اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدOn aging star clusters using red supergiants independent of the fraction of interacting binary stars
87
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We use the Binary Population and Spectral Synthesis (BPASS) models to test the recent suggestion that red supergiants can provide an accurate age estimate of a co-eval stellar population that is unaffected by interacting binary stars. Ages are estimated by using both the minimum luminosity red supergiant and the mean luminosity of red supergiants in a cluster. We test these methods on a number of observed star clusters and find our results in agreement with previous estimates. Importantly we find the difference between the ages derived from stellar population models with and without a realistic population of interacting binary stars is only a few 100,000 years at most. We find that the mean luminosity of red supergiants in a cluster is the best method to determine the age of a cluster because it is based o the entire red supergiant population rather than using only the least luminous red supergiant.
قيم البحث
اقرأ أيضاً
The binary fraction of unevolved massive stars is thought to be 70-100% but there are few observational constraints on the binary fraction of the evolved version of a subset of these stars, the red supergiants (RSGs). Here we identify a complete samp
le of RSGs in the Large Magellanic Cloud (LMC) using new spectroscopic observations and archival UV, IR and broadband optical photometry. We find 4090 RSGs with log L/Lo > 3.5 with 1820 of them having log L/Lo > 4, which we believe is our completeness limit. We additionally spectroscopically confirmed 38 new RSG+B star binaries in the LMC, bringing the total known up to 55. We then estimated the binary fraction using a k-nearest neighbors algorithm that classifies stars as single or binary based on photometry with a spectroscopic sample as a training set. We take into account observational biases such as line-of-sight stars and binaries in eclipse while also calculating model-dependent corrections for RSGs with companions that our observations were not designed to detect. Based on our data, we find an initial result of 13.5 +7.56/-6.67% for RSGs with O or B-type companions. Using the Binary Population and Spectral Synthesis (BPASS) models to correct for unobserved systems, this corresponds to a total RSG binary fraction of 19.5 +7.6/-6.7%. This number is in broad agreement with what we would expect given an initial OB binary distribution of 70%, a predicted merger fraction of 20-30% and a binary interaction fraction of 40-50%.
Galactic, young massive star clusters are approximately coeval aggregates of stars, close enough to resolve the individual stars, massive enough to have produced large numbers of massive stars, and young enough for these stars to be in a pre-supernov
a state. As such these objects represent powerful natural laboratories in which to study the evolution of massive stars. To be used in this way, it is crucial that accurate and precise distances are known, since this affects both the inferred luminosities of the cluster members and the age estimate for the cluster itself. Here we present distance estimates for three star clusters rich in Red Supergiants ($chi$ Per, NGC 7419 and Westerlund 1) based on their average astrometric parallaxes $bar{pi}$ in Gaia Data Release 2, where the measurement of $bar{pi}$ is obtained from a proper-motion screened sample of spectroscopically-confirmed cluster members. We determine distances of $d=2.25^{+0.16}_{-0.14}$kpc, $d=3.00^{+0.35}_{-0.29}$kpc, and $d=3.87^{+0.95}_{-0.64}$kpc for the three clusters respectively. We find that the dominant source of error is that in Gaias zero-point parallax offset $pi_{rm ZP}$, and we argue that more precise distances cannot be determined without an improved characterization of this quantity.
Populations of massive stars are directly reflective of the physics of stellar evolution. Counting subtypes of massive stars and ratios of massive stars in different evolutionary states have been used ubiquitously as diagnostics of age and metallicit
y effects. While the binary fraction of massive stars is significant, inferences are often based upon models incorporating only single-star evolution. In this work, we utilize custom synthetic stellar populations from the Binary Population and Stellar Synthesis (BPASS) code to determine the effect of stellar binaries on number count ratios of different evolutionary stages in both young massive clusters and galaxies with massive stellar populations. We find that many ratios are degenerate in metallicity, age, and/or binary fraction. We develop diagnostic plots using these stellar count ratios to help break this degeneracy, and use these plots to compare our predictions to observed data in the Milky Way and the Local Group. These data suggest a possible correlation between the massive star binary fraction and metallicity. We also examine the robustness of our predictions in samples with varying levels of completeness. We find including binaries and imposing a completeness limit can both introduce $gtrsim0.1$ dex changes in inferred ages. Our results highlight the impact that binary evolution channels can have on the massive star population.
We investigate the occurrence of crystalline silicates in oxygen-rich evolved stars across a range of metallicities and mass-loss rates. It has been suggested that the crystalline silicate feature strength increases with increasing mass-loss rate, im
plying a correlation between lattice structure and wind density. To test this, we analyse Spitzer IRS and Infrared Space Observatory SWS spectra of 217 oxygen-rich asymptotic giant branch stars and 98 red supergiants in the Milky Way, the Large and Small Magellanic Clouds and Galactic globular clusters. These encompass a range of spectral morphologies from the spectrally-rich which exhibit a wealth of crystalline and amorphous silicate features to naked (dust-free) stars. We combine spectroscopic and photometric observations with the GRAMS grid of radiative transfer models to derive (dust) mass-loss rates and temperature. We then measure the strength of the crystalline silicate bands at 23, 28 and 33 microns. We detect crystalline silicates in stars with dust mass-loss rates which span over 3 dex, down to rates of ~10^-9 solar masses/year. Detections of crystalline silicates are more prevalent in higher mass-loss rate objects, though the highest mass-loss rate objects do not show the 23-micron feature, possibly due to the low temperature of the forsterite grains or it may indicate that the 23-micron band is going into absorption due to high column density. Furthermore, we detect a change in the crystalline silicate mineralogy with metallicity, with enstatite seen increasingly at low metallicity.
The mass-loss rates of red supergiant stars (RSGs) are poorly constrained by direct measurements, and yet the subsequent evolution of these stars depends critically on how much mass is lost during the RSG phase. In 2012 the Geneva evolutionary group
updated their mass-loss prescription for RSGs with the result that a 20 solar mass star now loses 10x more mass during the RSG phase than in the older models. Thus, higher mass RSGs evolve back through a second yellow supergiant phase rather than exploding as Type II-P supernovae, in accord with recent observations (the so-called RSG Problem). Still, even much larger mass-loss rates during the RSG phase cannot be ruled out by direct measurements of their current dust-production rates, as such mass-loss is episodic. Here we test the models by deriving a luminosity function for RSGs in the nearby spiral galaxy M31 which is sensitive to the total mass loss during the RSG phase. We carefully separate RSGs from asymptotic giant branch stars in the color-magnitude diagram following the recent method exploited by Yang and collaborators in their Small Magellanic Cloud studies. Comparing our resulting luminosity function to that predicted by the evolutionary models shows that the new prescription for RSG mass-loss does an excellent job of matching the observations, and we can readily rule out significantly larger values.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
