J/MNRAS/515/3184    Asteroseismology M4 study with K2 data       (Howell+, 2022)

Integrated mass-loss of evolved stars in M4 using asteroseismology. Howell M., Campbell S.W., Stello D., De Silva G.M. <Mon. Not. R. Astron. Soc. 515, 3184-3198 (2022)> =2022MNRAS.515.3184H 2022MNRAS.515.3184H (SIMBAD/NED BibCode)
ADC_Keywords: Asteroseismology ; Clusters, globular ; Optical ; Photometry ; Stars, variable ; Stars, giant ; Effective temperatures ; Stars, diameters ; Stars, masses Keywords: asteroseismology - stars: low-mass - stars: mass-loss - stars: oscillations - galaxies: star clusters: individual: NGC 6121 (M4) Abstract: Mass-loss remains a major uncertainty in stellar modelling. In low-mass stars, mass-loss is most significant on the red giant branch (RGB), and will impact the star's evolutionary path and final stellar remnant. Directly measuring the mass difference of stars in various phases of evolution represents one of the best ways to quantify integrated mass-loss. Globular clusters (GCs) are ideal objects for this. M4 is currently the only GC for which asteroseismic data exist for stars in multiple phases of evolution. Using K2 photometry, we report asteroseismic masses for 75 red giants in M4, the largest seismic sample in a GC to date. We find an integrated RGB mass-loss of ΔMavg = 0.17 ± 0.01 M, equivalent to a Reimers' mass-loss coefficient of ηR = 0.39. Our results for initial mass, horizontal branch mass, ηR, and integrated RGB mass-loss show remarkable agreement with previous studies, but with higher precision using asteroseismology. We also report the first detections of solar- like oscillations in early asymptotic giant branch (EAGB) stars in GCs. We find an average mass of Mavg,EAGB = 0.54 ± 0.01 M, significantly lower than predicted by models. This suggests larger-than-expected mass-loss on the horizontal branch. Alternatively, it could indicate unknown systematics in the scaling relations for the EAGB. We discover a tentative mass bimodality in the RGB sample, possibly due to the multiple populations. In our red horizontal branch sample, we find a mass distribution consistent with a single value. We emphasize the importance of seismic studies of GCs since they could potentially resolve major uncertainties in stellar theory. Description: In this study, we substantially increase the number of M4 evolved stars with detected solar-like oscillations. The increase in sample size allows us to reduce the uncertainties on the mean masses in each phase of evolution, thereby measuring a precise value for the integrated mass-loss. To achieve this we completed our own membership study and used our custom detrending pipeline for K2 data to estimate masses for stars in the RGB, RHB, and early AGB. To do so, we targeted M4 stars using their GaiaDR2 astrometric and photemetric data (i.e section 2.1). We then proceed to K2 light curve and power spectrum data extraction of 75 solar-like oscillations stars (i.e section 2.2). Next, as fully shown in section 3, we use K2 derived data to measure νmax and Δν. Then, stellar parameters as Teff, L*, R* and M* are computed using scalling relations and equations exhibited along the section 4 & 5. The retreived final results are presented in the table2.dat for the 75 stars. Objects: ---------------------------------------------------------------------------- RA (2000) DE Designation(s) ---------------------------------------------------------------------------- 16 23 35.22 -26 31 32.7 M4 = C 1620-264 ---------------------------------------------------------------------------- File Summary: -------------------------------------------------------------------------------- FileName Lrecl Records Explanations -------------------------------------------------------------------------------- ReadMe 80 . This file table2.dat 111 75 Results of global seismic quantities, stellar properties and mass estimates for our M4 stars -------------------------------------------------------------------------------- See also: I/345 : Gaia DR2 (Gaia Collaboration, 2018) IV/34 : K2 Ecliptic Plane Input Catalog (EPIC) (Huber+, 2017) VII/195 : Globular Clusters in the Milky Way (Harris, 1996) VII/202 : Globular Clusters in the Milky Way (Harris, 1997) VII/233 : 2MASS All-Sky Extended Source Catalog (XSC) (IPAC-UMass+, 2006) J/AJ/124/1486 : M4 UBV color-magnitude diagrams (Mochejska+, 2002) J/ApJ/765/L41 : Asteroseismic classification of KIC objects (Stello+, 2013) J/ApJ/835/83 : K2 GAP data release. I. Campaign 1 (Stello+, 2017) J/ApJS/251/23 : K2 GAP DR2: campaigns 4, 6 & 7 (Zinn+, 2020) J/ApJS/239/32 : APOKASC-2 catalog of Kepler evolved stars (Pinsonneault+, 2018) J/ApJS/236/42 : Asteroseismology of ∼16000 Kepler red giants (Yu+, 2018) J/ApJS/193/23 : Fundamental stellar parameters in 47 Tucanae (McDonald+, 2011) J/A+A/490/625 : Abundances of NGC 6121 red giants (Marino+, 2008) J/A+A/650/A115 : Seismic global parameters of 2103 KIC (Dreau+, 2021) J/A+A/616/A94 : KIC red giants radial modes amplitude & lifetime (Vrard+, 2018) J/MNRAS/505/5978 : Gaia EDR3 view on Galactic globular clusters (Vasiliev+, 2021) J/MNRAS/481/373 : Spectroscopic observations on M4 AGB stars (MacLean+, 2018) J/MNRAS/456/2260 : K2 Variability Catalogue II (Armstrong+, 2016) J/PASP/124/1279 : Q3 Kepler's combined photometry (Christiansen+, 2012) Byte-by-byte Description of file: table2.dat -------------------------------------------------------------------------------- Bytes Format Units Label Explanations -------------------------------------------------------------------------------- 1- 8 A8 --- ID Star identifier designation in M4 (ID) (1) 10- 28 I19 --- GaiaDR2 Gaia DR2 unique source identifier (GaiaDR2ID) 30- 34 F5.2 mag Gmag G-band mean magnitude (Vega) (Gmag) 36- 40 F5.1 uHz Numax The frequency of the maximum acoustic power (νmax) (2) 42- 44 F3.1 uHz e_Numax Mean uncertainty of Numax (errνmax) (2) 46- 50 F5.2 uHz DNu The large frequency spacing between adjacent overtone oscillation modes (Δν) (2) 52- 55 F4.2 uHz e_DNu Mean uncertainty of DNu (errΔν) (2) 57- 58 A2 --- f_ID Visual quality flag of power inspection (QF) (3) 60- 63 I4 K Teff Estimated effective temperature (Teff) (4) 65- 67 I3 K e_Teff Mean uncertainty of Teff (errTeff) 69- 73 F5.1 Lsun L* Star luminosities calculated with the equation 8 of the section 4.2 (L/L) 75- 78 F4.1 Lsun e_L* Random uncertainty of L* from statistic measurements (randomL/L) 80- 83 F4.1 Lsun dL* Systematic uncertainty of L* from used astrophysical parameters and methods (sysL/L) 85- 88 F4.1 Rsun R* Stellar radius calculated using the equation 9 of the section 4.2 (R/R) 90- 92 F3.1 Rsun e_R* Random uncertainty of R* from statistic measurements (randomR/R) 94- 96 F3.1 Rsun dR* Systematic uncertainty of R* from used astrophysical parameters and methods (sysR/R) 98-101 F4.2 Msun M* Estimated stellar mass using the scalling relation equation 3 of the section 1 suggesting this relation as the most accurate and reliable of the four (M3/M) 103-106 F4.2 Msun e_M* Random uncertainty of M* from statistic measurements (randomM3/M) 108-111 F4.2 Msun dM* Systematic uncertainty of M* from used astrophysical parameters and methods (sysM3/M) -------------------------------------------------------------------------------- Note (1): Star designation as "M4" + "Star type" +"Sub-type-number", for M4RGB16. In this sample, we have 5 AGBs, 59 RGBs and 11 RHBs, AGB stands for asymptotic giant branch, RGB stands for red giant branch and RHB is for red horizontal branch. Note (2): As explained in section 3, using the resultant light curves and power spectra, νmax and Δν were measured using the pySYD pipeline, which is an adaptation of the SYD pipeline. The pySYD pipeline uses optimized Lorentzian-based models for background fitting and heavy smoothing of the power spectrum to estimate νmax. To measure Δν, pySYD uses an autocorrelation function. The pipeline estimates uncertainties using a Monte Carlo sampling routine. This routine perturbs the power spectrum with stochastic noise. The background of the new perturbed spectrum is then fitted again, and new global seismic parameters are estimated. This is repeated 200 times for each star. Note (3): We adopted quality flags based on a visual inspection of the power spectra as follows: MD = Stars observed to have a 'noisy' (non-smoothly varying) power excess were labelled as marginal detections, 24 cases in our sample D = Otherwise, a 'correct' detection flag was assigned, 51 cases in our sample Note (4): As explicited in section 4.1, we use an extinction-independent method of calculating Teff such as spectroscopy. Since photometric temperatures are dependent on reddening corrections, and often show systematic differences between various colour-Teff relations, we offset the photometric temperatures by +81 K for stars without a spectroscopic temperature estimate. An uncertainty of 108 K was adopted for the scaled temperatures, derived from the addition in quadrature of the average spectroscopic uncertainty and the scatter of the difference between the two-temperature methods. -------------------------------------------------------------------------------- History: From electronic version of the journal
(End) Luc Trabelsi [CDS] 07-Jul-2025
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