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School of Mathematical Sciences

Quantum Monte Carlo methods for simulations of complex geometric clusters

Supervisor: Professor Thomas Prellberg

Project description:

Efficient simulation of complex geometrical clusters such as tree-like branched polymers and clusters remains a central challenge for computational physics. Building on work of a current research student, who is using  quantum computing for the sampling of polymer ensembles using quadratic unconstrained binary optimisation (QUBO), this project will develop algorithms for quantum annealers such as the D-Wave machine and test these on a paradigmatic model of branched polymers, namely lattice trees and general lattice animals. Development of classical (non-quantum) algorithms for these structures is the topic of another current research student.

The existing QUBO algorithm only considers loops of linear polymers. While work on an extension to interacting polymers is underway, the extension to more complex geometries is a non-trivial extension in a different direction.

 

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