An Attempt to Construct an Activity Cycle Catalog with Kepler Long-Cadence Light Curves
Universe, 2022 Many stars show activity cycles like the Sun. Kepler has gathered ∼200,000 light curves. Most of the Kepler stars only have long-cadence light curves, which limits their applicable methods.
Yu-Fu Shen, Gang Zhao, Sarah A. Bird
doaj +1 more source
Meta-analysis of photometric and asteroseismic measurements of stellar rotation periods: the Lomb-Scargle periodogram, autocorrelation function, wavelet and rotational splitting analysis for 92 Kepler asteroseismic targets [PDF]
, 2022 We perform photometric (the Lomb-Scargle periodogram, autocorrelation, and wavelet) and asteroseismic analyses of 92 Kepler solar-like main-sequence stars to understand the reliability of the measured stellar rotation periods. We focus on the 70 stars without reported stellar companions, and classify them into four groups according to the quarter-to ...
arxiv +1 more source
Photometric stereo endoscopy [PDF]
Journal of Biomedical Optics, 2013 While color video endoscopy has enabled wide-field examination of the gastrointestinal tract, it often misses or incorrectly classifies lesions. Many of these missed lesions exhibit characteristic three-dimensional surface topographies. An endoscopic system that adds topographical measurements to conventional color imagery could therefore increase ...
Parot Fernández, Vicente José +6 more
openaire +5 more sources
Photometric redshifts from reconstructed QSO templates [PDF]
, 2001 From SDSS commissioning photometric and spectroscopic data, we investigate the utility of photometric redshift techniques to the task of estimating QSO redshifts. We consider empirical methods (e.g.
Alexander S. Szalay +21 more
core +2 more sources
Multiview Photometric Stereo [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008 This paper addresses the problem of obtaining complete, detailed reconstructions of textureless shiny objects. We present an algorithm which uses silhouettes of the object, as well as images obtained under changing illumination conditions. In contrast with previous photometric stereo techniques, ours is not limited to a single viewpoint but produces ...
Roberto Cipolla +2 more
openaire +3 more sources
Machine Learning Classification to Identify Catastrophic Outlier Photometric Redshift Estimates [PDF]
, 2021 We present results of using a basic binary classification neural network model to identify likely catastrophic outlier photometric redshift estimates of individual galaxies, based only on the galaxies' measured photometric band magnitude values. We find that a simple implementation of this classification can identify a significant fraction of galaxies ...
arxiv +1 more source
Photometric Redshifts of Galaxies in COSMOS [PDF]
, 2006 We measure photometric redshifts and spectral types for galaxies in the COSMOS survey. We use template fitting technique combined with luminosity function priors and with the option to simultaneously estimate dust extinction (i.e. E(B-V)) for each galaxy.
A. Iovino +37 more
core +3 more sources
A blind test of photometric redshift prediction [PDF]
, 1998 Results of a blind test of photometric redshift predictions against spectroscopic galaxy redshifts obtained in the Hubble Deep Field with the Keck Telescope are presented.
Alberto Fernández-Soto +19 more
core +3 more sources
EAZY: A Fast, Public Photometric Redshift Code [PDF]
, 2008 We describe a new program for determining photometric redshifts, dubbed EAZY. The program is optimized for cases where spectroscopic redshifts are not available, or are only available for a biased subset of the galaxies.
G. Brammer, P. V. van Dokkum, P. Coppi
semanticscholar +1 more source
Photometrically-Classified Superluminous Supernovae from the Pan-STARRS1 Medium Deep Survey: A Case Study for Science with Machine Learning-Based Classification [PDF]
The Astrophysical Journal, Volume 937, Number 1 (2022), 2022 With the upcoming Vera C.~Rubin Observatory Legacy Survey of Space and Time (LSST), it is expected that only $\sim 0.1\%$ of all transients will be classified spectroscopically. To conduct studies of rare transients, such as Type I superluminous supernovae (SLSNe), we must instead rely on photometric classification.
arxiv +1 more source