Oliver Dyer
PhD student, theory groupSupervisor: Robin C. Ball email: o dot dyer at warwick dot ac dot uk 

PhD Research
Motivations and Overview
Brownian dynamics algorithms simulate mesoscopic softmatter systems by accounting for the uninteresting solvent molecules with hydrodynamic equations. This greatly reduces the degrees of freedom simulations. However, calculating the evolution of the system can still be computationally expensive when long range hydrodynamic interactions (HIs) are included, and large systems are still out of reach.
The focus of my PhD is to develop an algorithm that replaces the explicit calculation of HIs with a Monte Carlo simulation which obeys hydrodynamics implicitly. This approach leads to a significantly simpler and faster algorithm with a cost that scales to large systems as .
Summary of Wavelet Monte Carlo Dynamics (WMCD)
Basic theory
In WMCD the HI tensor that correlates particle motions, the so called Oseen tensor, is written as the integral over wavelets
( = wavelet, = wavelet centre, = radius, = orientation.) Monte Carlo integration translates to a simulation using these wavelet displacements as Monte Carlo moves (see right for an example with particles inside the wavelet rotated around its axis) that evolves the system while ensuring the particle motions are correlated by the Oseen tensor. 
Periodic boundary conditions
Periodic systems must account for HIs of all images because of the long range nature of the Oseen tensor. In place of the expensive Ewald summation used in Brownian dynamics algorithms, we simply need to add rare plane wave moves at negligible extra cost (see cost plots below). 
Computational cost
The big success of WMCD is how its cost (time to run a simulation) scales with system size, with a significant improvement on established algorithms in fractal (dilute) systems with linear scaling, and a very competitive in periodic systems.
Fractal systems (e.g. isolated polymer)  Homogeneous systems 
Note: ^{}~time step; 'w' refers to a pure wavelet simulation, while 'w+F' includes plane wave moves.
LB = Lattice Boltzmann and BD = Brownian dynamics.
Smart WMCD
WMCD can now use a 'smart Monte Carlo' algorithm, biasing moves in the direction of forces present. The effects of this change include:
 lower rate of move rejection;
 more accurate data at a given time step, or
 larger time step for a given accuracy, decreasing computational cost;
 easy implementation of nonconservative forces.
Applications of WMCD
Time dependence of polymer diffusivity
The diffusion of isolated polymer chains is a complex problem thanks to longrange hydrodynamic interactions coupling all internal forces and thermal fluctuations to the motion of all particles along the chain.
We have undertaken the most comprehensive investigation into this problem to date, with data able to observe universal short and longtime behavior in the centre of mass velocity autocorrelation (= time derivative of diffusivity). Here is shown the data for Gaussian chains:
Shorttime  Longtime 
Rheological systems
WMCD is applicatble beyond equilibrium systems. For example externally imposed flows can be introduced via affine deformations of the simulation coordinates (follow this link for an example: Shear flow)
In collaboration with J. Ravi Prakash, WMCD is being used to look at the rheological properties of semidilute DNA (i.e. long polymer) solutions.
Simulations of microswimmers
Multipolar flow fields are commonly used to approximate the HIs between microswimmers and their surroundings. With the smart Monte Carlo adaptation these flow fields can be simulated in WMCD, extending the scope of the algorithm to simulations in this exciting field.
The scope of WMCD
Beyond the examples above, it is worth highlighting the full scope of systems WMCD is able to simulate in its current state.
Within the realm of systems of Brownian particles in low Reynolds number fluids on diffusive timescales:
 periodic boundary conditions or `unbounded';
 range of concentrations from ultradilute to the dense end of semidilute;
 equilibrium or active systems, including
 shear and extensional solvent flows and
 microswimmers (with simple multipole flow fields or approximations to the squirmer model);
 Brownian particles may or may not be connected into macromolecules, with soft or hard bond and excluded volume potentials between them;
 in the Oseen tesnor is regularised (close to RotnePrager), increasing the accuracy of the beahvour of nearby particles
 Brownian particles may be mono or polydisperse.
The most notable shortcoming is with hard walls, for which WMCD is currently unable to implement the correct mobility tensor. It remains possible for future work to find a solution to this.
Posters and presentations
Poster Summer 2017 (Awarded the Best Poster prize at the Statistical Physics (Sigma Phi) conference 2017)
Talk slides from Open Statistical Physics 2018
Publications
 Wavelet Monte Carlo dynamics: A new algorithm for simulating the hydrodynamics of interacting Brownian particles, Oliver T. Dyer and Robin C. Ball, J. Chem. Phys. 146, 124111 (2017)
 [Also on arXiv at: https://arxiv.org/abs/1611.09160, and the Warwick Research Archive Portal: http://wrap.warwick.ac.uk/86737/]
 [Also on arXiv at: https://arxiv.org/abs/1611.09160, and the Warwick Research Archive Portal: http://wrap.warwick.ac.uk/86737/]