PySME -- Spectroscopy Made Easier

The characterization of exoplanet requires reliable determination of the fundamental parameters of their host stars. Spectral fitting plays an important role in this process. For the majority of stellar parameters matching synthetic spectra to the observations provides a robust and unique solution for fundamental parameters, such as effective temperature, surface gravity, abundances, radial and rotational velocities and others. Here we present a new software package for fitting high resolution stellar spectra that is easy to use, available for common platforms and free from commercial licenses. We call it PySME. It is based on the proven Spectroscopy Made Easy (later referred to as IDL SME or "original SME") package. The IDL part of the original SME code has been rewritten in Python, but we kept the efficient C++ and FORTRAN code responsible for molecular-ionization equilibrium, opacities and spectral synthesis. In the process we have updated some components of the optimization procedure offering more flexibility and better analysis of the convergence. The result is a more modern package with the same functionality of the original SME. We apply PySME to a few stars of different spectral types and compared the derived fundamental parameters with the results from IDL SME and other techniques. We show that PySME works at least as well as the original SME.Comment: 23 pages, 13 figures, code is available on https://github.com/AWehrhahn/SM

The impact of stellar magnetic activity on the radial velocity search of exoplanets

Radial velocity measurements are critical in finding and confirming exoplanets. To confine the parameters of the planet we naturally want to minimise the errors on the measurement. However the observed measurement error is now on the same order as the precision of the instrument. This so called jitter is related to the stellar activity (Wright 2005), i.e. the magnetic field of the star. In this paper we investigate if we can discover any correlation between the radial velocity variation and the magnetic activity of the star using HARPSpol spectra for the two stars Epsilon Eridani and GJ674

The impact of stellar magnetic activity on the radial velocity search of exoplanets

Radial velocity measurements are critical in finding and confirming exoplanets. To confine the parameters of the planet we naturally want to minimise the errors on the measurement. However the observed measurement error is now on the same order as the precision of the instrument. This so called jitter is related to the stellar activity (Wright 2005), i.e. the magnetic field of the star. In this paper we investigate if we can discover any correlation between the radial velocity variation and the magnetic activity of the star using HARPSpol spectra for the two stars Epsilon Eridani and GJ674

High Resolution Transmission Spectroscopy of Exoplanets

A large number of exoplanets has been observed in the last three decades, but still for most of them we know comparatively little about the atmospheres of these distant planets. This is of particular interest as there exist types of planets that don't have an analogy in our own solar system, like hot Jupiters or super Earths. Studying these is instrumental in understanding planet and solar system formation. However just as planets are much smaller than their host stars, so is their signal in the observations. We therefore require high-precision measurements and analysis methods to study them. In this thesis I focus on ground-based high-resolution spectroscopy, as this allows us to use the information encoded in individual absorption lines of the spectrum. I developed tools for the entire process from the initial data reduction, over the analysis of the host star, to the final planet atmosphere characterization.The first tool I developed is PyReduce. It performs data reduction on raw observation images of high-resolution spectrographs by correcting for noise and bias in the data. Of special interest is the new extraction algorithm, which properly accounts for the optical distortions in the spectrograph, and thus improves the quality of the recovered spectrum.The second tool is PySME, which determines the fundamental parameters of the host stars, by modelling the stellar atmosphere and comparing it to the observed spectrum. Accurate stellar parameters help us understand the star-planet system, especially regarding the stellar irradiation on the planet which is important for the temperature. Finally I created ChEATS to determine the chemical components of the planet atmosphere using the cross-correlation method. This method combines all observed spectral lines to detect the faint planet signal in the data. We show that these tools provide excellent analyses in the papers presented here. Additionally PyReduce and PySME are in active use by scientists all over the world. Finally we present an analysis of WASP-107 b, in which we detect H2O and CO in the planet atmosphere.Zoom Room: https://uu-se.zoom.us/j/63222657226</p

The impact of stellar magnetic activity on the radial velocity search of exoplanets

Radial velocity measurements are critical in finding and confirming exoplanets. To confine the parameters of the planet we naturally want to minimise the errors on the measurement. However the observed measurement error is now on the same order as the precision of the instrument. This so called jitter is related to the stellar activity (Wright 2005), i.e. the magnetic field of the star. In this paper we investigate if we can discover any correlation between the radial velocity variation and the magnetic activity of the star using HARPSpol spectra for the two stars Epsilon Eridani and GJ674

Optimal extraction of echelle spectra : Getting the most out of observations

Context. The price of instruments and observing time on modern telescopes is quickly increasing. Therefore, it is worth revisiting the data reduction algorithms to extract every bit of scientific information from available observations. Echelle spectrographs are typical instruments used in high-resolution spectroscopy, but attempts to improve the wavelength coverage and versatility of these instruments has resulted in a complicated and variable footprint of the entrance slit projection onto the science detector. Traditional spectral extraction methods generally fail to perform a truly optimal extraction when the slit image is not aligned with the detector columns and, instead, is tilted or even curved. Aims. Here, we present the mathematical algorithms and examples of their application to the optimal extraction and the following reduction steps for echelle spectrometers equipped with an entrance slit that is imaged with various distortions. The new method minimises the loss of spectral resolution, maximises the signal-to-noise ratio, and efficiently identifies local outliers. In addition to the new optimal extraction, we present order splicing and a more robust continuum normalisation algorithm. Methods. We developed and implemented new algorithms that create a continuum-normalised spectrum. In the process, we account for the (variable) tilt or curvature of the slit image on the detector and achieve optimal extraction without prior assumptions about the slit illumination. Thus, the new method can handle arbitrary image slicers, slit scanning, and other observational techniques aimed at increasing the throughput or dynamic range. Results. We compare our methods with other techniques for different instruments to illustrate the superior performance of the new algorithms compared to commonly used procedures. Conclusions. Advanced modelling of the focal plane requires significant computational effort but it has proven worthwhile thanks to the retrieval of a greater store of science information from every observation. The described algorithms and tools are freely available as part of our PyReduce package

Non-LTE abundance corrections for late-type stars from 2000Å to 3 μm

Context. It is well known that cool star atmospheres depart from local thermodynamic equilibrium (LTE). Making an accurate abundance determination requires taking those effects into account, but the necessary non-LTE (hereafter NLTE) calculations are often lacking. Aims. Our goal is to provide detailed estimates of NLTE effects for FGK type stars for all spectral lines from the ultraviolet (UV) to the near infrared (NIR) that are potentially useful as abundance diagnostics. The first paper in this series focusses on the light elements Na, Mg, and Al. Methods. The code PySME was used to compute curves of growth for 2158 MARCS model atmospheres in the parameter range 3800 &lt; T-eff &lt; 8000 K, 0.0 &lt; log(g) &lt; 5.5, and -5 &lt; [Fe/H] &lt; +0.5. Two microturbulence values, 1 and 2 km s(-1), and nine abundance points spanning -1 &lt; [X/Fe] &lt; 1 for element X, are used to construct individual line curves of growth by calculating the equivalent widths of 35 Na lines, 134 Mg lines, and 34 Al lines. The lines were selected in the wavelength range between 2000 angstrom and 3 mu m. Results. We demonstrate the power of the new grids with LTE and NLTE abundance analysis by means of equivalent width measurements of five benchmark stars; the Sun, Arcturus, HD 84937, HD 140283 and HD 122563. For Na, the NLTE abundances are lower than in LTE and show markedly reduced line-to-line scatter in the metal-poor stars. For Mg, we confirm previous reports of a significant similar to 0.25 dex LTE ionisation imbalance in metal-poor stars that is only slightly improved in NLTE (similar to 0.18 dex). LTE abundances based on Mg II lines agree better with models of Galactic chemical evolution. For Al, NLTE calculations strongly reduce an similar to 0.6 dex ionisation imbalance seen in LTE for the metal-poor stars. The abundance corrections presented in this work are in good agreement with previous studies for the subset of lines that overlap, with the exception of strongly saturated lines. Conclusions. A consensus between different abundance diagnostics is the most powerful tool available to stellar spectroscopists to assess the accuracy of the models. Here we report that NLTE abundance analysis in general leads to improved agreement, in particular for metal-poor stars. The residual scatter is believed to be caused mainly by unresolved blends and/or poor atomic data, with the notable exception of Mg, which calls for further investigation.Title in WoS: Non-LTE abundance corrections for late-type stars from 2000 angstrom to 3 mu m</p