Working paper

Energy-preserving splitting integrators for sampling from Gaussian distributions with Hamiltonian Monte Carlo method

The diffusive behaviour of simple random-walk proposals of many Markov Chain Monte Carlo (MCMC) algorithms results in slow exploration of the state space making inefficient the convergence to a target distribution. Hamiltonian/Hybrid Monte Carlo (HMC), by introducing fictious momentum variables,…

Alya towards Exascale: Algorithmic Scalability using PSCToolkit

In this paper, we describe some work aimed at upgrading the Alya code with up-to-date parallel linear solvers capable of achieving reliability, efficiency, and scalability in the computation of the pressure field at each time step of the numerical procedure for solving an LES formulation of the…

IMPROVING SOLVE TIME OF AGGREGATION-BASED ADAPTIVE AMG

This paper proposed improving the solve time of the bootstrap AMG proposed previously by the authors. This is achieved by incorporating the information, set of algebraically smooth vectors, generated by the bootstrap algorithm, in a single hierarchy by using sufficiently large aggregates, and these…

the hilbert transform in signal processing

Convergence of new quadrature rules for approximating the Hilbert transform are given. Numerical tests show the goodness of such approximations

Why diffusion-based preconditioning of Richards equation works: spectral analysis and computational experiments at very large scale.

We consider here a cell-centered finite difference approximation of the Richards equation in three dimensions, averaging for interface values the hydraulic conductivity, a highly nonlinear function, by arithmetic, upstream and harmonic means. The nonlinearities in the equation can lead to changes…

Altered brain criticality in Schizophrenia: New insights from MEG

Schizophrenia has a complex etiology and symptomatology that is difficult to untangle. After decades of research, important advancements towards a central biomarker are still lacking. One of the missing pieces is a better understanding of how non-linear neural dynamics are altered in this patient…