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Ashwin Sah

Publications and source records attributed to Ashwin Sah.

At least 55 records · Page 3Linked to original sources

Non-classical polynomials and the inverse theorem

In this note we characterize when non-classical polynomials are necessary in the inverse theorem for the Gowers $U^k$-norm. We give a brief deduction of the fact that a bounded function on $\mathbb F_p^n$ with large $U^k$-norm must correlate with a classical polynomial when $k\leq p+1$. To the best of our knowledge, this result is new for $k=p+1$ (when $p>2$). We then prove that non-classical polynomials are necessary in the inverse theorem for the Gowers $U^k$-norm over $\mathbb F_p^n$ for all $k\geq p+2$, completely characterizing when classical polynomials suffice.

math.CO↗

Improving the $\frac{1}{3}-\frac{2}{3}$ Conjecture for Width Two Posets

Extending results of Linial (1984) and Aigner (1985), we prove a uniform lower bound on the balance constant of a poset $P$ of width $2$. This constant is defined as $δ(P) = \max_{(x, y)\in P^2}\min\{\mathbb{P}(x\prec y), \mathbb{P}(y\prec x)\}$, where $\mathbb{P}(x\prec y)$ is the probability $x$ is less than $y$ in a uniformly random linear extension of $P$. In particular, we show that if $P$ is a width $2$ poset that cannot be formed from the singleton poset and the three element poset with one relation using the operation of direct sum, then \[δ(P)\ge\frac{-3 + 5\sqrt{17}}{52}\approx 0.33876\ldots.\] This partially answers a question of Brightwell (1999); a full resolution would require a proof of the $\frac{1}{3}-\frac{2}{3}$ Conjecture that if $P$ is not totally ordered then $δ(P)\ge\frac{1}{3}$. Furthermore, we construct a sequence of posets $T_n$ of width $2$ with $δ(T_n)\rightarrowβ\approx 0.348843\ldots$, giving an improvement over a construction of Chen (2017) and over the finite posets found by Peczarski (2017). Numerical work on small posets by Peczarski suggests the constant $β$ may be optimal.

math.CO↗

Anticoncentration versus the number of subset sums

Let $\vec{w} = (w_1,\dots, w_n) \in \mathbb{R}^{n}$. We show that for any $n^{-2}\leε\le 1$, if \[\#\{\vecξ \in \{0,1\}^{n}: \langle \vecξ, \vec{w} \rangle = τ\} \ge 2^{-εn}\cdot 2^{n}\] for some $τ\in \mathbb{R}$, then \[\#\{\langle \vecξ, \vec{w} \rangle : \vecξ \in \{0,1\}^{n}\} \le 2^{O(\sqrtεn)}.\] This exponentially improves the $ε$ dependence in a recent result of Nederlof, Pawlewicz, Swennenhuis, and Węgrzycki and leads to a similar improvement in the parameterized (by the number of bins) runtime of bin packing.

math.CO↗

Random symmetric matrices: rank distribution and irreducibility of the characteristic polynomial

Conditional on the extended Riemann hypothesis, we show that with high probability, the characteristic polynomial of a random symmetric $\{\pm 1\}$-matrix is irreducible. This addresses a question raised by Eberhard in recent work. The main innovation in our work is establishing sharp estimates regarding the rank distribution of symmetric random $\{\pm 1\}$-matrices over $\mathbb{F}_p$ for primes $2 < p \leq \exp(O(n^{1/4}))$. Previously, such estimates were available only for $p = o(n^{1/8})$. At the heart of our proof is a way to combine multiple inverse Littlewood--Offord-type results to control the contribution to singularity-type events of vectors in $\mathbb{F}_p^{n}$ with anticoncentration at least $1/p + Ω(1/p^2)$. Previously, inverse Littlewood--Offord-type results only allowed control over vectors with anticoncentration at least $C/p$ for some large constant $C > 1$.

math.PR↗

Friendly bisections of random graphs

Resolving a conjecture of Füredi from 1988, we prove that with high probability, the random graph $G(n,1/2)$ admits a friendly bisection of its vertex set, i.e., a partition of its vertex set into two parts whose sizes differ by at most one in which $n-o(n)$ vertices have at least as many neighbours in their own part as across. The engine of our proof is a new method to study stochastic processes driven by degree information in random graphs; this involves combining enumeration techniques with an abstract second moment argument.

math.CO↗

Majority Dynamics: The Power of One

Consider $n=\ell+m$ individuals, where $\ell\le m$, with $\ell$ individuals holding an opinion $A$ and $m$ holding an opinion $B$. Suppose that the individuals communicate via an undirected network $G$, and in each time step, each individual updates her opinion according to a majority rule (that is, according to the opinion of the majority of the individuals she can communicate with in the network). This simple and well studied process is known as "majority dynamics in social networks". Here we consider the case where $G$ is a random network, sampled from the binomial model $\mathbb{G}(n,p)$, where $(\log n)^{-1/16}\le p\le 1-(\log n)^{-1/16}$. We show that for $n=\ell+m$ with $Δ=m-\ell\le(\log n)^{1/4}$, the above process terminates whp after three steps when a consensus is reached. Furthermore, we calculate the (asymptotically) correct probability for opinion $B$ to "win" and show it is \[Φ\bigg(\frac{pΔ\sqrt{2}}{\sqrt{πp(1-p)}}\bigg) + O(n^{-c}),\] where $Φ$ is the Gaussian CDF. This answers two conjectures of Tran and Vu and also a question raised by Berkowitz and Devlin. The proof technique involves iterated degree revelation and analysis of the resulting degree-constrained random graph models via graph enumeration techniques of McKay and Wormald as well as Canfield, Greenhill, and McKay.

math.CO↗

Sharp invertibility of random Bernoulli matrices

Let $p \in (0,1/2)$ be fixed, and let $B_n(p)$ be an $n\times n$ random matrix with i.i.d. Bernoulli random variables with mean $p$. We show that for all $t \ge 0$, \[\mathbb{P}[s_n(B_n(p)) \le tn^{-1/2}] \le C_p t + 2n(1-p)^{n} + C_p (1-p-ε_p)^{n},\] where $s_n(B_n(p))$ denotes the least singular value of $B_n(p)$ and $C_p, ε_p > 0$ are constants depending only on $p$. In particular, \[\mathbb{P}[B_{n}(p) \text{ is singular}] = 2n(1-p)^{n} + C_{p}(1-p-ε_p)^{n},\] which confirms a conjecture of Litvak and Tikhomirov. We also confirm a conjecture of Nguyen by showing that if $Q_{n}$ is an $n\times n$ random matrix with independent rows that are uniformly distributed on the central slice of $\{0,1\}^{n}$, then \[\mathbb{P}[Q_{n} \text{ is singular}] = (1/2 + o_n(1))^{n}.\] This provides, for the first time, a sharp determination of the logarithm of the probability of singularity in any natural model of random discrete matrices with dependent entries.

math.PR↗

Singularity of discrete random matrices

Let $ξ$ be a non-constant real-valued random variable with finite support, and let $M_{n}(ξ)$ denote an $n\times n$ random matrix with entries that are independent copies of $ξ$. For $ξ$ which is not uniform on its support, we show that \begin{align*} \mathbb{P}[M_{n}(ξ)\text{ is singular}] &= \mathbb{P}[\text{zero row or column}] + (1+o_n(1))\mathbb{P}[\text{two equal (up to sign) rows or columns}], \end{align*} thereby confirming a folklore conjecture. As special cases, we obtain: (1) For $ξ= \text{Bernoulli}(p)$ with fixed $p \in (0,1/2)$, \[\mathbb{P}[M_{n}(ξ)\text{ is singular}] = 2n(1-p)^{n} + (1+o_n(1))n(n-1)(p^2 + (1-p)^2)^{n},\] which determines the singularity probability to two asymptotic terms. Previously, no result of such precision was available in the study of the singularity of random matrices. (2) For $ξ= \text{Bernoulli}(p)$ with fixed $p \in (1/2,1)$, \[\mathbb{P}[M_{n}(ξ)\text{ is singular}] = (1+o_n(1))n(n-1)(p^2 + (1-p)^2)^{n}.\] Previously, only the much weaker upper bound of $(\sqrt{p} + o_n(1))^{n}$ was known due to the work of Bourgain-Vu-Wood. For $ξ$ which is uniform on its support: (1) We show that \begin{align*} \mathbb{P}[M_{n}(ξ)\text{ is singular}] &= (1+o_n(1))^{n}\mathbb{P}[\text{two rows or columns are equal}]. \end{align*} (2) Perhaps more importantly, we provide a sharp analysis of the contribution of the `compressible' part of the unit sphere to the lower tail of the smallest singular value of $M_{n}(ξ)$.

math.PR↗

A Gaussian fixed point random walk

In this note, we design a discrete random walk on the real line which takes steps $0, \pm 1$ (and one with steps in $\{\pm 1, 2\}$) where at least $96\%$ of the signs are $\pm 1$ in expectation, and which has $\mathcal{N}(0,1)$ as a stationary distribution. As an immediate corollary, we obtain an online version of Banaszczyk's discrepancy result for partial colorings and $\pm 1, 2$ signings. Additionally, we recover linear time algorithms for logarithmic bounds for the Komlós conjecture in an oblivious online setting.

cs.DS↗

Rank deficiency of random matrices

Let $M_n$ be a random $n\times n$ matrix with i.i.d. $\text{Bernoulli}(1/2)$ entries. We show that for fixed $k\ge 1$, \[\lim_{n\to \infty}\frac{1}{n}\log_2\mathbb{P}[\text{corank }M_n\ge k] = -k.\]

math.PR↗

Popular differences for matrix patterns

The following combinatorial conjecture arises naturally from recent ergodic-theoretic work of Ackelsberg, Bergelson, and Best. Let $M_1$, $M_2$ be $k\times k$ integer matrices, $G$ be a finite abelian group of order $N$, and $A\subseteq G^k$ with $|A|\geαN^k$. If $M_1$, $M_2$, $M_1-M_2$, and $M_1+M_2$ are automorphisms of $G^k$, is it true that there exists a popular difference $d \in G^k\setminus\{0\}$ such that \[\#\{x \in G^k: x, x+M_1d, x+M_2d, x+(M_1+M_2)d \in A\} \ge (α^4-o(1))N^k.\] We show that this conjecture is false in general, but holds for $G = \mathbb{F}_p^n$ with $p$ an odd prime given the additional spectral condition that no pair of eigenvalues of $M_1M_2^{-1}$ (over $\overline{\mathbb{F}}_p$) are negatives of each other. In particular, the "rotated squares" pattern does not satisfy this eigenvalue condition, and we give a construction of a set of positive density in $(\mathbb{F}_5^n)^2$ for which that pattern has no nonzero popular difference. This is in surprising contrast to three-point patterns, which we handle over all compact abelian groups and which do not require an additional spectral condition.

math.CO↗

The cylindrical width of transitive sets

We show that for every $1 \le k \le d/(\log d)^C$, every finite transitive set of unit vectors in $\mathbb{R}^d$ lies within distance $O(1/\sqrt{\log (d/k)})$ of some codimension $k$ subspace, and this distance bound is best possible. This extends a result of Ben Green, who proved it for $k=1$.

math.MG↗

Optimal and algorithmic norm regularization of random matrices

Let $A$ be an $n\times n$ random matrix whose entries are i.i.d. with mean $0$ and variance $1$. We present a deterministic polynomial time algorithm which, with probability at least $1-2\exp(-Ω(εn))$ in the choice of $A$, finds an $εn \times εn$ sub-matrix such that zeroing it out results in $\widetilde{A}$ with \[\|\widetilde{A}\| = O\left(\sqrt{n/ε}\right).\] Our result is optimal up to a constant factor and improves previous results of Rebrova and Vershynin, and Rebrova. We also prove an analogous result for $A$ a symmetric $n\times n$ random matrix whose upper-diagonal entries are i.i.d. with mean $0$ and variance $1$.

math.PR↗

On the smallest singular value of symmetric random matrices

We show that for an $n\times n$ random symmetric matrix $A_n$, whose entries on and above the diagonal are independent copies of a sub-Gaussian random variable $ξ$ with mean $0$ and variance $1$, \[\mathbb{P}[s_n(A_n) \le ε/\sqrt{n}] \le O_ξ(ε^{1/8} + \exp(-Ω_ξ(n^{1/2}))) \quad \text{for all } ε\ge 0.\] This improves a result of Vershynin, who obtained such a bound with $n^{1/2}$ replaced by $n^{c}$ for a small constant $c$, and $1/8$ replaced by $(1/8) + η$ (with implicit constants also depending on $η> 0$). Furthermore, when $ξ$ is a Rademacher random variable, we prove that \[\mathbb{P}[s_n(A_n) \le ε/\sqrt{n}] \le O(ε^{1/8} + \exp(-Ω((\log{n})^{1/4}n^{1/2}))) \quad \text{for all } ε\ge 0.\] The special case $ε= 0$ improves a recent result of Campos, Mattos, Morris, and Morrison, which showed that $\mathbb{P}[s_n(A_n) = 0] \le O(\exp(-Ω(n^{1/2}))).$ The main innovation in our work are new notions of arithmetic structure -- the Median Regularized Least Common Denominator and the Median Threshold, which we believe should be more generally useful in contexts where one needs to combine anticoncentration information of different parts of a vector.

math.PR↗

Cayley graphs without a bounded eigenbasis

Does every $n$-vertex Cayley graph have an orthonormal eigenbasis all of whose coordinates are $O(1/\sqrt{n})$? While the answer is yes for abelian groups, we show that it is no in general. On the other hand, we show that every $n$-vertex Cayley graph (and more generally, vertex-transitive graph) has an orthonormal basis whose coordinates are all $O(\sqrt{\log n / n})$, and that this bound is nearly best possible. Our investigation is motivated by a question of Assaf Naor, who proved that random abelian Cayley graphs are small-set expanders, extending a classic result of Alon--Roichman. His proof relies on the existence of a bounded eigenbasis for abelian Cayley graphs, which we now know cannot hold for general groups. On the other hand, we navigate around this obstruction and extend Naor's result to nonabelian groups.

math.CO↗

On the smoothed analysis of the smallest singular value with discrete noise

Let $A$ be an $n\times n$ real matrix, and let $M$ be an $n\times n$ random matrix whose entries are i.i.d sub-Gaussian random variables with mean $0$ and variance $1$. We make two contributions to the study of $s_n(A+M)$, the smallest singular value of $A+M$. (1) We show that for all $ε\geq 0$, $$\mathbb{P}[s_n(A + M) \leq ε] = O(ε\sqrt{n}) + 2e^{-Ω(n)},$$ provided only that $A$ has $Ω(n)$ singular values which are $O(\sqrt{n})$. This extends a well-known result of Rudelson and Vershynin, which requires all singular values of $A$ to be $O(\sqrt{n})$. (2) We show that any bound of the form $$\sup_{\|{A}\|\leq n^{C_1}}\mathbb{P}[s_n(A+M)\leq n^{-C_3}] \leq n^{-C_2}$$ must have $C_3 = Ω(C_1 \sqrt{C_2})$. This complements a result of Tao and Vu, who proved such a bound with $C_3 = O(C_1C_2 + C_1 + 1)$, and counters their speculation of possibly taking $C_3 = O(C_1 + C_2)$.

math.PR↗

The smallest singular value of dense random regular digraphs

Let $A$ be the adjacency matrix of a uniformly random $d$-regular digraph on $n$ vertices, and suppose that $\min(d,n-d)\geqλn$. We show that for any $κ\geq 0$, \[\mathbb{P}[s_n(A)\leqκ]\leq C_λκ\sqrt{n}+2e^{-c_λn}.\] Up to the constants $C_λ, c_λ> 0$, our bound matches optimal bounds for $n\times n$ random matrices, each of whose entries is an i.i.d $\text{Ber}(d/n)$ random variable. The special case $κ= 0$ of our result confirms a conjecture of Cook regarding the probability of singularity of dense random regular digraphs.

math.PR↗

Fast and memory-optimal dimension reduction using Kac's walk

In this work, we analyze dimension reduction algorithms based on the Kac walk and discrete variants. (1) For $n$ points in $\mathbb{R}^{d}$, we design an optimal Johnson-Lindenstrauss (JL) transform based on the Kac walk which can be applied to any vector in time $O(d\log{d})$ for essentially the same restriction on $n$ as in the best-known transforms due to Ailon and Liberty [SODA, 2008], and Bamberger and Krahmer [arXiv, 2017]. Our algorithm is memory-optimal, and outperforms existing algorithms in regimes when $n$ is sufficiently large and the distortion parameter is sufficiently small. In particular, this confirms a conjecture of Ailon and Chazelle [STOC, 2006] in a stronger form. (2) The same construction gives a simple transform with optimal Restricted Isometry Property (RIP) which can be applied in time $O(d\log{d})$ for essentially the same range of sparsity as in the best-known such transform due to Ailon and Rauhut [Discrete Comput. Geom., 2014]. (3) We show that by fixing the angle in the Kac walk to be $π/4$ throughout, one obtains optimal JL and RIP transforms with almost the same running time, thereby confirming -- up to a $\log\log{d}$ factor -- a conjecture of Avron, Maymounkov, and Toledo [SIAM J. Sci. Comput., 2010]. Our moment-based analysis of this modification of the Kac walk may also be of independent interest.

cs.DS↗