A Study of the [ITAL]B[/ITAL]−[ITAL]V[/ITAL] Color-Temperature Relation

ABSTRACTWe present EzGal, a flexible Python program designed to easily generate observable parameters (magnitudes, colors, and mass-to-light ratios) for arbitrary input stellar population synthesis (SPS) models. As has been demonstrated by various authors, for many applications the choice of input SPS models can be a significant source of systematic uncertainty. A key strength of EzGal is that it enables simple, direct comparison of different model sets so that the uncertainty introduced by choice of model set can be quantified. Its ability to work with new models will allow EzGal to remain useful as SPS modeling evolves to keep up with the latest research (such as varying IMFs). EzGal is also capable of generating composite stellar population models (CSPs) for arbitrary input star-formation histories and reddening laws, and it can be used to interpolate between metallicities for a given model set. To facilitate use, we have created an online interface to run EzGal and quickly generate magnitude and mass-to-light ratio predictions for a variety of star-formation histories and model sets. We make many commonly used SPS models available from the online interface, including the canonical Bruzual & Charlot models, an updated version of these models, the Maraston models, the BaSTI models, and the Flexible Stellar Population Synthesis (FSPS) models. We use EzGal to compare magnitude predictions for the model sets as a function of wavelength, age, metallicity, and star-formation history. From this comparison we quickly recover the well-known result that the models agree best in the optical for old solar-metallicity models, with differences at the level. Similarly, the most problematic regime for SPS modeling is for young ages (≲2 Gyr) and long wavelengths (λ ≳ 7500 Å), where thermally pulsating AGB stars are important and scatter between models can vary from 0.3 mag (Sloan i) to 0.7 mag (Ks). We find that these differences are not caused by one discrepant model set and should therefore be interpreted as general uncertainties in SPS modeling. Finally, we connect our results to a more physically motivated example by generating CSPs with a star-formation history matching the global star-formation history of the universe. We demonstrate that the wavelength and age dependence of SPS model uncertainty translates into a redshift-dependent model uncertainty, highlighting the importance of a quantitative understanding of model differences when comparing observations with models as a function of redshift.

We present new grids of colors and bolometric corrections for F-K stars having 4000 K < Teff < 6500 K, 0.0 < log g < 4.5 and -3.0 < [Fe/H] < 0.0. A companion paper extends these calculations into the M giant regime. Colors are tabulated for Johnson U-V and B-V; Cousins V-R and V-I; Johnson-Glass V-K, J-K and H-K; and CIT/CTIO V-K, J-K, H-K and CO. We have developed these color-temperature (CT) relations by convolving synthetic spectra with photometric filter-transmission-profiles. The synthetic spectra have been computed with the SSG spectral synthesis code using MARCS stellar atmosphere models as input. Both of these codes have been improved substantially, especially at low temperatures, through the incorporation of new opacity data. The resulting synthetic colors have been put onto the observational systems by applying color calibrations derived from models and photometry of field stars which have Teffs determined by the infrared-flux method. The color calibrations have zero points and slopes which change most of the original synthetic colors by less than 0.02 mag and 5%, respectively. The adopted Teff scale (Bell & Gustafsson 1989) is confirmed by the extraordinary agreement between the predicted and observed angular diameters of the field stars. We have also derived empirical CT relations from the field-star photometry. Except for the coolest dwarfs (Teff < 5000 K), our calibrated, solar-metallicity model colors are found to match these and other empirical relations quite well. Our calibrated, 4 Gyr, solar-metallicity isochrone also provides a good match to color-magnitude diagrams of M67. We regard this as evidence that our calibrated colors can be applied to many astrophysical problems, including modelling the integrated light of galaxies. (abridged)

We present a new release of the GALFORM semi-analytical model of galaxy formation and evolution, which exploits a Millennium Simulation-class N-body run performed with the WMAP7 cosmology. We use this new model to study the impact of the choice of stellar population synthesis (SPS) model on the predicted evolution of the galaxy luminosity function. The semi-analytical model is run using seven different SPS models. In each case we obtain the rest-frame luminosity function in the far-ultra-violet, optical and near-infrared (NIR) wavelength ranges. We find that both the predicted rest-frame ultra-violet and optical luminosity function are insensitive to the choice of SPS model. However, we find that the predicted evolution of the rest-frame NIR luminosity function depends strongly on the treatment of the thermally pulsating asymptotic giant branch (TP-AGB) stellar phase in the SPS models, with differences larger than a factor of 2 for model galaxies brighter than $M_{\rm AB}(K)-5$log$h<-22$ ($\sim$L$_*$ for $0\leq z\leq 1.5$). We have also explored the predicted number counts of galaxies, finding remarkable agreement between the results with different choices of SPS model, except when selecting galaxies with very red optical-NIR colours. The predicted number counts of these extremely red galaxies appear to be more affected by the treatment of star formation in disks than by the treatment of TP-AGB stars in the SPS models.

In this paper we investigate a hitherto unexplored source of potentially\nsignificant error in stellar population synthesis (SPS) models, caused by\nsystematic uncertainties associated with the three fundamental stellar\natmospheric parameters; effective temperature T_eff, surface gravity g, and\niron abundance [Fe/H]. All SPS models rely on calibrations of T_eff, logg and\n[Fe/H] scales, which are implicit in stellar models, isochrones and synthetic\nspectra, and are explicitly adopted for empirical spectral libraries. We assess\nthe effect of a mismatch in scales between isochrones and spectral libraries\n(the two key components of SPS models) and quantify the effects on 23 commonly\nused diagnostic line indices. We find that typical systematic offsets of 100K\nin T_eff, 0.15 dex in [Fe/H] and/or 0.25 dex in logg significantly alter\ninferred absolute ages of simple stellar populations (SSPs) and that in some\ncircumstances, relative ages also change. Offsets in T_eff, logg and [Fe/H]\nscales for a scaled-solar SSP produce deviations from the model which can mimic\nthe effects of altering abundance ratios to non-scaled-solar chemical\ncompositions, and could also be spuriously interpreted as evidence for a more\ncomplex population, especially when multiple-index or full-SED fitting methods\nare used. We stress that the behavior we find can potentially affect any SPS\nmodels, whether using full integrated spectra or fitting functions to determine\nline strengths. We present measured offsets in 23 diagnostic line indices and\nurge caution in the over-interpretation of line-index data for stellar\npopulations.\n

The upcoming all-sky infrared spectrophotometric SPHEREx mission is set to provide spatially resolved stellar mass maps of nearby galaxies, offering more detailed insights than integrated light observations. In this study, we develop a strategy for estimating stellar mass using SPHEREx by examining the dependence on different stellar population synthesis (SPS) models and proposing new scaling relations based on simulated SPHEREx data. We estimate the resolved stellar masses of 19 nearby late-type galaxies from the PHANGS-MUSE survey, treating these as fiducial masses. By testing four SPS models covering infrared wavelengths, i.e., E-MILES, Bruzual &amp; Charlot (BC03), Charlot &amp; Bruzual (CB19), and FSPS, we find systematic differences in mass-to-light ratios at 3.6 μm (M */L 3.6 μm) among the SPS models. In particular, BC03 and CB19 yield mass-to-light ratios on average ∼0.2−0.3 dex lower than those from E-MILES and FSPS. These mass-to-light ratios strongly correlate with stellar age, indicating a significant impact of young stellar populations on stellar mass measurements. Our analysis, incorporating fiducial masses and simulated SPHEREx data, identifies the 1.6 μm band as the optimal wavelength for stellar mass estimation, with the lowest scatter (0.15−0.20 dex) of the stellar mass. This scatter can be further reduced to 0.10−0.12 dex across all SPS models by incorporating optical and SPHEREx colors. These results can provide guidance for measuring the stellar masses of the numerous nearby galaxies that SPHEREx will survey.

We present a Bayesian hierarchical framework to analyze photometric galaxy survey data with stellar population synthesis (SPS) models. Our method couples robust modeling of spectral energy distributions with a population model and a noise model to characterize the statistical properties of the galaxy populations and real observations, respectively. By self-consistently inferring all model parameters, from high-level hyperparameters to SPS parameters of individual galaxies, one can separate sources of bias and uncertainty in the data. We demonstrate the strengths and flexibility of this approach by deriving accurate photometric redshifts for a sample of spectroscopically confirmed galaxies in the COSMOS field, all with 26-band photometry and spectroscopic redshifts. We achieve a performance competitive with publicly released photometric redshift catalogs based on the same data. Prior to this work, this approach was computationally intractable in practice due to the heavy computational load of SPS model calls; we overcome this challenge by the addition of neural emulators. We find that the largest photometric residuals are associated with poor calibration for emission-line luminosities and thus build a framework to mitigate these effects. This combination of physics-based modeling accelerated with machine learning paves the path toward meeting the stringent requirements on the accuracy of photometric redshift estimation imposed by upcoming cosmological surveys. The approach also has the potential to create new links between cosmology and galaxy evolution through the analysis of photometric data sets.

We present speculator—a fast, accurate, and flexible framework for emulating stellar population synthesis (SPS) models for predicting galaxy spectra and photometry. For emulating spectra, we use a principal component analysis to construct a set of basis functions and neural networks to learn the basis coefficients as a function of the SPS model parameters. For photometry, we parameterize the magnitudes (for the filters of interest) as a function of SPS parameters by a neural network. The resulting emulators are able to predict spectra and photometry under both simple and complicated SPS model parameterizations to percent-level accuracy, giving a factor of 103–104 speedup over direct SPS computation. They have readily computable derivatives, making them amenable to gradient-based inference and optimization methods. The emulators are also straightforward to call from a GPU, giving an additional order of magnitude speedup. Rapid SPS computations delivered by emulation offers a massive reduction in the computational resources required to infer the physical properties of galaxies from observed spectra or photometry and simulate galaxy populations under SPS models, while maintaining the accuracy required for a range of applications.

As the reconstruction of the star formation histories (SFHs) of galaxies from spectroscopic data becomes increasingly popular, we explore the best age resolution achievable with stellar population synthesis (SPS) models, relying on different constraints: broad-band colours, absorption indices, a combination of the two, and the full spectrum. We perform idealized experiments on SPS models and show that the minimum resolvable relative duration of a star formation episode (time difference between 10 per cent and 90 per cent of the stellar mass formed divided by the median age) is never better than 0.4, even when using spectra with signal-to-noise ratio (SNR) larger than 100 per Å. Typically, the best relative age resolution ranges between 0.4 and 0.7 over most of the age–metallicity plane, corresponding to minimum bin sizes for SFH sampling between 0.15 and 0.25 dex. This resolution makes the spectroscopic exploration of distant galaxies mandatory in order to reconstruct the early phases of galaxies’ SFHs. We show that spectroscopy with ${\rm SNR} \gtrsim 20\,$ Å−1 is essential for good age resolution. Remarkably, using the full spectrum does not prove significantly more effective than relying on absorption indices, especially at SNR ≲ 20 Å−1. We discuss the physical origins of the age resolution trends as a function of age and metallicity, and identify the presence of maxima in age resolution (i.e. minima in measurable relative time duration) at the characteristic ages that correspond to quick time variations in spectral absorption features. We connect these maxima to bumps commonly observed in reconstructed SFHs.

Interpreting galactic luminosity requires assumptions about the galaxy-wide initial mass function (gwIMF), often assumed invariant in most stellar population synthesis (SPS) models. If stars form in clusters with metallicity- and density-dependent stellar IMFs, the integrated galaxy-wide IMF (IGIMF) can be calculated, with its shape depending on the star formation rate (SFR) and metallicity. The shape of the IGIMF thus depends on the SFR and metallicity. We develop the SPS-VarIMF code which enables us for the first time to compute the spectra, luminosities, and remnant populations of galaxies in the context of the varying gwIMF with time, SFR, and an assumed metallicity. Using the SPS-VarIMF code one can calculate how the interpretation from the integrated galactic light may change if the underlying galaxy-wide IMF is assumed to be environmentally dependent instead of being invariant. In particular, we compare the time evolution of the galaxy colour and the stellar mass-to-light ratio in different bands for the IGIMF and invariant canonical gwIMF assuming constant and delayed-$\tau$ star formation histories. We show that the underlying gwIMF can be determined by examining the colours and luminosities of late-type galaxies in ultraviolet and optical bands. On the other hand, for early-type galaxies, it is difficult to distinguish which gwIMF is valid since adopting the different gwIMFs yields almost identical colours. However, their gwIMF-dependent mass-to-light ($M/L$) ratios differ by up to an order of magnitude. Massive present-day elliptical galaxies would have been $10^4$ times as bright as at present when they were forming.

Using high spatial resolution Hubble Space Telescope WFC3 and Advanced Camera for Surveys imaging of resolved stellar populations, we constrain the contribution of thermally pulsing asymptotic giant branch (TP-AGB) stars and red helium burning (RHeB) stars to the 1.6 μm near-infrared (NIR) luminosities of 23 nearby galaxies, including dwarfs and spirals. The TP-AGB phase contributes as much as 17% of the integrated F160W flux, even when the red giant branch is well populated. The RHeB population contribution can match or even exceed the TP-AGB contribution, providing as much as 21% (18% after a statistical correction for foreground) of the integrated F160W light. We estimate that these two short-lived phases may account for up to 70% of the rest-frame NIR flux at higher redshift. The NIR mass-to-light (M/L) ratio should therefore be expected to vary significantly due to fluctuations in the star formation rate (SFR) over timescales from 25 Myr to several Gyr, an effect that may be responsible for some of the lingering scatter in NIR galaxy scaling relations such as the Tully-Fisher and metallicity-luminosity relations. We compare our observational results to predictions based on optically derived star formation histories and stellar population synthesis (SPS) models, including models based on the 2008 Padova isochrones (used in popular SPS programs) and the updated 2010 Padova isochrones, which shorten the lifetimes of low-mass (old) low-metallicity TP-AGB populations. The updated (2010) SPS models generally reproduce the expected numbers of TP-AGB stars in the sample; indeed, for 65% of the galaxies, the discrepancy between modeled and observed numbers is smaller than the measurement uncertainties. The weighted mean model/data number ratio for TP-AGB stars is 1.5 (1.4 with outliers removed) with a standard deviation of 0.5. The same SPS models, however, give a larger discrepancy in the F160W flux contribution from the TP-AGB stars, overpredicting the flux by a weighted mean factor of 2.3 (2.2 with outliers removed) with a standard deviation of 0.8. This larger offset is driven by the prediction of modest numbers of high-luminosity TP-AGB stars at young (&lt;300 Myr) ages. The best-fit SPS models simultaneously tend to underpredict the numbers and fluxes of stars on the RHeB sequence, typically by a factor of 2.0 ± 0.6 for galaxies with significant numbers of RHeBs. Possible explanations for both the TP-AGB and RHeB model results include (1) difficulties with measuring the SFHs of galaxies especially on the short timescales over which these stars evolve (several Myr), (2) issues with the way the SPS codes populate the color-magnitude diagrams (e.g., how they handle pulsations or self-extinction), and/or (3) lingering issues with the lifetimes of these stars in the stellar evolution codes. Coincidentally these two competing discrepancies—overprediction of the TP-AGB and underprediction of the RHeBs—result in a predicted NIR M/L ratio largely unchanged for a rapid SFR, after correcting for these effects. However, the NIR-to-optical flux ratio of galaxies could be significantly smaller than AGB-rich models would predict, an outcome that has been observed in some intermediate-redshift post-starburst galaxies.

I introduce some improvements to the ppxf method, which measures the stellar and gas kinematics, star formation history (SFH) and chemical composition of galaxies. I describe the new optimization algorithm that ppxf uses and the changes I made to fit both spectra and photometry simultaneously. I apply the updated ppxf method to a sample of 3200 galaxies at redshift 0.6 &amp;lt; z &amp;lt; 1 (median z = 0.76, stellar mass $M_\ast \gtrsim 3\times 10^{10}$ M⊙), using spectroscopy from the LEGA-C survey (DR3) and 28-bands photometry from two different sources. I compare the masses from new JAM dynamical models with the ppxf stellar population M* and show the latter are more reliable than previous estimates. I use three different stellar population synthesis (SPS) models in ppxf and both photometric sources. I confirm the main trend of the galaxies’ global ages and metallicity [M/H] with stellar velocity dispersion σ* (or central density), but I also find that [M/H] depends on age at fixed σ*. The SFHs reveal a sharp transition from star formation to quenching for galaxies with $\lg (\sigma _\ast /\mathrm{km}\, s^{-1})\gtrsim 2.3$ ($\sigma _\ast \gtrsim 200$$\mathrm{km}\, s^{-1}$), or average mass density within 1 kpc $\lg (\Sigma _1^{\rm JAM}/\mathrm{\mathrm{M}_{\odot }kpc^{-2}})\gtrsim 9.9$ ($\Sigma _1^{\rm JAM}\gtrsim 7.9\times 10^9\, \mathrm{\mathrm{M}_{\odot }\ kpc^{-2}}$), or with $[M/H]\gtrsim -0.1$, or with Sersic index $\lg n_{\rm Ser}\gtrsim 0.5$ ($n_{\rm Ser}\gtrsim 3.2$). However, the transition is smoother as a function of M*. These results are consistent for two SPS models and both photometric sources, but they differ significantly from the third SPS model, which demonstrates the importance of comparing model assumptions.

The IR emission from galaxies is a unique window into multiple aspects of galaxy evolution including star-formation rates, the age of galaxies, and galactic-scale dust processes. However, asymptotic giant branch (AGB) stars continue to introduce uncertainty into stellar population synthesis (SPS) models and limit our ability to interpret the IR light of galaxies. Here we focus on incorporating circumstellar dust around AGB stars in SPS models and understanding the extent to which they influence the IR light of galaxies. We find that the significance of the AGB dust contribution depends on the characteristics of the galaxy. For quiescent galaxies and metal-poor star forming galaxies, circumstellar dust emission can have a large effect, whereas for dusty star-forming galaxies the circumstellar emission is dwarfed by emission from dust in the ISM. The models with circumstellar dust also suggest, in agreement with previous work, that IR colors can be a powerful age diagnostic for older stellar systems. Models such as these will be essential for interpreting data that will be provided by JWST and other next generation IR facilities.

Stellar population synthesis (SPS) models are a key ingredient of many galaxy evolution studies. Unfortunately, the models are still poorly calibrated for certain stellar evolution stages. Of particular concern is the treatment of the thermally-pulsing asymptotic giant branch (TP-AGB) phase, as different implementations lead to systematic differences in derived galaxy properties. Post-starburst galaxies are a promising calibration sample, as TP-AGB stars are thought to be most prominently visible during this phase. Here, we use post-starburst galaxies in the NEWFIRM medium-band survey to assess different SPS models. The available photometry allows the selection of a homogeneous and well-defined sample of 62 post-starburst galaxies at 0.7<z<2.0, from which we construct a well-sampled composite spectral energy distribution (SED) over the range 1200-40 000 Angstrom. The SED is well-fit by the Bruzual & Charlot SPS models, while the Maraston models do not reproduce the rest-frame optical and near-infrared parts of the SED simultaneously. When the fitting is restricted to lambda < 6000 Angstrom, the Maraston models overpredict the near-infrared luminosity, implying that these models give too much weight to TP-AGB stars. Using the flexible SPS models by Conroy et al, and assuming solar metallicity, we find that the contribution of TP-AGB stars to the integrated SED is a factor of ~3 lower than predicted by the latest Padova TP-AGB models. Whether this is due to lower bolometric luminosities, shorter lifetimes, and/or heavy dust obscuration of TP-AGB stars remains to be addressed. Altogether, our data demand a low contribution from TP-AGB stars to the SED of post-starburst galaxies.

Sustainable food colours

The luminosity and spectral energy distribution of high-z galaxies are sensitive to the stellar-population synthesis (SPS) models. In this paper, we study the effects of different SPS models on the measurements of high-z galaxies and the budget of ionizing photons during the epoch of reionization by employing each of them in the semianalytical galaxy formation model L-Galaxies 2020. We find that the different SPS models lead to ≲0.5 dex differences on the amplitudes of UV luminosity functions, while two modes of the same SPS model with and without the inclusion of binary stars lead to similar UV luminosity functions at z ≥ 6. Instead, the binary stars produce ∼40% more ionizing photons than the single stars, while such differences are smaller than those caused by different SPS models; for example, the BPASS model produces ∼100% more ionizing photons than other models.