Mission Overview
Stellar Magnetism, Activity, and Rotation with Time Series ("SMARTS")
Primary Investigator: Zachary R. Claytor
HLSP Authors: Zachary R. Claytor, Jennifer L. van Saders, Joe Llama, Peter Sadowski, Brandon Quach, Ellis Avallone, Jamie Tayar
Released: 2022-03-03
Updated: 2025-07-01
Primary Reference(s): Claytor et al. 2022, Claytor & Tayar 2025
DOI: 10.17909/davg-m919
Citations: See ADS Metrics
Slideshow
SMARTS-TESS light curve simulation
Example of a SMARTS-TESS light curve simulation. A pure-simulation light curve is joined with a real TESS galaxy light curve to produce the final product: a simulated, stellar rotational light curve with real TESS noise and systematics.
Example of a SMARTS-TESS wavelet transform
Example of a SMARTS-TESS wavelet transform. Wavelet power spectra are binned to 64x64 pixels to serve as input to machine learning models as in Claytor et al. (2022).
Overview
Conventional methods of detecting stellar rotation from TESS light curves have struggled to obtain periods longer than 13.7 days due to complicated systematics related to the telescope's orbit. Machine learning has been shown to see beyond TESS's systematics and obtain long periods, but it requires large training sets with known rotation periods. Data Release 1 of "SMARTS" (Stellar Magnetism, Activity, and Rotation with Time Series) consists of a training set of synthetic light curves and binned wavelet transforms designed to mimic the full-frame image light curves of the TESS continuous viewing zones. The light curves were generated using the physically realistic spot evolution models in butterpy and include rotation, varying activity levels, magnetic cycles, spot emergence and decay, and latitudinal differential rotation. They are combined with real TESS galaxy light curves and stitched sector-to-sector to emulate TESS's systematics and noise.
In SMARTS DR2, the authors present a new training set based on the Kepler Bonus Background light curves (KBONUS-BKG, Martinez-Palomera et al. 2023). This training set was used to infer new rotation periods from de-blending Kepler sources using machine learning (Claytor & Tayar 2025). Like DR1, the light curves use butterpy simulations to create the rotational modulation, but use flattened KBONUS-BKG red clump light curves as the noise templates.
The SMARTS-TESS data and butterpy are fully described by Claytor et al. (2022), while the SMARTS-KBONUS data are described by Claytor & Tayar (2025). Each release contains 1 million simulations spanning rotation periods of 0.1—180 days. The butterpy package can interact with the SMARTS datasets and is installable through the Python package index via pip or on GitHub. Users of the SMARTS data set should cite the Primary Reference linked at the top-left of this page.
Update 07/01/25: DR2 adds 1 million new simulations based on KBONUS-BKG light curves.
Update 08/30/24: Added a catalog of simulation input parameters and data cube of light curve wavelet transforms.
Update 06/15/23: The original delivery of SMARTS included a corrupted file for simulation #408. This file has been fixed and is now included in hlsp_smarts_tess_ffi_001_tess_v1.0_sim.tar.gz.
Data Products
The SMARTS simulations are described by their input parameters contained in the catalogs, along with the data cube of their light curve wavelet transforms:
hlsp_smarts_tess_ffi_all_tess_v1.0_cat.tar.gz (TESS)
hlsp_smarts_kepler_kepler_all_kepler_v1.0_cat.tar.gz (KBONUS)
The SMARTS simulation files are ordered by rotation period in increments of 1 day, and bundled into groups with the following naming convention:
hlsp_smarts_<mission>_<detector>_<mmm>_<filter>_v1.0_sim.tar.gz
where:
- <mission> is the mission the light curves are based on, either "tess" or "kepler"
- <detector> is the detector, either "ffi" for TESS or "kepler" for Kepler Bonus
- <mmm> is the maximum rotation period in the group in days. e.g., "002" = periods of 1-2 days, "065" = periods of 64-65 days.
- <filter> is the filter for the flux column, either "tess" or "kepler"
Within the bundles, each file is named according to:
smarts-tess-v1.0-<simid>.fits (TESS)
hlsp_smarts_kepler_kepler_<simid>_kepler_v1.0_sim-lc.fits (KBONUS)
where:
- <simid> = the 6-digit, zero-padded simulation ID.
Data file types:
| _cat.tar.gz | Catalog of simulation input parameters and data cube of light curve wavelet transforms. |
| _sim.tar.gz |
Bundle of light curves organized by rotation period in increments of 1 day. |
| .fits |
Metadata, light curve, and wavelet transform corresponding to a single simulation. |
Data Access
Files can be downloaded directly from https://archive.stsci.edu/hlsps/smarts. The following tables include cURL scripts for downloading groups of SMARTS files in 10-day increments of simulated rotation period. Each group contains 10 files comprising ~5 GB of data for TESS or ~30 GB of data for KBONUS, and is named for the simulated rotation periods included in it (e.g., "011-020" = bundles of light curves with periods 11-20 days). A cURL script is also provided for downloading all simulation files ("All", downloads ~99 GB of data for TESS, ~500 GB for KBONUS). The last item in each table is the link to the catalog with simulation input parameters and light curve wavelet transforms (2 GB compressed, 4.2 GB uncompressed).