We study the problem of algorithmically optimizing the Hamiltonian of a spherical or Ising
mean field spin glass. The maximum asymptotic value OPT of this random function is …

For general antiferromagnetic 2-spin systems, including the hardcore model on weighted
independent sets and the antiferromagnetic Ising model, there is an for the partition function …

We prove an optimal lower bound on a spectral gap of the Glauber dynamics for
antiferromagnetic two-spin systems with vertices in the tree uniqueness regime. This …

We develop a framework for sampling from discrete distributions µ on the hypercube {±1} n
by sampling from continuous distributions supported on ℝ n obtained by convolution with …

We study efficient optimization of the Hamiltonians of multi-species spherical spin glasses.
Our results characterize the maximum value attained by algorithms that are suitably …

We study the Langevin dynamics for spherical pp‐spin models, focusing on the short time
regime described by the Cugliandolo–Kurchan equations. Confirming a prediction of …

We present a new framework to derandomise certain Markov chain Monte Carlo (MCMC)
algorithms. As in MCMC, we first reduce counting problems to sampling from a sequence of …

We present a simple combinatorial framework for establishing approximate tensorization of
variance and entropy in the setting of spin systems (aka undirected graphical models) based …

For an integer b≥ 1, ab-matching (resp. b-edge cover) of a graph G=(V, E) is a subset S⊆ E
of edges such that every vertex is incident with at most (resp. at least) b edges from S. We …

Spectral independence is a recently developed framework for obtaining sharp bounds on
the convergence time of the classical Glauber dynamics. This new framework has yielded …