Related papers: Grist: Grid-based Data Mining for Astronomy
Breast cancer as a medical condition and mammograms as images exhibit many dimensions of variability across the population. Similarly, the way diagnostic systems are used and maintained by clinicians varies between imaging centres and…
Galaxy cluster surveys are power tools for studying the dark energy. In principle, the equation of state parameter w of the dark energy and its time evolution can be extracted from large solid angle, high yield surveys that deliver tens of…
We describe the scientific motivation behind, and the methodology of, the Stanford Cluster Search (StaCS), a program to compile a catalog of optically selected clusters of galaxies at intermediate and high (0.3 < z < 1) redshifts. The…
For numerical simulations of cosmic-ray propagation fast access to static magnetic field data is required. We present a data structure for multiresolution vector grids which is optimized for fast access, low overhead and shared memory use.…
In machine learning and computer vision, mean shift (MS) qualifies as one of the most popular mode-seeking algorithms used for clustering and image segmentation. It iteratively moves each data point to the weighted mean of its neighborhood…
Astronomy produces extremely large data sets from ground-based telescopes, space missions, and simulation. The volume and complexity of these rich data sets require new approaches and advanced tools to understand the information contained…
Context. Gamma-ray bursts (GRBs), observed at redshifts as high as 9.4, could serve as valuable probes for investigating the distant Universe. However, this necessitates an increase in the number of GRBs with determined redshifts, as…
This is the first paper of a series that will present data and scientific results from the WINGS project, a wide-field, multiwavelength imaging and spectroscopic survey of galaxies in 77 nearby clusters. The sample was extracted from the…
(abridged) The technique of gravitational microlensing is currently unique in its ability to provide a sample of terrestrial exoplanets around both Galactic disk and bulge stars, allowing to measure their abundance and determine their…
The information extracted from large galaxy surveys with the likes of DES, DESI, Euclid, LSST, SKA, and WFIRST will be greatly enhanced if the resultant galaxy catalogues can be cross-correlated with one another. Predicting the nature of…
The Large Synoptic Survey Telescope (LSST) is a large-aperture, wide-field, ground-based survey system that will image the sky in six optical bands from 320 to 1050 nm, uniformly covering approximately $18,000$deg$^2$ of the sky over 800…
The current role of data-driven science is constantly increasing its importance within Astrophysics, due to the huge amount of multi-wavelength data collected every day, characterized by complex and high-volume information requiring…
Grid computing has attracted many researchers over a few years, and as a result many new protocols have emerged and also evolved since its inception a decade ago. Grid protocols play major role in implementing services that facilitate…
The recent explosion of recorded digital data and its processed derivatives threatens to overwhelm researchers when analysing their experimental data or when looking up data items in archives and file systems. While current hardware…
Most of the services viewed in context to grid and cloud computing are mostly confined to services that are available for intellectual purposes. The grid or cloud computing are large scale distributed systems. The essence of large scale…
A good fraction of GRBs detected by Swift are at a large redshift (up to z=6.3, so far). Their study allows us to investigate, among other things, the cosmic star formation in the early Universe (possibly up to the re-ionization era) and…
We present a machine learning based information retrieval system for astronomical observatories that tries to address user defined queries related to an instrument. In the modern instrumentation scenario where heterogeneous systems and…
The New Vacuum Solar Telescope (NVST) is a 1-m solar telescope that aims to observe the fine structures in both the photosphere and the chromosphere of the Sun. The observational data acquired simultaneously from one channel for the…
We propose a new method for solving an important problem of astronomy that arises in observations with ultrahigh-angular-resolution interferometers. This method is based on the application of the theory of artificial neural networks. We…
The Sparse Grids Matlab Kit provides a Matlab implementation of sparse grids, and can be used for approximating high-dimensional functions and, in particular, for surrogate-model-based uncertainty quantification. It is lightweight,…