48,742 research outputs found
XMMPZCAT: A catalogue of photometric redshifts for X-ray sources
The third version of the XMM-Newton serendipitous catalogue (3XMM),
containing almost half million sources, is now the largest X-ray catalogue.
However, its full scientific potential remains untapped due to the lack of
distance information (i.e. redshifts) for the majority of its sources. Here we
present XMMPZCAT, a catalogue of photometric redshifts (photo-z) for 3XMM
sources. We searched for optical counterparts of 3XMM-DR6 sources outside the
Galactic plane in the SDSS and Pan-STARRS surveys, with the addition of near-
(NIR) and mid-infrared (MIR) data whenever possible (2MASS, UKIDSS, VISTA-VHS,
and AllWISE). We used this photometry data set in combination with a training
sample of 5157 X-ray selected sources and the MLZ-TPZ package, a supervised
machine learning algorithm based on decision trees and random forests for the
calculation of photo-z. We have estimated photo-z for 100,178 X-ray sources,
about 50% of the total number of 3XMM sources (205,380) in the XMM-Newton
fields selected to build this catalogue (4208 out of 9159). The accuracy of our
results highly depends on the available photometric data, with a rate of
outliers ranging from 4% for sources with data in the optical+NIR+MIR, up to
40% for sources with only optical data. We also addressed the reliability
level of our results by studying the shape of the photo-z probability density
distributions.Comment: 16 pages, 14 figures, A&A accepte
Dense and accurate motion and strain estimation in high resolution speckle images using an image-adaptive approach
Digital image processing methods represent a viable and well acknowledged alternative to strain gauges and interferometric techniques for determining full-field displacements and strains in materials under stress. This paper presents an image adaptive technique for dense motion and strain estimation using high-resolution speckle images that show the analyzed material in its original and deformed states. The algorithm starts by dividing the speckle image showing the original state into irregular cells taking into consideration both spatial and gradient image information present. Subsequently the Newton-Raphson digital image correlation technique is applied to calculate the corresponding motion for each cell. Adaptive spatial regularization in the form of the Geman-McClure robust spatial estimator is employed to increase the spatial consistency of the motion components of a cell with respect to the components of neighbouring cells. To obtain the final strain information, local least-squares fitting using a linear displacement model is performed on the horizontal and vertical displacement fields. To evaluate the presented image partitioning and strain estimation techniques two numerical and two real experiments are employed. The numerical experiments simulate the deformation of a specimen with constant strain across the surface as well as small rigid-body rotations present while real experiments consist specimens that undergo uniaxial stress. The results indicate very good accuracy of the recovered strains as well as better rotation insensitivity compared to classical techniques
Development of macroscopic waveguide and waveguide components for optical systems Final report, 28 Jan. - 28 Nov. 1964
Macroscopic waveguide and waveguide components for optical systems - laser
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