相关论文: Astroinformatics: Statistically Optimal Approximat…
Massive stars exhibit a perplexing mismatch between their inferred masses from different observational techniques, posing a significant challenge to our understanding of stellar evolution and structure. This discrepancy is believed to be…
Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) is acquiring integral-field spectroscopy for the largest sample of galaxies to date. By 2020, the MaNGA Survey --- one of three core programs in the fourth-generation Sloan Digital…
We have been doing a sample survey in UBV photometry and proper motions as part of an investigation of galactic structure and evolution. The programme is based on Schmidt plates (from OCA, Tautenburg, Palomar and ESO Schmidt telescopes)…
We present an analysis of six independent on-sky datasets taken with the Keck-II/NIRC2 instrument. Using the off-axis point spread function (PSF) reconstruction software AIROPA, we extract stellar astrometry, photometry, and other fitting…
We have compiled the first all-sky mid-infrared variable-star catalog based on Wide-field Infrared Survey Explorer (WISE) five-year survey data. Requiring more than 100 detections for a given object, 50,282 carefully and robustly selected…
We develop a polynomial time $\Omega\left ( \frac 1R \log R \right)$ approximate algorithm for Max 2CSP-$R$, the problem where we are given a collection of constraints, each involving two variables, where each variable ranges over a set of…
Partial measurements of relative position are a relatively common event during the observation of visual binary stars. However, these observations are typically discarded when estimating the orbit of a visual pair. In this article we…
This paper describes the first part of the photometric data from the 9x9 deg ASAS cameras monitoring the whole southern hemisphere in V-band. Data acquisition and reduction pipeline is described and preliminary list of variable stars is…
We calculate the fundamental stellar parameters effective temperature, surface gravity and iron abundance - T$_{\rm eff}$, log g, [Fe/H] - for the final release of the Mapping Nearby Galaxies at APO (MaNGA) Stellar Library (MaStar),…
Visual photometry, the estimation of stellar brightness by eye, continues to provide valuable data even in this highly-instrumented era. However, the eye-brain system functions differently from electronic sensors and its products can be…
The Variable Star One-shot Project (VSOP) is aimed at (1) providing the variability type and spectral type of all unstudied variable stars, (2) process, publish, and make the data available as automatically as possible, and (3) generate…
The analysis of astronomical interferometric data is often performed on the images obtained after deconvolution of the interferometer's point spread function (PSF). This strategy can be understood (especially for cases of sparse arrays) as…
Polynomial approximations of computationally intensive models are central to uncertainty quantification. This paper describes an adaptive method for non-intrusive pseudospectral approximation, based on Smolyak's algorithm with generalized…
We develop a Petrov-Galerkin stabilization method for multiscale convection-diffusion transport systems. Existing stabilization techniques add a limited number of degrees of freedom in the form of bubble functions or a modified diffusion,…
The aim of this paper is to describe a novel non-parametric noise reduction technique from the point of view of Bayesian inference that may automatically improve the signal-to-noise ratio of one- and two-dimensional data, such as e.g.…
Theoretical predictions of physical observables often involve extrapolations to regions that are poorly constrained by laboratory experiments and astrophysical observations. Without properly quantified theoretical errors, such model…
We introduce the Swift/UVOT+MaNGA (SwiM) value added catalog, which comprises 150 galaxies that have both SDSS/MaNGA integral field spectroscopy and archival Swift/UVOT near-UV (NUV) images. The similar angular resolution between the three…
Sparse Principal Component Analysis (sPCA) is a cardinal technique for obtaining combinations of features, or principal components (PCs), that explain the variance of high-dimensional datasets in an interpretable manner. This involves…
Measurements of the physical properties of stars at the lower end of the main sequence are scarce. In this context we report masses, radii and surface gravities of ten very-low-mass stars in eclipsing binary systems, with orbital periods of…
Bayesian nonparametric regression with dependent wavelets has dual shrinkage properties: there is shrinkage through a dependent prior put on functional differences, and shrinkage through the setting of most of the wavelet coefficients to…