In mathematics specifically, in large deviations theory the contraction principle is a theorem that states how a large deviation principle on one space "pushes forward" (via the pushforward of a probability measure) to a large deviation principle on another space via a continuous function.

Statement

Let X and Y be Hausdorff topological spaces and let (με)ε>0 be a family of probability measures on X that satisfies the large deviation principle with rate function I : X  [0, +∞]. Let T : X  Y be a continuous function, and let νε = T(με) be the push-forward measure of με by T, i.e., for each measurable set/event E  Y, νε(E) = με(T1(E)). Let

with the convention that the infimum of I over the empty set ∅ is +∞. Then:

  • J : Y  [0, +∞] is a rate function on Y,
  • J is a good rate function on Y if I is a good rate function on X, and
  • (νε)ε>0 satisfies the large deviation principle on Y with rate function J.

References

  • Dembo, Amir; Zeitouni, Ofer (1998). Large deviations techniques and applications. Applications of Mathematics (New York) 38 (Second ed.). New York: Springer-Verlag. pp. xvi+396. ISBN 0-387-98406-2. MR 1619036. (See chapter 4.2.1)
  • den Hollander, Frank (2000). Large deviations. Fields Institute Monographs 14. Providence, RI: American Mathematical Society. pp. x+143. ISBN 0-8218-1989-5. MR 1739680.
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