activity
20242026
collaborators

7 papers

cs.DS2026

Rank-1-perturbed trickledown theorems: Mixing time of Glauber dynamics for the Sherrington-Kirkpatrick model up to

Mathews Boban, Anqi Li, Shayan Oveis Gharan

We introduce a new family of trickledown theorems, a.k.a., local to global technique to bound the spectral gap of the Glauber dynamics for multi-state spin systems. In this techniq…

cs.DS2026

On Thin Perfect Matchings up to Polylogarithmic Factors

Alireza Haqi, Shayan Oveis Gharan

We resolve the thin matching problem proposed by Anari, Charikar and Ramakrishnan [ACR23] up to polylogarithmic factors. Given a fractional perfect matching , we say a perfect m…

cs.DS2026

High-Dimensional Expanders, the Sparsest Cut Problem, and Steurer's Conjecture

Farzam Ebrahimnejad, Shayan Oveis Gharan

In 2010, Steurer conjectured that any family of unit-norm vectors with polynomially small average correlation $\mathbb{E}_{i,j}|\langle v_i,v_j\rangle|\leq n^{-…

math.CO2025

Trickle-down Theorems via C-Lorentzian Polynomials II: Pairwise Spectral Influence and Improved Dobrushin's Condition

Jonathan Leake, Shayan Oveis Gharan

Let be a probability distribution on a multi-state spin system on a set of sites; equivalently, a -partite simplicial complex with distribution on maximal faces. For…

math.CO2025

Optimal Trickle-Down Theorems for Path Complexes via C-Lorentzian Polynomials with Applications to Sampling and Log-Concave Sequences

Jonathan Leake, Kasper Lindberg, Shayan Oveis Gharan

Let be a -partite -dimensional simplicial complex with parts and let be a distribution on the facets of . Informally, we say is a path comp…

math.CO2025

Unweighted One-Sided Code Sparsifiers and Thin Subgraphs

Shayan Oveis Gharan, Arvin Sahami

For a linear code and , call a set an (unweighted) one-sided -sparsifier of if for all $c \in…

cs.DS2024

On approximability of the Permanent of PSD matrices

Farzam Ebrahimnejad, Ansh Nagda, Shayan Oveis Gharan

We study the complexity of approximating the permanent of a positive semidefinite matrix . 1. We design a new approximation algorithm for $\mathrm{per}…