The role of carbon in red giant spectro-seismology

Abstract: Although red clump stars function as reliable standard candles, their surface characteristics (i.e. $T_\text{eff}$, $\log g$, and [Fe/H]) overlap with those of red giant branch stars, which are not standard candles. Recent results have revealed that spectral features containing carbon (e.g. CN molecular bands) carry information correlating with the "gold-standard" asteroseismic classifiers that distinguish red clump from red giant branch stars. However, the underlying astrophysical processes driving the correlation between these spectroscopic and asteroseismic quantities in red giants remain inadequately explored. This study aims to enhance our understanding of this "spectro-seismic" effect, by refining the list of key spectral features predicting red giant evolutionary state. In addition, we conduct further investigation into those key spectral features to probe the astrophysical processes driving this connection. We employ the data-driven The Cannon algorithm to analyse high-resolution ($R\sim80,000$) Veloce Rosso spectra from the Anglo-Australian Telescope for 301 red giant stars (where asteroseismic classifications from the TESS mission are known for 123 of the stars). The results highlight molecular spectroscopic features, particularly those containing carbon (e.g. CN), as the primary indicators of the evolutionary states of red giant stars. Furthermore, by investigating CN isotopic pairs (that is, $^{12}$C$^{14}$N and $^{13}$C$^{14}$N) we find suggestions of statistically significant differences in the reduced equivalent widths of such lines, suggesting that physical processes that change the surface abundances and isotopic ratios in red giant stars, such as deep mixing, are the driving forces of the "spectro-seismic" connection of red giants.

• The paper demonstrates that CN molecular bands driven by carbon abundance offer a reliable way to differentiate red clump stars from RGB stars.
• It employs high-resolution Veloce Rosso spectra and the data-driven algorithm The Cannon to correlate spectroscopic indicators with seismic classifications.
• The findings enhance spectroscopic survey capabilities, improving our mapping of stellar populations and insights into red giant internal processes.

The Role of Carbon in Red Giant Spectro-seismology

This study investigates the spectral characteristics of red giant stars, with a focus on distinguishing red clump (RC) stars from those on the red giant branch (RGB) using spectro-seismology. Despite their similar surface features, RC stars are effective standard candles due to their stable luminosity, a property that facilitates detailed galactic studies. Identifying RC stars through spectroscopy has traditionally been challenging because their parameters (, log $g$, and [Fe/H]) often overlap with those of RGB stars. However, the recent integration of asteroseismic data has improved the differentiation by capturing the distinct internal structures.

The paper leverages high-resolution Veloce Rosso spectra to analyze key spectral features associated with the evolutionary states of red giants. Using the data-driven algorithm, The Cannon, the researchers extract spectroscopic indicators that correlate with asteroseismic classifications derived from the TESS mission. Notably, molecular features, particularly those involving carbon, such as CN molecular bands, emerge as primary discriminants between RC and RGB stars. This finding corroborates past work indicating the significance of CN features due to mixing processes on the RGB that alter the surface abundances of carbon and nitrogen.

In examining 301 red giant stars with known asteroseismic classifications for 123 of them, the study presents a refined list of spectral features that serve as reliable predictors of red giant evolutionary state. The investigation into CN isotopic pairs suggests statistically significant differences in the line strengths of 12\ and 13\ isotopes, hinting at physical processes like deep mixing being influential in the spectro-seismic connection. This blend of spectroscopic and seismic data promises enhanced accuracy in classifying red giants, which holds substantial implications for galactic archaeology, particularly in mapping stellar populations and their distribution across the Galaxy.

The implications of this research are twofold. Practically, the ability to spectroscopically classify RC stars more efficiently expands the potential for high-volume spectroscopic surveys across the Galaxy. Theoretically, the study advances our understanding of the internal processes in red giants that lead to observable changes in their spectroscopic signatures. As spectroscopic technology continues to advance, future research may explore the chemical peculiarities of red giants, offering more insight into the intricate evolution of stars and the broader structure of our Galaxy. The integration of high-resolution spectroscopy with asteroseismology stands to revolutionize our ability to conduct precise stellar and galactic studies.