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Register a new userSPISEA: A Python-Based Simple Stellar Population Synthesis Code for Star Clusters
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We present SPISEA (Stellar Population Interface for Stellar Evolution and Atmospheres), an open-source Python package that simulates simple stellar populations. The strength of SPISEA is its modular interface which offers the user control of 13 input properties including (but not limited to) the Initial Mass Function, stellar multiplicity, extinction law, and the metallicity-dependent stellar evolution and atmosphere model grids used. The user also has control over the Initial-Final Mass Relation in order to produce compact stellar remnants (black holes, neutron stars, and white dwarfs). We demonstrate several outputs produced by the code, including color-magnitude diagrams, HR-diagrams, luminosity functions, and mass functions. SPISEA is object-oriented and extensible, and we welcome contributions from the community. The code and documentation are available on GitHub and ReadtheDocs, respectively.
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We present a new Milky Way microlensing simulation code, dubbed PopSyCLE (Population Synthesis for Compact object Lensing Events). PopSyCLE is the first resolved microlensing simulation to include a compact object distribution derived from numerical supernovae explosion models and both astrometric and photometric microlensing effects. We demonstrate the capabilities of PopSyCLE by investigating the optimal way to find black holes (BHs) with microlensing. Candidate BHs have typically been selected from wide-field photometric microlensing surveys, such as OGLE, by selecting events with long Einstein crossing times ($t_E>120$ days). These events can be selected at closest approach and monitored astrometrically in order to constrain the mass of each lens; PopSyCLE predicts a BH detection rate of ~40% for such a program. We find that the detection rate can be enhanced to ~85% by selecting events with both $t_E>120$ days and a microlensing parallax of $pi_E<0.08$. Unfortunately, such a selection criterion cannot be applied during the event as $pi_E$ requires both pre- and post-peak photometry. However, historical microlensing events from photometric surveys can be revisited using this new selection criteria in order to statistically constrain the abundance of BHs in the Milky Way. The future WFIRST microlensing survey provides both precise photometry and astrometry and will yield individual masses of $mathcal{O}(100-1000) black holes, which is at least an order of magnitude more than is possible with individual candidate follow-up with current facilities. The resulting sample of BH masses from WFIRST will begin to constrain the shape of the black hole present-day mass function, BH multiplicity, and BH kick velocity distributions.
The ESO public survey VISTA Variables in the Via Lactea (VVV) has contributed with deep multi-epoch photometry of the Galactic bulge and the adjacent part of the disk over 526 square degrees. More than a hundred cluster candidates have been reported thanks to this survey. We present the fifth article in a series of papers focused on young and massive clusters discovered in the VVV survey. In this paper, we present the physical characterization of five clusters with a spectroscopically confirmed OB-type stellar population. To characterize the clusters, we used near-infrared photometry ($J$, $H,$ and $K_S$) from the VVV survey and near-infrared $K$-band spectroscopy from ISAAC at VLT, following the methodology presented in the previous articles of the series. All clusters in our sample are very young (ages between 1-20 Myr), and their total mass are between $(1.07^{+0.40}_{-0.30})cdot10^2$ $M_{odot}$ and $(4.17^{+4.15}_{-2.08})cdot10^3$ $M_{odot}$. We observed a relation between the clusters total mass $M_{ecl}$ and the mass of their most massive stellar member $m_{max}$, even for clusters with an age $<$ 10 Myr.
The amount of mass lost by stars during the red-giant branch (RGB) phase is one of the main parameters to understand and correctly model the late stages of stellar evolution. Nevertheless, a fully-comprehensive knowledge of the RGB mass loss is still missing. Galactic Globular Clusters (GCs) are ideal targets to derive empirical formulations of mass loss, but the presence of multiple populations with different chemical compositions has been a major challenge to constrain stellar masses and RGB mass losses. Recent work has disentangled the distinct stellar populations along the RGB and the horizontal branch (HB) of 46 GCs, thus providing the possibility to estimate the RGB mass loss of each stellar population. The mass losses inferred for the stellar populations with pristine chemical composition (called first-generation or 1G stars) tightly correlate with cluster metallicity. This finding allows us to derive an empirical RGB mass-loss law for 1G stars. In this paper we investigate seven GCs with no evidence of multiple populations and derive the RGB mass loss by means of high-precision {it Hubble-Space Telescope} photometry and accurate synthetic photometry. We find a cluster-to-cluster variation in the mass loss ranging from $sim$0.1 to $sim$0.3 $M_{odot}$. The RGB mass loss of simple-population GCs correlates with the metallicity of the host cluster. The discovery that simple-population GCs and 1G stars of multiple population GCs follow similar mass-loss vs. metallicity relations suggests that the resulting mass-loss law is a standard outcome of stellar evolution.
In this paper, I review to what extent we can understand the photometric properties of star clusters, and of low-mass, unresolved galaxies, in terms of population synthesis models designed to describe `simple stellar populations (SSPs), i.e., groups of stars born at the same time, in the same volume of space, and from a gas cloud of homogeneous chemical composition. The photometric properties predicted by these models do not readily match the observations of most star clusters, unless we properly take into account the expected variation in the number of stars occupying sparsely populated evolutionary stages, due to stochastic fluctuations in the stellar initial mass function. In this case, population synthesis models reproduce remarkably well the full ranges of observed integrated colours and absolute magnitudes of star clusters of various ages and metallicities. The disagreement between the model predictions and observations of cluster colours and magnitudes may indicate problems with or deficiencies in the modelling, and dioes not necessarily tell us that star clusters do not behave like SSPs. Matching the photometric properties of star clusters using SSP models is a necessary (but not sufficient) condition for clusters to be considered simple stellar populations. Composite models, characterized by complex star-formation histories, also match the observed cluster colours.
Spectral energy distributions (SEDs) are useful primary and complementary tools in the analysis of observations of young stars. However, the process of collating, inspecting, and flux-converting archival photometry and spectroscopy to build spectral energy distributions for young stars can be time-consuming. Here, I present SEDBYS (Spectral Energy Distribution Builder for Young Stars), a python-based repository of command-line tools built to (i) query online photometric and spectroscopic catalogs and a distributed database of archival photometry, (ii) use a look-up table of zero points to flux-convert the acquired data, (iii) enable visual inspection of the SED and (iv) handle book-keeping to collate references in bibTeX format. The code is distributed via git and is equipped with additional tools to enable users to add existing or forthcoming catalogs to the list of sources queried, ensuring the longevity of SEDBYS as a tool for the star formation community.
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