The evolution and lifetimes of thermally pulsing asymptotic giant branch (TP-AGB) stars suffer from significant uncertainties. We present a detailed framework for constraining model luminosity functions of TP-AGB stars using resolved stellar populations. We show an example of this method that compares various TP-AGB mass-loss prescriptions that differ in their treatments of mass loss before the onset of dust-driven winds (pre-dust). We find that models with more efficient pre-dust driven mass loss produce results consistent with observations, as opposed to more canonical mass-loss models. Efficient pre-dust driven mass-loss predicts, for [Fe/H] ≲ -1.2, that lower mass TP-AGB stars (M≲ 1 M☉) must have lifetimes less than about 1.2 Myr

Aringer, B.

Bressan, A.

Dalcanton, J. J.

Dolphin, A.

GIRARDI, Leo Alberto

GULLIEUSZIK, MARCO

Marigo, P.

Rosenfield, P.

Weisz, D. R.

Williams, B. F.

OA@INAF - Istituto Nazionale di Astrofisica

2015Publication Year2020-03-20T16:46:28ZAcceptance in OA@INAFConstraining Mass Loss and Lifetimes of Low Mass, Low Metallicity AGB StarsTitleRosenfield, P.; Marigo, P.; GIRARDI, Leo Alberto; Dalcanton, J. J.; Bressan, A.; et al.Authorshttp://hdl.handle.net/20.500.12386/23443HandleASTRONOMICAL SOCIETY OF THE PACIFIC CONFERENCE SERIESSeries497NumberWHY GALAXIES CARE ABOUT AGB STARS III:A CLOSER LOOK IN SPACE AND TIMEASP Conference Series, Vol. 497Kerschbaum, Wing, and Hron, eds.c©2015 Astronomical Society of the PacificConstraining Mass Loss and Lifetimes of Low Mass,Low Metallicity AGB StarsPhilip Rosenfield,1 Paola Marigo,1 Léo Girardi,2 Julianne J. Dalcanton,3Alessandro Bressan,4 Marco Gullieuszik,2 Daniel R. Weisz,3,5 Benjamin F.Williams,3 Andrew Dolphin,6 and Bernhard Aringer71Dept. of Physics and Astronomy G. Galilei, University of Padova, Italy2Osservatorio Astronomico di Padova – INAF, Padova, Italy3Dept. of Astronomy, University of Washington, Seattle WA, USA4Astrophysics Sector, SISSA, Trieste, Italy5Hubble Fellow6Raytheon Company, Tucson AZ, USA7Dept. of Astrophysics, University of Vienna, Wien, AustriaAbstract. The evolution and lifetimes of thermally pulsing asymptotic giant branch(TP-AGB) stars suffer from significant uncertainties. We present a detailed frameworkfor constraining model luminosity functions of TP-AGB stars using resolved stellarpopulations. We show an example of this method that compares various TP-AGB mass-loss prescriptions that differ in their treatments of mass loss before the onset of dust-driven winds (pre-dust). We find that models with more efficient pre-dust driven massloss produce results consistent with observations, as opposed to more canonical mass-loss models. Efficient pre-dust driven mass-loss predicts, for [Fe/H] . −1.2, that lowermass TP-AGB stars (M . 1 M) must have lifetimes less than about 1.2 Myr.1. IntroductionResolved stellar populations (RSPs) are powerful laboratories for understanding uncer-tain phases of stellar evolution, including the thermally pulsing asymptotic giant branch(TP-AGB; e.g. Marigo et al. 2008). Understanding TP-AGB stars in dwarf galaxiessheds light on the processes of galaxies at larger redshift where resolving the stellarcontent is impossible. In addition, TP-AGB stars can contribute ∼ 20% of a galaxy’snear-infrared (NIR) light (Melbourne et al. 2012).Despite their importance, TP-AGB models are uncertain in their prediction of thebrightness distribution (i.e. the luminosity function, LF) of AGB stars beyond the Mag-ellanic Clouds (e.g., see discussion in Girardi et al. 2010). The differences betweenobserved and modeled LFs of TP-AGB stars found in a RSP is mainly due to modelTP-AGB lifetimes, which are primarily set by mass loss (e.g. Vassiliadis & Wood 1993).Recently, the Hubble Space Telescope has optically imaged ∼ 70 nearby galaxiesthat together house thousands of TP-AGB stars (Dalcanton et al. 2009). In this sam-ple, 23 galaxies also have HST/NIR imaging (Dalcanton et al. 2012). These datasetsprovide over 1000 low-metallicity TP-AGB stars which we use to constrain model TP-423424 Rosenfield et al.Figure 1. Schematic diagram of the method to statistically compare the predictedTP-AGB model luminosity function to that observed (see text).AGB mass-loss prescriptions, and thus TP-AGB model lifetimes. Here, we outline amethod expanded from Girardi et al. (2010) to constrain uncertain parameters of TP-AGB models with observations of RSPs, and we illustrate the method with a summaryof the analysis presented in Rosenfield et al. (2014). By ensuring a large model param-eter search space, this method is a step toward the goal of a fully Bayesian frameworkfor constraining stellar evolution models.2. MethodFigure 1 is a schematic diagram of the method to statistically compare TP-AGB modelswith observations. We are primarily interested in the shape of the LF brighter thanthe tip of the red giant branch (TRGB). However, this method is applicable to higher-dimensional data, such as color-magnitude diagrams (CMDs) and color-color diagramsof any RSP. Briefly, we compare the observed LFs to synthetic RSPs that are createdbased on the most likely star formation history (SFH) of the data and a specified TP-AGB mass-loss prescription.2.1. Observed Luminosity FunctionsBeginning at the top left of Fig. 1, luminosity functions are obtained from the opticaland NIR data. Using the optical data, we also calculate at least 100,000 artificial startests for each image (described in, e.g., Dalcanton et al. 2009), which are used to estab-lish a faint magnitude limit (set at 90% completeness), and to compare LFs, which areapplied to the stellar evolution models when deriving the SFH and applied to the modelLFs to correct for completeness. In addition, RGB stars are counted in order to scalethe population synthesis models that provide the model LFs (RGB stars are usuallyidentified by a CMD box, c.f. Girardi et al. 2010; Rosenfield et al. 2014; Melbourneet al. 2012).Constraining Mass Loss and Lifetimes of AGB Stars 4252.2. Model Luminosity Functions2.2.1. Stellar Evolution ModelsTwo stellar evolution codes are used in recovering the SFH of the galaxy and to createsynthetic stellar populations (top and right of Fig. 1): (1) Padova and Trieste StellarEvolution Code: PARSEC v1.1 (Bressan et al. 2012) is an updated Padova Stellar Evo-lution code, containing models spanning Z= 0.0001–0.06, M = 0.1–12 M, from thepre-main sequence to either the TP-AGB or core carbon ignition; (2) COLIBRI: Fol-lowing the first thermal pulse on the AGB, COLIBRI takes over the stellar evolutioncalculations from PARSEC (Marigo et al. 2013). Briefly, COLIBRI optimizes the ratioof physical accuracy over computational issues typical of TP-AGB models, countingon a detailed envelope model in which the molecular chemistry of > 800 species andgas opacities are computed on-the-fly (Marigo & Aringer 2009).2.2.2. Star Formation HistoriesSFHs are derived using the CMD-fitting MATCH package (Dolphin 2000) and thedeeper optical data. MATCH finds the most-likely CMD that fits the optical CMDbased on a given initial mass function (IMF), binary fraction, artificial star tests, andstellar models. We adopt a Kroupa (2001) IMF and a binary fraction of 0.35.The input stellar models used in MATCH are from PARSEC; that is, we excludeTP-AGB models in the SFH derivation and give no weight to the regions of the observedCMD above the measured TRGB and redder than the main sequence.Uncertainties in the SFHs propagate to a spread in the predicted LF (see Figure 2).We use the most-likely SFH and its random uncertainties as inputs to the populationsynthesis models (for complete details see Dolphin 2013).2.2.3. Population SynthesisWe model the photometry of RSPs with the TRILEGAL population synthesis code(Girardi et al. 2005). TRILEGAL takes as input the PARSEC and COLIBRI stellarevolution models, an IMF, binary fraction, and the time evolution of metallicity and starformation rate. Importantly, TRILEGAL also simulates the L−Teff variations due to thethermal pulse cycles on the TP-AGB (Girardi & Marigo 2007). The TRILEGAL inputparameters are set to remain consistent with the parameters listed in § 2.2.2. Finally,to fully explore the possible parameter space, we randomly draw SFHs from the most-likely SFH and its given uncertainties.Each synthetic RSP is scaled to match the number of RGB stars identified fromthe observations. The scaled luminosity functions are finally corrected for completenessbased on the artificial star tests.2.3. Statistical ComparisonsThe resulting set of model and observed LFs are compared by using a statistic similarto χ2 but for a Poisson probability distribution (e.g. Dolphin 2002).3. Comparing Three Mass Loss PrescriptionsAs an example of the success of this method, we summarize recent findings fromRosenfield et al. (2014) which emphasize the importance of mass loss on the AGB426 Rosenfield et al.Figure 2. LFs of DDO71 with three mass loss prescriptions η = 0, R75, andmSC05. The spread in model LFs is due to sampling the most-likely SFH and itsuncertainties. The faintest shaded region marks the 90% completeness limit, and thebrighter shaded region denotes the TRGB (Dalcanton et al. 2009, 2012).before the onset of dust-driven winds. In this work, we compare the results of thismethod using three pre-dust mass loss regimes: 1) no pre-dust mass loss (η = 0); 2) Thecanonical (Reimers 1975, R75) mass-loss with efficiency η = 0.4; and 3) a modifiedversion of Schröder & Cuntz (2005) based on Cranmer & Saar (2011), mSC05. Figure 2shows the model LFs with each mass loss prescription as a visual guide. Clearly, ignor-ing pre-dust mass loss or simply using R75 over-predicts the number of TP-AGB stars,and mSC05 is a promising fit. In terms of the Poisson likelihood parameter, mSC05 isa factor of 2-3 lower than the other prescriptions. Using mSC05, we show the resultinglifetimes of TP-AGB stars as a function of mass for a range of metallicities in Figure 3.4. ConclusionsWe have presented a framework for constraining stellar evolution models and haveshown its use in constraining low mass, low metallicity, TP-AGB mass-loss rates, em-phasizing the importance of including efficient pre-dust mass loss in TP-AGB mod-els. Specifically, mSC05 predicts, for [Fe/H] . −1.2, that lower mass TP-AGB stars(M . 1 M) must have lifetimes less than about 1.2 Myr.Acknowledgments. This work is based on observations made with the NASA/ESAHubble Space Telescope, obtained from the Data Archive at the Space Telescope Sci-ence Institute (STScI), which is operated by the Association of Universities for Re-search in Astronomy, Inc., under NASA contract NAS 5-26555. We acknowledge sup-port from Progetto di Ateneo 2012 (University of Padova, ID: CPDA125588/12), HSTGO-10915, and an ERC Consolidator Grant (ID: 610654, project STARKEY). Supportfor DRW is from NASA through Hubble Fellowship grant HST-HF-51331.01 awardedby STScI.Constraining Mass Loss and Lifetimes of AGB Stars 427Figure 3. Lifetime of TP-AGB stars as a function of initial mass for several metal-licities predicted by the mSC05 model. Left: the total lifetime of the pre-dust phase.Right: the lifetime of the TP-AGB phase brighter than the TRGB (measurable fromobservations).ReferencesBressan, A., Marigo, P., Girardi, L., Salasnich, B., Dal Cero, C., Rubele, S., & Nanni, A. 2012,MNRAS, 427, 127Cranmer, S. R., & Saar, S. H. 2011, ApJ, 741:54Dalcanton, J. J., Williams, B. F., Melbourne, J. L., et al. 2012, ApJS, 198:6Dalcanton, J. J., Williams, B. F., Seth, A. C., et al. 2009, ApJS, 183, 67Dolphin, A. E. 2000, PASP, 112, 1383— 2002, MNRAS, 332, 91— 2013, ApJ, 775, 76Girardi, L., Groenewegen, M. A. T., Hatziminaoglou, E., & da Costa, L. 2005, A&A, 436, 895Girardi, L., & Marigo, P. 2007, A&A, 462, 237Girardi, L., Williams, B. F., Gilbert, K. M., Rosenfield, P., et al. 2010, ApJ, 724, 1030Kroupa, P. 2001, MNRAS, 322, 231Marigo, P., & Aringer, B. 2009, A&A, 508, 1539Marigo, P., Bressan, A., Nanni, A., Girardi, L., & Pumo, M. L. 2013, MNRAS, 434, 488Marigo, P., Girardi, L., Bressan, A., Groenewegen, M. A. T., Silva, L., & Granato, G. L. 2008,A&A, 482, 883Melbourne, J., Williams, B. F., Dalcanton, J. J., Rosenfield, P., et al. 2012, ApJ, 748:47Reimers, D. 1975, Mem. Soc. Roy. Sci. Liège, 8, 369Rosenfield, P., Marigo, P., Girardi, L., Dalcanton, J. J., Bressan, A., Gullieuszik, M., Weisz, D.,Williams, B. F., Dolphin, A., & Aringer, B. 2014, ApJ, 790, 22Schröder, K.-P., & Cuntz, M. 2005, ApJL, 630, L73Vassiliadis, E., & Wood, P. R. 1993, ApJ, 413, 641

Constraining Mass Loss and Lifetimes of Low Mass, Low Metallicity AGB Stars

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Constraining Mass Loss and Lifetimes of Low Mass, Low Metallicity AGB Stars

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