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ERC Consolidator Grant 772466
Noise-Sensitivity Everywhere (NOISE)
Gábor Pete

Alfréd Rényi Institute of Mathematics
February 2018 - January 2024

Press release of highlighted projects by the European Research Council, including mine.

Postdoc position open now.

Website at the Rényi Institute.

Mathematical summary:

Noise-sensitivity of a Boolean function with iid random input bits means that resampling a tiny proportion of the input makes the output unpredictable. This notion arises naturally in computer science, but perhaps the most striking example comes from statistical physics, in large part due to the PI: the macroscopic geometry of planar percolation is very sensitive to noise. This can be recast in terms of Fourier analysis on the hypercube: a function is noise sensitive iff most of its Fourier weight is on “high energy” eigenfunctions of the random walk operator.

This project proposes to use noise sensitivity ideas in three main directions:

We will also apply ideas of statistical physics to group theory in other novel ways, such as understanding the relation between the first ell-2-Betti number of a group and its measurable cost, or using random walks in random environment to prove amenability of certain groups.

Project members (present and past):

Ádám Timár (Senior researcher 2019- Rényi)
Percolation processes and unimodular random graphs.

Péter Mester (Part-time senior researcher 2020- Rényi)
Group-invariant percolation processes.

Miklós Abért (Senior researcher, part-time advising the project, 2023 Rényi)
Geometric group theory, measurable group actions, unimodularity beyond graphs.

Bálint Tóth (Senior researcher, part-time advising the project, 2023 Rényi)
Random walks in random environments. The interchange process and the quantum Heisenberg model.

Balázs Ráth (Senior researcher, part-time advising the project, 2023 Rényi)
Percolation processes, self-organized criticality, endogeny, random interlacements.

Adam Arras (PostDoc 2023 Rényi)
Spectral theory of random graphs.

Zsolt Bartha (PostDoc 2023- Rényi)
Bootstrap percolation, constrained satisfaction problems on random graphs.

Jacob Richey (PostDoc 2023- Rényi)
All sorts of discrete probability: interacting particle systems, subshifts of finite type, random graphs.

András Tóbiás (PostDoc 2023 Rényi)
Geometric percolation and population genetics processes.

László Márton Tóth (PostDoc 2023 Rényi)
Measurable group actions, factor of iid processes.

Caio Alves (PostDoc 2020-2022 Rényi, currently at Oak Ridge National Lab)
Percolation theory, loop soup, random graphs.

Olle Elias (PostDoc 2020-2022 Rényi, currently at Uni Köln)
Percolation theory, interlacements.

Ábel Farkas (PostDoc 2018-2020 Rényi, currently doing improv theatre)
Fractal percolation, geometric measure theory.

Pál Galicza (PhD student 2014-2020 CEU, PostDoc 2020-2023 Rényi)
Noise sensitivity of Boolean functions and percolation. Sparse reconstruction in spin systems.

Ágnes Cs. Kúsz (PhD student 2020- BME)
Random trees.

Sándor Rokob (PhD student 2018- BME, co-advised with Balázs Ráth)
Random interlacements and other Poissonian percolation models, Uniform Spanning Forests.

Márton Szőke (PhD student 2021- BME, advised by Balázs Ráth)
Stochastic processes on random graphs. Endogeny questions.

Richárd Patkó (PhD student 2017-2018 BME, currently at Bosch)
Representation theory and random walks on groups

Mahefa Ravelonanosy (MSc student 2020 CEU, Research intern 2020 Rényi, currently PhD student at TU Eindhoven)
Concentration of distances in graph sequences

Gergő Lukáts (MSc student 2019 BME, currently PhD student at Univ Oslo)
Mixing time of critical Ising Glauber dynamics

Some papers and talks:

An award-winning visual introduction to percolation theory by the Spectral Collective (Caio Alves, Aranka Hrušková, Vilas Winstein), Summer of Math Exposition, 2022.

(Last updated: February 2023.)