TS-Stellar: Unified Stellar Analysis

Updated 29 November 2025

TS-Stellar is a comprehensive framework integrating databases, methodologies, and processing pipelines to measure and model stellar time-series, magnetic activity, and contamination effects in exoplanet studies.
It consolidates long-baseline activity records, cross-matched survey catalogs, and advanced photometric pipelines to enable robust variability analyses and empirical investigations of stellar evolution.
It employs Bayesian retrieval and dynamical modeling techniques to correct stellar contamination in transit spectra and to calibrate dynamo theories using asteroseismic data.

TS-Stellar is a collective term encompassing databases, methodologies, and frameworks for the measurement, analysis, and modeling of stellar time-series and properties, particularly as they pertain to magnetic activity, stellar evolution, observational characterization, and contamination effects in exoplanet studies. TS-Stellar solutions aggregate published time-series observations, provide cross-matched catalogs for survey missions, enable robust processing pipelines, and facilitate quantitative modeling and retrieval in exoplanet transmission spectroscopy and dynamical studies.

1. Time Series Databases: Sunstardb and Solar–Stellar Connection

The Sunstardb database is designed to standardize the aggregation and analysis of stellar magnetic activity records, which are essential for solar–stellar connection research. Decades-long time-series of magnetic proxies such as the Mount Wilson S-index, $R'_{HK}$ , X-ray flux, and rotational/cycle periods are scattered across literature and disparate databases. Sunstardb consolidates these into a relational PostgreSQL data model keyed by star names and aliases, ensuring unambiguous star-datatype-provenance mapping, fine-grained provenance, and support for both scalar and time-series measurements. Specialized data tables for each property (dat_S_mean, dat_Rprime_HK, dat_P_rot) and for time-series (dat_S_ts, dat_Rprime_HK_ts, etc.) provide consistent storage of values, uncertainties, time, duration, and per-datum metadata via JSONB columns.

Sunstardb exposes these records via fast Python and SQL interfaces, supporting queries for long-baseline activity series, filtering by time coverage, and integration with cycle-search algorithms (e.g., Lomb–Scargle for $P_{\text{cyc}}$ estimation). These design principles eliminate ad-hoc catalog cross-matching, lower the barrier to assembling large homogeneous cycle-analysis datasets, and directly support the empirical and theoretical study of stellar magnetic dynamos (Egeland, 2018).

2. Survey Property Catalogs: K2–TESS Database

The K2–TESS Stellar Properties Catalog is a cross-matched repository offering homogeneous stellar parameters for Kepler/K2 targets, synthesized via positional tolerance matching ($1''$) between the TESS Target Catalog (primarily 2MASS $J<13$ ) and the Kepler EPIC catalog. Following further augmentation with NOMAD, Tycho-2, Hipparcos, APASS, UCAC4, and dedicated M-dwarf lists, the catalog provides 117,521 vetted targets (plus a faint-extended subset) with robust identifiers, coordinates, multi-band photometry ( $JHK, V$ , Kepler-band), proper motions, and luminosity-class flags (dwarf/giant/subgiant via reduced proper motion, RPM).

Key methodologies include empirical color– $T_{\text{eff}}$ relations for dwarfs, subgiants, and giants (using $(V-K_S)$ and, where available, [Fe/H]), with fully propagated uncertainties. Spectroscopic cross-matches with APOGEE, RAVE, and LAMOST supplement the data, providing independently measured $T_{\text{eff}}$ , $\log g$ , and metallicity for select subsets. The catalog’s interactive portal supports map and tabular views and is optimized for bulk downloads required for population studies, luminosity-function modeling, and selection in exoplanet surveys (Stassun et al., 2014).

3. Photometric Time-Series Processing: STRESS Survey Pipeline

The STRESS (STEREO TRansiting Exoplanet and Stellar Survey) pipeline is oriented toward the reduction and analysis of wide-field, high-cadence stellar photometry from the STEREO/HI-1 and HI-2 imagers. The pipeline encompasses bias/dark subtraction, flat-fielding, pixel-specific corrections for "shutterless" CCD readouts, robust F-corona background subtraction, catalog-based source extraction (NOMAD, $R<12$ ), confusion filtering for crowded fields, PSF/centroiding, and rigorous aperture photometry with fully accounted error budgets (photon, sky, read noise).

Detrending and variability analysis utilize 3 hr and 1 d boxcar smoothing, polynomial fits, and outlier rejection (interquartile range diagnostics). Transit and variability searches deploy Lomb–Scargle, phase-dispersion minimization, and box-fitting least squares, with ongoing exploration of advanced trend-filtering (SysRem, TFA). The pipeline achieves $P_{\text{cyc}}$ 0 relative precision for bright stars ( $P_{\text{cyc}}$ 1), delivers multi-month light curves for millions of targets, and has demonstrated the recovery and discovery of numerous variable/eclipsing systems, complementing Kepler/TESS capabilities (Sangaralingam et al., 2011).

4. Forward Modeling and Retrieval: STCTM for Stellar Contamination

STCTM (STellar ConTamination Modeling) is a Bayesian retrieval framework that addresses the Transit Light Source Effect (TLSE)—the contamination of exoplanetary transmission spectra by stellar surface heterogeneity. The forward model constructs disk-integrated stellar flux as a mixture of quiescent and heterogeneous spectra (spots, faculae), parameterized by filling factors and temperatures. The effective transit-depth correction,

$P_{\text{cyc}}$ 2

is solved jointly for stellar and planetary parameters using Markov-chain Monte Carlo (emcee), with arbitrary priors and parallel sampling. The exotune sub-module enables fitting of out-of-transit spectra to derive empirical priors on spot/facula coverings and temperatures, feeding back into TLSE mitigation.

Diagnostic outputs include posterior samples, best-fit spectra, contamination transfer functions, and publication-quality figures. Case studies on TRAPPIST-1, GJ 9827, and GJ 3090 have shown that 1–5% spot covering can dominate apparent transmission signals, necessitating careful stellar contamination modeling for robust exoplanet atmosphere interpretation (Piaulet-Ghorayeb, 25 Aug 2025).

5. Tidal Stream Catalogs and Dynamical Modeling

The Stellar Tidal Stream Survey systematically images external Milky-Way analogs to detect and characterize faint tidal stellar streams—key tracers of hierarchical assembly predicted by $P_{\text{cyc}}$ 3CDM cosmology. Using robotic, privately-owned telescopes, the Survey achieves $P_{\text{cyc}}$ 4 surface-brightness limits of $P_{\text{cyc}}$ 5 mag arcsec $P_{\text{cyc}}$ 6, uncovering $P_{\text{cyc}}$ 750 streams around 50 hosts with diverse morphologies (great-circle loops, umbrella-shaped plumes, shells, jets, and active tidal tails).

The data pipeline entails meticulous flat-fielding, background modeling, artifact masking, and isophotal analysis to derive surface brightness, physical scales, and luminosities. N-body orbital reconstructions and mass-fitting (e.g., for NGC 5907 and NGC 1097) allow inference of host halo mass profiles and shapes. The empirical frequency (1 stream per galaxy at $P_{\text{cyc}}$ 8 mag arcsec $P_{\text{cyc}}$ 9) matches simulation forecasts, providing strong validation of $1''$0CDM merger rates and halo structure. Planned extensions include deeper imaging, spectroscopic campaigns for velocity/metallicity, and eventual application of 6D phase-space modeling techniques (Martinez-Delgado, 2018).

6. Dynamo Theory and Asteroseismic Calibration: Tayler–Spruit Modeling

TS-Stellar research also encompasses modeling and calibration of angular momentum transport mechanisms in stellar interiors. Eggenberger et al. (2024) present a general formulation for the Tayler–Spruit (TS) dynamo, integrating shellular rotation, meridional circulation, and magnetic instabilities. The effective angular momentum diffusivity is given by

$1''$1

where $1''$2 is a dimensionless calibration factor for field damping timescales, $1''$3 is angular velocity, $1''$4 quantifies shear, and $1''$5 is the thermally reduced buoyancy frequency. A crucial empirical finding is that $1''$6—a factor $1''$7200 larger than the original Spruit prescription—is required to reproduce observed slow core-rotation rates from Kepler asteroseismology in subgiant and red giant stars.

This mass-independence of core spin-down is consistent across Geneva and MESA models, robustly explaining the absence of an $1''$8–$1''$9 correlation, and providing a predictive framework for RGB, clump, and subgiant rotational evolution. This calibration reconciles theoretical dynamo efficiency with large Kepler and ground-based datasets, and is straightforward to implement in leading stellar evolution codes (Eggenberger et al., 2023).

TS-Stellar unifies several key domains: long-baseline magnetic activity databases, cross-matched survey catalogs, advanced photometric pipelines, forward modeling of stellar contamination in exoplanet spectroscopy, statistical catalogs of external tidal streams, and physically calibrated dynamo theory. Collectively, these resources enable high-fidelity empirical and theoretical studies of stellar evolution, magnetic activity cycles, variable stars, exoplanet characterization, and galactic assembly, supporting a broad spectrum of contemporary stellar astrophysics research.