NEWS
Spatial Networks
 STAT C206A (= MATH C223A) Fall 2013:  David Aldous
STAT 206, with catalog description 
 Advanced Topics in Probability and Stochastic Processes, 
is intended to have a different subject each semester.  
My subject is 
Spatial Networks
This is a broad and diffuse topic which has been studied in many disciplines, but
the course will emphasize stochastic aspects. 
-  
We start with an overview in
this 100-page survey by Marc Barthelemy,
which examines models and data from a statistical physics viewpoint and shows some 
interesting real data.   The survey does not emphasize math theorems, but  
I will use it as a starting point for discussing what is known mathematics and what are possible 
math research problems.
-  We then segue into more specific technical work,
from the list of possibly-relevant papers. 
-  There is no systematic definition-theorem-proof account of our central topic, 
general random spatial networks, but the books below treat related topics such as 
-  Stochastic geometry 
-  The random geometric graph, continuum percolation and their use in models of 
wireless communication
-  Algorithmic aspects of spatial network construction
 and we will cover some of this material.
For the record I will maintain a list of networks 
that are mentioned in the course.
Books
There are no books with precisely the focus of this course.  
The most closely related, as regards math topics, are 
-  Baccelli - Blaszczyszyn (2009): 
  Stochastic Geometry and Wireless Networks: Volume I Theory.
 
-   Franceschetti - Meester (2007): Random networks for communication: 
 from statistical physics to information systems. 
 
-  Narasimhan - Smid (2007): Geometric spanner networks.
  
-  Penrose (2003): Random geometric graphs.
  
-  Preparata - Shamos (1993):  Computational Geometry: An Introduction.
  
-  Steele (1997): Probability theory and combinatorial optimization.
 
-  Stoyan - Kendall - Mecke (1995): Stochastic geometry and its applications.
 
(2,3,4,7 are on reserve in the Math-Stat library). 
 For a broad-ranging overview of quantitative aspects of networks, without specialized math, 
 by far the best book is
 
For a textbook on some basic math see-  Newman (2010): 
  Networks: An Introduction.
 
Similar courses elsewhere
These are courses with useful info online.  
Mostly with less mathematical emphasis.
Administration
Lecture times: 
MWF  1.00 - 2.00pm   room 330 EVANS
Office Hours
Thursdays 2.15 - 3.45 in 351 Evans
If you email me (aldous@stat.berkeley.edu) put "STAT 206" in subject line.
 Requirements for students.
Students taking the course for credit need to do one of the following.
Class-by-class schedule
This will mostly be a debriefing of what I have done, rather than a plan for the future......
-  8/30 Abstract graph, planar graph, spatial network, Delaunay triangulation.
-   9/4 Euler's formula, triangulations, planar duals, Gabriel graph.
-   9/6 Relationship between PPP and finite-n random model; 
calculations with PPP; Gabriel gaph on random points. 
-   9/9  Minimum spanning tree, relative neighborhood graph, Steiner tree. 
-   9/11 Worst-case and average-case length of MST.  
Start topics from Barthelemy (2011) survey.  Road-dual networks, 
hop distance, betweenness centrality.
-   9/13 Mention leaf-labeled spatial network.  
Gastner - Newman (2006) study of k-hop networks.  
Hub-spoke model from Aldous (2008a).
-   9/16 - 9/18 Continue hub-spoke model; approximate equidistribution conditions.
"Route-length in tree-networks" conjecture.  Construction from Aldous-Kendall (2008);  
three statistics for route-length efficiency. 
-  9/20 Stretch: worst-case and average-case results.  
And some slides from this lecture.
-   9/23  The beta-skeleton family and simulations. 
Networks based on powers of edge-lengths.
-   9/25 We will go to 1011 Evans to hear Ravi Kannan talk on
A Point Process.
-   9/27  "your friends have more friends than you do" theorem.  Ideas from 
Barthelemy survey; assortivity coefficient, betweenness centrality, 
P-space and L-space for rail networks.
-  
-   9/30  Overview of next part of course.  Subaddutivity and local weak convergence as 
``first moment" methodologies for network length.  Mention CLT and LD techniques.
- 
-  Slides from lectures above omitting material from other sources.  
 
-   10/2 - 10/7   Material from Steele (1997).  Basic subadditivity lemma, 
application to longest common subsequence.  
 de Bruijn -  Erdos subadditivity result. General 
"subadditive Euclidean functionals" limit theorem.  
Easy application to TSP.  Indirect application in Aldous-Krikun (2006).
-   10/9 - 10/11; 10/18  Review variation distance; weak convergence and product spaces; 
stationarity, ergodicity and relation to dynamical systems.
-   10/21  Local weak convergence for sequences.  
-   10/23 - 10/25  Local weak convergence for spatial networks; outline 
application to optimal networks.
- 
-   10/28  Stochastic geometry: intersections of TRI network with fixed line. 
-   10/30   The Poisson line process: construction and basic formulas.
-   11/1 Lower-bounding length for networks with given stretch.
- 
-   11/4   The Poisson line process: more formulas.
-   11/6 - 11/8 
Random networks with linear route-lengths, from Aldous (2009).
Application of general result to the RNG.
- 
-   11/13   
Technique of comparison with oriented percolation; outline proof of general result.
-   11/15   Subadditive ergodic theorem and the  shape theorem for 
first-passage percolation;  limits of route-lengths in random networks (Aldous - Garet 2013).
- 
-   11/18   Random geometric graphs.  Definition, motifs (Penrose sec 3.1).
-   11/20   Maximum degree and connectivity.
-   11/22 - 11/25   Subcritical continuum percolation (Penrose sec 10.1),
- 
-   11/27 
Supercritical continuum percolation (Penrose sec 10.2-10.3).
- 
-  Start student talks.
-  12/2
-  12/4
-  12/6
-  12/9
-  12/11