Telluric correction in the near-infrared: Standard star or synthetic transmission?

Ulmer-Moll, S.; Figueira, P.; Neal, J. J.; Santos, N. C.; Bonnefoy, M.

doi:10.1051/0004-6361/201833282

Cited by 27 publications

(21 citation statements)

References 46 publications

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“…The fit's residuals deviate from unity by 1.0% on average, comparable to the unaffected regions of the spectrum and the performance of radiative transfer codes. (Ulmer-Moll, S. et al 2019). One potential flaw in our model is that modelling all points without significant telluric signal as unity creates discontinuities in the telluric wings, however, Figure 6 (bottom) indicates these discontinuities are small, and most users will prefer to mask affected pixels rather than dividing out.…”

Section: Model Goodness Of Fitmentioning

confidence: 99%

Toward a Self-calibrating, Empirical, Light-weight Model for Tellurics in High-resolution Spectra

Leet

Fischer

Valenti

2019

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To discover Earth analogs around other stars, next generation spectrographs must measure radial velocity (RV) with 10 cm/s precision. To achieve 10cm/s precision, however, the effects of telluric contamination must be accounted for. The standard approaches to telluric removal are: (a) observing a standard star and (b) using a radiative transfer code. Observing standard stars, however, takes valuable observing time away from science targets. Radiative transfer codes, meanwhile, rely on imprecise line data in the HITRAN database (typical line position uncertainties range from a few to several hundred m/s) and require difficult-to-obtain measurements of water vapor column density for best performance. To address these issues, we present SELENITE: a SELf-calibrating, Empricial, Light-Weight liNear regressIon TElluric model for high-resolution spectra. The model exploits two simple observations: (a) water tellurics grow proportionally to precipitable water vapor and therefore proportionally to each other and (b) non-water tellurics grow proportionally to airmass. Water tellurics can be identified by looking for pixels whose growth correlates with a known calibration water telluric and modelled by regression against it, and likewise non-water tellurics with airmass. The model doesn't require line data, water vapor measurements and additional observations (beyond one-time calibration observations), achieves fits with a χ 2 red of 1.17 on B stars and 2.95 on K dwarfs, and leaves residuals of 1% (B stars) and 1.1% (K dwarfs) of continuum. Fitting takes seconds on laptop PCs: SELENITE is light-weight enough to guide observing runs.

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Section: Model Goodness Of Fitmentioning

confidence: 99%

Toward a Self-calibrating, Empirical, Light-weight Model for Tellurics in High-resolution Spectra

Leet

Fischer

Valenti

2019

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“…On a final note, the method described here will certainly fail in the infrared where the lines density of water is too high. A possible solution would be to perform a first order correction by telluric lines modelling (Seifahrt et al 2010;Ulmer-Moll et al 2019) before applying the PCA as a second-stage correction on the residuals.…”

Section: Telluric Line Correctionmentioning

confidence: 99%

YARARA: Significant improvement in RV precision through post-processing of spectral time series

Cretignier

Dumusque

Hara

et al. 2021

A&A

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Aims. Even the most precise radial-velocity instruments gather high-resolution spectra that present systematic errors that a data reduction pipeline cannot identify and correct for efficiently by simply analysing a set of calibrations and a single science frame. In this paper we aim at improving the radial-velocity precision of HARPS measurements by 'cleaning' individual extracted spectra using the wealth of information contained in spectral time series. Methods. We developed YARARA, a post-processing pipeline designed to clean high-resolution spectra of instrumental systematics and atmospheric contamination. Spectra are corrected for: tellurics, interference patterns, detector stitching, ghosts, and fibre B contaminations, as well as more advanced spectral line-by-line corrections. YARARA uses principal component analysis on spectral time series with prior information to disentangle contaminations from real Doppler shifts. We applied YARARA to three systems, HD10700, HD215152, and HD10180, and compared our results to the standard HARPS data reduction software and the SERVAL post-processing pipeline.Results. We ran YARARA on the radial-velocity dataset of three stars intensively observed with HARPS: HD10700, HD215152, and HD10180. For HD10700, we show that YARARA enables us to obtain radial-velocity measurements that present an rms smaller than 1 m s −1 over the 13 years of the HARPS observations, which is 20% and 10% better than the HARPS data reduction software and the SERVAL post-processing pipeline, respectively. We also injected simulated planets into the data of HD10700 and demonstrated that YARARA does not alter pure Doppler-shifted signals. For HD215152, we demonstrated that the 1-year signal visible in the periodogram becomes marginal after processing with YARARA and that the signals of the known planets become more significant. Finally, for HD10180, the six known exoplanets are well recovered, although different orbital parameters and planetary masses are provided by the new reduced spectra. Conclusions. The post-processing correction of spectra using spectral time series allows the radial-velocity precision of HARPS data to be significantly improved and demonstrates that for the extremely quiet star HD10700 a radial-velocity rms better than 1 m/s can be reached over the 13 years of HARPS observations. Since the processing proposed in this paper does not absorb planetary signals, its application to intensively followed systems is promising and will certainly result in advances in the detections of the lightest exoplanets.

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“…A.1. Recent work by Ulmer-Moll et al (2019) demonstrated that MOLECFIT is an excellent tool for removing telluric lines from CRIRES spectra and that it performs better than the classical approach of using a telluric standard star. In our correction, each of the CRIRES detectors was treated independently.…”

Section: Observations and Data Reductionmentioning

confidence: 99%

Characterising the surface magnetic fields of T Tauri stars with high-resolution near-infrared spectroscopy

Lavail

Kochukhov

Hussain

2019

A&A

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Aims. In this paper, we aim to characterise the surface magnetic fields of a sample of eight T Tauri stars from high-resolution nearinfrared spectroscopy. Some stars in our sample are known to be magnetic from previous spectroscopic or spectropolarimetric studies. Our goals are firstly to apply Zeeman broadening modelling to T Tauri stars with high-resolution data, secondly to expand the sample of stars with measured surface magnetic field strengths, thirdly to investigate possible rotational or long-term magnetic variability by comparing spectral time series of given targets, and fourthly to compare the magnetic field modulus B tracing small-scale magnetic fields to those of large-scale magnetic fields derived by Stokes V Zeeman Doppler Imaging (ZDI) studies. Methods. We modelled the Zeeman broadening of magnetically sensitive spectral lines in the near-infrared K-band from highresolution spectra by using magnetic spectrum synthesis based on realistic model atmospheres and by using different descriptions of the surface magnetic field. We developped a Bayesian framework that selects the complexity of the magnetic field prescription based on the information contained in the data. Results. We obtain individual magnetic field measurements for each star in our sample using four different models. We find that the Bayesian Model 4 performs best in the range of magnetic fields measured on the sample (from 1.5 kG to 4.4 kG). We do not detect a strong rotational variation of B with a mean peak-to-peak variation of 0.3 kG. Our confidence intervals are of the same order of magnitude, which suggests that the Zeeman broadening is produced by a small-scale magnetic field homogeneously distributed over stellar surfaces. A comparison of our results with mean large-scale magnetic field measurements from Stokes V ZDI show different fractions of mean field strength being recovered, from 25-42% for relatively simple poloidal axisymmetric field topologies to 2-11% for more complex fields.

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Telluric correction in the near-infrared: Standard star or synthetic transmission?

Cited by 27 publications

References 46 publications

Toward a Self-calibrating, Empirical, Light-weight Model for Tellurics in High-resolution Spectra

Toward a Self-calibrating, Empirical, Light-weight Model for Tellurics in High-resolution Spectra

YARARA: Significant improvement in RV precision through post-processing of spectral time series

Characterising the surface magnetic fields of T Tauri stars with high-resolution near-infrared spectroscopy

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