Characterization of spatial–temporal patterns in dynamic speckle sequences using principal component analysis

Abstract. Speckle is being used as a characterization tool for the analysis of the dynamics of slow-varying phenomena occurring in biological and industrial samples at the surface or near-surface regions. The retrieved data take the form of a sequence of speckle images. These images contain information about the inner dynamics of the biological or physical process taking place in the sample. Principal component analysis (PCA) is able to split the original data set into a collection of classes. These classes are related to processes showing different dynamics. In addition, statistical descriptors of speckle images are used to retrieve information on the characteristics of the sample. These statistical descriptors can be calculated in almost real time and provide a fast monitoring of the sample. On the other hand, PCA requires a longer computation time, but the results contain more information related to spatial–temporal patterns associated to the process under analysis. This contribution merges both descriptions and uses PCA as a preprocessing tool to obtain a collection of filtered images, where statistical descriptors are evaluated on each of them. The method applies to slow-varying biological and industrial processes.

Near-infrared and star-forming properties of local luminous infrared galaxies

We use Hubble Space Telescope (HST) NICMOS continuum and Paα observations to study the near-infrared and star formation properties of a representative sample of 30 local (d ~ 35-75 Mpc) luminous infrared galaxies (LIRGs, infrared [8-1000 μm] luminosities of log L_IR = 11-11.9 L_☉). The data provide spatial resolutions of 25-50 pc and cover the central ~3.3-7.1 kpc regions of these galaxies. About half of the LIRGs show compact (~1-2 kpc) Paα emission with a high surface brightness in the form of nuclear emission, rings, and minispirals. The rest of the sample show Paα emission along the disk and the spiral arms extending over scales of 3-7 kpc and larger. About half of the sample contains H II regions with Hα luminosities significantly higher than those observed in normal galaxies. There is a linear empirical relationship between the mid-IR 24 μm and hydrogen recombination (extinction-corrected Paα) luminosity for these LIRGs, and the H II regions in the central part of M51. This relation holds over more than four decades in luminosity, suggesting that the mid-IR emission is a good tracer of the star formation rate (SFR). Analogous to the widely used relation between the SFR and total IR luminosity of R. Kennicutt, we derive an empirical calibration of the SFR in terms of the monochromatic 24 μm luminosity that can be used for luminous, dusty galaxies.