Principal Component Analysis of Results Obtained from Finite-Difference Time-Domain Algorithms

Finite-Differences Time-Domain (FDTD) algorithms are well established tools of computational electromagnetism. Because of their practical implementation as computer codes, they are affected by many numerical artefact and noise. In order to obtain better results we propose using Principal Component Analysis (PCA) based on multivariate statistical techniques. The PCA has been successfully used for the analysis of noise and spatial temporal structure in a sequence of images. It allows a straightforward discrimination between the numerical noise and the actual electromagnetic variables, and the quantitative estimation of their respective contributions. Besides, The GDTD results can be filtered to clean the effect of the noise. In this contribution we will show how the method can be applied to several FDTD simulations: the propagation of a pulse in vacuum, the analysis of two-dimensional photonic crystals. In this last case, PCA has revealed hidden electromagnetic structures related to actual modes of the photonic crystal.

Influence of the sputtering flow regime on the structural properties and magnetic behavior of Fe-Ga thin films (Ga ∼ 30 at.%)

In this paper we analyze the structure of Fe-Ga layers with a Ga content of ∼30 at.% deposited by the sputtering technique under two different regimes. We also studied the correlation between the structure and magnetic behavior of the samples. Keeping the Ar pressure fixed, we modified the flow regime from ballistic to diffusive by increasing the distance between the target and the substrate. X-ray diffraction measurements have shown a lower structural quality when growing in the diffusive flow. We investigated the impact of the growth regime by means of x-ray absorption fine structure (XAFS) measurements and obtained signs of its influence on the local atomic order. Full multiple scattering and finite difference calculations based on XAFS measurements point to a more relevant presence of a disordered A2 phase and of orthorhombic Ga clusters on the Fe-Ga alloy deposited under a diffusive regime; however, in the ballistic sample, a higher presence of D0_3/B2 phases is evidenced. Structural characteristics, from local to long range, seem to determine the magnetic behavior of the layers. Whereas a clear in-plane magnetic anisotropy is observed in the film deposited under ballistic flow, the diffusive sample is magnetically isotropic. Therefore, our experimental results provide evidence of a correlation between flow regime and structural properties and its impact on the magnetic behavior of a rather unexplored compositional region of Fe-Ga compounds.

Reconstruction of inclusions in photothermal imaging

Photothermal imaging allows to inspect the structure of composite materials by means of nondestructive tests. The surface of a medium is heated at a number of locations. The resulting temperature field is recorded on the same surface. Thermal waves are strongly damped. Robust schemes are needed to reconstruct the structure of the medium from the decaying time dependent temperature field. The inverse problem is formulated as a weighted optimization problem with a time dependent constraint. The inclusions buried in the medium and their material constants are the design variables. We propose an approximation scheme in two steps. First, Laplace transforms are used to generate an approximate optimization problem with a small number of stationary constraints. Then, we implement a descent strategy alternating topological derivative techniques to reconstruct the geometry of inclusions with gradient methods to identify their material parameters. Numerical simulations assess the effectivity of the technique.

Efficient numerical methods for the random-field Ising model: Finite-size scaling, reweighting extrapolation, and computation of response functions

It was recently shown [Phys. Rev. Lett. 110, 227201 (2013)] that the critical behavior of the random-field Ising model in three dimensions is ruled by a single universality class. This conclusion was reached only after a proper taming of the large scaling corrections of the model by applying a combined approach of various techniques, coming from the zero-and positive-temperature toolboxes of statistical physics. In the present contribution we provide a detailed description of this combined scheme, explaining in detail the zero-temperature numerical scheme and developing the generalized fluctuation-dissipation formula that allowed us to compute connected and disconnected correlation functions of the model. We discuss the error evolution of our method and we illustrate the infinite limit-size extrapolation of several observables within phenomenological renormalization. We present an extension of the quotients method that allows us to obtain estimates of the critical exponent a of the specific heat of the model via the scaling of the bond energy and we discuss the self-averaging properties of the system and the algorithmic aspects of the maximum-flow algorithm used.