Stellar Mass Estimates Research Articles

The outer stellar mass of massive galaxies: a simple tracer of halo mass with scatter comparable to richness and reduced projection effects

ABSTRACT Using the weak gravitational lensing data from the Hyper Suprime-Cam Subaru Strategic Program (HSC survey), we study the potential of different stellar mass estimates in tracing halo mass. We consider galaxies with log10(M⋆/M⊙) > 11.5 at 0.2 < z < 0.5 with carefully measured light profiles, and clusters from the redMaPPer and CAMIRA richness-based algorithms. We devise a method (the ‘Top-N test’) to evaluate the scatter in the halo mass–observable relation for different tracers, and to inter-compare halo mass proxies in four number density bins using stacked galaxy–galaxy lensing profiles. This test reveals three key findings. Stellar masses based on CModel photometry and aperture luminosity within R <30 kpc are poor proxies of halo mass. In contrast, the stellar mass of the outer envelope is an excellent halo mass proxy. The stellar mass within R = [50, 100] kpc, M⋆, [50, 100], has performance comparable to the state-of-the-art richness-based cluster finders at log10Mvir ≳ 14.0 and could be a better halo mass tracer at lower halo masses. Finally, using N-body simulations, we find that the lensing profiles of massive haloes selected by M⋆, [50, 100] are consistent with the expectation for a sample without projection or mis-centring effects. Richness-selected clusters, on the other hand, display an excess at R ∼ 1 Mpc in their lensing profiles, which may suggest a more significant impact from selection biases. These results suggest that M⋆-based tracers have distinct advantages in identifying massive haloes, which could open up new avenues for cluster cosmology. The codes and data used in this work can be found here:

Characterisation of the stellar content of SDSS EELGs through self-consistent spectral modelling

Extreme emission line galaxies (EELGs) are a notable galaxy genus, ultimately being regarded as local prototypes of early galaxies at the cosmic noon. Robust characterisation of their stellar content, however, is hindered by the exceptionally high nebular emission present in their optical spectroscopic data. This study is dedicated into recovering the stellar properties of a sample of 414 EELGs as observed by the SDSS Survey. Such is achieved by means of the spectral synthesis code FADO, which self-consistently considers the stellar and nebular emission in an optical spectrum. Additionally, a comparative analysis was carried on, by further processing the EELGs sample with the purely stellar spectral synthesis code STARLIGHT, and by extending the analysis to a sample of 697 normal star-forming galaxies, expected to be less affected by nebular contribution. We find that, for both galaxy samples, stellar mass and mean age estimates by STARLIGHT are systematically biased towards higher values, and that an adequate determination of the physical and evolutionary properties of EELGs via spectral synthesis is only possible when nebular continuum emission is taken into account. Moreover, the differences between the two population synthesis codes can be ascribed to the degree of star-formation activity through the specific star-formation rate and the sum of the flux of the most prominent emission lines. As expected, on the basis of the theoretical framework, our results emphasise the importance of considering the nebular emission while performing spectral synthesis, even for galaxies hosting typical levels of star-formation activity.

Stellar mass and radius estimation using artificial intelligence

Context. Estimating stellar masses and radii for most stars is a challenge, but it is critical to know them for many different astrophysical fields, such as exoplanet characterization or stellar structure and evolution. One of the most extended techniques for estimating these variables is the so-called empirical relations. Aims. We propose a group of frontier artificial intelligence (AI) regression models, with the aim of studying their proficiency in estimating stellar masses and radii. We select the model that provides the best accuracy with the least possible bias. Some of these AI techniques do not treat uncertainties properly, but in the current context, in which statistical analyses of massive databases in different fields are conducted, the most accurate estimate possible of stellar masses and radii can provide valuable information. We publicly release the database, the AI models, and an online tool for stellar mass and radius estimation to the community. Methods. We used a sample of 726 MS stars from the literature with accurate M, R, Teff, L, log ɡ, and [Fe/H]. We split our data sample into training and testing sets and then analyzed the different AI techniques with them. In particular, we experimentally evaluated the accuracy of the following models: linear regression, Bayesian regression, regression trees, random forest, support-vector regression (SVR), neural networks, K-nearest neighbour, and stacking. We propose a series of experiments designed to evaluate the accuracy of the estimates, and also the generalization capability of AI models. We also analyzed the impact of reducing the number of input parameters and compared our results with those from current empirical relations in the literature. Results. We have found that stacking several regression models is the most suitable technique for estimating masses and radii. In the case of the mass, neural networks also provide precise results, and for the radius, SVR and neural networks work as well. Compared with other currently used empirical relation-based models, our stacking improves the accuracy by a factor of two for both variables. In addition, bias is reduced to one order of magnitude in the case of stellar mass. Finally, we found that using our stacking and only Teff and L as input features, the accuracies obtained are slightly higher than 5%, with a bias of ≈1.5%. In the case of the mass, including [Fe/H] significantly improves the results. For the radius, including log ɡ yields better results. Finally, the proposed AI models exhibit an interesting generalization capability: they are able to perform estimations for masses and radii that were never observed during the training step.

What are the spectroscopic binaries with high-mass functions near the Gaia DR3 main sequence?

ABSTRACT The third data release of the Gaia mission includes orbital solutions for >105 single-lined spectroscopic binaries, representing more than an order of magnitude increase in sample size over all previous studies. This data set is a treasure trove for searches for quiescent black hole + normal star binaries. We investigate one population of black hole candidate binaries highlighted in the data release: sources near the main sequence in the colour–magnitude diagram (CMD) with dynamically inferred companion masses M2 larger than the CMD-inferred mass of the luminous star. We model light curves, spectral energy distributions, and archival spectra of the 14 such objects in DR3 with high-significance orbital solutions and inferred $M_2 \gt 3\, {\rm M}_{\odot }$. We find that 100 per cent of these sources are mass-transfer binaries containing a highly stripped lower giant donor (0.2 ≲ M/M⊙ ≲ 0.4) and much more massive (2 ≲ M/M⊙ ≲ 2.5) main-sequence accretor. The Gaia orbital solutions are for the donors, which contribute about half the light in the Gaia RVS bandpass but only $\lesssim 20{{\ \rm per\ cent}}$ in the g band. The accretors’ broad spectral features likely prevented the sources from being classified as double-lined. The donors are all close to Roche lobe filling ($R/R_{\rm Roche\, lobe}\gt 0.8$), but modelling suggests that a majority are detached ($R/R_{\rm Roche\, lobe}\lt 1$). Binary evolution models predict that these systems will soon become detached helium white dwarf + main-sequence ‘EL CVn’ binaries. Our investigation highlights both the power of Gaia data for selecting interesting subpopulations of binaries and the ways in which binary evolution can bamboozle standard CMD-based stellar-mass estimates.

Systematic errors on optical-SED stellar-mass estimates for galaxies across cosmic time and their impact on cosmology

Studying galaxies at different cosmic epochs entails several observational effects that need to be taken into account to compare populations across a large time-span in a consistent manner. We use a sample of 166 nearby galaxies that hosted type Ia supernovae (SNe Ia) and have been observed with the integral field spectrograph MUSE as part of the AMUSING survey. Here, we present a study of the systematic errors and bias on the host stellar mass with increasing redshift, which are generally overlooked in SNe Ia cosmological analyses. We simulate observations at different redshifts (0.1 < z < 2.0) using four photometric bands (griz, similar to the Dark Energy Survey-SN program) to then estimate the host galaxy properties across cosmic time. We find that stellar masses are systematically underestimated as we move towards higher redshifts, due mostly to different rest-frame wavelength coverage, with differences reaching 0.3 dex at z ∼ 1. We used the newly derived corrections as a function of redshift to correct the stellar masses of a known sample of SN Ia hosts and derive cosmological parameters. We show that these corrections have a small impact on the derived cosmological parameters. The most affected is the value of the mass step ΔM, which is reduced by ∼0.004 (6% lower). The dark energy equation of state parameter w changes by Δw∼ 0.006 (0.6% higher) and the value of Ωm increases at most by 0.001 (∼0.3%), all within the derived uncertainties of the model. While the systematic error found in the estimate of the host stellar mass does not significantly affect the derived cosmological parameters, it is an important source of systematic error that needs to be corrected for as we enter a new era of precision cosmology.

Euclidpreparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes andH-band images

ABSTRACTNext-generation telescopes, like Euclid, Rubin/LSST, and Roman, will open new windows on the Universe, allowing us to infer physical properties for tens of millions of galaxies. Machine-learning methods are increasingly becoming the most efficient tools to handle this enormous amount of data, because they are often faster and more accurate than traditional methods. We investigate how well redshifts, stellar masses, and star-formation rates (SFRs) can be measured with deep-learning algorithms for observed galaxies within data mimicking the Euclid and Rubin/LSST surveys. We find that deep-learning neural networks and convolutional neural networks (CNNs), which are dependent on the parameter space of the training sample, perform well in measuring the properties of these galaxies and have a better accuracy than methods based on spectral energy distribution fitting. CNNs allow the processing of multiband magnitudes together with $H_{\scriptscriptstyle \rm E}$-band images. We find that the estimates of stellar masses improve with the use of an image, but those of redshift and SFR do not. Our best results are deriving (i) the redshift within a normalized error of <0.15 for 99.9 ${{\ \rm per\ cent}}$ of the galaxies with signal-to-noise ratio >3 in the $H_{\scriptscriptstyle \rm E}$ band; (ii) the stellar mass within a factor of two ($\sim\!0.3 \rm \ dex$) for 99.5 ${{\ \rm per\ cent}}$ of the considered galaxies; and (iii) the SFR within a factor of two ($\sim\!0.3 \rm \ dex$) for $\sim\!70{{\ \rm per\ cent}}$ of the sample. We discuss the implications of our work for application to surveys as well as how measurements of these galaxy parameters can be improved with deep learning.

Mass–effective temperature–surface gravity relation for intermediate-mass main-sequence stars

Context. In this work a mass–effective temperature–surface gravity relation (MTGR) is developed for main-sequence stars in the range 6400 K ≤ Teff ≤ 20 000 K with log g ≳ 3.44. The MTGR allows the simple estimation of the masses of stars from their effective temperatures and surface gravities. It can be used for solar metallicity and can be rescaled for any metallicity within −1.0 ≤ [Fe/H] ≤ 0.7. The effect of α-enhanced compositions can also be considered with the help of correction terms. Aims. It is aimed to develop an MTGR that can estimate the masses of main-sequence stars from their atmospheric parameters. One advantage of an MTGR over the classical mass–luminosity relations is that its mass estimation is based on parameters that can be obtained by purely spectroscopic methods, and, therefore, the interstellar extinction or reddening do not have to be known. The use of surface gravity (g) also relates an MTGR with stellar evolution and provides a more reliable mass estimation. Methods. A synthetical MTGR is obtained from theoretical isochrones using a Levenberg-Marquardt χ2 minimization algorithm. The validity of the MTGR is then checked by testing over 278 binary components with precise absolute masses. Results. Very good agreement has been obtained between the absolute masses of 278 binary star components and their masses estimated from the MTGR. A mathematical expression is also given to calculate the propagated uncertainties of the MTGR masses. Conclusions. For the typical uncertainties in atmospheric parameters and metallicity (i.e., ±2.8% for Teff, ±0.1 dex for log g and ±0.15 dex for [Fe/H]) the typical uncertainties in the masses estimated from the MTGR mostly remain around 5–9%. The fact that this uncertainty level is only on average about three times as large as that of the absolute masses indicates that the MTGR is a very powerful tool for stellar mass estimation. A computer code, mtgr.pro, written in GDL or IDL is also provided for the relation.

Deep Extragalactic VIsible Legacy Survey (DEVILS): SED fitting in the D10-COSMOS field and the evolution of the stellar mass function and SFR–M⋆ relation

ABSTRACT We present catalogues of stellar masses, star formation rates (SFRs), and ancillary stellar population parameters for galaxies spanning 0 < z < 9 from the Deep Extragalactic VIsible Legacy Survey (DEVILS). DEVILS is a deep spectroscopic redshift survey with very high completeness, covering several premier deep fields including COSMOS (D10). Our stellar mass and SFR estimates are self-consistently derived using the spectral energy distribution (SED) modelling code ProSpect, using well-motivated parametrizations for dust attenuation, star formation histories, and metallicity evolution. We show how these improvements, and especially our physically motivated assumptions about metallicity evolution, have an appreciable systematic effect on the inferred stellar masses, at the level of ∼0.2 dex. To illustrate the scientific value of these data, we map the evolving galaxy stellar mass function (SMF) and the SFR–M⋆ relation for 0 < z < 4.25. In agreement with past studies, we find that most of the evolution in the SMF is driven by the characteristic density parameter, with little evolution in the characteristic mass and low-mass slopes. Where the SFR–M⋆ relation is indistinguishable from a power law at z > 2.6, we see evidence of a bend in the relation at low redshifts (z < 0.45). This suggests evolution in both the normalization and shape of the SFR–M⋆ relation since cosmic noon. It is significant that we only clearly see this bend when combining our new DEVILS measurements with consistently derived values for lower redshift galaxies from the Galaxy And Mass Assembly (GAMA) survey: this shows the power of having consistent treatment for galaxies at all redshifts.

The LOFAR Two-metre Sky Survey Deep Fields

In this paper, we investigate the relationship between 150 MHz luminosity and the star-formation rate – the SFR-L150 MHzrelation – using 150 MHz measurements for a near-infrared selected sample of 118 517z< 1 galaxies. New radio survey data offer compelling advantages over previous generation surveys for studying star formation in galaxies, including huge increases in sensitivity, survey speed, and resolution, while remaining impervious to extinction. The LOFAR Surveys Key Science Project is transforming our understanding of the low-frequency radio sky, with the 150 MHz data over the European Large Area Infrared Space Observatory Survey-North 1 field reaching an rms sensitivity of 20μJy beam−1over 10 deg2at 6 arcsec resolution. All of the galaxies studied have SFR and stellar mass estimates that were derived from energy balance spectral energy distribution fitting using redshifts and aperture-matched forced photometry from the LOFAR Two-metre Sky Survey (LoTSS) Deep Fields data release. The impact of active galactic nuclei (AGN) is minimised by leveraging the deep ancillary data in the LoTSS data release, alongside median-likelihood methods that we demonstrate are resistant to AGN contamination. We find a linear and non-evolving SFR-L150 MHzrelation, apparently consistent with expectations based on calorimetric arguments, down to the lowest SFRs < 0.01M⊙yr−1. However, we also recover compelling evidence for stellar mass dependence in line with previous work on this topic, in the sense that higher mass galaxies have a larger 150 MHz luminosity at a given SFR, suggesting that the overall agreement with calorimetric arguments may be a coincidence. We conclude that, in the absence of AGN, 150 MHz observations can be used to measure accurate galaxy SFRs out toz= 1 at least, but it is necessary to account for stellar mass in the estimation in order to obtain 150 MHz-derived SFRs accurate to better than 0.5 dex. Our best-fit relation is log10(L150 MHz ∕W Hz−1) = (0.90 ± 0.01)log10(ψ∕M⊙yr−1) + (0.33 ± 0.04)log10(M∕1010M⊙) + 22.22 ± 0.02.

The Infrared Emission and Vigorous Star Formation of Low-redshift Quasars

Abstract The star formation activity of the host galaxies of active galactic nuclei provides valuable insights into the complex interconnections between black hole growth and galaxy evolution. A major obstacle arises from the difficulty of estimating accurate star formation rates (SFRs) in the presence of a strong active galactic nucleus. Analyzing the 1–500 μm spectral energy distributions and high-resolution mid-infrared spectra of low-redshift (z < 0.5) Palomar–Green quasars with bolometric luminosity of ∼1044.5–1047.5 erg s−1, we find, from comparison with an independent SFR indicator based on [Ne II] 12.81 μm and [Ne III] 15.56 μm, that the torus-subtracted, total infrared (8–1000 μm) emission yields robust SFRs in the range of ∼1–250 M ⊙ yr−1. Combined with available stellar mass estimates, the vast majority (∼75%–90%) of the quasars lie on or above the main sequence of local star-forming galaxies, including a significant fraction (∼50%–70%) that would qualify as starburst systems. This is further supported by the high star formation efficiencies derived from the gas content inferred from the dust masses. Inspection of high-resolution Hubble Space Telescope images reveals a wide diversity of morphological types, including a number of starbursting hosts that have not experienced significant recent dynamical perturbations. The origin of the high star formation efficiency is unknown.

The LOFAR Two-meter Sky Survey: Deep Fields Data Release 1

The Low Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS) is a sensitive, high-resolution 120-168 MHz survey split across multiple tiers over the northern sky. The first LoTSS Deep Fields data release consists of deep radio continuum imaging at 150 MHz of the Boötes, European Large Area Infrared Space Observatory Survey-North 1, and Lockman Hole fields, down to rms sensitivities of ~32, 20, and 22 μJy beam−1, respectively. In this paper we present consistent photometric redshift (photo-z) estimates for the optical source catalogues in all three fields – totalling over 7 million sources (~5 million after limiting to regions with the best photometric coverage). Our photo-z estimation uses a hybrid methodology that combines template fitting and machine learning and is optimised to produce the best possible performance for the radio continuum selected sources and the wider optical source population. Comparing our results with spectroscopic redshift samples, we find a robust scatter ranging from 1.6 to 2% for galaxies and 6.4 to 7% for identified optical, infrared, or X-ray selected active galactic nuclei. Our estimated outlier fractions (|zphot−zspec|/(1+zspec)>0.15) for the corresponding subsets range from 1.5 to 1.8% and 18 to 22%, respectively. Replicating trends seen in analyses of previous wide-area radio surveys, we find no strong trend in photo-z quality as a function of radio luminosity for a fixed redshift. We exploit the broad wavelength coverage available within each field to produce galaxy stellar mass estimates for all optical sources at z < 1.5. Stellar mass functions derived for each field are used to validate our mass estimates, with the resulting estimates in good agreement between each field and with published results from the literature.

The Dragonfly Wide Field Survey. II. Accurate Total Luminosities and Colors of Nearby Massive Galaxies and Implications for the Galaxy Stellar-mass Function

Abstract Stellar-mass estimates of massive galaxies are susceptible to systematic errors in their photometry, due to their extended light profiles. In this study, we use data from the Dragonfly Wide Field Survey to accurately measure the total luminosities and colors of nearby massive galaxies. The low surface brightness limits of the survey (μ g ≈ 31 mag arcsec−2 on a 1′ scale) allow us to implement a method, based on integrating the 1D surface brightness profile, that is minimally dependent on any parameterization. We construct a sample of 1188 massive galaxies with based on the Galaxy Mass and Assembly (GAMA) survey and measure their total luminosities and g − r colors. We then compare our measurements to various established methods applied to imaging from the Sloan Digital Sky Survey (SDSS), focusing on those favored by the GAMA survey. In general, we find that galaxies are brighter in the r band by an average of ∼0.05 mag and bluer in g − r colors by ∼0.06 mag compared to the GAMA measurements. These two differences have opposite effects on the stellar-mass estimates. The total luminosities are larger by 5% but the mass-to-light ratios are lower by ∼10%. The combined effect is that the stellar-mass estimate of massive galaxies decreases by 7%. This, in turn, implies a small change in the number density of massive galaxies: ≤30% at .

Reconciling EHT and Gas-dynamics Measurements in M87: Is the Jet Misaligned at Parsec Scales?

Abstract The Event Horizon Telescope mass estimate for M87* is consistent with the stellar dynamics mass estimate and inconsistent with the gas-dynamics mass estimates by up to 2σ. We have previously explored a new gas-dynamics model that incorporated sub-Keplerian gas velocities and could, in principle, explain the discrepancy in the stellar and gas-dynamics mass estimate. In this paper, we extend this gas-dynamical model to also include non-trivial disk heights, which may also resolve the mass discrepancy independent of sub-Keplerian velocity components. By combining the existing velocity measurements and the Event Horizon Telescope mass estimate, we place constraints on the gas disk inclination and sub-Keplerian fraction. These constraints require the parsec-scale ionized gas disk to be misaligned with the milliarcsecond radio jet by at least 11°, and more typically 27°. Modifications to the gas-dynamics model either by introducing sub-Keplerian velocities or thick disks produce further misalignment with the radio jet. If the jet is produced in a Blandford–Znajek-type process, the angular momentum of the black hole is decoupled with the angular momentum of the large-scale gas feeding M87*.

The dependence of the galaxy stellar-to-halo mass relation on galaxy morphology

ABSTRACT We investigate the dependence of the local galaxy stellar-to-halo mass relation (SHMR) on galaxy morphology. We use data from the Sloan Digital Sky Survey (SDSS) data release 7 with morphological classifications from Galaxy Zoo, and compare with the EAGLE cosmological simulation. At fixed halo mass in the mass range $10^{11.7}\!-\!10^{12.9}\, {\rm M_{\odot }}$, the median stellar masses of SDSS disc galaxies are up to a factor of 1.4 higher than the median masses of their elliptical counterparts. However, when we switch from the stellar masses from Kauffmann et al. to those calculated by Chang et al. or Brinchmann et al., the median SHMR from discs and ellipticals coincides in this mass range. For halo masses larger than $10^{13}\, {\rm M_{\odot }}$, discs are less massive than ellipticals in same-mass haloes, regardless of whose stellar mass estimates we use. However, we find that for these high halo masses the results for discs may be affected by central/satellite misclassifications. The EAGLE simulation predicts that discs are up to a factor of 1.5 more massive than elliptical galaxies residing in same-mass haloes less massive than $10^{13}\, {\rm M_{\odot }}$, in agreement with the Kauffmann et al. data. Haloes with masses between 1011.5 and $10^{12}\, {\rm M_{\odot }}$, which host disc galaxies, were assembled earlier than those hosting ellipticals. This suggests that the discs are more massive because they had more time for gas accretion and star formation. In $10^{12}\!-\!10^{12.5}\, {\rm M_{\odot }}$ haloes, the central black holes in elliptical galaxies grew faster and became more massive than their counterparts in disc galaxies. This suggests that in this halo mass range the ellipticals are less massive because active galactic nucleus feedback ejected more of the halo’s gas reservoir, reducing star formation, and suppressing the (re)growth of stellar discs.

The significant effects of stellar mass estimation on galaxy pair fractions.

ABSTRACT Theoretical models suggest that galaxy mergers may have profoundly shaped galaxy morphologies through cosmic time. However, observational estimates of galaxy pair fractions, and implied galaxy mergers, still do not converge, suggesting different numbers and redshift evolution. This paper explores the connection between stellar mass estimation and the pair fraction of galaxies using $\rm {\small STEEL}$, the Statistical sEmi-Emprical modeL, in which galaxies are mapped on to host dark matter haloes via a stellar mass–halo mass (SMHM) relation. As haloes of different mass are predicted to undergo, on average, different degrees of mergers, we expect that galaxy merger rates at fixed stellar mass will also vary depending on the shape of the input SMHM relation. Using a variety of input SMHM relations, also including one that matches the outputs of the Illustris TNG simulation, we thoroughly explore how systematic variations in the stellar mass functions propagate on to the normalization and redshift dependence of the galaxy pair fraction. We find that (i) stellar mass functions characterized by larger number densities of massive galaxies and thus a steeper SMHM relation, result in a substantial reduction of the pair fractions of massive galaxies; (ii) a time-varying SMHM relation produces galaxy pair fractions that can have varied redshift evolutions. We argue that in a hierarchical, dark matter dominated Universe, stellar mass estimates are a considerable cause of bias that must be accounted for when comparing pair fractions from different data sets or from theoretical models developed independently of the fitted survey data.

A panchromatic spatially resolved analysis of nearby galaxies – II. The main sequence – gas relation at sub-kpc scale in grand-design spirals

ABSTRACT In this work, we analyse the connection between gas availability and the position of a region with respect to the spatially resolved main-sequence (MS) relation. Following the procedure presented in Enia et al. (2020), for a sample of five face-on, grand design spiral galaxies located on the MS we obtain estimates of stellar mass and star formation rate surface densities (Σ⋆ and ΣSFR) within cells of 500 pc size. Thanks to H i 21cm and 12CO(2–1) maps of comparable resolution, within the same cells we estimate the surface densities of the atomic (ΣH i) and molecular ($\Sigma _{\rm {H_2}}$) gas and explore the correlations among all these quantities. Σ⋆, ΣSFR, and $\Sigma _{\rm {H_2}}$ define a 3D relation whose projections are the spatially resolved MS, the Kennicutt–Schmidt law and the molecular gas MS. We find that $\Sigma _{\rm {H_2}}$ steadily increases along the MS relation and is almost constant perpendicular to it. ΣH i is nearly constant along the MS and increases in its upper envelope. As a result, ΣSFR can be expressed as a function of Σ⋆ and ΣH i, following the relation log ΣSFR = 0.97log Σ⋆ + 1.99log ΣH i − 11.11. We show that the total gas fraction significantly increases towards the starburst regions, accompanied by a weak increase in star formation efficiency. Finally, we find that H2/H i varies strongly with the distance from the MS, dropping dramatically in regions of intense star formation, where the UV radiation from newly formed stars dissociates the H2 molecule, illustrating the self-regulating nature of the star formation process.

The Radial Acceleration Relation in CLASH Galaxy Clusters

Abstract The radial acceleration relation (RAR) in galaxies describes a tight empirical scaling law between the total acceleration observed in galaxies and that expected from their baryonic mass , with a characteristic acceleration scale of m s−2. Here, we examine if such a correlation exists in galaxy clusters using weak-lensing, strong-lensing, and X-ray data sets available for 20 high-mass clusters targeted by the Cluster Lensing And Supernova survey with Hubble (CLASH). By combining our CLASH data with stellar mass estimates for the brightest cluster galaxies (BCGs) and accounting for the stellar baryonic component in clusters, we determine, for the first time, an RAR on BCG–cluster scales. The resulting RAR is well described by a tight power-law relation, , with lognormal intrinsic scatter of . The slope is consistent with the low acceleration limit of the RAR in galaxies, , whereas the intercept implies a much higher acceleration scale of m s−2, indicating that there is no universal RAR that holds on all scales from galaxies to clusters. We find that the observed RAR in CLASH clusters is consistent with predictions from a semianalytical model developed in the standard ΛCDM framework. Our results also predict the presence of a baryonic Faber–Jackson relation ( ) on cluster scales.

Investigating surface correction relations for RGB stars

ABSTRACTState-of-the-art stellar structure and evolution codes fail to adequately describe turbulent convection. For stars with convective envelopes such as red giants, this leads to an incomplete depiction of the surface layers. As a result, the predicted stellar oscillation frequencies are haunted by systematic errors, the so-called surface effect. Different empirically and theoretically motivated correction relations have been proposed to deal with this issue. In this paper, we compare the performance of these surface correction relations for red giant branch stars. For this purpose, we apply the different surface correction relations in asteroseismic analyses of eclipsing binaries and open clusters. In accordance with previous studies of main-sequence stars, we find that the use of different surface correction relations biases the derived global stellar properties, including stellar age, mass, and distance estimates. We, furthermore, demonstrate that the different relations lead to the same systematic errors for two different open clusters. Our results overall discourage from the use of surface correction relations that rely on reference stars to calibrate free parameters. Due to the demonstrated systematic biasing of the results, the use of appropriate surface correction relations is imperative to any asteroseismic analysis of red giants. Accurate mass, age, and distance estimates for red giants are fundamental when addressing questions that deal with the chemo-dynamical evolution of the Milky Way galaxy. In this way, our results also have implications for fields such as galactic archaeology that draw on findings from stellar physics.

See Change: VLT spectroscopy of a sample of high-redshift Type Ia supernova host galaxies

ABSTRACT The Supernova Cosmology Project has conducted the ‘See Change’ programme, aimed at discovering and observing high-redshift (1.13 ≤ z ≤ 1.75) Type Ia supernovae (SNe Ia). We used multifilter Hubble Space Telescope (HST) observations of massive galaxy clusters with sufficient cadence to make the observed SN Ia light curves suitable for a cosmological probe of dark energy at z > 0.5. This See Change sample of SNe Ia with multi-colour light curves will be the largest to date at these redshifts. As part of the See Change programme, we obtained ground-based spectroscopy of each discovered transient and/or its host galaxy. Here, we present Very Large Telescope (VLT) spectra of See Change transient host galaxies, deriving their redshifts, and host parameters such as stellar mass and star formation rate. Of the 39 See Change transients/hosts that were observed with the VLT, we successfully determined the redshift for 26, including 15 SNe Ia at z > 0.97. We show that even in passive environments, it is possible to recover secure redshifts for the majority of SN hosts out to z = 1.5. We find that with typical exposure times of 3−4 h on an 8-m-class telescope we can recover ∼75 per cent of SN Ia redshifts in the range of 0.97 < z < 1.5. Furthermore, we show that the combination of HST photometry and VLT spectroscopy is able to provide estimates of host galaxy stellar mass that are sufficiently accurate for use in a mass-step correction in the cosmological analysis.

On the (Lack of) Evolution of the Stellar Mass Function of Massive Galaxies from z = 1.5 to 0.4

Abstract We study the evolution in the number density of galaxies at the highest stellar masses over the past ≈9 Gyr ( ) using the Spitzer/HETDEX Exploratory Large-Area Survey (SHELA). SHELA includes complete imaging in eight photometric bands spanning 0.3–4.5 μm over 17.5 deg2 within the SDSS Stripe 82 field. The size of SHELA produces the lowest counting uncertainties and cosmic variance yet for massive galaxies at z ∼ 1.0. We study the evolution in the intrinsic stellar mass function (SMF) for galaxies with using a forward-modeling method that takes into full account the statistical and systematic uncertainties on stellar mass. From z = 0.4 to 1.5, the evolution in the massive end of the intrinsic SMF shows minimal change in its shape: the characteristic mass (M*) evolves by less than 0.1 dex (±0.05 dex); furthermore, the number density of galaxies with 11 stays roughly constant at (±0.05) from z = 1 to z = 0.4, consistent with no evolution, then declines to = −3.7 (±0.05) at z = 1.5. We discuss the uncertainties in the derived SMF, which are dominated by assumptions in the star formation history and details of stellar population synthesis models for stellar mass estimations. We also study the evolution in the SMF for samples of star-forming and quiescent galaxies selected by their specific star formation rate. For quiescent galaxies, the data are consistent with no (or slight) evolution (≲0.1 dex) in either the characteristic mass or number density from z ∼ 1.5 to the present even after accounting for the systematic uncertainty and the random error in the stellar mass measurement. The lack of number density evolution in the quiescent massive galaxy population means that any mass growth (presumably through “dry” mergers) must balance the rate of stellar mass losses owing to processes of late-stage stellar evolution and the formation of newly quiescent galaxies from the star-forming population. We provide an upper limit on this mass growth from z = 1.0 to 0.4 of ΔM */M * = 45% (i.e., ≃0.16 dex) for quiescent galaxies more massive than 1011 M ⊙.