict to Q with single local minimum and minimal label 0.
Labeling on Q is a distance to a distinguished vertex.
Bijection between rooted pointed quadrangulations and rooted
labeled trees with minimal label 1.
Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98]
Restrict to Q with single local minimum and minimal label 0.
Labeling on Q is a distance to a distinguished vertex.
Bijection between rooted pointed quadrangulations and rooted
labeled trees with minimal label 1.
Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98]
Restrict to Q with single local minimum and minimal label 0.
Labeling on Q is a distance to a distinguished vertex.
Bijection between rooted pointed quadrangulations and rooted
labeled trees with minimal label 1.
Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98]
Restrict to Q with single local minimum and minimal label 0.
Labeling on Q is a distance to a distinguished vertex.
Bijection between rooted pointed quadrangulations and rooted
labeled trees with minimal label 1.
Assigning couplings to local maxima
Assign coupling g to the local maxima of the
distance function.
Assigning couplings to local maxima
Assign coupling g to the local maxima of the
distance function.
In terms of labeled trees:
5 4
44
4
4 4
5
3
3
5
5
Assigning couplings to local maxima
Assign coupling g to the local maxima of the
distance function.
In terms of labeled trees:
5 4
44
4
4 4
5
3
3
5
5
Assigning couplings to local maxima
Assign coupling g to the local maxima of the
distance function.
In terms of labeled trees:
5 4
4
5
5
5
Assigning couplings to local maxima
Assign coupling g to the local maxima of the
distance function.
In terms of labeled trees:
0
0
0
0
0
Assigning couplings to local maxima
Assign coupling g to the local maxima of the
distance function.
In terms of labeled trees:
0
0
0
0
0
Generating function z0(g, g) for number of rooted labeled trees with
N edges and Nmax local maxima.
Similarly z1(g, g) but local maximum at the root not counted.
Assigning couplings to local maxima
Assign coupling g to the local maxima of the
distance function.
In terms of labeled trees:
0
0
0
0
0
Generating function z0(g, g) for number of rooted labeled trees with
N edges and Nmax local maxima.
Similarly z1(g, g) but local maximum at the root not counted.
Satisfy recursion relations:
z1 =
∞
k=0
(z1 + z0 + z0)
k
gk
= (1 − gz1 − 2gz0)
−1
z0 =
∞
k=0
(z1 + z0 + z0)
k
gk
+ (g − 1)
∞
k=0
(z1 + z0)
k
gk
= z1 + (g − 1) (1 − gz1 − gz0)
−1
z1 = (1 − gz1 − 2gz0)
−1
z0 = z1 + (g − 1) (1 − gz1 − gz0)
−1
Combine into one equation for z1(g, g):
3g2
z4
1 − 4gz3
1 + (1 + 2g(1 − 2g))z2
1 − 1 = 0
z1 = (1 − gz1 − 2gz0)
−1
z0 = z1 + (g − 1) (1 − gz1 − gz0)
−1
Combine into one equation for z1(g, g):
3g2
z4
1 − 4gz3
1 + (1 + 2g(1 − 2g))z2
1 − 1 = 0
Phase diagram for weighted labeled trees (constant g):
g = 0g = 1
z1 = (1 − gz1 − 2gz0)
−1
z0 = z1 + (g − 1) (1 − gz1 − gz0)
−1
Combine into one equation for z1(g, g):
3g2
z4
1 − 4gz3
1 + (1 + 2g(1 − 2g))z2
1 − 1 = 0
Phase diagram for weighted labeled trees (constant g):
g = 0g = 1
z1 = (1 − gz1 − 2gz0)
−1
z0 = z1 + (g − 1) (1 − gz1 − gz0)
−1
Combine into one equation for z1(g, g):
3g2
z4
1 − 4gz3
1 + (1 + 2g(1 − 2g))z2
1 − 1 = 0
Phase diagram for weighted labeled trees (constant g):
g = 0g = 1
The number of local maxima Nmax (g) scales with N at the critical
point,
Nmax (g) N
N
= 2
g
2
2/3
+ O(g),
Nmax (g = 1) N
N
= 1/2
The number of local maxima Nmax (g) scales with N at the critical
point,
Nmax (g) N
N
= 2
g
2
2/3
+ O(g),
Nmax (g = 1) N
N
= 1/2
Therefore, to obtain a finite continuum density of critical points one
should scale g ∝ N−3/2
, i.e. g = gs
3
as observed in [ALWZ ’07].
The number of local maxima Nmax (g) scales with N at the critical
point,
Nmax (g) N
N
= 2
g
2
2/3
+ O(g),
Nmax (g = 1) N
N
= 1/2
Therefore, to obtain a finite continuum density of critical points one
should scale g ∝ N−3/2
, i.e. g = gs
3
as observed in [ALWZ ’07].
This is the only scaling leading to a continuum limit qualitatively
different from DT and CDT.
The number of local maxima Nmax (g) scales with N at the critical
point,
Nmax (g) N
N
= 2
g
2
2/3
+ O(g),
Nmax (g = 1) N
N
= 1/2
Therefore, to obtain a finite continuum density of critical points one
should scale g ∝ N−3/2
, i.e. g = gs
3
as observed in [ALWZ ’07].
This is the only scaling leading to a continuum limit qualitatively
different from DT and CDT.
Continuum limit g = gc (g)(1 − Λ 2
),
z1 = z1,c (1 − Z1 ), g = gs
3
:
Z3
1 − Λ + 3
gs
2
2/3
Z1 − gs = 0
The number of local maxima Nmax (g) scales with N at the critical
point,
Nmax (g) N
N
= 2
g
2
2/3
+ O(g),
Nmax (g = 1) N
N
= 1/2
Therefore, to obtain a finite continuum density of critical points one
should scale g ∝ N−3/2
, i.e. g = gs
3
as observed in [ALWZ ’07].
This is the only scaling leading to a continuum limit qualitatively
different from DT and CDT.
Continuum limit g = gc (g)(1 − Λ 2
),
z1 = z1,c (1 − Z1 ), g = gs
3
:
Z3
1 − Λ + 3
gs
2
2/3
Z1 − gs = 0
Can compute:
Two-point functions
Continuum amplitude for surfaces with
root at distance T from origin.
Two-point functions
Continuum amplitude for surfaces with
root at distance T from origin.
Rooted pointed quadrangulations with
distance t between origin and furthest
end-point of the root edge...
Two-point functions
Continuum amplitude for surfaces with
root at distance T from origin.
Rooted pointed quadrangulations with
distance t between origin and furthest
end-point of the root edge...
...are counted by z0(t) − z0(t − 1),
with z0(t) the gen. fun. for rooted
labeled trees with positive labels and
label t on root.
Two-point functions
Continuum amplitude for surfaces with
root at distance T from origin.
Rooted pointed quadrangulations with
distance t between origin and furthest
end-point of the root edge...
...are counted by z0(t) − z0(t − 1),
with z0(t) the gen. fun. for rooted
labeled trees with positive labels and
label t on root.
Idem for z1(t), but local max at root
not weighted by g. They satisfy
z1(t) =
1
1 − gz1(t − 1) − gz0(t) − gz0(t + 1)
z0(t) = z1(t) +
g − 1
1 − gz1(t − 1) − gz0(t)
z1(0) = 0 z0(∞) = z0
Solution is (using methods of [Bouttier, Di Francesco, Guitter, ’03]):
z1(t) = z1
1 − σt
1 − σt+1
1 − (1 − β)σ − βσt+3
1 − (1 − β)σ − βσt+2
,
z0(t) = z0
1 − σt
1 − (1 − β)σ − βσt+1
(1 − (1 − β)σ)2
− β2
σt+3
1 − (1 − β)σ − βσt+2
,
with β = β(g, g) and σ = σ(g, g) fixed by
g(1 + σ)(1 + βσ)z1 − σ(1 − 2g z0) = 0,
(1 − β)σ − g(1 + σ)z1 + g(1 − σ + 2βσ)z0 = 0.
Solution is (using methods of [Bouttier, Di Francesco, Guitter, ’03]):
z1(t) = z1
1 − σt
1 − σt+1
1 − (1 − β)σ − βσt+3
1 − (1 − β)σ − βσt+2
,
z0(t) = z0
1 − σt
1 − (1 − β)σ − βσt+1
(1 − (1 − β)σ)2
− β2
σt+3
1 − (1 − β)σ − βσt+2
,
with β = β(g, g) and σ = σ(g, g) fixed by
g(1 + σ)(1 + βσ)z1 − σ(1 − 2g z0) = 0,
(1 − β)σ − g(1 + σ)z1 + g(1 − σ + 2βσ)z0 = 0.
Continuum limit, g = gs
3
, g = gc (1 − Λ 2
), t = T/ , gives
∼
dZ0(T)
dT
= Σ3 gs
α
Σ sinh ΣT + α cosh ΣT
Σ cosh ΣT + α sinh ΣT
3
Solution is (using methods of [Bouttier, Di Francesco, Guitter, ’03]):
z1(t) = z1
1 − σt
1 − σt+1
1 − (1 − β)σ − βσt+3
1 − (1 − β)σ − βσt+2
,
z0(t) = z0
1 − σt
1 − (1 − β)σ − βσt+1
(1 − (1 − β)σ)2
− β2
σt+3
1 − (1 − β)σ − βσt+2
,
with β = β(g, g) and σ = σ(g, g) fixed by
g(1 + σ)(1 + βσ)z1 − σ(1 − 2g z0) = 0,
(1 − β)σ − g(1 + σ)z1 + g(1 − σ + 2βσ)z0 = 0.
Continuum limit, g = gs
3
, g = gc (1 − Λ 2
), t = T/ , gives
∼
dZ0(T)
dT
= Σ3 gs
α
Σ sinh ΣT + α cosh ΣT
Σ cosh ΣT + α sinh ΣT
3
gs →∞
−→ Λ3/4 cosh(Λ1/4
T )
sinh3
(Λ1/4T )
T = g1/6
s T
DT two-point function appears as gs → ∞! [Ambjørn, Watabiki, ’95]
Theorem 1−
The map Ψ− : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local maxima of Q} = #{faces of Ψ(Q)}
#{local minima of Q} = #{local minima of Ψ(Q)}
Min label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Theorem 1−
The map Ψ− : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local maxima of Q} = #{faces of Ψ(Q)}
#{local minima of Q} = #{local minima of Ψ(Q)}
Min label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Restricting Ψ−
to Q with single minimum labeled 0
Theorem 1−
The map Ψ− : Q(l)
→ M(l)
is a bijection satisfying
#{faces of Q} = #{edges of Ψ(Q)}
#{local maxima of Q} = #{faces of Ψ(Q)}
#{local minima of Q} = #{local minima of Ψ(Q)}
Min label on root edge of Q = label on root of Ψ(Q)
Minimal label on Q = minimal label on Ψ(Q)
t t
t +1
t - 1
t t
t +1
t +1
Restricting Ψ−
to Q with single minimum labeled 0 gives a bijection
between pointed rooted quadrangulations and pointed rooted planar
maps.
Ψ−
(Q) has a face for each local maximum of Q. Within each face
the structure of Q is similar to CDT.
Restricting Ψ−
to Q with single minimum labeled 0 gives a bijection
between pointed rooted quadrangulations and pointed rooted planar
maps.
Two-point function for planar maps
The generating function for Q with max label t on the root edge is
z0(t) − z0(t − 1)
Two-point function for planar maps
The generating function for Q with max label t on the root edge is
z0(t) − z0(t − 1)
Therefore one obtains an explicit generating function
z0(t + 1) − z0(t) =
∞
N=0
∞
n=0
Nt(N, n)gN
gn
for the number Nt(N, n) of planar maps with N edges, n faces, and
a marked point at distance t from the root.
Two loop identity in generalized CDT
Consider surfaces with two boundaries separated
by a geodesic distance D.
Two loop identity in generalized CDT
Consider surfaces with two boundaries separated
by a geodesic distance D.
One can assign time T1, T2 to the boundaries
(|T1 − T2| ≤ D) and study a “merging” process.
Two loop identity in generalized CDT
Consider surfaces with two boundaries separated
by a geodesic distance D.
One can assign time T1, T2 to the boundaries
(|T1 − T2| ≤ D) and study a “merging” process.
For a given surface the foliation depends on
T1 − T2, hence also Nmax and its weight.
Two loop identity in generalized CDT
Consider surfaces with two boundaries separated
by a geodesic distance D.
One can assign time T1, T2 to the boundaries
(|T1 − T2| ≤ D) and study a “merging” process.
For a given surface the foliation depends on
T1 − T2, hence also Nmax and its weight.
However, in [ALWZ ’07] it was shown that the
amplitude is independent of T1 − T2.
Two loop identity in generalized CDT
Consider surfaces with two boundaries separated
by a geodesic distance D.
One can assign time T1, T2 to the boundaries
(|T1 − T2| ≤ D) and study a “merging” process.
For a given surface the foliation depends on
T1 − T2, hence also Nmax and its weight.
However, in [ALWZ ’07] it was shown that the
amplitude is independent of T1 − T2.
Refoliation symmetry at the quantum level in the
presence of topology change!
Two loop identity in generalized CDT
Consider surfaces with two boundaries separated
by a geodesic distance D.
One can assign time T1, T2 to the boundaries
(|T1 − T2| ≤ D) and study a “merging” process.
For a given surface the foliation depends on
T1 − T2, hence also Nmax and its weight.
However, in [ALWZ ’07] it was shown that the
amplitude is independent of T1 − T2.
Refoliation symmetry at the quantum level in the
presence of topology change!
Can we better understand this symmetry at the
discrete level?
Two loop identity in generalized CDT
Consider surfaces with two boundaries separated
by a geodesic distance D.
One can assign time T1, T2 to the boundaries
(|T1 − T2| ≤ D) and study a “merging” process.
For a given surface the foliation depends on
T1 − T2, hence also Nmax and its weight.
However, in [ALWZ ’07] it was shown that the
amplitude is independent of T1 − T2.
Refoliation symmetry at the quantum level in the
presence of topology change!
Can we better understand this symmetry at the
discrete level?
For simplicity set the boundary lengths to zero.
Straightforward generalization to finite boundaries.
Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d}
Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d}
Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d}
Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d}
Let Ld
t1,t2
: Qd → Q(l)
with |t1 − t2| − d = 2, 4, . . . be the labeled
quad. with local minima ti on vi .
Qd
Q(l)
Ld
t1,t2
Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d}
Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d}
Let Ld
t1,t2
: Qd → Q(l)
with |t1 − t2| − d = 2, 4, . . . be the labeled
quad. with local minima ti on vi .
Qd
Q(l)
M(l)
Ld
t1,t2
Ψ−
Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d}
Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d}
Let Ld
t1,t2
: Qd → Q(l)
with |t1 − t2| − d = 2, 4, . . . be the labeled
quad. with local minima ti on vi .
Qd
Q(l)
M(l)
Md ∪ Md−1
Ld
t1,t2
Ψ−
Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d}
Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d}
Let Ld
t1,t2
: Qd → Q(l)
with |t1 − t2| − d = 2, 4, . . . be the labeled
quad. with local minima ti on vi .
Qd Md ∪ Md−1
Ψd
t1,t2
Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d}
Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d}
Let Ld
t1,t2
: Qd → Q(l)
with |t1 − t2| − d = 2, 4, . . . be the labeled
quad. with local minima ti on vi .
Qd
Q(l)
M(l)
Md ∪ Md−1
Ld
t1,t2
Ψ−
Ψd
t1,t2
Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d}
Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d}
Let Ld
t1,t2
: Qd → Q(l)
with |t1 − t2| − d = 2, 4, . . . be the labeled
quad. with local minima ti on vi .
Qd Md ∪ Md−1
Ψd
t1,t2
Ψd
t1,t2
Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d}
Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d}
Let Ld
t1,t2
: Qd → Q(l)
with |t1 − t2| − d = 2, 4, . . . be the labeled
quad. with local minima ti on vi .
Qd Md ∪ Md−1
Ψd
t1,t2
(Ψd
t1,t2
)−1
Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d}
Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d}
Let Ld
t1,t2
: Qd → Q(l)
with |t1 − t2| − d = 2, 4, . . . be the labeled
quad. with local minima ti on vi .
Qd Md ∪ Md−1
Ψd
t1,t2
(Ψd
t1,t2
)−1
Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d}
Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d}
Let Ld
t1,t2
: Qd → Q(l)
with |t1 − t2| − d = 2, 4, . . . be the labeled
quad. with local minima ti on vi .
We have found a bijection (Ψd
t1,t2
)−1
◦ Ψd
t1,t2
: Qd → Qd preserving
the distance between v1 and v2, mapping Nmax maxima w.r.t.
(t1, t2) to Nmax maxima w.r.t. (t1, t2).
Proof of Ψd
t1,t2
(Qd) ⊂ Md ∪ Md−1
For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on
v is min{d(v, v1), d(v, v2)}.
Proof of Ψd
t1,t2
(Qd) ⊂ Md ∪ Md−1
For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on
v is min{d(v, v1), d(v, v2)}.
The same holds in the planar map.
Proof of Ψd
t1,t2
(Qd) ⊂ Md ∪ Md−1
For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on
v is min{d(v, v1), d(v, v2)}.
The same holds in the planar map.
Proof of Ψd
t1,t2
(Qd) ⊂ Md ∪ Md−1
For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on
v is min{d(v, v1), d(v, v2)}.
The same holds in the planar map.
For each path of length d in Q there is a path of length d − 1 or d
in M.
Proof of Ψd
t1,t2
(Qd) ⊂ Md ∪ Md−1
For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on
v is min{d(v, v1), d(v, v2)}.
The same holds in the planar map.
For each path of length d in Q there is a path of length d − 1 or d
in M.
Proof of Ψd
t1,t2
(Qd) ⊂ Md ∪ Md−1
For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on
v is min{d(v, v1), d(v, v2)}.
The same holds in the planar map.
For each path of length d in Q there is a path of length d − 1 or d
in M.
Proof of Ψd
t1,t2
(Qd) ⊂ Md ∪ Md−1
For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on
v is min{d(v, v1), d(v, v2)}.
The same holds in the planar map.
For each path of length d in Q there is a path of length d − 1 or d
in M.
Conclusions & Outlook
Conclusions
The Cori–Vauquelin–Schaeffer bijection and its generalizations are
ideal for studying “proper-time foliations” of random surfaces.
Generalized CDT appears naturally as the scaling limit of random
planar maps with a fixed finite number of faces.
Continuum DT (Brownian map?) seems to be recovered by taking
gs → ∞.
The relation to planar maps explains the mysterious loop-loop
identity in the continuum.
Conclusions & Outlook
Conclusions
The Cori–Vauquelin–Schaeffer bijection and its generalizations are
ideal for studying “proper-time foliations” of random surfaces.
Generalized CDT appears naturally as the scaling limit of random
planar maps with a fixed finite number of faces.
Continuum DT (Brownian map?) seems to be recovered by taking
gs → ∞.
The relation to planar maps explains the mysterious loop-loop
identity in the continuum.
Outlook
Is there a convergence towards a random measure on metric spaces,
i.e. analogue of the Brownian map? Should first try to understand
2d geometry of random causal triangulations.
Does the loop-loop identity generalize? Is there some structure to
the associated symmetries?
Various stochastic processes involved in generalized CDT. How are
they related?
Conclusions & Outlook
Conclusions
The Cori–Vauquelin–Schaeffer bijection and its generalizations are
ideal for studying “proper-time foliations” of random surfaces.
Generalized CDT appears naturally as the scaling limit of random
planar maps with a fixed finite number of faces.
Continuum DT (Brownian map?) seems to be recovered by taking
gs → ∞.
The relation to planar maps explains the mysterious loop-loop
identity in the continuum.
Outlook
Is there a convergence towards a random measure on metric spaces,
i.e. analogue of the Brownian map? Should first try to understand
2d geometry of random causal triangulations.
Does the loop-loop identity generalize? Is there some structure to
the associated symmetries?
Various stochastic processes involved in generalized CDT. How are
they related?
Further reading: arXiv:1302.1763
These slides and more: http://www.nbi.dk/~budd/
Thanks for your attention!
Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12]
A quadrangulations with
boundary length 2l
Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12]
A quadrangulations with
boundary length 2l and an
origin.
Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12]
A quadrangulations with
boundary length 2l and an
origin.
Applying the same prescription
we obtain a forest rooted at the
boundary.
5
6
7
6
5
6
5 4
3
4
5
4
3
2
3
4
3
4
5
6
7
8
9
89
8
7
6
Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12]
A quadrangulations with
boundary length 2l and an
origin.
Applying the same prescription
we obtain a forest rooted at the
boundary.
The labels on the boundary
arise from a (closed) random
walk.
5
6
7
6
5
6
5 4
3
4
5
4
3
2
3
4
3
4
5
6
7
8
9
89
8
7
6
5
6
7
6
5
6
5
4
3
4
5
4
3
2
3
4
3
4
5
6
7
8
9
8
9
8
7
6
Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12]
A quadrangulations with
boundary length 2l and an
origin.
Applying the same prescription
we obtain a forest rooted at the
boundary.
The labels on the boundary
arise from a (closed) random
walk.
A (possibly empty) tree grows
at the end of every +-edge.
5
6
7
6
5
6
5 4
3
4
5
4
3
2
3
4
3
4
5
6
7
8
9
89
8
7
6
Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12]
A quadrangulations with
boundary length 2l and an
origin.
Applying the same prescription
we obtain a forest rooted at the
boundary.
The labels on the boundary
arise from a (closed) random
walk.
A (possibly empty) tree grows
at the end of every +-edge.
There is a bijection
5
6
7
6
5
6
5 4
3
4
5
4
3
2
3
4
3
4
5
6
7
8
9
89
8
7
6
Quadrangulations with origin
and boundary length 2l
↔ {(+, −)-sequences} × {tree}
l
Disk amplitudes
Disk amplitudes
Disk amplitudes
w(g, l) = z(g)l
w(g, x) =
∞
l=0
w(g, l)xl
=
1
1 − z(g)x
w(g, l) =
2l
l
z(g)l
w(g, x) =
1
1 − 4z(g)x
Disk amplitudes
w(g, l) = z(g)l
w(g, x) =
∞
l=0
w(g, l)xl
=
1
1 − z(g)x
w(g, l) =
2l
l
z(g)l
w(g, x) =
1
1 − 4z(g)x
Generating function
for unlabeled trees:
z(g) =
1 −
√
1 − 4g
2g
0
000
0
0 0
00
Generating function
for labeled trees:
z(g) =
1 −
√
1 − 12g
6g
Continuum limit
w(g, x) =
1
1 − zx
w(g, x) =
1
√
1 − 4zx
z(g) = 1−
√
1−4g
2g
0
000
0
0 0
00
z(g) = 1−
√
1−12g
6g
Continuum limit
w(g, x) =
1
1 − zx
w(g, x) =
1
√
1 − 4zx
z(g) = 1−
√
1−4g
2g
0
000
0
0 0
00
z(g) = 1−
√
1−12g
6g
Expanding around critical point in terms of “lattice spacing” :
g = gc (1 − Λ 2
), z(g) = zc (1 − Z ), x = xc (1 − X )
Continuum limit
w(g, x) =
1
1 − zx
WΛ(X) =
1
X + Z
w(g, x) =
1
√
1 − 4zx
WΛ(X) =
1
√
X + Z
z(g) = 1−
√
1−4g
2g
Z =
√
Λ
0
000
0
0 0
00
z(g) = 1−
√
1−12g
6g
Z =
√
Λ
Expanding around critical point in terms of “lattice spacing” :
g = gc (1 − Λ 2
), z(g) = zc (1 − Z ), x = xc (1 − X )
Continuum limit
w(g, x) =
1
1 − zx
WΛ(X) =
1
X + Z
w(g, x) =
1
√
1 − 4zx
WΛ(X) =
1
√
X + Z
z(g) = 1−
√
1−4g
2g
Z =
√
Λ
0
000
0
0 0
00
z(g) = 1−
√
1−12g
6g
Z =
√
Λ
Expanding around critical point in terms of “lattice spacing” :
g = gc (1 − Λ 2
), z(g) = zc (1 − Z ), x = xc (1 − X )
CDT disk amplitude: WΛ(X) = 1
X+
√
Λ
Continuum limit
w(g, x) =
1
1 − zx
WΛ(X) =
1
X + Z
w(g, x) =
1
√
1 − 4zx
WΛ(X) =
1
√
X + Z
z(g) = 1−
√
1−4g
2g
Z =
√
Λ
0
000
0
0 0
00
z(g) = 1−
√
1−12g
6g
Z =
√
Λ
Expanding around critical point in terms of “lattice spacing” :
g = gc (1 − Λ 2
), z(g) = zc (1 − Z ), x = xc (1 − X )
CDT disk amplitude: WΛ(X) = 1
X+
√
Λ
DT disk amplitude with marked point: WΛ(X) = 1√
X+
√
Λ
. Integrate
w.r.t. Λ to remove mark: WΛ(X) = 2
3 (X − 1
2
√
Λ) X +
√
Λ.

More Related Content

What's hot

A Szemeredi-type theorem for subsets of the unit cube
A Szemeredi-type theorem for subsets of the unit cubeA Szemeredi-type theorem for subsets of the unit cube
A Szemeredi-type theorem for subsets of the unit cube
VjekoslavKovac1
 
On maximal and variational Fourier restriction
On maximal and variational Fourier restrictionOn maximal and variational Fourier restriction
On maximal and variational Fourier restriction
VjekoslavKovac1
 
A sharp nonlinear Hausdorff-Young inequality for small potentials
A sharp nonlinear Hausdorff-Young inequality for small potentialsA sharp nonlinear Hausdorff-Young inequality for small potentials
A sharp nonlinear Hausdorff-Young inequality for small potentials
VjekoslavKovac1
 
Some Examples of Scaling Sets
Some Examples of Scaling SetsSome Examples of Scaling Sets
Some Examples of Scaling Sets
VjekoslavKovac1
 
Internal workshop jub talk jan 2013
Internal workshop jub talk jan 2013Internal workshop jub talk jan 2013
Internal workshop jub talk jan 2013Jurgen Riedel
 
Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applie...
Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applie...Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applie...
Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applie...
The Statistical and Applied Mathematical Sciences Institute
 
Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)
IJERD Editor
 
Divergence center-based clustering and their applications
Divergence center-based clustering and their applicationsDivergence center-based clustering and their applications
Divergence center-based clustering and their applications
Frank Nielsen
 
Patch Matching with Polynomial Exponential Families and Projective Divergences
Patch Matching with Polynomial Exponential Families and Projective DivergencesPatch Matching with Polynomial Exponential Families and Projective Divergences
Patch Matching with Polynomial Exponential Families and Projective Divergences
Frank Nielsen
 
Supersymmetric Q-balls and boson stars in (d + 1) dimensions
Supersymmetric Q-balls and boson stars in (d + 1) dimensionsSupersymmetric Q-balls and boson stars in (d + 1) dimensions
Supersymmetric Q-balls and boson stars in (d + 1) dimensions
Jurgen Riedel
 
On Twisted Paraproducts and some other Multilinear Singular Integrals
On Twisted Paraproducts and some other Multilinear Singular IntegralsOn Twisted Paraproducts and some other Multilinear Singular Integrals
On Twisted Paraproducts and some other Multilinear Singular Integrals
VjekoslavKovac1
 
Multilinear singular integrals with entangled structure
Multilinear singular integrals with entangled structureMultilinear singular integrals with entangled structure
Multilinear singular integrals with entangled structure
VjekoslavKovac1
 
CLIM Fall 2017 Course: Statistics for Climate Research, Statistics of Climate...
CLIM Fall 2017 Course: Statistics for Climate Research, Statistics of Climate...CLIM Fall 2017 Course: Statistics for Climate Research, Statistics of Climate...
CLIM Fall 2017 Course: Statistics for Climate Research, Statistics of Climate...
The Statistical and Applied Mathematical Sciences Institute
 
Computational Information Geometry: A quick review (ICMS)
Computational Information Geometry: A quick review (ICMS)Computational Information Geometry: A quick review (ICMS)
Computational Information Geometry: A quick review (ICMS)
Frank Nielsen
 
Classification with mixtures of curved Mahalanobis metrics
Classification with mixtures of curved Mahalanobis metricsClassification with mixtures of curved Mahalanobis metrics
Classification with mixtures of curved Mahalanobis metrics
Frank Nielsen
 
Scattering theory analogues of several classical estimates in Fourier analysis
Scattering theory analogues of several classical estimates in Fourier analysisScattering theory analogues of several classical estimates in Fourier analysis
Scattering theory analogues of several classical estimates in Fourier analysis
VjekoslavKovac1
 
Bellman functions and Lp estimates for paraproducts
Bellman functions and Lp estimates for paraproductsBellman functions and Lp estimates for paraproducts
Bellman functions and Lp estimates for paraproducts
VjekoslavKovac1
 
Divergence clustering
Divergence clusteringDivergence clustering
Divergence clustering
Frank Nielsen
 
Trilinear embedding for divergence-form operators
Trilinear embedding for divergence-form operatorsTrilinear embedding for divergence-form operators
Trilinear embedding for divergence-form operators
VjekoslavKovac1
 

What's hot (20)

A Szemeredi-type theorem for subsets of the unit cube
A Szemeredi-type theorem for subsets of the unit cubeA Szemeredi-type theorem for subsets of the unit cube
A Szemeredi-type theorem for subsets of the unit cube
 
On maximal and variational Fourier restriction
On maximal and variational Fourier restrictionOn maximal and variational Fourier restriction
On maximal and variational Fourier restriction
 
A sharp nonlinear Hausdorff-Young inequality for small potentials
A sharp nonlinear Hausdorff-Young inequality for small potentialsA sharp nonlinear Hausdorff-Young inequality for small potentials
A sharp nonlinear Hausdorff-Young inequality for small potentials
 
Some Examples of Scaling Sets
Some Examples of Scaling SetsSome Examples of Scaling Sets
Some Examples of Scaling Sets
 
Internal workshop jub talk jan 2013
Internal workshop jub talk jan 2013Internal workshop jub talk jan 2013
Internal workshop jub talk jan 2013
 
Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applie...
Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applie...Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applie...
Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applie...
 
Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)
 
Dsp lecture vol 1 introduction
Dsp lecture vol 1 introductionDsp lecture vol 1 introduction
Dsp lecture vol 1 introduction
 
Divergence center-based clustering and their applications
Divergence center-based clustering and their applicationsDivergence center-based clustering and their applications
Divergence center-based clustering and their applications
 
Patch Matching with Polynomial Exponential Families and Projective Divergences
Patch Matching with Polynomial Exponential Families and Projective DivergencesPatch Matching with Polynomial Exponential Families and Projective Divergences
Patch Matching with Polynomial Exponential Families and Projective Divergences
 
Supersymmetric Q-balls and boson stars in (d + 1) dimensions
Supersymmetric Q-balls and boson stars in (d + 1) dimensionsSupersymmetric Q-balls and boson stars in (d + 1) dimensions
Supersymmetric Q-balls and boson stars in (d + 1) dimensions
 
On Twisted Paraproducts and some other Multilinear Singular Integrals
On Twisted Paraproducts and some other Multilinear Singular IntegralsOn Twisted Paraproducts and some other Multilinear Singular Integrals
On Twisted Paraproducts and some other Multilinear Singular Integrals
 
Multilinear singular integrals with entangled structure
Multilinear singular integrals with entangled structureMultilinear singular integrals with entangled structure
Multilinear singular integrals with entangled structure
 
CLIM Fall 2017 Course: Statistics for Climate Research, Statistics of Climate...
CLIM Fall 2017 Course: Statistics for Climate Research, Statistics of Climate...CLIM Fall 2017 Course: Statistics for Climate Research, Statistics of Climate...
CLIM Fall 2017 Course: Statistics for Climate Research, Statistics of Climate...
 
Computational Information Geometry: A quick review (ICMS)
Computational Information Geometry: A quick review (ICMS)Computational Information Geometry: A quick review (ICMS)
Computational Information Geometry: A quick review (ICMS)
 
Classification with mixtures of curved Mahalanobis metrics
Classification with mixtures of curved Mahalanobis metricsClassification with mixtures of curved Mahalanobis metrics
Classification with mixtures of curved Mahalanobis metrics
 
Scattering theory analogues of several classical estimates in Fourier analysis
Scattering theory analogues of several classical estimates in Fourier analysisScattering theory analogues of several classical estimates in Fourier analysis
Scattering theory analogues of several classical estimates in Fourier analysis
 
Bellman functions and Lp estimates for paraproducts
Bellman functions and Lp estimates for paraproductsBellman functions and Lp estimates for paraproducts
Bellman functions and Lp estimates for paraproducts
 
Divergence clustering
Divergence clusteringDivergence clustering
Divergence clustering
 
Trilinear embedding for divergence-form operators
Trilinear embedding for divergence-form operatorsTrilinear embedding for divergence-form operators
Trilinear embedding for divergence-form operators
 

Similar to From planar maps to spatial topology change in 2d gravity

Generalized CDT as a scaling limit of planar maps
Generalized CDT as a scaling limit of planar mapsGeneralized CDT as a scaling limit of planar maps
Generalized CDT as a scaling limit of planar maps
Timothy Budd
 
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
The Statistical and Applied Mathematical Sciences Institute
 
Fractal dimensions of 2d quantum gravity
Fractal dimensions of 2d quantum gravityFractal dimensions of 2d quantum gravity
Fractal dimensions of 2d quantum gravity
Timothy Budd
 
SMB_2012_HR_VAN_ST-last version
SMB_2012_HR_VAN_ST-last versionSMB_2012_HR_VAN_ST-last version
SMB_2012_HR_VAN_ST-last versionLilyana Vankova
 
2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...
2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...
2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...
The Statistical and Applied Mathematical Sciences Institute
 
Bayesian inference on mixtures
Bayesian inference on mixturesBayesian inference on mixtures
Bayesian inference on mixtures
Christian Robert
 
parameterized complexity for graph Motif
parameterized complexity for graph Motifparameterized complexity for graph Motif
parameterized complexity for graph Motif
AMR koura
 
On approximating the Riemannian 1-center
On approximating the Riemannian 1-centerOn approximating the Riemannian 1-center
On approximating the Riemannian 1-center
Frank Nielsen
 
Convolution linear and circular using z transform day 5
Convolution   linear and circular using z transform day 5Convolution   linear and circular using z transform day 5
Convolution linear and circular using z transform day 5
vijayanand Kandaswamy
 
2018 MUMS Fall Course - Sampling-based techniques for uncertainty propagation...
2018 MUMS Fall Course - Sampling-based techniques for uncertainty propagation...2018 MUMS Fall Course - Sampling-based techniques for uncertainty propagation...
2018 MUMS Fall Course - Sampling-based techniques for uncertainty propagation...
The Statistical and Applied Mathematical Sciences Institute
 
Matrix 2 d
Matrix 2 dMatrix 2 d
Matrix 2 dxyz120
 
Zeros of orthogonal polynomials generated by a Geronimus perturbation of meas...
Zeros of orthogonal polynomials generated by a Geronimus perturbation of meas...Zeros of orthogonal polynomials generated by a Geronimus perturbation of meas...
Zeros of orthogonal polynomials generated by a Geronimus perturbation of meas...
Edmundo José Huertas Cejudo
 
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...
Leo Asselborn
 
f00a5f08-14cf-4f73-a749-f8e30a016fa4.pdf
f00a5f08-14cf-4f73-a749-f8e30a016fa4.pdff00a5f08-14cf-4f73-a749-f8e30a016fa4.pdf
f00a5f08-14cf-4f73-a749-f8e30a016fa4.pdf
SRSstatusking
 
Tucker tensor analysis of Matern functions in spatial statistics
Tucker tensor analysis of Matern functions in spatial statistics Tucker tensor analysis of Matern functions in spatial statistics
Tucker tensor analysis of Matern functions in spatial statistics
Alexander Litvinenko
 
Trigonometry
TrigonometryTrigonometry
Trigonometry
Murali BL
 
Trigonometry and its basic rules and regulation
Trigonometry and its basic rules and regulationTrigonometry and its basic rules and regulation
Trigonometry and its basic rules and regulation
Kartikey Rohila
 
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
The Statistical and Applied Mathematical Sciences Institute
 
QMC: Transition Workshop - Applying Quasi-Monte Carlo Methods to a Stochastic...
QMC: Transition Workshop - Applying Quasi-Monte Carlo Methods to a Stochastic...QMC: Transition Workshop - Applying Quasi-Monte Carlo Methods to a Stochastic...
QMC: Transition Workshop - Applying Quasi-Monte Carlo Methods to a Stochastic...
The Statistical and Applied Mathematical Sciences Institute
 
Litvinenko low-rank kriging +FFT poster
Litvinenko low-rank kriging +FFT  posterLitvinenko low-rank kriging +FFT  poster
Litvinenko low-rank kriging +FFT poster
Alexander Litvinenko
 

Similar to From planar maps to spatial topology change in 2d gravity (20)

Generalized CDT as a scaling limit of planar maps
Generalized CDT as a scaling limit of planar mapsGeneralized CDT as a scaling limit of planar maps
Generalized CDT as a scaling limit of planar maps
 
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
 
Fractal dimensions of 2d quantum gravity
Fractal dimensions of 2d quantum gravityFractal dimensions of 2d quantum gravity
Fractal dimensions of 2d quantum gravity
 
SMB_2012_HR_VAN_ST-last version
SMB_2012_HR_VAN_ST-last versionSMB_2012_HR_VAN_ST-last version
SMB_2012_HR_VAN_ST-last version
 
2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...
2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...
2018 MUMS Fall Course - Statistical Representation of Model Input (EDITED) - ...
 
Bayesian inference on mixtures
Bayesian inference on mixturesBayesian inference on mixtures
Bayesian inference on mixtures
 
parameterized complexity for graph Motif
parameterized complexity for graph Motifparameterized complexity for graph Motif
parameterized complexity for graph Motif
 
On approximating the Riemannian 1-center
On approximating the Riemannian 1-centerOn approximating the Riemannian 1-center
On approximating the Riemannian 1-center
 
Convolution linear and circular using z transform day 5
Convolution   linear and circular using z transform day 5Convolution   linear and circular using z transform day 5
Convolution linear and circular using z transform day 5
 
2018 MUMS Fall Course - Sampling-based techniques for uncertainty propagation...
2018 MUMS Fall Course - Sampling-based techniques for uncertainty propagation...2018 MUMS Fall Course - Sampling-based techniques for uncertainty propagation...
2018 MUMS Fall Course - Sampling-based techniques for uncertainty propagation...
 
Matrix 2 d
Matrix 2 dMatrix 2 d
Matrix 2 d
 
Zeros of orthogonal polynomials generated by a Geronimus perturbation of meas...
Zeros of orthogonal polynomials generated by a Geronimus perturbation of meas...Zeros of orthogonal polynomials generated by a Geronimus perturbation of meas...
Zeros of orthogonal polynomials generated by a Geronimus perturbation of meas...
 
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...
Robust Control of Uncertain Switched Linear Systems based on Stochastic Reach...
 
f00a5f08-14cf-4f73-a749-f8e30a016fa4.pdf
f00a5f08-14cf-4f73-a749-f8e30a016fa4.pdff00a5f08-14cf-4f73-a749-f8e30a016fa4.pdf
f00a5f08-14cf-4f73-a749-f8e30a016fa4.pdf
 
Tucker tensor analysis of Matern functions in spatial statistics
Tucker tensor analysis of Matern functions in spatial statistics Tucker tensor analysis of Matern functions in spatial statistics
Tucker tensor analysis of Matern functions in spatial statistics
 
Trigonometry
TrigonometryTrigonometry
Trigonometry
 
Trigonometry and its basic rules and regulation
Trigonometry and its basic rules and regulationTrigonometry and its basic rules and regulation
Trigonometry and its basic rules and regulation
 
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
QMC Program: Trends and Advances in Monte Carlo Sampling Algorithms Workshop,...
 
QMC: Transition Workshop - Applying Quasi-Monte Carlo Methods to a Stochastic...
QMC: Transition Workshop - Applying Quasi-Monte Carlo Methods to a Stochastic...QMC: Transition Workshop - Applying Quasi-Monte Carlo Methods to a Stochastic...
QMC: Transition Workshop - Applying Quasi-Monte Carlo Methods to a Stochastic...
 
Litvinenko low-rank kriging +FFT poster
Litvinenko low-rank kriging +FFT  posterLitvinenko low-rank kriging +FFT  poster
Litvinenko low-rank kriging +FFT poster
 

Recently uploaded

EY - Supply Chain Services 2018_template.pptx
EY - Supply Chain Services 2018_template.pptxEY - Supply Chain Services 2018_template.pptx
EY - Supply Chain Services 2018_template.pptx
AlguinaldoKong
 
GBSN - Biochemistry (Unit 5) Chemistry of Lipids
GBSN - Biochemistry (Unit 5) Chemistry of LipidsGBSN - Biochemistry (Unit 5) Chemistry of Lipids
GBSN - Biochemistry (Unit 5) Chemistry of Lipids
Areesha Ahmad
 
ESR_factors_affect-clinic significance-Pathysiology.pptx
ESR_factors_affect-clinic significance-Pathysiology.pptxESR_factors_affect-clinic significance-Pathysiology.pptx
ESR_factors_affect-clinic significance-Pathysiology.pptx
muralinath2
 
filosofia boliviana introducción jsjdjd.pptx
filosofia boliviana introducción jsjdjd.pptxfilosofia boliviana introducción jsjdjd.pptx
filosofia boliviana introducción jsjdjd.pptx
IvanMallco1
 
PRESENTATION ABOUT PRINCIPLE OF COSMATIC EVALUATION
PRESENTATION ABOUT PRINCIPLE OF COSMATIC EVALUATIONPRESENTATION ABOUT PRINCIPLE OF COSMATIC EVALUATION
PRESENTATION ABOUT PRINCIPLE OF COSMATIC EVALUATION
ChetanK57
 
Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...
Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...
Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...
muralinath2
 
general properties of oerganologametal.ppt
general properties of oerganologametal.pptgeneral properties of oerganologametal.ppt
general properties of oerganologametal.ppt
IqrimaNabilatulhusni
 
Comparative structure of adrenal gland in vertebrates
Comparative structure of adrenal gland in vertebratesComparative structure of adrenal gland in vertebrates
Comparative structure of adrenal gland in vertebrates
sachin783648
 
platelets- lifespan -Clot retraction-disorders.pptx
platelets- lifespan -Clot retraction-disorders.pptxplatelets- lifespan -Clot retraction-disorders.pptx
platelets- lifespan -Clot retraction-disorders.pptx
muralinath2
 
Hemoglobin metabolism_pathophysiology.pptx
Hemoglobin metabolism_pathophysiology.pptxHemoglobin metabolism_pathophysiology.pptx
Hemoglobin metabolism_pathophysiology.pptx
muralinath2
 
Richard's aventures in two entangled wonderlands
Richard's aventures in two entangled wonderlandsRichard's aventures in two entangled wonderlands
Richard's aventures in two entangled wonderlands
Richard Gill
 
Lab report on liquid viscosity of glycerin
Lab report on liquid viscosity of glycerinLab report on liquid viscosity of glycerin
Lab report on liquid viscosity of glycerin
ossaicprecious19
 
Citrus Greening Disease and its Management
Citrus Greening Disease and its ManagementCitrus Greening Disease and its Management
Citrus Greening Disease and its Management
subedisuryaofficial
 
4. An Overview of Sugarcane White Leaf Disease in Vietnam.pdf
4. An Overview of Sugarcane White Leaf Disease in Vietnam.pdf4. An Overview of Sugarcane White Leaf Disease in Vietnam.pdf
4. An Overview of Sugarcane White Leaf Disease in Vietnam.pdf
ssuserbfdca9
 
GBSN - Microbiology (Lab 4) Culture Media
GBSN - Microbiology (Lab 4) Culture MediaGBSN - Microbiology (Lab 4) Culture Media
GBSN - Microbiology (Lab 4) Culture Media
Areesha Ahmad
 
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...
Scintica Instrumentation
 
What is greenhouse gasses and how many gasses are there to affect the Earth.
What is greenhouse gasses and how many gasses are there to affect the Earth.What is greenhouse gasses and how many gasses are there to affect the Earth.
What is greenhouse gasses and how many gasses are there to affect the Earth.
moosaasad1975
 
Orion Air Quality Monitoring Systems - CWS
Orion Air Quality Monitoring Systems - CWSOrion Air Quality Monitoring Systems - CWS
Orion Air Quality Monitoring Systems - CWS
Columbia Weather Systems
 
Body fluids_tonicity_dehydration_hypovolemia_hypervolemia.pptx
Body fluids_tonicity_dehydration_hypovolemia_hypervolemia.pptxBody fluids_tonicity_dehydration_hypovolemia_hypervolemia.pptx
Body fluids_tonicity_dehydration_hypovolemia_hypervolemia.pptx
muralinath2
 
Nutraceutical market, scope and growth: Herbal drug technology
Nutraceutical market, scope and growth: Herbal drug technologyNutraceutical market, scope and growth: Herbal drug technology
Nutraceutical market, scope and growth: Herbal drug technology
Lokesh Patil
 

Recently uploaded (20)

EY - Supply Chain Services 2018_template.pptx
EY - Supply Chain Services 2018_template.pptxEY - Supply Chain Services 2018_template.pptx
EY - Supply Chain Services 2018_template.pptx
 
GBSN - Biochemistry (Unit 5) Chemistry of Lipids
GBSN - Biochemistry (Unit 5) Chemistry of LipidsGBSN - Biochemistry (Unit 5) Chemistry of Lipids
GBSN - Biochemistry (Unit 5) Chemistry of Lipids
 
ESR_factors_affect-clinic significance-Pathysiology.pptx
ESR_factors_affect-clinic significance-Pathysiology.pptxESR_factors_affect-clinic significance-Pathysiology.pptx
ESR_factors_affect-clinic significance-Pathysiology.pptx
 
filosofia boliviana introducción jsjdjd.pptx
filosofia boliviana introducción jsjdjd.pptxfilosofia boliviana introducción jsjdjd.pptx
filosofia boliviana introducción jsjdjd.pptx
 
PRESENTATION ABOUT PRINCIPLE OF COSMATIC EVALUATION
PRESENTATION ABOUT PRINCIPLE OF COSMATIC EVALUATIONPRESENTATION ABOUT PRINCIPLE OF COSMATIC EVALUATION
PRESENTATION ABOUT PRINCIPLE OF COSMATIC EVALUATION
 
Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...
Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...
Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...
 
general properties of oerganologametal.ppt
general properties of oerganologametal.pptgeneral properties of oerganologametal.ppt
general properties of oerganologametal.ppt
 
Comparative structure of adrenal gland in vertebrates
Comparative structure of adrenal gland in vertebratesComparative structure of adrenal gland in vertebrates
Comparative structure of adrenal gland in vertebrates
 
platelets- lifespan -Clot retraction-disorders.pptx
platelets- lifespan -Clot retraction-disorders.pptxplatelets- lifespan -Clot retraction-disorders.pptx
platelets- lifespan -Clot retraction-disorders.pptx
 
Hemoglobin metabolism_pathophysiology.pptx
Hemoglobin metabolism_pathophysiology.pptxHemoglobin metabolism_pathophysiology.pptx
Hemoglobin metabolism_pathophysiology.pptx
 
Richard's aventures in two entangled wonderlands
Richard's aventures in two entangled wonderlandsRichard's aventures in two entangled wonderlands
Richard's aventures in two entangled wonderlands
 
Lab report on liquid viscosity of glycerin
Lab report on liquid viscosity of glycerinLab report on liquid viscosity of glycerin
Lab report on liquid viscosity of glycerin
 
Citrus Greening Disease and its Management
Citrus Greening Disease and its ManagementCitrus Greening Disease and its Management
Citrus Greening Disease and its Management
 
4. An Overview of Sugarcane White Leaf Disease in Vietnam.pdf
4. An Overview of Sugarcane White Leaf Disease in Vietnam.pdf4. An Overview of Sugarcane White Leaf Disease in Vietnam.pdf
4. An Overview of Sugarcane White Leaf Disease in Vietnam.pdf
 
GBSN - Microbiology (Lab 4) Culture Media
GBSN - Microbiology (Lab 4) Culture MediaGBSN - Microbiology (Lab 4) Culture Media
GBSN - Microbiology (Lab 4) Culture Media
 
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...
 
What is greenhouse gasses and how many gasses are there to affect the Earth.
What is greenhouse gasses and how many gasses are there to affect the Earth.What is greenhouse gasses and how many gasses are there to affect the Earth.
What is greenhouse gasses and how many gasses are there to affect the Earth.
 
Orion Air Quality Monitoring Systems - CWS
Orion Air Quality Monitoring Systems - CWSOrion Air Quality Monitoring Systems - CWS
Orion Air Quality Monitoring Systems - CWS
 
Body fluids_tonicity_dehydration_hypovolemia_hypervolemia.pptx
Body fluids_tonicity_dehydration_hypovolemia_hypervolemia.pptxBody fluids_tonicity_dehydration_hypovolemia_hypervolemia.pptx
Body fluids_tonicity_dehydration_hypovolemia_hypervolemia.pptx
 
Nutraceutical market, scope and growth: Herbal drug technology
Nutraceutical market, scope and growth: Herbal drug technologyNutraceutical market, scope and growth: Herbal drug technology
Nutraceutical market, scope and growth: Herbal drug technology
 

From planar maps to spatial topology change in 2d gravity

  • 1. Journ´ees Cartes, Jun. 20, 2013 From planar maps to spatial topology change in 2d gravity Timothy Budd (joint work with J. Ambjørn) Niels Bohr Institute, Copenhagen. budd@nbi.dk http://www.nbi.dk/~budd/
  • 2. Outline Introduction to the (generalized) CDT model of 2d gravity Bijection between labeled quadrangulations and labeled planar maps Generalized CDT solved in terms of labeled trees Two-point functions Bijection between pointed quadrangulations and pointed planar maps Loop identity of generalized CDT
  • 3. Causal Dynamical Triangulations (CDT) [Ambjørn, Loll, ’98] CDT in 2d is a statistical system with partition function ZCDT = T 1 CT gN(T ) ZCDT (g) is a generating function for the number of causal triangulations T of S2 with N triangles.
  • 4. Causal Dynamical Triangulations (CDT) [Ambjørn, Loll, ’98] CDT in 2d is a statistical system with partition function ZCDT = T 1 CT gN(T ) ZCDT (g) is a generating function for the number of causal triangulations T of S2 with N triangles. The triangulations have a foliated structure t
  • 5. Causal Dynamical Triangulations (CDT) [Ambjørn, Loll, ’98] CDT in 2d is a statistical system with partition function ZCDT = T 1 CT gN(T ) ZCDT (g) is a generating function for the number of causal triangulations T of S2 with N triangles. The triangulations have a foliated structure May as well view them as causal quadrangulations with a unique local maximum of the distance function from the origin. t
  • 6. Causal Dynamical Triangulations (CDT) [Ambjørn, Loll, ’98] CDT in 2d is a statistical system with partition function ZCDT = T 1 CT gN(T ) ZCDT (g) is a generating function for the number of causal triangulations T of S2 with N triangles. The triangulations have a foliated structure May as well view them as causal quadrangulations with a unique local maximum of the distance function from the origin. What if we allow more than one local maximum? t
  • 7. Generalized CDT Allow spatial topology to change in time. Assign a coupling gs to each baby universe.
  • 8. Generalized CDT Allow spatial topology to change in time. Assign a coupling gs to each baby universe. The model was solved in the continuum by gluing together chunks of CDT. [Ambjørn, Loll, Westra, Zohren ’07]
  • 9. Generalized CDT Allow spatial topology to change in time. Assign a coupling gs to each baby universe. The model was solved in the continuum by gluing together chunks of CDT. [Ambjørn, Loll, Westra, Zohren ’07] Can we understand the geometry in more detail by obtaining generalized CDT as a scaling limit of a discrete model?
  • 10. Generalized CDT Allow spatial topology to change in time. Assign a coupling gs to each baby universe. The model was solved in the continuum by gluing together chunks of CDT. [Ambjørn, Loll, Westra, Zohren ’07] Can we understand the geometry in more detail by obtaining generalized CDT as a scaling limit of a discrete model? Generalized CDT partition function Z(g, g) = Q 1 CQ gN gNmax , sum over quadrangulations Q with N faces, a marked origin, and Nmax local maxima of the distance to the origin.
  • 11. Generalized CDT Allow spatial topology to change in time. Assign a coupling gs to each baby universe. The model was solved in the continuum by gluing together chunks of CDT. [Ambjørn, Loll, Westra, Zohren ’07] Can we understand the geometry in more detail by obtaining generalized CDT as a scaling limit of a discrete model? Generalized CDT partition function Z(g, g) = Q 1 CQ gN gNmax , sum over quadrangulations Q with N faces, a marked origin, and Nmax local maxima of the distance to the origin. −→
  • 12. N = 2000, g = 0, Nmax = 1
  • 13. N = 5000, g = 0.00007, Nmax = 12
  • 14. N = 7000, g = 0.0002, Nmax = 38
  • 15. N = 7000, g = 0.004, Nmax = 221
  • 16. N = 4000, g = 0.02, Nmax = 362
  • 17. N = 2500, g = 1, Nmax = 1216
  • 19. Causal triangulations and trees Union of all left-most geodesics running away from the origin.
  • 20. Causal triangulations and trees Union of all left-most geodesics running away from the origin. Simple enumeration of planar trees: # N = C(N), C(N) = 1 N + 1 2N N [Malyshev, Yambartsev, Zamyatin ’01] [Krikun, Yambartsev ’08] [Durhuus, Jonsson, Wheater ’09]
  • 21. Causal triangulations and trees Union of all left-most geodesics running away from the origin. Simple enumeration of planar trees: # N = C(N), C(N) = 1 N + 1 2N N [Malyshev, Yambartsev, Zamyatin ’01] [Krikun, Yambartsev ’08] [Durhuus, Jonsson, Wheater ’09] Union of all left-most geodesics running towards the origin.
  • 22. Causal triangulations and trees Union of all left-most geodesics running away from the origin. Simple enumeration of planar trees: # N = C(N), C(N) = 1 N + 1 2N N [Malyshev, Yambartsev, Zamyatin ’01] [Krikun, Yambartsev ’08] [Durhuus, Jonsson, Wheater ’09] Union of all left-most geodesics running towards the origin. Both generalize to generalized CDT leading to different representations.
  • 24. Causal triangulations and trees Labeled planar trees: Schaeffer’s bijection.
  • 25. Causal triangulations and trees Labeled planar trees: Schaeffer’s bijection. Unlabeled planar maps (one face per local maximum).
  • 26. Labeled quadrangulations Q(l) = {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) :
  • 27. Labeled quadrangulations Q(l) = {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) :
  • 28. Labeled quadrangulations Q(l) = {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 29. Labeled quadrangulations Q(l) = {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 30. Labeled quadrangulations Q(l) = {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 31. Labeled quadrangulations Q(l) = {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 32. Labeled quadrangulations Q(l) = {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 33. Labeled quadrangulations Q(l) = {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 34. Labeled quadrangulations Q(l) = {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 35. Labeled quadrangulations Q(l) = {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 36. Labeled quadrangulations Q(l) = {quadrangulations Q with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 37. Labeled quadrangulations Q(l) = {quadrangulations Q rooted on an edge with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 38. Labeled quadrangulations Q(l) = {quadrangulations Q rooted on an edge with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M with labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 39. Labeled quadrangulations Q(l) = {quadrangulations Q rooted on an edge with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M w rooted on a corner ith labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : t t t +1 t - 1 t t t +1 t +1
  • 40. Labeled quadrangulations Q(l) = {quadrangulations Q rooted on an edge with labels : {v} → Z, s.t. | (v1) − (v2)| = 1} M(l) = {planar maps M w rooted on a corner ith labels : {v} → Z, s.t. | (v1) − (v2)| = 0, 1} Schaeffer’s rules define a map Ψ : Q(l) → M(l) : →
  • 41. Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB] The map Ψ : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local minima of Q} = #{faces of Ψ(Q)} #{local maxima of Q} = #{local maxima of Ψ(Q)} Max label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) minus 1 Maximal label on Q = maximal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1
  • 42. Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB] The map Ψ : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local minima of Q} = #{faces of Ψ(Q)} #{local maxima of Q} = #{local maxima of Ψ(Q)} Max label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) minus 1 Maximal label on Q = maximal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1
  • 43. Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB] The map Ψ : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local minima of Q} = #{faces of Ψ(Q)} #{local maxima of Q} = #{local maxima of Ψ(Q)} Max label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) minus 1 Maximal label on Q = maximal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1
  • 44. Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB] The map Ψ : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local minima of Q} = #{faces of Ψ(Q)} #{local maxima of Q} = #{local maxima of Ψ(Q)} Max label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) minus 1 Maximal label on Q = maximal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1
  • 45. Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB] The map Ψ : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local minima of Q} = #{faces of Ψ(Q)} #{local maxima of Q} = #{local maxima of Ψ(Q)} Max label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) minus 1 Maximal label on Q = maximal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1
  • 46. Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB] The map Ψ : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local minima of Q} = #{faces of Ψ(Q)} #{local maxima of Q} = #{local maxima of Ψ(Q)} Max label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) minus 1 Maximal label on Q = maximal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1
  • 47. Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB] The map Ψ : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local minima of Q} = #{faces of Ψ(Q)} #{local maxima of Q} = #{local maxima of Ψ(Q)} Max label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) minus 1 Maximal label on Q = maximal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1
  • 48. Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB] The map Ψ : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local minima of Q} = #{faces of Ψ(Q)} #{local maxima of Q} = #{local maxima of Ψ(Q)} Max label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) minus 1 Maximal label on Q = maximal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1
  • 49. Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB] The map Ψ : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local minima of Q} = #{faces of Ψ(Q)} #{local maxima of Q} = #{local maxima of Ψ(Q)} Max label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) minus 1 Maximal label on Q = maximal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1
  • 50. Theorem 1 [Schaeffer, Miermont,...][Ambjørn, TB] The map Ψ : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local minima of Q} = #{faces of Ψ(Q)} #{local maxima of Q} = #{local maxima of Ψ(Q)} Max label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) minus 1 Maximal label on Q = maximal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1 Theorem 1− The map Ψ− : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local maxima of Q} = #{faces of Ψ(Q)} #{local minima of Q} = #{local minima of Ψ(Q)} Min label on root edge of Q = label on root of Ψ(Q) Maximal label on Q = maximal label on Ψ(Q) plus 1 Minimal label on Q = minimal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1
  • 51. Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98] Restrict to Q with single local minimum and minimal label 0.
  • 52. Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98] Restrict to Q with single local minimum and minimal label 0. Labeling on Q is a distance to a distinguished vertex.
  • 53. Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98] Restrict to Q with single local minimum and minimal label 0. Labeling on Q is a distance to a distinguished vertex. Bijection between rooted pointed quadrangulations and rooted labeled trees with minimal label 1.
  • 54. Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98] Restrict to Q with single local minimum and minimal label 0. Labeling on Q is a distance to a distinguished vertex. Bijection between rooted pointed quadrangulations and rooted labeled trees with minimal label 1.
  • 55. Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98] Restrict to Q with single local minimum and minimal label 0. Labeling on Q is a distance to a distinguished vertex. Bijection between rooted pointed quadrangulations and rooted labeled trees with minimal label 1.
  • 56. Cori–Vauquelin–Schaeffer bijection [Cori, Vauquelin, ’81][Schaeffer, ’98] Restrict to Q with single local minimum and minimal label 0. Labeling on Q is a distance to a distinguished vertex. Bijection between rooted pointed quadrangulations and rooted labeled trees with minimal label 1.
  • 57. Assigning couplings to local maxima Assign coupling g to the local maxima of the distance function.
  • 58. Assigning couplings to local maxima Assign coupling g to the local maxima of the distance function. In terms of labeled trees: 5 4 44 4 4 4 5 3 3 5 5
  • 59. Assigning couplings to local maxima Assign coupling g to the local maxima of the distance function. In terms of labeled trees: 5 4 44 4 4 4 5 3 3 5 5
  • 60. Assigning couplings to local maxima Assign coupling g to the local maxima of the distance function. In terms of labeled trees: 5 4 4 5 5 5
  • 61. Assigning couplings to local maxima Assign coupling g to the local maxima of the distance function. In terms of labeled trees: 0 0 0 0 0
  • 62. Assigning couplings to local maxima Assign coupling g to the local maxima of the distance function. In terms of labeled trees: 0 0 0 0 0 Generating function z0(g, g) for number of rooted labeled trees with N edges and Nmax local maxima. Similarly z1(g, g) but local maximum at the root not counted.
  • 63. Assigning couplings to local maxima Assign coupling g to the local maxima of the distance function. In terms of labeled trees: 0 0 0 0 0 Generating function z0(g, g) for number of rooted labeled trees with N edges and Nmax local maxima. Similarly z1(g, g) but local maximum at the root not counted. Satisfy recursion relations: z1 = ∞ k=0 (z1 + z0 + z0) k gk = (1 − gz1 − 2gz0) −1 z0 = ∞ k=0 (z1 + z0 + z0) k gk + (g − 1) ∞ k=0 (z1 + z0) k gk = z1 + (g − 1) (1 − gz1 − gz0) −1
  • 64. z1 = (1 − gz1 − 2gz0) −1 z0 = z1 + (g − 1) (1 − gz1 − gz0) −1 Combine into one equation for z1(g, g): 3g2 z4 1 − 4gz3 1 + (1 + 2g(1 − 2g))z2 1 − 1 = 0
  • 65. z1 = (1 − gz1 − 2gz0) −1 z0 = z1 + (g − 1) (1 − gz1 − gz0) −1 Combine into one equation for z1(g, g): 3g2 z4 1 − 4gz3 1 + (1 + 2g(1 − 2g))z2 1 − 1 = 0 Phase diagram for weighted labeled trees (constant g): g = 0g = 1
  • 66. z1 = (1 − gz1 − 2gz0) −1 z0 = z1 + (g − 1) (1 − gz1 − gz0) −1 Combine into one equation for z1(g, g): 3g2 z4 1 − 4gz3 1 + (1 + 2g(1 − 2g))z2 1 − 1 = 0 Phase diagram for weighted labeled trees (constant g): g = 0g = 1
  • 67. z1 = (1 − gz1 − 2gz0) −1 z0 = z1 + (g − 1) (1 − gz1 − gz0) −1 Combine into one equation for z1(g, g): 3g2 z4 1 − 4gz3 1 + (1 + 2g(1 − 2g))z2 1 − 1 = 0 Phase diagram for weighted labeled trees (constant g): g = 0g = 1
  • 68. The number of local maxima Nmax (g) scales with N at the critical point, Nmax (g) N N = 2 g 2 2/3 + O(g), Nmax (g = 1) N N = 1/2
  • 69. The number of local maxima Nmax (g) scales with N at the critical point, Nmax (g) N N = 2 g 2 2/3 + O(g), Nmax (g = 1) N N = 1/2 Therefore, to obtain a finite continuum density of critical points one should scale g ∝ N−3/2 , i.e. g = gs 3 as observed in [ALWZ ’07].
  • 70. The number of local maxima Nmax (g) scales with N at the critical point, Nmax (g) N N = 2 g 2 2/3 + O(g), Nmax (g = 1) N N = 1/2 Therefore, to obtain a finite continuum density of critical points one should scale g ∝ N−3/2 , i.e. g = gs 3 as observed in [ALWZ ’07]. This is the only scaling leading to a continuum limit qualitatively different from DT and CDT.
  • 71. The number of local maxima Nmax (g) scales with N at the critical point, Nmax (g) N N = 2 g 2 2/3 + O(g), Nmax (g = 1) N N = 1/2 Therefore, to obtain a finite continuum density of critical points one should scale g ∝ N−3/2 , i.e. g = gs 3 as observed in [ALWZ ’07]. This is the only scaling leading to a continuum limit qualitatively different from DT and CDT. Continuum limit g = gc (g)(1 − Λ 2 ), z1 = z1,c (1 − Z1 ), g = gs 3 : Z3 1 − Λ + 3 gs 2 2/3 Z1 − gs = 0
  • 72. The number of local maxima Nmax (g) scales with N at the critical point, Nmax (g) N N = 2 g 2 2/3 + O(g), Nmax (g = 1) N N = 1/2 Therefore, to obtain a finite continuum density of critical points one should scale g ∝ N−3/2 , i.e. g = gs 3 as observed in [ALWZ ’07]. This is the only scaling leading to a continuum limit qualitatively different from DT and CDT. Continuum limit g = gc (g)(1 − Λ 2 ), z1 = z1,c (1 − Z1 ), g = gs 3 : Z3 1 − Λ + 3 gs 2 2/3 Z1 − gs = 0 Can compute:
  • 73. Two-point functions Continuum amplitude for surfaces with root at distance T from origin.
  • 74. Two-point functions Continuum amplitude for surfaces with root at distance T from origin. Rooted pointed quadrangulations with distance t between origin and furthest end-point of the root edge...
  • 75. Two-point functions Continuum amplitude for surfaces with root at distance T from origin. Rooted pointed quadrangulations with distance t between origin and furthest end-point of the root edge... ...are counted by z0(t) − z0(t − 1), with z0(t) the gen. fun. for rooted labeled trees with positive labels and label t on root.
  • 76. Two-point functions Continuum amplitude for surfaces with root at distance T from origin. Rooted pointed quadrangulations with distance t between origin and furthest end-point of the root edge... ...are counted by z0(t) − z0(t − 1), with z0(t) the gen. fun. for rooted labeled trees with positive labels and label t on root. Idem for z1(t), but local max at root not weighted by g. They satisfy z1(t) = 1 1 − gz1(t − 1) − gz0(t) − gz0(t + 1) z0(t) = z1(t) + g − 1 1 − gz1(t − 1) − gz0(t) z1(0) = 0 z0(∞) = z0
  • 77. Solution is (using methods of [Bouttier, Di Francesco, Guitter, ’03]): z1(t) = z1 1 − σt 1 − σt+1 1 − (1 − β)σ − βσt+3 1 − (1 − β)σ − βσt+2 , z0(t) = z0 1 − σt 1 − (1 − β)σ − βσt+1 (1 − (1 − β)σ)2 − β2 σt+3 1 − (1 − β)σ − βσt+2 , with β = β(g, g) and σ = σ(g, g) fixed by g(1 + σ)(1 + βσ)z1 − σ(1 − 2g z0) = 0, (1 − β)σ − g(1 + σ)z1 + g(1 − σ + 2βσ)z0 = 0.
  • 78. Solution is (using methods of [Bouttier, Di Francesco, Guitter, ’03]): z1(t) = z1 1 − σt 1 − σt+1 1 − (1 − β)σ − βσt+3 1 − (1 − β)σ − βσt+2 , z0(t) = z0 1 − σt 1 − (1 − β)σ − βσt+1 (1 − (1 − β)σ)2 − β2 σt+3 1 − (1 − β)σ − βσt+2 , with β = β(g, g) and σ = σ(g, g) fixed by g(1 + σ)(1 + βσ)z1 − σ(1 − 2g z0) = 0, (1 − β)σ − g(1 + σ)z1 + g(1 − σ + 2βσ)z0 = 0. Continuum limit, g = gs 3 , g = gc (1 − Λ 2 ), t = T/ , gives ∼ dZ0(T) dT = Σ3 gs α Σ sinh ΣT + α cosh ΣT Σ cosh ΣT + α sinh ΣT 3
  • 79. Solution is (using methods of [Bouttier, Di Francesco, Guitter, ’03]): z1(t) = z1 1 − σt 1 − σt+1 1 − (1 − β)σ − βσt+3 1 − (1 − β)σ − βσt+2 , z0(t) = z0 1 − σt 1 − (1 − β)σ − βσt+1 (1 − (1 − β)σ)2 − β2 σt+3 1 − (1 − β)σ − βσt+2 , with β = β(g, g) and σ = σ(g, g) fixed by g(1 + σ)(1 + βσ)z1 − σ(1 − 2g z0) = 0, (1 − β)σ − g(1 + σ)z1 + g(1 − σ + 2βσ)z0 = 0. Continuum limit, g = gs 3 , g = gc (1 − Λ 2 ), t = T/ , gives ∼ dZ0(T) dT = Σ3 gs α Σ sinh ΣT + α cosh ΣT Σ cosh ΣT + α sinh ΣT 3 gs →∞ −→ Λ3/4 cosh(Λ1/4 T ) sinh3 (Λ1/4T ) T = g1/6 s T DT two-point function appears as gs → ∞! [Ambjørn, Watabiki, ’95]
  • 80. Theorem 1− The map Ψ− : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local maxima of Q} = #{faces of Ψ(Q)} #{local minima of Q} = #{local minima of Ψ(Q)} Min label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1
  • 81. Theorem 1− The map Ψ− : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local maxima of Q} = #{faces of Ψ(Q)} #{local minima of Q} = #{local minima of Ψ(Q)} Min label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1 Restricting Ψ− to Q with single minimum labeled 0
  • 82. Theorem 1− The map Ψ− : Q(l) → M(l) is a bijection satisfying #{faces of Q} = #{edges of Ψ(Q)} #{local maxima of Q} = #{faces of Ψ(Q)} #{local minima of Q} = #{local minima of Ψ(Q)} Min label on root edge of Q = label on root of Ψ(Q) Minimal label on Q = minimal label on Ψ(Q) t t t +1 t - 1 t t t +1 t +1 Restricting Ψ− to Q with single minimum labeled 0 gives a bijection between pointed rooted quadrangulations and pointed rooted planar maps.
  • 83. Ψ− (Q) has a face for each local maximum of Q. Within each face the structure of Q is similar to CDT. Restricting Ψ− to Q with single minimum labeled 0 gives a bijection between pointed rooted quadrangulations and pointed rooted planar maps.
  • 84. Two-point function for planar maps The generating function for Q with max label t on the root edge is z0(t) − z0(t − 1)
  • 85. Two-point function for planar maps The generating function for Q with max label t on the root edge is z0(t) − z0(t − 1) Therefore one obtains an explicit generating function z0(t + 1) − z0(t) = ∞ N=0 ∞ n=0 Nt(N, n)gN gn for the number Nt(N, n) of planar maps with N edges, n faces, and a marked point at distance t from the root.
  • 86. Two loop identity in generalized CDT Consider surfaces with two boundaries separated by a geodesic distance D.
  • 87. Two loop identity in generalized CDT Consider surfaces with two boundaries separated by a geodesic distance D. One can assign time T1, T2 to the boundaries (|T1 − T2| ≤ D) and study a “merging” process.
  • 88. Two loop identity in generalized CDT Consider surfaces with two boundaries separated by a geodesic distance D. One can assign time T1, T2 to the boundaries (|T1 − T2| ≤ D) and study a “merging” process. For a given surface the foliation depends on T1 − T2, hence also Nmax and its weight.
  • 89. Two loop identity in generalized CDT Consider surfaces with two boundaries separated by a geodesic distance D. One can assign time T1, T2 to the boundaries (|T1 − T2| ≤ D) and study a “merging” process. For a given surface the foliation depends on T1 − T2, hence also Nmax and its weight. However, in [ALWZ ’07] it was shown that the amplitude is independent of T1 − T2.
  • 90. Two loop identity in generalized CDT Consider surfaces with two boundaries separated by a geodesic distance D. One can assign time T1, T2 to the boundaries (|T1 − T2| ≤ D) and study a “merging” process. For a given surface the foliation depends on T1 − T2, hence also Nmax and its weight. However, in [ALWZ ’07] it was shown that the amplitude is independent of T1 − T2. Refoliation symmetry at the quantum level in the presence of topology change!
  • 91. Two loop identity in generalized CDT Consider surfaces with two boundaries separated by a geodesic distance D. One can assign time T1, T2 to the boundaries (|T1 − T2| ≤ D) and study a “merging” process. For a given surface the foliation depends on T1 − T2, hence also Nmax and its weight. However, in [ALWZ ’07] it was shown that the amplitude is independent of T1 − T2. Refoliation symmetry at the quantum level in the presence of topology change! Can we better understand this symmetry at the discrete level?
  • 92. Two loop identity in generalized CDT Consider surfaces with two boundaries separated by a geodesic distance D. One can assign time T1, T2 to the boundaries (|T1 − T2| ≤ D) and study a “merging” process. For a given surface the foliation depends on T1 − T2, hence also Nmax and its weight. However, in [ALWZ ’07] it was shown that the amplitude is independent of T1 − T2. Refoliation symmetry at the quantum level in the presence of topology change! Can we better understand this symmetry at the discrete level? For simplicity set the boundary lengths to zero. Straightforward generalization to finite boundaries.
  • 93. Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d} Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d}
  • 94. Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d} Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d} Let Ld t1,t2 : Qd → Q(l) with |t1 − t2| − d = 2, 4, . . . be the labeled quad. with local minima ti on vi . Qd Q(l) Ld t1,t2
  • 95. Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d} Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d} Let Ld t1,t2 : Qd → Q(l) with |t1 − t2| − d = 2, 4, . . . be the labeled quad. with local minima ti on vi . Qd Q(l) M(l) Ld t1,t2 Ψ−
  • 96. Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d} Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d} Let Ld t1,t2 : Qd → Q(l) with |t1 − t2| − d = 2, 4, . . . be the labeled quad. with local minima ti on vi . Qd Q(l) M(l) Md ∪ Md−1 Ld t1,t2 Ψ−
  • 97. Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d} Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d} Let Ld t1,t2 : Qd → Q(l) with |t1 − t2| − d = 2, 4, . . . be the labeled quad. with local minima ti on vi . Qd Md ∪ Md−1 Ψd t1,t2
  • 98. Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d} Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d} Let Ld t1,t2 : Qd → Q(l) with |t1 − t2| − d = 2, 4, . . . be the labeled quad. with local minima ti on vi . Qd Q(l) M(l) Md ∪ Md−1 Ld t1,t2 Ψ− Ψd t1,t2
  • 99. Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d} Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d} Let Ld t1,t2 : Qd → Q(l) with |t1 − t2| − d = 2, 4, . . . be the labeled quad. with local minima ti on vi . Qd Md ∪ Md−1 Ψd t1,t2 Ψd t1,t2
  • 100. Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d} Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d} Let Ld t1,t2 : Qd → Q(l) with |t1 − t2| − d = 2, 4, . . . be the labeled quad. with local minima ti on vi . Qd Md ∪ Md−1 Ψd t1,t2 (Ψd t1,t2 )−1
  • 101. Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d} Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d} Let Ld t1,t2 : Qd → Q(l) with |t1 − t2| − d = 2, 4, . . . be the labeled quad. with local minima ti on vi . Qd Md ∪ Md−1 Ψd t1,t2 (Ψd t1,t2 )−1
  • 102. Qd = {rooted quadr. Q with marked vert. v1, v2, s.t. d(v1, v2) = d} Md = {rooted maps M with marked vert. v1, v2, s.t. d(v1, v2) = d} Let Ld t1,t2 : Qd → Q(l) with |t1 − t2| − d = 2, 4, . . . be the labeled quad. with local minima ti on vi . We have found a bijection (Ψd t1,t2 )−1 ◦ Ψd t1,t2 : Qd → Qd preserving the distance between v1 and v2, mapping Nmax maxima w.r.t. (t1, t2) to Nmax maxima w.r.t. (t1, t2).
  • 103. Proof of Ψd t1,t2 (Qd) ⊂ Md ∪ Md−1 For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on v is min{d(v, v1), d(v, v2)}.
  • 104. Proof of Ψd t1,t2 (Qd) ⊂ Md ∪ Md−1 For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on v is min{d(v, v1), d(v, v2)}. The same holds in the planar map.
  • 105. Proof of Ψd t1,t2 (Qd) ⊂ Md ∪ Md−1 For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on v is min{d(v, v1), d(v, v2)}. The same holds in the planar map.
  • 106. Proof of Ψd t1,t2 (Qd) ⊂ Md ∪ Md−1 For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on v is min{d(v, v1), d(v, v2)}. The same holds in the planar map. For each path of length d in Q there is a path of length d − 1 or d in M.
  • 107. Proof of Ψd t1,t2 (Qd) ⊂ Md ∪ Md−1 For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on v is min{d(v, v1), d(v, v2)}. The same holds in the planar map. For each path of length d in Q there is a path of length d − 1 or d in M.
  • 108. Proof of Ψd t1,t2 (Qd) ⊂ Md ∪ Md−1 For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on v is min{d(v, v1), d(v, v2)}. The same holds in the planar map. For each path of length d in Q there is a path of length d − 1 or d in M.
  • 109. Proof of Ψd t1,t2 (Qd) ⊂ Md ∪ Md−1 For simplicity let us set t0 = t1 = 0 (and d = 4). Then the label on v is min{d(v, v1), d(v, v2)}. The same holds in the planar map. For each path of length d in Q there is a path of length d − 1 or d in M.
  • 110. Conclusions & Outlook Conclusions The Cori–Vauquelin–Schaeffer bijection and its generalizations are ideal for studying “proper-time foliations” of random surfaces. Generalized CDT appears naturally as the scaling limit of random planar maps with a fixed finite number of faces. Continuum DT (Brownian map?) seems to be recovered by taking gs → ∞. The relation to planar maps explains the mysterious loop-loop identity in the continuum.
  • 111. Conclusions & Outlook Conclusions The Cori–Vauquelin–Schaeffer bijection and its generalizations are ideal for studying “proper-time foliations” of random surfaces. Generalized CDT appears naturally as the scaling limit of random planar maps with a fixed finite number of faces. Continuum DT (Brownian map?) seems to be recovered by taking gs → ∞. The relation to planar maps explains the mysterious loop-loop identity in the continuum. Outlook Is there a convergence towards a random measure on metric spaces, i.e. analogue of the Brownian map? Should first try to understand 2d geometry of random causal triangulations. Does the loop-loop identity generalize? Is there some structure to the associated symmetries? Various stochastic processes involved in generalized CDT. How are they related?
  • 112. Conclusions & Outlook Conclusions The Cori–Vauquelin–Schaeffer bijection and its generalizations are ideal for studying “proper-time foliations” of random surfaces. Generalized CDT appears naturally as the scaling limit of random planar maps with a fixed finite number of faces. Continuum DT (Brownian map?) seems to be recovered by taking gs → ∞. The relation to planar maps explains the mysterious loop-loop identity in the continuum. Outlook Is there a convergence towards a random measure on metric spaces, i.e. analogue of the Brownian map? Should first try to understand 2d geometry of random causal triangulations. Does the loop-loop identity generalize? Is there some structure to the associated symmetries? Various stochastic processes involved in generalized CDT. How are they related? Further reading: arXiv:1302.1763 These slides and more: http://www.nbi.dk/~budd/ Thanks for your attention!
  • 113. Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12] A quadrangulations with boundary length 2l
  • 114. Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12] A quadrangulations with boundary length 2l and an origin.
  • 115. Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12] A quadrangulations with boundary length 2l and an origin. Applying the same prescription we obtain a forest rooted at the boundary. 5 6 7 6 5 6 5 4 3 4 5 4 3 2 3 4 3 4 5 6 7 8 9 89 8 7 6
  • 116. Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12] A quadrangulations with boundary length 2l and an origin. Applying the same prescription we obtain a forest rooted at the boundary. The labels on the boundary arise from a (closed) random walk. 5 6 7 6 5 6 5 4 3 4 5 4 3 2 3 4 3 4 5 6 7 8 9 89 8 7 6 5 6 7 6 5 6 5 4 3 4 5 4 3 2 3 4 3 4 5 6 7 8 9 8 9 8 7 6
  • 117. Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12] A quadrangulations with boundary length 2l and an origin. Applying the same prescription we obtain a forest rooted at the boundary. The labels on the boundary arise from a (closed) random walk. A (possibly empty) tree grows at the end of every +-edge. 5 6 7 6 5 6 5 4 3 4 5 4 3 2 3 4 3 4 5 6 7 8 9 89 8 7 6
  • 118. Including boundaries [Bouttier, Guitter ’09, Bettinelli ’11, Curien, Miermont ’12] A quadrangulations with boundary length 2l and an origin. Applying the same prescription we obtain a forest rooted at the boundary. The labels on the boundary arise from a (closed) random walk. A (possibly empty) tree grows at the end of every +-edge. There is a bijection 5 6 7 6 5 6 5 4 3 4 5 4 3 2 3 4 3 4 5 6 7 8 9 89 8 7 6 Quadrangulations with origin and boundary length 2l ↔ {(+, −)-sequences} × {tree} l
  • 121. Disk amplitudes w(g, l) = z(g)l w(g, x) = ∞ l=0 w(g, l)xl = 1 1 − z(g)x w(g, l) = 2l l z(g)l w(g, x) = 1 1 − 4z(g)x
  • 122. Disk amplitudes w(g, l) = z(g)l w(g, x) = ∞ l=0 w(g, l)xl = 1 1 − z(g)x w(g, l) = 2l l z(g)l w(g, x) = 1 1 − 4z(g)x Generating function for unlabeled trees: z(g) = 1 − √ 1 − 4g 2g 0 000 0 0 0 00 Generating function for labeled trees: z(g) = 1 − √ 1 − 12g 6g
  • 123. Continuum limit w(g, x) = 1 1 − zx w(g, x) = 1 √ 1 − 4zx z(g) = 1− √ 1−4g 2g 0 000 0 0 0 00 z(g) = 1− √ 1−12g 6g
  • 124. Continuum limit w(g, x) = 1 1 − zx w(g, x) = 1 √ 1 − 4zx z(g) = 1− √ 1−4g 2g 0 000 0 0 0 00 z(g) = 1− √ 1−12g 6g Expanding around critical point in terms of “lattice spacing” : g = gc (1 − Λ 2 ), z(g) = zc (1 − Z ), x = xc (1 − X )
  • 125. Continuum limit w(g, x) = 1 1 − zx WΛ(X) = 1 X + Z w(g, x) = 1 √ 1 − 4zx WΛ(X) = 1 √ X + Z z(g) = 1− √ 1−4g 2g Z = √ Λ 0 000 0 0 0 00 z(g) = 1− √ 1−12g 6g Z = √ Λ Expanding around critical point in terms of “lattice spacing” : g = gc (1 − Λ 2 ), z(g) = zc (1 − Z ), x = xc (1 − X )
  • 126. Continuum limit w(g, x) = 1 1 − zx WΛ(X) = 1 X + Z w(g, x) = 1 √ 1 − 4zx WΛ(X) = 1 √ X + Z z(g) = 1− √ 1−4g 2g Z = √ Λ 0 000 0 0 0 00 z(g) = 1− √ 1−12g 6g Z = √ Λ Expanding around critical point in terms of “lattice spacing” : g = gc (1 − Λ 2 ), z(g) = zc (1 − Z ), x = xc (1 − X ) CDT disk amplitude: WΛ(X) = 1 X+ √ Λ
  • 127. Continuum limit w(g, x) = 1 1 − zx WΛ(X) = 1 X + Z w(g, x) = 1 √ 1 − 4zx WΛ(X) = 1 √ X + Z z(g) = 1− √ 1−4g 2g Z = √ Λ 0 000 0 0 0 00 z(g) = 1− √ 1−12g 6g Z = √ Λ Expanding around critical point in terms of “lattice spacing” : g = gc (1 − Λ 2 ), z(g) = zc (1 − Z ), x = xc (1 − X ) CDT disk amplitude: WΛ(X) = 1 X+ √ Λ DT disk amplitude with marked point: WΛ(X) = 1√ X+ √ Λ . Integrate w.r.t. Λ to remove mark: WΛ(X) = 2 3 (X − 1 2 √ Λ) X + √ Λ.