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:
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RA (2000) DE Designation(s)
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16 23 35.22 -26 31 32.7 M4 = C 1620-264
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File Summary:
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FileName Lrecl Records Explanations
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ReadMe 80 . This file
table2.dat 111 75 Results of global seismic quantities, stellar
properties and mass estimates for our M4 stars
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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
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Bytes Format Units Label Explanations
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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☉)
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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.
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History:
From electronic version of the journal
(End) Luc Trabelsi [CDS] 07-Jul-2025