Adaptive dating and fast proposals: Revisiting the phylogenetic relaxed clock model

Relaxed clock models enable estimation of molecular substitution rates across lineages and are widely used in phylogenetics for dating evolutionary divergence times. Under the (uncorrelated) relaxed clock model, tree branches are associated with molecular substitution rates which are independently and identically distributed. In this article we delved into the internal complexities of the relaxed clock model in order to develop efficient MCMC operators for Bayesian phylogenetic inference. We compared three substitution rate parameterisations, introduced an adaptive operator which learns the weights of other operators during MCMC, and we explored how relaxed clock model estimation can benefit from two cutting-edge proposal kernels: the AVMVN and Bactrian kernels. This work has produced an operator scheme that is up to 65 times more efficient at exploring continuous relaxed clock parameters compared with previous setups, depending on the dataset. Finally, we explored variants of the standard narrow exchange operator which are specifically designed for the relaxed clock model. In the most extreme case, this new operator traversed tree space 40% more efficiently than narrow exchange. The methodologies introduced are adaptive and highly effective on short as well as long alignments. The results are available via the open source optimised relaxed clock (ORC) package for BEAST 2 under a GNU licence (https://github.com/jordandouglas/ORC).

Convergence of time-splitting approximations for degenerate convection-diffusion equations with a random source

In this paper we propose a time-splitting method for degenerate convection-diffusion equations perturbed stochastically by white noise. This work generalizes previous results on splitting operator techniques for stochastic hyperbolic conservation laws for the degenerate parabolic case. The convergence in $\begin{array}{} \displaystyle L^p_{loc} \end{array}$ of the time-splitting operator scheme to the unique weak entropy solution is proven. Moreover, we analyze the performance of the splitting approximation by computing its convergence rate and showing numerical simulations for some benchmark examples, including a fluid flow application in porous media.

Preconditioned Symmetric Linear BCG Method for Solving FEM Electromagnetism Problems

A new preconditioning technique for solving large linear systems arising from edge-based finite element method (FEM) analysis of three-dimensional (3-D) electromagnetic problems is presented. This method is achieved by applying a shifted-Laplace operator scheme and sparse approximate inverse to symmetric linear BCG (LBCG). The main purpose is to generate a more robust and efficient preconditioner. Numerical results on several electromagnetic problems show that, by comparing with other conventional preconditioning techniques, this technique is more efficient and robust, and can greatly reduce the simulation time.