Kernel continuum regression

The continuum regression technique provides an appealing regression framework connecting ordinary least squares, partial least squares and principal component regression in one family. It offers some insight on the underlying regression model for a given application. Moreover, it helps to provide deep understanding of various regression techniques. Despite the useful framework, however, the current development on continuum regression is only for linear regression. In many applications, nonlinear regression is necessary. The extension of continuum regression from linear models to nonlinear models using kernel learning is considered. The proposed kernel continuum regression technique is quite general and can handle very flexible regression model estimation. An efficient algorithm is developed for fast implementation. Numerical examples have demonstrated the usefulness of the proposed technique

Detecting Quasars in Large-Scale Astronomical Surveys

We present a classification-based approach to identify quasi-stellar radio sources (quasars) in the Sloan Digital Sky Survey and evaluate its performance on a manually labeled training set. While reasonable results can already be obtained via approaches working only on photometric data, our experiments indicate that simple but problem-specific features extracted from spectroscopic data can significantly improve the classification performance. Since our approach works orthogonal to existing classification schemes used for building the spectroscopic catalogs, our classification results are well suited for a mutual assessment of the approaches' accuracies.Comment: 6 pages, 8 figures, published in proceedings of 2010 Ninth International Conference on Machine Learning and Applications (ICMLA) of the IEE

Brightness of Solar Magnetic Elements as a Function of Magnetic Flux at High Spatial Resolution

We investigate the relationship between the photospheric magnetic field of small-scale magnetic elements in the quiet Sun (QS) at disc centre, and the brightness at 214 nm, 300 nm, 313 nm, 388 nm, 397 nm, and at 525.02 nm. To this end we analysed spectropolarimetric and imaging time series acquired simultaneously by the IMaX magnetograph and the SuFI filter imager on-board the balloon-borne observatory Sunrise during its first science flight in 2009, with high spatial and temporal resolution. We find a clear dependence of the contrast in the near ultraviolet (NUV) and the visible on the line-of-sight component of the magnetic field, $B_{\rm LOS}$, which is best described by a logarithmic model. This function represents well the relationship between the Ca II H-line emission and $B_{\rm LOS}$, and works better than a power-law fit adopted by previous studies. This, along with the high contrast reached at these wavelengths, will help with determining the contribution of small-scale elements in the QS to the irradiance changes for wavelengths below 388 nm. At all wavelengths including the continuum at 525.40 nm the intensity contrast does not decrease with increasing $B_{\rm LOS}$. This result also strongly supports that Sunrise has resolved small strong magnetic field elements in the internetwork, resulting in constant contrasts for large magnetic fields in our continuum contrast at 525.40 nm vs. $B_{\rm LOS}$ scatterplot, unlike the turnover obtained in previous observational studies. This turnover is due to the intermixing of the bright magnetic features with the dark intergranular lanes surrounding them

Using the equivalent kernel to understand Gaussian process regression

The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit

CARMA Survey Toward Infrared-bright Nearby Galaxies (STING): Molecular Gas Star Formation Law in NGC4254

This study explores the effects of different assumptions and systematics on the determination of the local, spatially resolved star formation law. Using four star formation rate (SFR) tracers (H\alpha with azimuthally averaged extinction correction, mid-infrared 24 micron, combined H\alpha and mid-infrared 24 micron, and combined far-ultraviolet and mid-infrared 24 micron), several fitting procedures, and different sampling strategies we probe the relation between SFR and molecular gas at various spatial resolutions and surface densities within the central 6.5 kpc in the disk of NGC4254. We find that in the high surface brightness regions of NGC4254 the form of the molecular gas star formation law is robustly determined and approximately linear and independent of the assumed fraction of diffuse emission and the SFR tracer employed. When the low surface brightness regions are included, the slope of the star formation law depends primarily on the assumed fraction of diffuse emission. In such case, results range from linear when the fraction of diffuse emission in the SFR tracer is ~30% or less (or when diffuse emission is removed in both the star formation and the molecular gas tracer), to super-linear when the diffuse fraction is ~50% and above. We find that the tightness of the correlation between gas and star formation varies with the choice of star formation tracer. The 24 micron SFR tracer by itself shows the tightest correlation with the molecular gas surface density, whereas the H\alpha corrected for extinction using an azimuthally-averaged correction shows the highest dispersion. We find that for R<0.5R_25 the local star formation efficiency is constant and similar to that observed in other large spirals, with a molecular gas depletion time ~2 Gyr.Comment: accepted for publication in ApJ, vol 729, March 10 2011 issue; 30 pages; 14 figures; revised version includes referee's comments; results unchange