Seminar on Random Walks on Graphs 2009/2010 Ilan Ben Bassat Omri Weinstein Mixing Time – General Chains.

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Presentation transcript:

Seminar on Random Walks on Graphs 2009/2010 Ilan Ben Bassat Omri Weinstein Mixing Time – General Chains

Mixing Time - Lazy Chains Given that: Then:

Proof Sketch Bound distance to stationary distribution by some function h: Bound the value of h t (x) inductively. Derive a bound on the mixing time.

Proof Sketch Bound distance to stationary distribution by some function h: Bound the value of h t (x) inductively. Derive a bound on the mixing time.

Bounding Distributions Distance For every

So, choosing for every S yields: And for every vertex w we can get:

H(x) Values Order the graph vertices: And define. Find k such that: Then the value of h t (x) is obtained by: And we get:

Function H - Analysis Piece-wise linear function. Concave Breakpoints at On the interval [0,1]: and

Proof Sketch Bound distance to stationary distribution by some function h: Bound the value of h t (x) inductively. Derive a bound on the mixing time.

Proof Sketch and Intuition We will prove for every x and t: Intuition: Bound the value h(x) in time t by going one step backwards, and a bit towards the endpoints. Prove will be in three parts: For a finite group of discrete x values. For all x values satisfying (and symmetric case). For all x values and

Proof – Breakpoints Fix k and let

Proof – cont’d

Proof – second case

Proof – Third Part So, for every x we get:

Base Case

Induction For t=0 trivial. For and

Induction

Proof Sketch Bound distance to stationary distribution by some function h: Bound the value of h t (x) inductively. Derive a bound on the mixing time.

Mixing Time Proof Given