For clathrate-hydrate polymorphic structure-type (sI versus sII), geometric recognition criteria have been developed and validated. These are applied to the study of the rich interplay and development of both sI and sII motifs in a variety of hydrate-nucleation events for methane and H2S hydrate studied by direct and enhanced-sampling molecular dynamics (MD) simulations.

Magnetoencephalopgraphy (MEG) is a non-invasive functional imaging modality for mapping cerebral electromagnetic activity from measurements of the weak magnetic field that it generates. It is well known that the MEG inverse problem, i.e. the problem of identifying electric currents from the induced magnetic fields, is a severely underdetermined problem and, without complementary prior information, no unique solution can be found.

The nucleation mechanisms of methane hydrates are studied using well-tempered metadynamics and restrained molecular dynamics. The collective variables we used to follow the process are the methane-methane and methane-water coordination numbers, from which we computed the corresponding Landau free energy surface. This surface is characterized by two minima, corresponding to the two-phase methane bubble/water solution and clathrate crystal, and a transition state.

We study the impact of the Peterlin approximation on the statistics of the end-to-end separation of polymers in a turbulent flow. The finitely extensible nonlinear elastic (FENE) model and the FENE model with the Peterlin approximation (FENE-P) are numerically integrated along a large number of Lagrangian trajectories resulting from a direct numerical simulation of three-dimensional homogeneous isotropic turbulence. Although the FENE-P model yields results in qualitative agreement with those of the FENE model, quantitative differences emerge.

The formation of methane-hydrate precursors at large planar water-methane interfaces has been studied using massively parallel molecular dynamics in systems of varying size from around 10 000 to almost 7 x 10(6) molecules. This process took two distinct steps. First, the concentration of solvated methane clusters increases just inside the aqueous domain via slow diffusion from the methane-water interface, forming "clusters" of solvated methane molecules.

Introduction: The brain is a connected network, requiring complex-system measures to describe its organization principles [1,2]. Here, we aim at testing whether the normalized compression distance (NCD) [3] is a suitable quantifier of the functional connectivity between cortical regions. This new measure estimates the information shared by two signals comparing the compression length of one signal given the other, without requiring any representation of the single in harmonics or selecting a specific time window where to compare the two signals.

We study a hybrid tree/finite-difference method which permits to obtain efficient and accurate European and American option prices in the Heston Hull-White and Heston Hull-White2d models. Moreover, as a by-product, we provide a new simulation scheme to be used for Monte Carlo evaluations. Numerical results show the reliability and the efficiency of the proposed methods.

Transport phenomena still stand as one of the most challenging problems in computational physics. By exploiting the analogies between Dirac and lattice Boltzmann equations, we develop a quantum simulator based on pseudospin-boson quantum systems, which is suitable for encoding fluid dynamics transport phenomena within a lattice kinetic formalism. It is shown that both the streaming and collision processes of lattice Boltzmann dynamics can be implemented with controlled quantum operations, using a heralded quantum protocol to encode non-unitary scattering processes.