Kingman's subadditive ergodic theorem

Summary

In mathematics, Kingman's subadditive ergodic theorem is one of several ergodic theorems. It can be seen as a generalization of Birkhoff's ergodic theorem.[1] Intuitively, the subadditive ergodic theorem is a kind of random variable version of Fekete's lemma (hence the name ergodic).[2] As a result, it can be rephrased in the language of probability, e.g. using a sequence of random variables and expected values. The theorem is named after John Kingman.

Statement of theorem edit

Let   be a measure-preserving transformation on the probability space  , and let   be a sequence of   functions such that   (subadditivity relation). Then

 

for  -a.e. x, where g(x) is T-invariant.

In particular, if T is ergodic, then g(x) is a constant.

Equivalent statement edit

Given a family of real random variables  , with  , such that they are subadditive in the sense that

 
Then there exists a random variable   such that  ,   is invariant with respect to  , and   a.s..

They are equivalent by setting

  •   with  ;
  •   with  .

Proof edit

Proof due to (J. Michael Steele, 1989).[3]

Subadditivity by partition edit

Fix some  . By subadditivity, for any  

 

We can picture this as starting with the set  , and then removing its length  tail.

Repeating this construction until the set   is all gone, we have a one-to-one correspondence between upper bounds of   and partitions of  .

Specifically, let   be a partition of  , then we have

 

Constructing g edit

Let  , then it is  -invariant.

By subadditivity,

 

Taking the   limit, we have

 
We can visualize   as hill-climbing on the graph of  . If   actually causes a nontrivial amount of hill-climbing, then we would get a spatial contraction, and so   does not preserve measure. Therefore   a.e.

Let  , then

 
and since both sides have the same measure, by squeezing, they are equal a.e..

That is,  , a.e..

Now apply this for all rational  .

Reducing to the case of gₙ ≤ 0 edit

By subadditivity, using the partition of   into singletons.

 
Now, construct the sequence
 
which satisfies   for all  .

By the special case,   converges a.e. to a   -invariant function.

By Birkhoff's pointwise ergodic theorem, the running average

 
converges a.e. to a   -invariant function. Therefore, their sum does as well.

Bounding the truncation edit

Fix arbitrary  , and construct the truncated function, still   -invariant:

 
With these, it suffices to prove an a.e. upper bound
 
since it would allow us to take the limit  , then the limit  , giving us a.e.

 
And by squeezing, we have   converging a.e. to  . Define two families of sets, one shrinking to the empty set, and one growing to the full set. For each "length"  , define
 
 
Since  , the   family shrinks to the empty set.


Fix  . Fix  . Fix  . The ordering of these qualifiers is vitally important, because we will be removing the qualifiers one by one in the reverse order.

To prove the a.e. upper bound, we must use the subadditivity, which means we must construct a partion of the set  . We do this inductively:

Take the smallest   not already in a partition.

If  , then   for some  . Take one such   – the choice does not matter.

If  , then we cut out  . Call these partitions “type 1”. Else, we cut out  . Call these partitions “type 2”.

Else, we cut out  . Call these partitions “type 3”.

Now convert this partition into an inequality:

 
where   are the heads of the partitions, and   are the lengths.

Since all  , we can remove the other kinds of partitions:

 
By construction, each  , thus
 
Now it would be tempting to continue with  , but unfortunately  , so the direction is the exact opposite. We must lower bound the sum  .

The number of type 3 elements is equal to

 
If a number   is of type 2, then it must be inside the last   elements of  . Thus the number of type 2 elements is at most  . Together, we have the lower bound:
 

Peeling off the first qualifier edit

Remove the   qualifier by taking the   limit.

By Birkhoff's pointwise ergodic theorem, there exists an a.e. pointwise limit

 
satisfying
 
At the limit, we find that for a.e.  ,
 

Peeling off the second qualifier edit

Remove the   qualifier by taking the   limit.

Since we have

 
and   as  , we can apply the same argument used for proving Markov's inequality, to obtain
 
for a.e.  .


In detail, the argument is as follows: since  , and  , we know that for any small  , all large enough   satisfies   everywhere except on a set of size  . Thus,

 
with probability  . Now take both  .

Applications edit

Taking   recovers Birkhoff's pointwise ergodic theorem.

Taking all   constant functions, we recover the Fekete’s subadditive lemma.

Kingman's subadditive ergodic theorem can be used to prove statements about Lyapunov exponents. It also has applications to percolations and longest increasing subsequence.[4]

Longest increasing subsequence edit

To study the longest increasing subsequence of a random permutation  , we generate it in an equivalent way. A random permutation on   is equivalently generated by uniformly sampling   points in a square, then find the longest increasing subsequence of that.

Now, define the Poisson point process with density 1 on  , and define the random variables   to be the length of the longest increasing subsequence in the square  . Define the measure-preserving transform   by shifting the plane by  , then chopping off the parts that have fallen out of  .

The process is subadditive, that is,  . To see this, notice that the right side constructs an increasing subsequence first in the square  , then in the square  , and finally concatenate them together. This produces an increasing subsequence in  , but not necessarily the longest one.

Also,   is ergodic, so by Kingman's theorem,   converges to a constant almost surely. Since at the limit, there are   points in the square, we have   converging to a constant almost surely.

References edit

  1. ^ S. Lalley, Kingman's subadditive ergodic theorem lecture notes, http://galton.uchicago.edu/~lalley/Courses/Graz/Kingman.pdf
  2. ^ Chen. "Subadditive ergodic theorems" (PDF). New York University.
  3. ^ Steele, J. Michael (1989). "Kingman's subadditive ergodic theorem" (PDF). Annales de l'I.H.P. Probabilités et statistiques. 25 (1): 93–98. ISSN 1778-7017.
  4. ^ Pitman, Lecture 12: Subadditive ergodic theory, http://www.stat.berkeley.edu/~pitman/s205s03/lecture12.pdf