Evolved Stars: Identification Methods, Variability Mechanisms, and Applications

Evolved stars from red giant branch and asymptotic giant branch stars to red supergiants, govern late-stage mass loss and chemical enrichment. Their exceptional near-infrared brightness and distinctive variability make them key probes of galactic structure and evolution, as well as natural laboratories for stellar oscillation and convection theory. In recent years, coordinated space- and ground-based observing campaigns have begun to build new, multi-timescale and multi-metallicity samples of evolved stars, laying the foundation for subsequent physical studies and applications. High-precision astrometry and multiband photometry from Gaia and JWST/HST, together with diverse time-domain surveys, have accelerated observational and modeling advances in pulsation and granulation. These developments have sharpened constraints on the internal physics of evolved stars and strengthened their use as standard candles via near-infrared period-luminosity relations. Moreover, evolved stars serve as powerful astrophysical tracers, enabling high-resolution extinction maps, the reconstruction of stellar populations and star formation histories, and the characterization of dust-gas coupling and galaxy-scale structure.This Research Topic aims to integrate observational, methodological, and theoretical progress to: (1) Establish robust identification of evolved-star samples, quantify selection effects, completeness, and purity across different strategies, and develop reusable datasets. (2) Advance a comprehensive understanding of variability mechanisms by linking observations with models, clarifying the relative roles of pulsation, convection, and long secondary periods, and tightening constraints on internal structure and mass-loss processes. (3) Calibrate and unify period-luminosity relations, especially in the near-infrared, while assessing their systematics as distance indicators and external calibrators. (4) Demonstrate the breadth of applications of evolved stars as astrophysical probes, including the construction and cross-calibration of resolved extinction maps, improving stellar-population inferences and star formation history recovery, and mapping metallicity gradients.To gather further insights across evolved-star populations, their variability, physical processes, and astrophysical applications, we welcome contributions addressing, but not limited to, the following themes: 1. Sample identification and classification: Gaia astrometry; photometric color–color and color–magnitude diagrams; machine-learning and probabilistic frameworks; and the assessment and mitigation of foreground, quasar, and asymptotic giant branch contamination.2. Variability mechanisms: Mode identification and period–luminosity relation calibration; statistical modeling of granulation and irregular variability (e.g., continuous-time autoregressive moving-average models and Gaussian-process models); long secondary periods and binary effects; three-dimensional radiative–hydrodynamic simulations compared with observations.3. Applications: Construction of resolved extinction maps and cross-calibration with gas and dust indicators; star formation history and metallicity gradients; mass loss, dust yields, and feedback; distance measurements and external calibration.Article types: Original Research, Review. We encourage open data and code. Topic editors: Yi Ren, Mingxu Sun Source: https://www.frontiersin.org/research-topics/85966/evolved-stars-identification-methods-variability-mechanisms-and-applications