With this package that builds on lightkurve, you can reduce TESS data while preserving transient signals. You can supply a TPF or give coordinates and sector to construct a TPF with TESScut. The background subtraction accounts for the smooth background and detector straps. Alongisde background subtraction TESSreduce also aligns images, performs difference imaging, and can even detect transient events!

An additional component that is in development is calibration of TESS photometry, and reliably link muti-sector light curves.

TESSreduce can be installed through pip:

pip install git+https://github.com/CheerfulUser/TESSreduce.git

Example reduction for SN 2018fub:

import tessreduce as tr
obs = tr.sn_lookup('sn2018fub')

|   Sector | Covers   |   Time difference  |
|          |          |             (days) |
|----------+----------+--------------------|
|        2 | True     |                  0 |
|       29 | False    |                721 |

tess = tr.tessreduce(obs_list=obs)

OR

import tessreduce as tr
ra = 10.127
dec = -50.687
sector = 2
tess = tr.tessreduce(ra=ra,dec=dec,sector=sector)

If you have a downloaded TPF you can load that directly into tessreduce.

tess = tr.tessreduce(tpf='file')

Photometry method

TESSreduce can perform aperture and PSF photometry. The photometry method used is set by the phot_method option which can either be aperture or psf. In general the PSF method appears to be more robust, however, there are cases where aperture still provides a better lightcurve. The default method is aperture. Using the example above we can use different photometry methods as follows.

tess = tr.tessreduce(obs_list=obs,phot_method='psf') # runs PSF photometry for reduction
tess = tr.tessreduce(obs_list=obs,phot_method='aperture') # runs aperture photometry for reduction

You can also define the photometry method when creating a lightcurve with diff_lc as follows.

lc, sky = tess.diff_lc(phot_method='psf')

The PRF photometry method uses the TESS_PRF package which can be found here: https://github.com/keatonb/TESS_PRF

Flux calibration

TESSreduce can calibrate TESS counts to physical flux, or AB magnitudes, by using PS1 data, If your field is dec >-30, and SkyMapper data for Southern field. IF you want a flux calibrated light curve then use:

tess.to_flux()

OR

tess.to_mag()

Several options are available for flux and are interchangeable, however, mag is currently not reversible. To easily plot the resulting light curve:

tess.plotter()

Extracting key variables

The main variables that TESSreduce assigns during the reduction can be accessed as follows:

• flux: tess.flux
• background: tess.bkg
• reference: tess.ref
• reference index: tess.ref_ind
• lightcurve: tess.lc
• Mask: tess.mask
• Source catalog: tess.cat

TESS data can be complicated, and there are a lot of other functions burried in TESSreduce, so if you want some guidence on how to do a specific analysis contact me at: [email protected]

Example reductions

We include a few notebooks for some possible reductions and science cases in the examples folder.

Citing TESSreduce

If you make use of TESSreduce, please cite Ridden-Harper et al. (2021):

@ARTICLE{2021arXiv211115006R,
       author = {{Ridden-Harper}, R. and {Rest}, A. and {Hounsell}, R. and {M{\"u}ller-Bravo}, T.~E. and {Wang}, Q. and {Villar}, V.~A.},
        title = "{TESSreduce: transient focused TESS data reduction pipeline}",
      journal = {arXiv e-prints},
     keywords = {Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena},
         year = 2021,
        month = nov,
          eid = {arXiv:2111.15006},
        pages = {arXiv:2111.15006},
archivePrefix = {arXiv},
       eprint = {2111.15006},
 primaryClass = {astro-ph.IM},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2021arXiv211115006R},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}