Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With:...
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![Page 1: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/1.jpg)
Limits of randomly growngraph sequences
Katalin VesztergombiEötvös University, Budapest
With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós
![Page 2: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/2.jpg)
Convergent graph sequences
1 2( , ,...) ( , )convergent: isconvergentnG G F t F G"
with probability 1
Example: random graphs
( )| ( )|12
12( , )( , )
E Fnt F ®Gt
| ( )|
hom( , )| ( ) |
( , ) V F
F GV G
t F G Probability that random mapV(F)V(G) is a hom
![Page 3: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/3.jpg)
The limit object
{ }20 : [0,1] [0,1] symmetric, measurableW= ®W
( ) ( )[0,1]
( , )( , )V F
i jij E F
W x x dxt F WÎ
= Õò( , ( ): ) ,nn F t F G WW tG F® " ®
For every convergent graph sequence (Gn)there is a such that0W Î W nG W®
Lovász-Szegedy
![Page 4: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/4.jpg)
0 0 1 0 0 1 1 0 0 0 1 0 0 10 0 1 0 1 0 1 0 0 0 0 0 1 01 1 0 1 0 1 1 1 1 0 1 0 1 10 0 1 0 1 0 1 0 1 0 1 1 0 00 1 0 1 0 1 1 0 0 0 1 0 0 11 0 1 0 1 0 1 1 0 1 1 1 0 11 1 1 1 1 1 0 1 0 1 1 1 1 00 0 1 0 0 1 1 0 1 0 1 0 1 10 0 1 1 0 0 0 1 1 1 0 1 0 00 0 0 0 0 1 1 0 1 0 1 0 1 01 0 1 1 1 1 1 1 0 1 0 1 1 10 0 0 1 0 1 1 0 1 0 1 0 1 00 1 1 0 0 0 1 1 0 1 1 1 0 11 0 1 0 1 1 0 1 0 0 1 0 1 0
![Page 5: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/5.jpg)
Half-graphs
![Page 6: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/6.jpg)
A random graph with
100 nodes and with edge density 1/2W1/2
![Page 7: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/7.jpg)
Rearranging the rows and columns
![Page 8: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/8.jpg)
A random graph with
100 nodes and with edge density 1/2W1/2
(no matter how you reorder the nodes)
![Page 9: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/9.jpg)
Randomly grown uniform attachment graph
At step n:- a new node is born;- any two nodes are connected with probability 1/n
Ignore multiplicity of edges
![Page 10: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/10.jpg)
A randomly grown
uniform attachment graph
with 200 nodes
![Page 11: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/11.jpg)
probability that nodes i < j are not connected:
1 1 11
j j n jj j n n- - -=+ L
expected degree of j:
1 ( 1)( 2)2 2
n j jn
- - --
expected number of edges:2 16
n -
After n steps:
![Page 12: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/12.jpg)
probability that nodes i and j are connected:
max( , ) 11 i jn
--
The limit:
if i=xn and j=yn
1 max( , )x y» -
These are independent events for different i,j.
![Page 13: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/13.jpg)
A randomly grown
uniform attachment graph
with 200 nodes
( , ) 1 max( , )W x y x y= -
Proof: By estimating the cut-distance.
![Page 14: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/14.jpg)
Randomly grown prefix attachment graph
At step n:- a new node is born;- connects to a random previous node and all its predecessors
![Page 15: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/15.jpg)
A randomly grown prefix attachment graph
with 200 nodes
Is this graph sequenceconvergent at all?
Yes, by computing subgraph densities!
This tends to some shades of gray; is that the limit?
No, by computing triangle densities!
![Page 16: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/16.jpg)
A randomly grown prefix attachment graph
with 200 nodes (ordered by degrees)
This also tends to some shades of gray; is that the limit?
No…
![Page 17: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/17.jpg)
Label node born in step k, connecting to {1,…,m}, by (k/n, m/k)
1 22
1 22
21 2 ork k m k m
kx y
n nx
æ ö÷ç ÷£ £ç ÷ç ÷çè ø£
- Nodes with label (x1, y1) and (x2, y2) (x1< x2) are connected iff
- Labels are uniformly distributed in the unit square
Limit can be represented as2 2
1 2 2
:[0,1] [0,1] [0,1]1 ,
( , )0,, if
otherwise
Wx x y
W x y
´ ®ì £ïï=íïïî
![Page 18: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/18.jpg)
The limit of randomly grown prefix attachment graphs
(as a function on [0,1]2)
![Page 19: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/19.jpg)
Preferential attachment graph on n fixed nodes
At step m: any two nodes i and j are connected with probability (d(i)+1)(d(j)+1)/(2m+n)2
Allow multiple edges!!!
Repeat until we insert edges. 1
22n
mæö÷ç= ÷ç ÷ç ÷çè ø
![Page 20: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/20.jpg)
A preferential attachment graph
with 200 fixed nodes
and with 5,000 (multiple) edges
![Page 21: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/21.jpg)
( , ) ln( ) ln( )W x z x y=A randomly grown
preferential attachment graph
with 200 fixed nodes ordered by degrees
and with 5,000 (multiple) edges
Proof by computing t(F,Gn)
![Page 22: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/22.jpg)
Can we construct a sequence converging to 1-xy?
Method 1: W-random graph
x1,…,xn,…: independent points from [0,1]
connect xi and xj with probability 1-xi xj
Works for any W
![Page 23: Limits of randomly grown graph sequences Katalin Vesztergombi Eötvös University, Budapest With: Christian Borgs, Jennifer Chayes, László Lovász, Vera Sós.](https://reader035.fdocuments.us/reader035/viewer/2022062311/5a4d1ae17f8b9ab05997788c/html5/thumbnails/23.jpg)
Method 2: growing in order
At step n: - a new node is born, and connected to i with prob (n-i)/n - any two old nodes are connected with probability 1/n
Ignore multiplicity of edges
Works for any monotone decreasing W