Pooya Hatami

Variations on the Sensitivity Conjecture

We present a selection of known as well as new variants of the Sensitivity Conjecture and point out some weaker versions that are also open.

Every locally characterized affine-invariant property is testable

Set F = Fp for any fixed prime p ≥ 2. An affine-invariant property is a property of functions over Fn that is closed under taking affine transformations of the domain. We prove that all affine-invariant properties having local characterizations are testable. In fact, we show a proximity-oblivious test for any such property cP, meaning that given an input function f, we make a constant number of queries to f, always accept if f satisfies cP, and otherwise reject with probability larger than a positive number that depends only on the distance between f and cP. More generally, we show that any affine-invariant property that is closed under taking restrictions to subspaces and has bounded complexity is testable. We also prove that any property that can be described as the property of decomposing into a known structure of low-degree polynomials is locally characterized and is, hence, testable. For example, whether a function is a product of two degree-

A characterization of functions with vanishing averages over products of disjoint sets

d

Improved pseudorandomness for unordered branching programs through local monotonicity

polynomials, whether a function splits into a product of d linear polynomials, and whether a function has low rank are all examples of degree-structural properties and are therefore locally characterized. Our results depend on a new Gowers inverse theorem by Tao and Ziegler for low characteristic fields that decomposes any polynomial with large Gowers norm into a function of a small number of low-degree non-classical polynomials. We establish a new equidistribution result for high rank non-classical polynomials that drives the proofs of both the testability results and the local characterization of degree-structural properties.

Pseudorandom Generators for Low Sensitivity Functions

Given α 1 , � , α m � ( 0 , 1 ) , we characterize all integrable functions f : 0 , 1 m � C satisfying � A 1 � � � A m f = 0 for any collection of disjoint measurable sets A 1 , � , A m � 0 , 1 of respective measures α 1 , � , α m . We use this characterization to settle some of the conjectures in Janson and Sos (2015) about the relation between subgraph counts and quasi-randomness.

Pseudorandom generators from polarizing random walks

We present an explicit pseudorandom generator with seed length Õ((logn)w+1) for read-once, oblivious, width w branching programs that can read their input bits in any order. This improves upon the work of Impagliazzo, Meka and Zuckerman (FOCS’12) where they required seed length n1/2+o(1). A central ingredient in our work is the following bound that we prove on the Fourier spectrum of branching programs. For any width w read-once, oblivious branching program B:{0,1}n→ {0,1}, any k ∈ {1,…,n}, [complex formula not displayed] This settles a conjecture posed by Reingold, Steinke and Vadhan (RANDOM’13). Our analysis crucially uses a notion of local monotonicity on the edge labeling of the branching program. We carry critical parts of our proof under the assumption of local monotonicity and show how to deduce our results for unrestricted branching programs.

On the Structure of Quintic Polynomials

A Boolean function is said to have maximal sensitivity s if s is the largest number of Hamming neighbors of a point which differ from it in function value. We initiate the study of pseudorandom generators fooling low-sensitivity functions as an intermediate step towards settling the sensitivity conjecture. We construct a pseudorandom generator with seed-length 2^{O(s^{1/2})} log(n) that fools Boolean functions on n variables with maximal sensitivity at most s. Prior to our work, the (implicitly) best pseudorandom generators for this class of functions required seed-length 2^{O(s)} log(n).

Algorithmic regularity for polynomials and applications

We propose a new framework for constructing pseudorandom generators for n-variate Boolean functions. It is based on two new notions. First, we introduce fractional pseudorandom generators, which are pseudorandom distributions taking values in [-1, 1]n. Next, we use a fractional pseudorandom generator as steps of a random walk in [-1, 1]n that converges to {-1, 1}n. We prove that this random walk converges fast (in time logarithmic in n) due to polarization. As an application, we construct pseudorandom generators for Boolean functions with bounded Fourier tails. We use this to obtain a pseudorandom generator for functions with sensitivity s, whose seed length is polynomial in s. Other examples include functions computed by branching programs of various sorts or by bounded depth circuits.

General systems of linear forms: Equidistribution and true complexity

We study the structure of bounded degree polynomials over finite fields. Haramaty and Shpilka [STOC 2010] showed that biased degree three or four polynomials admit a strong structural property. We confirm that this is the case for degree five polynomials also. Let

An Arithmetic Analogue of Fox's Triangle Removal Argument

\mathbb{F}=\mathbb{F}_q