5 citations · 12 across the 22 of their papers we have counts for
6 papers · 1 filter
Sampling from the Sherrington-Kirkpatrick Model up to Criticality
Hang Du, Brice Huang, Sidhanth Mohanty +1
We prove that the simulated annealing algorithm efficiently samples from the Sherrington-Kirkpatrick model at inverse temperature to an arbitrary inverse polynomial accuracy…
Eigenvalue Bounds for Random Matrices via Zerofreeness
Sidhanth Mohanty, Amit Rajaraman
We introduce a new technique to prove bounds for the spectral radius of a random matrix, based on using Jensen's formula to establish the zerofreeness of the associated characteris…
Weak Poincaré Inequalities, Simulated Annealing, and Sampling from Spherical Spin Glasses
Brice Huang, Sidhanth Mohanty, Amit Rajaraman +1
There has been a recent surge of powerful tools to show rapid mixing of Markov chains, via functional inequalities such as Poincaré inequalities. In many situations, Markov chains…
Fast Mixing in Sparse Random Ising Models
Kuikui Liu, Sidhanth Mohanty, Amit Rajaraman +1
Motivated by the community detection problem in Bayesian inference, as well as the recent explosion of interest in spin glasses from statistical physics, we study the classical Gla…
Testing thresholds for high-dimensional sparse random geometric graphs
Siqi Liu, Sidhanth Mohanty, Tselil Schramm +1
In the random geometric graph model , we identify each of our vertices with an independently and uniformly sampled vector from the -dimensional unit sph…
Many nodal domains in random regular graphs
Shirshendu Ganguly, Theo McKenzie, Sidhanth Mohanty +1
Let be a random -regular graph. We prove that for every constant , with high probability every eigenvector of the adjacency matrix of with eigenvalue less than $-2…