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A novel application of machine-learning (ML) based image processing algorithms is proposed to analyze an all-sky map (ASM) obtained using the Fermi Gamma-ray Space Telescope. An attempt was made to simulate a one-year ASM from a…
The Low Frequency Array (LOFAR) is an ideal instrument to conduct deep extragalactic surveys. It has a large field of view and is sensitive to large scale and compact emission. It is, however, very challenging to synthesize thermal noise…
We have developed a low-cost off-the-shelf component star sensor (StarSense) for use in minisatellites and CubeSats to determine the attitude of a satellite in orbit. StarSense is an imaging camera with a limiting magnitude of 6.5, which…
The amdlib AMBER data reduction software is meant to produce AMBER data products from the raw data files that are sent to the PIs of different proposals or that can be found in the ESO data archive. The way defined by ESO to calibrate the…
Automated techniques have been developed to automate the process of classification of objects or their analysis. The large datasets provided by upcoming spectroscopic surveys with dedicated telescopes urges scientists to use these automated…
Scalable machine learning over big data is an important problem that is receiving a lot of attention in recent years. On popular distributed environments such as Hadoop running on a cluster of commodity machines, communication costs are…
Cosmological observations from ground at millimetre and sub-millimetre wavelengths are affected by atmospheric absorption and consequent emission. The low and high frequency (sky noise) fluctuations of atmospheric performance imply careful…
In the last decade a new generation of telescopes and sensors has allowed the production of a very large amount of data and astronomy has become a data-rich science. New automatic methods largely based on machine learning are needed to cope…
The Square Kilometer Array (SKA) would be the world's largest radio telescope with eventually over a square kilometer of collecting area. However, there are enormous challenges in its data processing. The using of modern distributed…
We present a robust method, as well as a new metric, for the comparison of permittivity models in terahertz timedomain spectroscopy (THz-TDS). In this work, we perform an extensive noise analysis of a THz-TDS system, we remove and model the…
A 2-D spatio-temporal analysis of terahertz generation by optical rectification of tilted-pulse-fronts is presented. Closed form expressions of terahertz transients and spectra in two spatial dimensions are furnished in the undepleted…
We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that…
Calibration and higher order statistics (HOS) are standard components of many image steganalysis systems. These techniques have not yet found adequate attention in audio steganalysis context. Specifically, most of current works are either…
We have reduced the data taken with the Spectral and Photometric Imaging Receiver (SPIRE) photometer on board the Herschel Space Observatory in the Science Demonstration Phase (SDP) of the Herschel Astrophysical Terahertz Large Area Survey…
We describe the data processing pipeline of the Planck Low Frequency Instrument (LFI) data processing centre (DPC) to create and characterize full-sky maps based on the first 15.5 months of operations at 30, 44 and 70 GHz. In particular, we…
SpectraPy is an Astropy affiliated package for spectroscopic data reduction. It collects algorithms and methods for data reduction of astronomical spectra obtained by through-slits spectrographs. It has been created to fill the gap in…
We apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time series data. We preprocessed over 94 GB of Kepler light curves from MAST to classify according to ten distinct physical…
A fundamental challenge for wide-field imaging surveys is obtaining follow-up spectroscopic observations: there are > $10^9$ photometrically cataloged sources, yet modern spectroscopic surveys are limited to ~few x $10^6$ targets. As we…
We used the Robo-AO laser adaptive optics system to image 99 main sequence and subgiant stars that have Kepler-detected asteroseismic signals. Robo-AO allows us to resolve blended secondary sources at separations as close as 0.15" that may…
We have begun a large-scale photometric survey of nearby open clusters and star-forming regions, the Monitor project, aiming to measure time-series photometry for >10,000 cluster members over >10 sq.deg of sky, to find low-mass eclipsing…