Results 31 to 40 of about 502 (78)
Data reduction methods for single-mode optical interferometry - Application to the VLTI two-telescopes beam combiner VINCI [PDF]
, 2004 The interferometric data processing methods that we describe in this paper use a number of innovative techniques. In particular, the implementation of the wavelet transform allows us to obtain a good immunity of the fringe processing to false detections ...
Berger +32 more
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The Astrophysical JournalEmulators using machine learning techniques have emerged to efficiently generate mock data matching the large survey volume for upcoming experiments, as an alternative approach to large-scale numerical simulations.
Kangning Diao, Yi Mao
doaj +1 more source
Photometric Redshift Estimation of Quasars by a Cross-modal Contrast Learning Method
The Astronomical JournalEstimating photometric redshifts (photo- z ) of quasars is crucial for measuring cosmic distances and monitoring cosmic evolution. While numerous point estimation methods have successfully determined photo- z , they often struggle with the inherently ill-
Chen Zhang +4 more
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The Astrophysical JournalMolecular emission from the galactic and extragalactic interstellar medium (ISM) is often used to determine the physical conditions of the dense gas. However, even from spatially resolved regions, the observed molecules do not necessarily arise from a ...
Damien de Mijolla +3 more
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Regression for Astronomical Data with Realistic Distributions, Errors, and Nonlinearity
The Astronomical JournalWe have developed a new regression technique, the maximum likelihood (ML)–based method and its variant, the Kolmogorov–Smirnov (KS) test–based method, designed to obtain unbiased regression results from typical astronomical data. A normalizing flow model
Tao Jing, Cheng Li
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Bayesian Methods for Analysis and Adaptive Scheduling of Exoplanet Observations
, 2018 We describe work in progress by a collaboration of astronomers and statisticians developing a suite of Bayesian data analysis tools for extrasolar planet (exoplanet) detection, planetary orbit estimation, and adaptive scheduling of observations. Our work
Balan +28 more
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AstroM3: A Self-supervised Multimodal Model for Astronomy
The Astronomical JournalWhile machine-learned models are now routinely employed to facilitate astronomical inquiry, model inputs tend to be limited to a primary data source (namely images or time series) and, in the more advanced approaches, some metadata.
M. Rizhko, J. S. Bloom
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Statistical Properties of a Polarization Vector’s Ellipticity Angle
The Astrophysical JournalThe orientation of a polarization vector on the Poincaré sphere is defined by its position angle (PA) and ellipticity angle (EA). The radio emission from pulsars, magnetars, and fast radio bursts can be elliptically polarized, and measurements of the EA ...
M. M. McKinnon
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Identifying Diffuse Spatial Structures in High-energy Photon Lists
The Astronomical Journal, 2023 Data from high-energy observations are usually obtained as lists of photon events. A common analysis task for such data is to identify whether diffuse emission exists, and to estimate its surface brightness, even in the presence of point sources that may
Minjie Fan +5 more
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Insights on the Spectral Signatures of Stellar Activity and Planets from PCA
, 2017 Photospheric velocities and stellar activity features such as spots and faculae produce measurable radial velocity signals that currently obscure the detection of sub-meter-per-second planetary signals.
Cisewski, Jessi +4 more
core +1 more source