DOI: 10.5281/zenodo.15130190
title: Reduced CRIRES+ spectroscopy observations of GJ 3470

description:  Reduced CRIRES+ spectroscopy observations of GJ 3470 from 2022-02-10

This records contains yet unpublished reduced data obtained with the CRIRES+ spectrograph at the Very Large Telescope. The time-series of observations was acquired covering a transit of the exoplanet GJ3470b. The raw data from the CRIRES+ instrument were reduced using the instrument pipeline and the reduction steps are identical as the step described in e.g Lesjak et al. 2024 "Retrieving wind properties from the ultra-hot dayside of WASP-189 b with CRIRES+".

Acknowledgements

If you make use of this data in your research, please cite this record with its DOI (10.5281/zenodo.15130190) and its reference, the bibtex reference is:

@dataset{lavail_2025_15130190,  author       = {Lavail, Alexis and                  Chabrol, Estelle},  title        = {Reduced CRIRES+ spectroscopy observations of GJ                    3470                  },  month        = apr,  year         = 2025,  publisher    = {Zenodo},  doi          = {10.5281/zenodo.15130190},  url          = {https://doi.org/10.5281/zenodo.15130190},}

Note also that ESO requests an acknowledgement, which in this case would be: "Based on observations made with ESO Telescopes at the La Silla Paranal Observatory under programme ID 108.22PH.003".

This data is released under a Creative Commons Attribution 4.0 International license.

Format of the data

The data are contained in a pickle file. Instructions on how to read pickle files can be found on the python wiki at https://wiki.python.org/moin/UsingPickle:

import pickle
data = pickle.load(open('GJ3470-220209.pickle','rb'))

The data consists of a dictionary, the keys can be explored with the following command:

print(data.keys())The keys are the following:



'script_version',

'nodpos',

'rawfilename',

'nodpair',

'wave', 

'wave_modelA',

'wave_modelB',

'spec', 

'err', 

'snr',

'airmass',

'bjd_tdb',

'berv',

'orders',

'spec_interpolated',

'tell',

'rawheaders',

'slitfunctionFWHM-det1',

'slitfunctionFWHM-det2',

'slitfunctionFWHM-det3'


The keys in boldface (wave, spec, err) contain the reduced data, respectively the wavelength (expressed in vacuum in nanometres), the extracted spectrum (in ADU), and the error spectrum (in ADU). The other keys contain metadata and supplementary information as explained below. Each key contains a numPy array. The shape of the arrays can be expressed using three sizes:



n_obs: the number of observations in the dataset

n_pix = 2008: the number of pixels in each segment

n_orders : the numbers of segment (each spectral order is split over three detectors creating three segments)


The size of each array can be investigated with e.g

for key in data.keys():
    try:
        print(key,':', data[key].shape)
    except:
        print(key)


which results in

script_versionnodpos : (46,)rawfilename : (46,)nodpair : (46,)wave : (19, 46, 2008)wave_modelA : (19, 2008)wave_modelB : (19, 2008)spec : (19, 46, 2008)err : (19, 46, 2008)snr : (19, 46)airmass : (46,)bjd_tdb : (46,)berv : (46,)orders : (19,)spec_interpolated : (19, 46, 2008)tell : (19, 2008)rawheaders : (46, 2484, 3)slitfunctionFWHM-det1 : (46, 8, 3)slitfunctionFWHM-det2 : (46, 7, 3)slitfunctionFWHM-det3 : (46, 7, 3)

What's in the data?



script_version: version number of the python script used to produce the data

nodpos: string, ('A' or 'B') the nodding position of the observation

rawfilename: string, the filename of the raw science file from the ESO archive 

nodpair: string, ('pairNN') where NN is the number of nodding pair used in the data reduction: science files are reduced in pair with one nodding 'A' spectrum and one 'B'

wave: array containing the pipeline-derived wavelength solution for the spectrum in nanometers in vacuum

wave_modelA: refined and more precise wavelength solution for spectra in nodding position A, using molecfit fitting the telluric spectrum

wave_modelB: refined and more precise wavelength solution for spectra in nodding position B, using molecfit fitting the telluric spectrum

spec: reduced spectrum in ADU from the CRIRES+ pipeline. 

err: the error spectrum in ADU corresponding to the spec (signal to noise ration can be computed using spec/err)

snr: median signal to noise ratio for each segment/observation

airmass: airmass for each observation taken from the raw file header (mean of airmass at start and end of each exposure)

bjd_tdb: bjd_tdb (barycentric julian date expressed in temps dynamique barycentrique) time at the middle of the exposure computed with barycorrpy (https://github.com/shbhuk/barycorrpy)

berv: berv correction at middle of exposure computed with barycorrpy

orders: string (D-OO) identifying the segment where D is the detector number (1-3) and OO is the order number (02-08)

spec_interpolated: the spectrum array (spec) interpolated on the wave_modelA wavelength solution

tell: a telluric spectrum as output by molecfit.

rawheaders: the fits header from the raw science files

slitfunctionFWHM-det1: contains information on the FWHM of the slit function taken from the reduced file headers for the orders of detector 1

slitfunctionFWHM-det2: same for detector 2

slitfunctionFWHM-det3: same for detector 3