README file for TESS-SVC: TESS Stellar Variability Catalog
MAST webpage: https://archive.stsci.edu/hlsp/tess-svc
Refer to this HLSP with DOI: https://doi.org/10.17909/f8pz-vj63
########## Data Columns:
tess_id: (int) TESS Input Catalog object identifier
Solution: (string) Best model from variability analysis; can be Single-sinusoidal (1sin), Double-sinusoidal (2sin), or Auto-Correlation Function (acf)
Sector: (string) TESS Sector number from which this variability analysis is extracted; sp indicates the short-period periodogram search (0.01-1.5 days) was preferred
period_var(_1,_2): (float) Measured photometric variability period (days)
period_var_uncert(_1,_2): (float) Uncertainty in the measured photometric variability period (days)
amp_var(_1,_2): (float) Flux amplitude of photometric variability (ppm)
amp_var_uncert(_1,_2): (float) Uncertainty in the flux amplitude of photometric variability (ppm)
bjd0_var(_1,_2): (float) Time offset for sinusoidal fit to the photometric variability (days)
bjd0_var_uncert(_1,_2): (float) Uncertainty in the time offset for sinusoidal fit to the photometric variability (days)
offset(_1,_2): (float) Average flux offset of light curve (ppm)
power(_1,_2,correlation): (float) Normalized Lomb-Scargle periodogram power or maximum correlation of the Auto-Correlation Function
RMS_no(_1,_2): (float) Root-Mean-Square of light curve relative to average flux (ppm)
RMS_line(_1,_2): (float) Root-Mean-Square of light curve with linear function fit (ppm)
RMS_sin(_1,_2): (float) Root-Mean-Square of light curve with sinusoidal function (ppm)
bRMS_no(_1,_2): (float) Binned Root-Mean-Square of light curve relative to average flux (ppm)
bRMS_sin(_1,_2): (float) Binned Root-Mean-Square of light curve with sinusoidal function (ppm)
Chi2_no(_1,_2): (float) Reduced chi-squared statistic relative to average flux
Chi2_line(_1,_2): (float) Reduced chi-squared statistic relative to linear function fit
Chi2_sin(_1,_2): (float) Reduced chi-squared statistic relative to sinusoidal function
bChi2_no(_1,_2): (float) Reduced chi-squared statistic relative to binned average flux
bChi2_sin(_1,_2): (float) Reduced chi-squared statistic relative to binned sinusoidal function
thrust_med(_1,_2): (float) Median timing of spacecraft thruster firing relative to the phase of the measured photometric variability
thrust_std(_1,_2): (float) Standard deviation timing of spacecraft thruster firings relative to the phase of the measured photometric variability
slope: (float) Slope of linear function fit to light curve
lum_calc: (float) Stellar luminosity; calculated from stellar effective temperature and stellar radius (solLum)
All remaining columns are sourced directly from the TESS Input Catalog (Stassun et al. 2018; Stassun et al. 2019). Column descriptions can be found in the Data Release Notes for the TESS Input Catalog (TIC) and Candidate Target List (CTL).
########## Summary:
The TESS Stellar Variability Catalog (TESS-SVC) describes which stars among those observed at 2-min cadence in the TESS light curve photometry show periodic variability over the timescales of 0.01 to 13 days. The TESS-SVC includes a broad range of periodic variable stars (rotation, pulsation, eclipsing binaries, etc.) that were selected based on the photometric periodogram analysis described in Fetherolf et al. (2023). Each star in the TESS-SVC includes the measured period of photometric variability, time and amplitude of the maximum flux, significance of the detected variability signal, properties extracted from the TESS Input Catalog, and a summary figure. Each summary figure shows the full TESS light curve (left panels), Lomb-Scargle periodogram or auto-correlation function (center panels), and the light curve phase-folded on the measured photometric variability period (right panels). The periodogram results provided are extracted from a single sector of TESS PDCSAP photometry, and the method for selecting the specific sector for stars observed in multiple TESS sectors is described in Fetherolf et al. (2023). A visualization tool for this dataset is also available at: https://filtergraph.com/tessvariability
The current version of the TESS-SVC (v1.0) includes 84,046 stars that are considered significantly variable on timescales of 0.01-13 days based on the stars that were observed at 2-min cadence during the TESS Prime Mission (Sectors 1-26). There are 68,497 stars with photometric variability that is best described by a single-sinusoidal function (1sin), 10,887 stars with photometric variability that is best described by a double-sinusoidal function (2sin), and 4662 stars with photometric variability that is best described by an auto-correlation function (acf). The catalog will continue to be updated as new sectors become available, and will later include stars that exhibit photometric variability on timescales longer than 13 days.
########## Data products:
The full catalog's file name in v1.0 is "hlsp_tess-svc_tess_lcf_all-s0001-s0026_tess_v1.0_cat.csv", which will change in future data releases following this pattern:
hlsp_tess-svc_tess_lcf_-_tess__cat.csv
where:
= a designation of the method that best described the photometric variability, which can be a single-sinusoidal function (1sin), double-sinusoidal function (2sin), or auto-correlation function (acf). The combined variability catalog is represented by "all" and contains an additional "Solution" column.
= the dash-separated range of sectors covered by the catalog. In v1.0, this field is s0001-s0026, meaning TESS Sectors 1 through 26.
= MAST version number of the catalog, e.g. "v1.0".
The summary figures show the results from the variability analysis and their naming follows this pattern:
hlsp_tess-svc_tess_lcf_tic_tess__img.png
where:
= TESS Input Catalog object identifier
= MAST version number of the catalog, e.g. "v1.0".
########## HLSP authors:
Tara Fetherolf (University of California, Riverside, USA)
Joshua Pepper (Lehigh University, USA)
Emilie Simpson (SETI Institute, USA)
Stephen R. Kane (University of California, Riverside, USA)
Teo Mocnik (Gemini Observatory/NSF's NOIRLab, USA)
John Edward English (University of California, Irvine, USA)
Victoria Antoci (Technical University of Denmark, Denmark)
Daniel Huber (University of Hawai'i, USA)
Jon M. Jenkins (NASA Ames Research Center, USA)
Keivan Stassun (Vanderbilt University, USA)
Joseph D. Twicken (SETI Institute, USA)
Roland Vanderspek (Massachusetts Institute of Technology, USA)
Joshua N. Winn (Princeton University, USA)
########## References:
Fetherolf et al. 2023, ApJS, (in press)