A class of multiscale decompositions for scattered discrete data is introduced, motivated by sensor network applications. A specific feature of these decompositions is that they do not rely on any type of mesh or connectivity between the data points. The decomposition is based on a thinning procedure that organizes the points in a multiscale hierarchy and on a local prediction operator based on...

Semiclassical techniques are used to analyze highly excited pure bending vibrational dynamics from spectra of C2H2. An analytic bifurcation approach is developed, based on critical points of a classical version of the quantum fitting Hamiltonian. At high energy four new types of anharmonic modes are born in bifurcations of the normal modes: local, orthogonal, precessional, and counter-rotator. ...

This work relates the development of an optical fiber (OF) sensor for the detection and quantification of single walled carbon nanotubes in aqueous solutions. The developed OF displays a compact design, it requires less expensive materials and equipment as well as low volume of sample (0.2 mL). This methodology was also validated by the comparison of its analytical performance with that of a st...

We propose Kernel Hamiltonian Monte Carlo (KMC), a gradient-free adaptive MCMC algorithm based on Hamiltonian Monte Carlo (HMC). On target densities where classical HMC is not an option due to intractable gradients, KMC adaptively learns the target’s gradient structure by fitting an exponential family model in a Reproducing Kernel Hilbert Space. Computational costs are reduced by two novel effi...

We demonstrate a self-contained methodology for predicting conductance histograms of atomic and molecular junctions. Fast classical molecular-dynamics simulations are combined with accurate density functional theory calculations predicting both quantum transport properties and molecular-dynamics force field parameters. The methodology is confronted with experiments on atomic-sized indium nanoju...

[1] Space-fractional advection-dispersion models provide attractive alternatives to the classical advection-dispersion equation for model applications that exhibit early arrivals and plume skewness. This paper develops a flexible method for estimating the parameters of the fractional transport model on the basis of spatial plume snapshots or temporal breakthrough curve data. A particle-tracking...