a new analyse of the OGLE survey. The difficulty in accurately measuring the orientation of the bulge might be aggravated if, actually, there are more than one population present in the region and if these populations have different origins.  presented a smart explanation for the disagreement, which they attribute partly to the cone effect and partly to the putative existence of leading or trailing overdensities at the end of the bar. In this context, metallicity distribution can be useful constraints for distinguishing populations. ,  and  highlight a bimodal metallicity distribution in the Baade’s window and several fields on the bulge minor axis, identifying a mixture of populations. Concerning the kinematics, proper motions are difficult to obtain due to the large distance of the bulge, while radial velocities are expensive to process for large number of stars.  studied proper motions from OGLEIII survey and compared with a dynamical model. However the OGLE fields avoid the Galactic plane and the northern part of the bulge, are limited by extinction being at visible wavelength, and the mean proper motion error is large for giving accurate velocities at the bulge distance.  have undertaken a wide survey (BRAVA, for Bulge Radial Velocity Assay) of radial velocities at longitudes between −10 deg and 10 deg at latitudes −4 deg and −8 deg. Their first results from the latitude −4 deg data set showed that the slope of the rotation curve flattens considerably at longitude |l| > 5 deg indicating a probable change of the dominant population at this point. Since 2010, there have been several studies showing the existence of double clumps in a number of fields in the bulge [56–58]. This is also a feature that should be taken into account in an overall view of the bulge region and that the models should explain.
We thank the anonymous referee for the constructive com- ments which improved the quality and readability of the paper. It is a pleasure to acknowledge the contribution to this work by the NMBS and 3DHST collaboration. We also thank Rik Williams and Ryan Quadri for their help with the UDS cata- logs, and thank Andrew Newman for providing the corrected stellar masses. The authors furthermore wish to thank Daniel Szomoru and Adam Muzzin interesting discussions which con- tributed to this paper. This research was supported by grants from the Netherlands Foundation for Research (NWO), the Leids Kerkhoven-Bosscha Fonds. This work is based on ob- servations taken by the 3D-HST Treasury Program (GO 12177 and 12328) with the NASA/ESA HST, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555.
We investigated the properties of the stellar populations in the discs of a sample of 10 spiral galaxies. Our analysis focused on the galaxy region where the disc contributes more than 95 per cent of total surface brightness in order to minimize the contamination of the bulge and bar. The luminosity-weighted age and metallicity were obtained by fitting the galaxy spectra with a linear combination of stellarpopulationsynthesis models, while the total overabundance of α-elements over iron was derived by measuring the line-strength indices. Most of the sample discs display a bimodal age distribution and they are characterized by a total [ α/ Fe] enhancement ranging from solar and supersolar. We interpreted the age bimodality as due to the simultaneous presence of both a young (Age ≤ 4 Gyr) and an old (Age > 4 Gyr) stellarpopulation. The old stellar component usually dominates the disc surface brightness and its light contribution is almost constant within the observed radial range. For this reason, no age gradient is observed in half of the sample galaxies. The old component is slightly more metal poor than the young one. The metallicity gradient is negative and slightly positive in the old and young components, respectively. These results are in agreement with an inside-out scenario of disc formation and suggest a reduced impact of the radial migration on the stellar populations of the disc. The young component could be the result of a second burst of star formation in gas captured from the environment.
In addition to cosmological constraints from cluster masses, the galaxy spectra themselves convey a multitude of informa- tion about their stellar populations. In recent years, with the development of more robust statistical techniques, there has been great progress in the ﬁ tting of galaxy spectra to extract stellarpopulation information. These efforts have focused on building a more robust statistical framework around the early methods of stellarpopulationsynthesis ( Tinsley 1972; Searle et al. 1973; Larson & Tinsley 1978 ) used for modeling the spectral energy distributions ( SEDs ) of galaxies. These early stellarpopulationsynthesis methods have been improved over the years to incorporate a more complete understanding of galactic processes ( see Walcher et al. 2011 for a review ) . In the past few years, new efforts have been made to apply Bayesian techniques to ﬁ t these stellarpopulation models. BayeSED ( Han & Han 2014 ) and BEAGLE ( Chevallard & Charlot 2016 ) are two recently developed Bayesian models aimed at ﬁ tting SEDs of galaxies over a large wavelength coverage. However, these models are geared towards SEDs, which sample only a few band passes over a large wavelength range ( from γ -rays to IR ) . And most recently, Meneses-Goytia et al. ( 2015 ) developed a single stellarpopulation model with Bayesian statistical techniques to ﬁ t spectra in the near-infrared.
Differences in handling uncertain physics by model makers leads to large differences in the interpretation of galaxy colors from varying SSP models. Although it is difficult to estimate uncertainties in the derived stellarpopulation parameters (like age and metallicity), comparing the BC03 models that we use here with other available models suggests how much our results are dependent on our choice of stellarpopulation mod- els. The treatment of advanced stages in evolution, such as the Thermal-Pulsating Asymptotic Giant Branch phase (TP-AGB), has received much attention in the past decade. TP-AGB stars are extremely bright and dominate the NIR light of a galaxy following a burst of star formation, but are difficult to model theoretically because of the combined effects of thermal pulses, changes from heavy element dredge-up, and mass loss (BC03). The stellarpopulationsynthesis models of Maraston (2005) use a different prescription for the TP-AGB phase than BC03 and the effect on the model colors has been demonstrated in the literature (Tonini et al. 2009). A revised ver- sion of the Bruzual and Charlot stellarpopulationsynthesis code has been developed (Charlot & Bruzual 2009, private communication) which includes a new prescription for TP-AGB evolution of low and intermediate mass stars following Marigo & Girardi (2007) and uses tracks from models with updated input physics from Bertelli et al. (2008). Eminian et al. (2008) has demonstrated a significant change with the new Bruzual and Charlot models in NIR model colors for intermediate populations.
We used the latest release of the Cloudy photoion- ization code (C17, Ferland et al. 2017) to build our grid of models. We chose SEDs from the latest BPASSv2.1 mod- els (Eldridge et al. 2017) as input, which account for stel- lar binaries and stellar rotation effects. Indeed, several re- cent observations point out that high-redshift galaxies can exhibit UV emission lines requiring hard ionizing photons (e.g., C iii ]λλ1907, 1909, C iv λλ1548 , 1550; Stark et al. 2014; Amor´ın et al. 2017; Vanzella et al. 2017), and there are mounting evidences that these UV lines are due to star for- mation since they are spatially associated with star form- ing regions (Smit et al. 2017). These kind of strong emission lines can be reproduced by including stellar rotation and/or stellar binaries in the stellar models (e.g., Eldridge et al. 2008) or using stellar templates updated with recent UV spectral libraries and stellar evolutionary tracks as in the lat- est Charlot & Bruzual single star models (e.g., Gutkin et al. 2016). Regarding the ISM properties, we adopt the same interstellar abundances and depletion factors of metals on to dust grains, and dust properties as Gutkin et al. (2016). These authors show that these modeling assumptions span a range that can reproduce most of the observed UV and op- tical emission lines at low- and high-redshift (Stark et al. 2014, 2015a,b, 2017; Chevallard & Charlot 2016). While Gutkin et al. (2016) use different stellarpopulation synthe- sis model than used here, namely an updated version of the Bruzual & Charlot (2003) stellarpopulationsynthesis model, a comparison of these two SPS models show that they provide similar results in interpreting stellar and neb- ular emissions of local massive star-clusters (Wofford et al. 2016). For the grid used in this work, we use stellar metallici- ties from Z = 0.001 to Z = 0.008 with an initial mass function (IMF) index of −2.35 and an upper mass cutoff of 300M ⊙ .
As a first step in extracting the individual properties of our two distinct stellar structural components in these galaxies we used the Cappellari & Emsellem (2004) Penalized Pixel-Fitting (pPXF) and the Gas AND emission Line Fitting (GANDALF) Sarzi et al. (2006) methods to recover the velocity, velocity dis- persion, and the h3 and h4 coefficients of the Gauss-Hermite parametrisation van der Marel & Franx (1993) of the line-of- sight (stellar) velocity distribution (LOSVD) and any potential ionized-gas emission line properties in each Voronoi bin. The pPXF procedure uses a model, which is parametrised in terms of Gauss-Hermite functions for the LOSVD and a set of linearly combined template spectra to best match the observed galaxy spectrum in pixel space. An important requirement for the ex- traction of an accurate LOSVD is that the spectral resolution of the templates provided to build the observed galaxy spectrum matches the instrumental one. The spectral resolution was mea- sured by fitting high-resolution solar spectrum template to the twilight spectra, after having combined them following the same sequence of the science observations, similar to (Sarzi et al. 2018). The measured instrumental FWHM is 2.8 Å, its variation across the field of view and the wavelength range is ∼ 0.1 Å. The adopted method ensures the measurement of the effective instrumental spectral resolution, that includes both the instru- ment properties and data reduction steps. With these considera- tions in mind we adopted as template spectra the Vazdekis et al. (2012, MIUSCAT) stellarpopulationsynthesis models (SSPs), spanning the broad 3465–9469 Å wavelength range based on the Girardi et al. (2000) stellar isochrones with -0.71<[Z/H]<+0.22, 0.06<t<18 Gyr, and with an unimodal initial-mass function with a power-law slope coefficient of 1.3 (Salpeter 1955). This stel- lar populationsynthesis model template library with a constant FWHM resolution of 2.8 Å was retrieved through the on-line portal 1 . Prior to performing both pPXF and GANDALF fits,
Broadly speaking the agreement between observational con- straints and BPASS predictions as a function of redshift is good. For type Ia SNe, the predicted rates consistently tend towards the upper end of the range of observed values, although they coincide with a reasonable fraction of the observed data points, and repro- duce the observed redshift trend. A slight overestimate may arise because we have too loose a definition of what leads to a type Ia SN and some fraction of our progenitor models may in fact give rise to some other kind of low luminosity transient as discussed earlier. Type Ia rates are known to differ in cluster environments relative to the field, so a certain amount of scatter is expected. It is also, of course, possible that there are completeness corrections or other systematic offsets in some of the observational data, but overall the predictions, based purely on stellarpopulationsynthesis and the volume-averaged cosmic history are excellent.
One reason for such uncertainty is the unfortunate necessity of extrapolation below the limits of observational data. Only a few, rare z > 5 galaxies are bright enough for detailed spectroscopic analysis. Observations of high-redshift galaxies are typically limited to their broad-band colours in the rest-frame ultraviolet (and sometimes op- tical) and perhaps a measurement of particularly strong emission lines (such as Lyman α at 1216 Å; e.g. Labb´e et al. 2013; Caruana et al. 2014; Oesch et al. 2015; Smit et al. 2015). Given a measured rest-frame 1500 Å flux continuum density, usually derived from photometry in a broad bandpass, the number of ionizing photons shortwards of 912 Å (the ionization limit of hydrogen or ‘Lyman break’) must be inferred (e.g. Madau, Haardt & Rees 1999; Bunker et al. 2004; Robertson et al. 2015). This ‘Lyman-continuum’ flux is estimated through the use of stellarpopulationsynthesis models, fitted to the available data. For a stellarpopulation of known age, metallicity and ultraviolet flux, the ionizing photon flux can be reli- ably estimated. However, difficulties arise when any of these proper- ties are unknown. A young starburst will contain a larger proportion of hot, massive stars than an older one and so emit more ionizing photons for a given 1500 Å continuum measurement. By contrast, a stellarpopulation that has formed stars continuously over its life- time will show an ultraviolet spectral energy distribution (SED) to which both young stars and older sources contribute, resulting in a modified but far more stable ionizing photon-to-continuum ratio. At low metallicities, different stellar evolution pathways, including those which result from binary star interactions or rotation, become increasingly important — again resulting in a modified ionizing photon output (Eldridge, Izzard & Tout 2008; Stanway et al. 2014; Zhang et al. 2013; Topping & Schull 2015). While some of these variations can be inferred from stellarpopulation modelling, this has traditionally been tuned to match the properties of the local galaxy distribution – largely comprising mature galaxies and stellar populations with a near-solar average metallicity.
The actual near-infrared counterpart selected is based on the coordinates derived from the mid-infrared astrometry (see Section 2.4). We selected the best match based on a visual comparison of the mid- and near-infrared data. Some objects have no direct counterpart, since they are obscured even in the K-band, although extended emission such as reflection nebulosity may be present. All these objects are guaranteed to be sufficiently red to satisfy the color criteria described in Section 2.5. Of course, this matching still leaves the possibility that some of our sources are not visible in the near-infrared and that we have picked a neighboring near-infrared source that has a chance alignment with the real target, given the resolution of the data. This fact may be especially true in massive star forming regions where dense clusters of associated stars are present (e.g., Carpenter et al. 1993; Hodapp 1994) and in some cases the true massive young stellar object (MYSO) may be completely obscured. Such dense clusters however appear to be rare in our sample, and we are therefore confident that the number of incorrectly attributed near-infrared fluxes remains small.
The DES data set, though designed for DE studies, presents a gold mine for galaxy evolution science. The science covered is very broad and includes studies of galaxies and galaxy properties across red- shift space from the nearby universe to epochs close to reionization around z ∼ 6. This will be possible thanks to the unprecedented com- bination of wavelength coverage, width and depth of DES + VHS photometry. Here we describe some of the broad science themes enabled by the DES data: (1) the evolution of the multivariate and stellarpopulation properties of galaxies and their evolution with redshift, (2) galaxy environment, (3) galaxy luminosity and mass functions and their evolution with redshift, (4) massive galaxies at high redshift, (5) connecting galaxies to their DM context, (6) galaxy properties in galaxy clusters and (7) intracluster light (ICL). A major shortcoming in traditional galaxy surveys designed for galaxy evolution studies is the lack of sufficient volume required to overcome limitations caused by both cosmic variance and the low number density of massive galaxies. Thanks to the large survey area of 5000 sq deg, the volume sampled in DES is orders of magnitude larger than existing galaxy evolution surveys, at the price of being shallower by several magnitudes. With this unique combination of intermediate depth and large volume, the DES data set will allow a major step forward in the field. In the following, we briefly discuss the key topics that we envisage being addressed by DES.
the early phases of mergers (Teyssier et al. 2010; Hopkins et al. 2013; Renaud et al. 2015). In this sense, integral field spec- troscopy (IFS) is a very promising technique, because it can provide relevant information to characterize the extent of star formation, and how/when it is produced. Extended star forma- tion has also been observationally reported in many early-stage mergers, mainly in the form of widespread star clusters, most of which are located at the intersections between progenitors and/or tidal structures (Wang et al. 2004; Elmegreen et al. 2006; Smith et al. 2016), and through stellarpopulation analysis re- lying on IFS (Cortijo-Ferrero et al. 2017; hereafter CF17). In fact, the results of the two early-stage merger LIRGs reported in CF17, IC 1623 W and NGC 6090, are compared throughout the paper with the merger LIRG NGC 2623. The advantage of NGC 2623 is that it is a more advanced system, in the merger stage, where a triggering of the star formation is expected to oc- cur, but at the same time, it also keeps a fossil record in the stellar populations of previous star formation bursts (i.e., when it was at the early-stage merger phase). Therefore, NGC 2623 represents an interesting nearby LIRG to study the role that major mergers play in galaxy evolution using spatially resolved spectroscopy.
We present AGNfitter, a publicly available open-source algorithm implementing a fully Bayesian Markov Chain Monte Carlo method to fit the spectral energy distributions (SEDs) of active galactic nuclei (AGN) from the sub-mm to the UV, allowing one to robustly disentangle the physical processes responsible for their emission. AGNfitter makes use of a large library of theoretical, empirical, and semi-empirical models to characterize both the nuclear and host galaxy emission simultaneously. The model consists of four physical emission components: an accretion disk, a torus of AGN heated dust, stellar populations, and cold dust in star forming regions. AGNfitter determines the posterior distributions of numerous parameters that govern the physics of AGN with a fully Bayesian treatment of errors and parameter degeneracies, allowing one to infer integrated luminosities, dust attenuation parameters, stellar masses, and star formation rates. We tested AGNfitter’s performance on real data by fitting the SEDs of a sample of 714 X–ray selected AGN from the XMM–COSMOS survey, spectroscopically clas- sified as Type1 (unobscured) and Type2 (obscured) AGN by their optical-UV emission lines. We find that two independent model parameters, namely the reddening of the accretion disk and the column density of the dusty torus, are good proxies for AGN obscuration, allowing us to develop a strategy for classifying AGN as Type1 or Type2, based solely on an SED-fitting analysis. Our classification scheme is in excellent agreement with the spectroscopic classifi- cation, giving a completeness fraction of ∼ 86% and ∼ 70%, and an efficiency of ∼ 80% and ∼ 77%, for Type1 and Type2 AGNs, respectively .
cSFGs have been proposed as a transition population between being star-forming and quiescence ( e.g., Barro et al. 2013, 2014; Nelson et al. 2014; Williams et al. 2014; van Dokkum et al. 2015 ) . Revealing their nature implies revealing whether the transition to quiescence occurred secularly or rapidly. Phases of abrupt changes in increasing sSFR are typical of SBs. The time a galaxy is detectable in such a phase is short, since they are short-lived ( e.g., Di Matteo et al. 2008; Tacconi et al. 2008 ) . This means that the number of detectable SBs is small compared to the general population, but the phase can still be very relevant in terms of stellar mass assembly. We examined three diagnostics of the burstiness of star formation: ( 1 ) SFE, ( 2 ) ISM, and ( 3 ) radio emission. The aim is to explore whether cSFGs can be considered as normal SFGs, pointing to a more secular evolution, or as SBs, pointing to a more rapid evolution. We refer to normal SFGs as those that obey the general trends of SFGs in each diagnostic. Conversely, SBs are outliers to these general trends in each diagnostic ( see the sections on diagnostics for a more detailed explanation ) . These de ﬁ nitions of normal SFGs and SBs are independent of their position with respect to the MS. The latter would be a consequence of the physical mechanisms in place ( related to our diagnostics ) and the effect of these mechanisms on the integrated properties of the galaxies at the time of observation. Note also that the galaxies selected for each of the three diagnostics are not the same sources because the selections do not overlap.
The young ages of the stellar populations in all three regions of J0025 − 10 probed by our high quality spectra unambiguously demonstrate that the luminous quasar-like nucleus in J0025−10 has been triggered at around the same time as a major episode of star formation immediately prior to the coalescence of the nuclei in a gas-rich merger. The low reddening deduced for all three apertures using the YSP continuum and the narrow-line emission measure- ments clearly indicate that, even at this early stage of the merger, outflows driven either by the AGN or starburst have been effective in driving much of the dust and gas from the visible star formation regions. These results are fully consistent with the trend found by Tadhunter et al. (2011) that luminous quasars host starburst popu- lations with t ysp < 0.1 Gyr.
However, the relative vertical positions of our relationship and the Gallazzi et al. (2014) relationship at z ∼ 0.7 do not follow the expected trend of earlier formation with increasing observed redshift at fixed stellar mass. This is likely to be due to the significant methodological differences between the two studies. Gallazzi et al. (2014) fit indices derived from rest-frame optical spectra and use an exponentially declining SFH model, whereas we apply a full-spectral-fitting approach to rest-frame UV spectra using a double-power-law SFH model. The use of different SFH models and priors is known to affect derived ages, which could plausibly give rise to this effect (e.g. Carnall et al. 2019; Leja et al. 2019a,b). It is additionally likely that the optical spectra of quiescent galaxies are dominated by an older population than dominates in the UV, meaning that fitting different spectral regions could result in different SFHs.
The resulting half-light radius corresponds to an HWHM ( Gaussian HWHM, 1.1774s ) of 0. 20 1 ( ). At a redshift of z = 0.193, an angle of 1 corresponds to a projected distance of 3.31 kpc, hence the half-light radius is 0.68 3 ( ) kpc. Under the assumption that the diffuse emission due to the underlying stellarpopulation can be represented by a Gaussian ( which, given the irregular nature of dwarf galaxies may not be valid ) , the knot is located 0. 57 ( 1.9 kpc ) from the nominal centroid of the diffuse emission, which itself has a half-light diameter ( Gaussian FWHM ) between 1. 5 and 2. 0 ( 5 to 7 kpc ) . The higher spatial resolution and greater depth of the HST observations improve upon the 4 kpc diameter we estimated in Tendulkar et al. ( 2017 ) . The centroid of the knot, as measured in the drizzled F110W image, is located at
For the comparison with our planet population model, we restrict the hot white dwarf sample of Barstow et al. ( 2014 ) to single stars. We therefore inspected the literature and carried out a search for common proper motion companions using the Gaia Data Release 2 ( Gaia Collaboration et al. 2018 ) , and identi ﬁ ed 29 white dwarfs that have a stellar companion. For our planet population mode, we required the progenitor masses of the single white dwarfs ( Table 1 ) . Given the uncertainties on the post-main-sequence mass loss, we computed the average progenitor masses of the 58 single white dwarfs using the initial-to- ﬁ nal mass relations of Weidemann ( 2000 ) , Catalán et al. ( 2008 ) , Kalirai et al. ( 2008 ) , Casewell et al. ( 2009 ) , and Williams et al. ( 2009 ) .
Pandya et al. (2017) also measure a higher rejuvena- tion fraction (31%) in their SAM (see Section 1). They define the quiescent region to be 1.4dex below the SFMS, considerably more strict than our definition, and they additionally define a transition region (0.6 − 1.4dex be- low SFMS) between the star-forming and quiescent se- quence. Defining our quiescent region in the same man- ner results in our rejuvenation fraction decreasing to 5%. However, if we instead define the quiescent region to be 0.6dex below the SFMS, i.e. combine Pandya et al. (2017)’s transition and quiescent population, our reju- venation fraction increases to 18%, still lower than their value of 31%. The discrepancy between these results may suggest that our sample contains galaxies with hid- den rejuvenation at larger lookback times ( & 10Gyrs), or that the fraction of rejuvenated galaxies is higher at z = 0. However, we note that Pandya et al. (2017)’s SAM underproduces quiescent galaxies at z > 0.5, and they suggest that one of the reasons could be that qui- escent galaxies are rejuvenating too much in their SAM. Our rejuvenation fraction is in agreement with Behroozi et al. (2018)’s measurements (∼ 10 − 20%). Their SFR distribution is assumed to be the sum of two log-normal distributions corresponding to a quenched population and a star-forming population, at fixed red- shift and peak circular velocity at the redshift of peak halo mass, and rejuvenation is defined as at least 300 Myr of quiescence followed by at least 300 Myr of star formation.
We use deep near-infrared VLT/ISAAC imaging to study the rest-frame color-magnitude distribution of infrared selected galaxies in the redshift range 1 < z < 3. We find a well-defined blue peak of star-forming galaxies at all redshifts. The blue galaxies populate a color-magnitude relation (CMR), such that more luminous galaxies in the rest-frame V -band tend to have redder ultraviolet-to-optical colors. The slope of the CMR does not evolve with time, and is similar to the slope of blue, late-type galaxies in the local universe. Analysis of spectra of nearby late-type galaxies suggests that the steepness of the slope can be fully explained by the observed correlation of dust content with optical luminosity. The zeropoint of the blue CMR at a given magnitude reddens smoothly from z = 3 to z = 0, likely reflecting an increase of the mean stellar age and an increase in the mean dust opacity of blue-sequence galaxies. A distinct feature is that the color scatter around the z ∼ 3 CMR is asymmetric, with a blue “ridge” and a skew towards red col- ors. We have explored which types of star formation histories can reproduce the scatter and the skewed shape of the color distribution. These included models with constant star formation rates and sudden cutoffs, exponentially declining star formation rates, burst models, and models with episodic star formation. The episodic models reproduced the color distribution best, with quiescent periods lasting 30-50% of the length of an active period, and dura- tion of the duty cycle between 150 Myr to 1 Gyr. The episodic star formation in these models rejuvenate the galaxies during each episode, making it sig- nificantly bluer than a galaxy with constant star formation of the same age. This could be a solution of the enigmatic observation that z = 3 galaxies are much bluer than expected if they were as old as the universe. Finally, the color distribution has a strong tail of very red galaxies. The relative number of red galaxies increases sharply from z ∼ 3 to z ∼ 1. The rest-frame V - band luminosity density in luminous blue-sequence galaxies is constant, or decreases, whereas that in red galaxies rises with time. We are viewing the progressive formation of red, passively evolving galaxies.