Eric Jankowski

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Swarms of self-propelled particles exhibit complex behavior that can arise from simple models, with large changes in swarm behavior resulting from small changes in model parameters. We investigate the steady-state swarms formed by self-propelled Morse particles in three dimensions using molecular dynamics simulations optimized for graphics processing units.(More)
Partition functions encode all the thermodynamics of a system, but for most systems of practical importance, they cannot be calculated exactly. In this work we present a new hierarchical method for calculating partition functions to arbitrary precision. We discuss the algorithmic details of our implementation, including elements of shape-matching and(More)
Reconfigurability of two-dimensional colloidal crystal structures assembled by anisometric particles capable of changing their shape were studied by molecular dynamics computer simulation. We show that when particles change shape on cue, the assembled structures reconfigure into different ordered structures, structures with improved order, or more densely(More)
We consider the thermodynamically driven self-assembly of spheres onto the surface of a central sphere. This assembly process forms self-limiting, or terminal, anisotropic clusters (N-clusters) with well-defined structures. We use Brownian dynamics to model the assembly of N-clusters varying in size from two to twelve outer spheres and free energy(More)
Through the design and manipulation of discrete, nanoscale systems capable of encoding massive amounts of information, the basic components of computation are open to reinvention. These components will enable tagging, memory storage, and sensing in unusual environments - elementary functions crucial for soft robotics and "wet computing". Here we show how(More)
Current trends in parallel processors call for the design of efficient massively parallel algorithms for scientific computing. Parallel algorithms for Monte Carlo simulations of thermodynamic ensembles of particles have received little attention because of the inherent serial nature of the statistical sampling. In this paper, we present a massively parallel(More)
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Self-assembly holds promise for creating new materials and devices because of its inherent parallelism, allowing many building blocks to simultaneously organize using preprogrammed interactions. An important trend in nanoparticle and colloid science is the synthesis of particles with unusual shapes and/or directional (‘‘patchy’’) interactions, whose(More)