No Arabic abstract
Optimal extraction is a key step in processing the raw images of spectra as registered by two-dimensional detector arrays to a one-dimensional format. Previously reported algorithms reconstruct models for a mean one-dimensional spatial profile to assist a properly weighted extraction. We outline a simple optimal extraction algorithm including error propagation, which is very suitable for stabilised, fibre-fed spectrographs and does not model the spatial profile shape. A high signal-to-noise, master-flat image serves as reference image and is directly used as an extraction profile mask. Each extracted spectral value is the scaling factor relative to the cross-section of the unnormalised master-flat which contains all information about the spatial profile as well as pixel-to-pixel variations, fringing, and blaze. The extracted spectrum is measured relative to the flat spectrum. Using echelle spectra of the HARPS spectrograph we demonstrate a competitive extraction performance in terms of signal-to-noise and show that extracted spectra can be used for high precision radial velocity measurement. Pre- or post-flat-fielding of the data is not necessary, since all spectrograph inefficiencies inherent to the extraction mask are automatically accounted for. Also the reconstruction of the mean spatial profile by models is not needed, thereby reducing the number of operations to extract spectra. Flat-relative optimal extraction is a simple, efficient, and robust method that can be applied easily to stabilised, fibre-fed spectrographs.
We present an open-source Python package, Orbits from Radial Velocity, Absolute, and/or Relative Astrometry (orvara), to fit Keplerian orbits to any combination of radial velocity, relative astrometry, and absolute astrometry data from the Hipparcos-Gaia Catalog of Accelerations. By combining these three data types, one can measure precise masses and sometimes orbital parameters even when the observations cover a small fraction of an orbit. orvara achieves its computational performance with an eccentric anomaly solver five to ten times faster than commonly used approaches, low-level memory management to avoid python overheads, and by analytically marginalizing out parallax, barycenter proper motion, and the instrument-specific radial velocity zero points. Through its integration with the Hipparcos and Gaia intermediate astrometry package htof, orvara can properly account for the epoch astrometry measurements of Hipparcos and the measurement times and scan angles of individual Gaia epochs. We configure orvara with modifiable .ini configuration files tailored to any specific stellar or planetary system. We demonstrate orvara with a case study application to a recently discovered white dwarf/main sequence (WD/MS) system, HD 159062. By adding absolute astrometry to literature RV and relative astrometry data, our comprehensive MCMC analysis improves the precision of HD 159062Bs mass by more than an order of magnitude to $0.6083^{+0.0083}_{-0.0073},M_odot$. We also derive a low eccentricity and large semimajor axis, establishing HD 159062AB as a system that did not experience Roche lobe overflow.
We present new advances in the spectral extraction of point-like sources adapted to the Infrared Spectrograph onboard the Spitzer Space Telescope. For the first time, we created a super-sampled point spread function of the low-resolution modules. We describe how to use the point spread function to perform optimal extraction of a single source and of multiple sources within the slit. We also examine the case of the optimal extraction of one or several sources with a complex background. The new algorithms are gathered in a plugin called Adopt which is part of the SMART data analysis software.
Project 1640 is a high contrast near-infrared instrument probing the vicinities of nearby stars through the unique combination of an integral field spectrograph with a Lyot coronagraph and a high-order adaptive optics system. The extraordinary data reduction demands, similar those which several new exoplanet imaging instruments will face in the near future, have been met by the novel software algorithms described herein. The Project 1640 Data Cube Extraction Pipeline (PCXP) automates the translation of 3.8*10^4 closely packed, coarsely sampled spectra to a data cube. We implement a robust empirical model of the spectrograph focal plane geometry to register the detector image at sub-pixel precision, and map the cube extraction. We demonstrate our ability to accurately retrieve source spectra based on an observation of Saturns moon Titan.
ImageJ is a graphical user interface (GUI) driven, public domain, Java-based, software package for general image processing traditionally used mainly in life sciences fields. The image processing capabilities of ImageJ are useful and extendable to other scientific fields. Here we present AstroImageJ (AIJ), which provides an astronomy specific image display environment and tools for astronomy specific image calibration and data reduction. Although AIJ maintains the general purpose image processing capabilities of ImageJ, AIJ is streamlined for time-series differential photometry, light curve detrending and fitting, and light curve plotting, especially for applications requiring ultra-precise light curves (e.g., exoplanet transits). AIJ reads and writes standard FITS files, as well as other common image formats, provides FITS header viewing and editing, and is World Coordinate System (WCS) aware, including an automated interface to the astrometry.net web portal for plate solving images. AIJ provides research grade image calibration and analysis tools with a GUI driven approach, and easily installed cross-platform compatibility. It enables new users, even at the level of undergraduate student, high school student, or amateur astronomer, to quickly start processing, modeling, and plotting astronomical image data with one tightly integrated software package.
Photometric observations of planetary transits may show localized bumps, called transit anomalies, due to the possible crossing of photospheric starspots. The aim of this work is to analyze the transit anomalies and derive the temperature profile inside the transit belt along the transit direction. We develop the algorithm TOSC, a tomographic inverse-approach tool which, by means of simple algebra, reconstructs the flux distribution along the transit belt. We test TOSC against some simulated scenarios. We find that TOSC provides robust results for light curves with photometric accuracies better than 1~mmag, returning the spot-photosphere temperature contrast with an accuracy better than 100~K. TOSC is also robust against the presence of unocculted spots, provided that the apparent planetary radius given by the fit of the transit light curve is used in place of the true radius. The analysis of real data with TOSC returns results consistent with previous studies.