51 citations · 179 across the 11 of their papers we have counts for
11 papers
Confusion-driven machine learning of structural phases of a flexible, magnetic Stockmayer polymer
Dilina Perera, Samuel McAllister, Joan Josep Cerdà +1
We use a semi-supervised, neural-network based machine learning technique, the confusion method, to investigate structural transitions in magnetic polymers, which we model as chain…
Supervised and Unsupervised Machine Learning of Structural Phases of Polymers Adsorbed to Nanowires
Quinn Parker, Dilina Perera, Ying Wai Li +1
We identify configurational phases and structural transitions in a polymer nanotube composite by means of machine learning. We employ various unsupervised dimensionality reduction…
Chook -- A comprehensive suite for generating binary optimization problems with planted solutions
Dilina Perera, Inimfon Akpabio, Firas Hamze +4
We present Chook, an open-source Python-based tool to generate discrete optimization problems of tunable complexity with a priori known solutions. Chook provides a cross-platform u…
Computational hardness of spin-glass problems with tile-planted solutions
Dilina Perera, Firas Hamze, Jack Raymond +2
We investigate the computational hardness of spin-glass instances on a square lattice, generated via a recently introduced tunable and scalable approach for planting solutions. The…
Combined Molecular and Spin Dynamics Simulation of BCC Iron with Vacancy Defects
Mark Mudrick, Markus Eisenbach, Dilina Perera +1
Utilizing an atomistic computational model which handles both translational and spin degrees of freedom, combined molecular and spin dynamics simulations have been performed to inv…
From Near to Eternity: Spin-glass planting, tiling puzzles, and constraint satisfaction problems
Firas Hamze, Darryl C. Jacob, Andrew J. Ochoa +3
We present a methodology for generating Ising Hamiltonians of tunable complexity and with a priori known ground states based on a decomposition of the model graph into edge-disjoin…