Related papers: Data-Collection for the Sloan Digital Sky Survey: …
Physics perception very often faces the problem that only limited data or partial measurements on the scene are available. In this work, we propose a strategy to learn the full state of sloshing liquids from measurements of the free…
The Chinese Space Station Optical Survey (CSS-OS) is a mission to explore the vast universe. This mission will equip a 2-meter space telescope to perform a multi-band NUV-optical large area survey (over 40% of the sky) and deep survey (~1%…
The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will soon carry out an unprecedented wide, fast, and deep survey of the sky in multiple optical bands. The data from LSST will open up a new discovery space in astronomy…
The Sloan Digital Sky Survey (SDSS) automated spectroscopic reduction pipeline provides >1.5 million intermediate resolution, R~2000, moderate signal-to-noise ratio (SNR), SNR~15, astronomical spectra of unprecedented homogeneity that cover…
We describe a statistical approach for measuring the influence that a galaxy's closest companion has on the galaxy's properties out to arbitrarily wide separations. We begin by identifying the closest companion for every galaxy in a large…
We correct the observed Milky Way satellite luminosity function for luminosity bias using published completeness limits for the Sloan Digital Sky Survey DR5. Assuming that the spatial distribution of Milky Way satellites tracks the subhalos…
Ahead-of-time forecasting of the output power of power plants is essential for the stability of the electricity grid and ensuring uninterrupted service. However, forecasting renewable energy sources is difficult due to the chaotic behavior…
The Faint Sky Variability Survey is aimed at finding photometric and/or astrometric variable objects in the brightness range between 16<V<24 on timescales between tens of minutes and years with photometric precisions ranging from 3…
The Sloan Digital Sky Survey (SDSS) currently provides by far the largest homogeneous sample of intermediate signal-to-noise ratio (S/N) optical spectra of galaxies and quasars. The fully automated SDSS spectroscopic reduction pipeline has…
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…
We present and describe a catalog of galaxy photometric redshifts (photo-z's) for the Sloan Digital Sky Survey (SDSS) Data Release 6 (DR6). We use the Artificial Neural Network (ANN) technique to calculate photo-z's and the Nearest Neighbor…
This paper describes a new algorithm for solar energy forecasting from a sequence of Cloud Optical Depth (COD) images. The algorithm is based on the following simple observation: the dynamics of clouds represented by COD images resembles…
Two-dimensional high-resolution density field of galaxies of the Early Data Release of the Sloan Digital Sky Survey with a smoothing lengths 0.8 h^{-1} Mpc is applied to extract clusters of galaxies, and a low-resolution field with…
The advent of deep, wide, accurate, digital photometric surveys exemplified by the Sloan Digital Sky Survey (SDSS) has had a profound impact on studies of the Milky Way. In the past decade, we have transitioned from a scarcity to an…
We have used the Parkes Multibeam system and the Sloan Digital Sky Survey (SDSS) to assemble a sample of 195 galaxies selected originally from their HI signature to avoid biases against unevolved or low surface brightness objects. For each…
Using the stellar photometry catalogue based on the latest data release (DR4) of the Sloan Digital Sky Survey (SDSS), a study of the Galactic structure using star counts is carried out for selected areas of the sky. The sample areas are…
We discuss the rationale and the present status of a large redshift survey aiming at measuring distances for all the clusters of galaxies detected by the ROSAT X--ray All--Sky Survey in the southern hemisphere, with flux larger than $\sim…
We present a catalogue of about 6 million unresolved photometric detections in the Sloan Digital Sky Survey Seventh Data Release classifying them into stars, galaxies and quasars. We use a machine learning classifier trained on a subset of…
One of important aims of astronomical data mining is to systematically search for specific rare objects in a massive spectral dataset, given a small fraction of identified samples with the same type. Most existing methods are mainly based…
Absorption of light is one of the main selection effects limiting our ability to detect celestial sources, and ultimately, appearance of the sky across most of the electromagnetic spectrum. Recent advances in quantity and quality of…