diffusion entropy and the geometry of small sets

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diffusion, entropy, and the geometry of small sets James R. Lee University of Washington

diffusion, entropy, and the geometry of small sets James R. Lee University of Washington Joint work with Ronen Eldan

a prelude

a prelude

noise and smoothness

noise and smoothness

noise and smoothness Many applications: PCPs & hardness of approximation, statistical physics, threshold phenomena,

noise and smoothness Many applications: PCPs & hardness of approximation, statistical physics, threshold phenomena, social choice, circuit complexity,

noise and smoothness Hypercontractive inequality [Bonami, Gross, Nelson]:

noise and smoothness Hypercontractive inequality [Bonami, Gross, Nelson]:

noise and smoothness Hypercontractive inequality [Bonami, Gross, Nelson]:

noise and smoothness Hypercontractive inequality [Bonami, Gross, Nelson]:

noise and smoothness Hypercontractive inequality [Bonami, Gross, Nelson]:

noise and smoothness Hypercontractive inequality [Bonami, Gross, Nelson]:

the convolution conjecture

the convolution conjecture

anti-concentration of temperature Convolution conjecture [Talagrand 1989]: Equivalent to the conjecture that “heat” cannot

anti-concentration of temperature Convolution conjecture [Talagrand 1989]: Equivalent to the conjecture that “heat” cannot concentrate near a single (high) “temperature”

the Gaussian case

the Gaussian case

the Gaussian case

the Gaussian case

the Gaussian case Ornstein-Uhlenbeck semi-group:

the Gaussian case Ornstein-Uhlenbeck semi-group:

the Gaussian case Theorem [Eldan-L 2014]:

the Gaussian case Theorem [Eldan-L 2014]:

the Gaussian case Theorem [Eldan-L 2014]:

the Gaussian case Theorem [Eldan-L 2014]:

the Gaussian case Theorem [Eldan-L 2014]:

the Gaussian case Theorem [Eldan-L 2014]:

some difficulties Good: noise insensitive Bad: boundary far from origin half space dust

some difficulties Good: noise insensitive Bad: boundary far from origin half space dust

proof ideas arguing about small-probability events is tough, but remember the prelude… random measure

proof ideas arguing about small-probability events is tough, but remember the prelude… random measure

conditioning

conditioning

Explicit form: Theorem [Lehec 2010]:

Explicit form: Theorem [Lehec 2010]:

an optimal coupling is a martingale

an optimal coupling is a martingale

proof sketch

proof sketch

proof sketch

proof sketch

Girsanov’s theorem Then under the change of measure:

Girsanov’s theorem Then under the change of measure:

the masochistic part

the masochistic part

the masochistic part

the masochistic part

conclusion

conclusion

Peres-Tetali conjecture

Peres-Tetali conjecture