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March 15, 2017

Functional Equations VI: Using Probability Theory to Solve Functional Equations

Posted by Tom Leinster

A functional equation is an entirely deterministic thing, such as f(x+y)=f(x)+f(y) f(x + y) = f(x) + f(y) or f(f(f(x)))=x f(f(f(x))) = x or f(cos(e f(x)))+2x=sin(f(x+1)). f\Bigl(\cos\bigl(e^{f(x)}\bigr)\Bigr) + 2x = \sin\bigl(f(x+1)\bigr). So it’s a genuine revelation that one can solve some functional equations using probability theory — more specifically, the theory of large deviations.

This week and next week, I’m explaining how. Today (pages 22-25 of these notes) was mainly background:

  • an introduction to the theory of large deviations;

  • an introduction to convex duality, which Simon has written about here before;

  • how the two can be combined to get a nontrivial formula for sums of powers of real numbers.

Next time, I’ll explain how this technique produces a startlingly simple characterization of the pp-norms.

Posted at March 15, 2017 12:56 AM UTC

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