arXiv subjects

Malgorzata Siudek

Publications and source records attributed to Malgorzata Siudek.

28 records · Page 2Linked to original sources

arXiv2022

Deep Extragalactic VIsible Legacy Survey (DEVILS): The emergence of bulges and decline of disk growth since $z = 1$

We present a complete structural analysis of the ellipticals (E), diffuse bulges (dB), compact bulges (cB), and disks (D) within a redshift range $0 < z < 1$, and stellar mass $\log_{10}(\mathrm{M}_*/\mathrm{M}_\odot) \geq 9.5$ volume-limited sample drawn from the combined DEVILS and HST-COSMOS region. We use the {\sc ProFit} code to profile over $\sim35,000$ galaxies for which visual classification into single or double-component was predefined in Paper-I. Over this redshift range, we see a growth in the total stellar mass density (SMD) of a factor of 1.5. At all epochs we find that the dominant structure, contributing to the total SMD, is the disk, and holds a fairly constant share of $\sim60\%$ of the total SMD from $z = 0.8$ to $z = 0.2$, dropping to $\sim30\%$ at $z = 0.0$ (representing $\sim33\%$ decline in the total disk SMD). Other classes (E, dB, and cB) show steady growth in their numbers and integrated stellar mass densities. By number, the most dramatic change across the full mass range is in the growth of diffuse bulges. In terms of total SMD, the biggest gain is an increase in massive elliptical systems, rising from 20\% at $z = 0.8$ to equal that of disks at $z = 0.0$ (30\%) representing an absolute mass growth of a factor of 2.5. Overall we see a clear picture of the emergence and growth of all three classes of spheroids over the past 8 Gyrs, and infer that in the later half of the Universe's timeline spheroid forming-processes and pathways (secular evolution, mass-accretion, and mergers) appear to dominate mass transformation over quiescent disk growth.

astro-ph.GA↗

arXiv2022

The DESI PRObabilistic Value-Added Bright Galaxy Survey (PROVABGS) Mock Challenge

The PRObabilistic Value-Added Bright Galaxy Survey (PROVABGS) catalog will provide measurements of galaxy properties, such as stellar mass ($M_*$), star formation rate (${\rm SFR}$), stellar metallicity ($Z_{\rm MW}$), and stellar age ($t_{\rm age, MW}$), for >10 million galaxies of the DESI Bright Galaxy Survey. Full posterior distributions of the galaxy properties will be inferred using state-of-the-art Bayesian spectral energy distribution (SED) modeling of DESI spectroscopy and Legacy Surveys photometry. In this work, we present the SED model, Bayesian inference framework, and methodology of PROVABGS. Furthermore, we apply the PROVABGS SED modeling on realistic synthetic DESI spectra and photometry, constructed using the L-GALAXIES semi-analytic model. We compare the inferred galaxy properties to the true galaxy properties of the simulation using a hierarchical Bayesian framework to quantify accuracy and precision. Overall, we accurately infer the true $M_*$, ${\rm SFR}$, $Z_{\rm MW}$, and $t_{\rm age, MW}$ of the simulated galaxies. However, the priors on galaxy properties induced by the SED model have a significant impact on the posteriors. They impose a ${\rm SFR}{>}10^{-1} M_\odot/{\rm yr}$ lower bound on ${\rm SFR}$, a ${\sim}0.3$ dex bias on $\log Z_{\rm MW}$ for galaxies with low spectral signal-to-noise, and $t_{\rm age, MW} < 8\,{\rm Gyr}$ upper bound on stellar age. This work also demonstrates that a joint analysis of spectra and photometry significantly improves the constraints on galaxy properties over photometry alone and is necessary to mitigate the impact of the priors. With the methodology presented and validated in this work, PROVABGS will maximize information extracted from DESI observations and provide a probabilistic value-added galaxy catalog that will extend current galaxy studies to new regimes and unlock cutting-edge probabilistic analyses.

astro-ph.GA↗

arXiv2021

Deep Extragalactic VIsible Legacy Survey (DEVILS): Identification of AGN through SED Fitting and the Evolution of the Bolometric AGN Luminosity Function

Active galactic nuclei (AGN) are typically identified through radio, mid-infrared, or X-ray emission or through the presence of broad and/or narrow emission lines. AGN can also leave an imprint on a galaxy's spectral energy distribution (SED) through the re-processing of photons by the dusty torus. Using the SED fitting code ProSpect with an incorporated AGN component, we fit the far ultraviolet to far-infrared SEDs of $\sim$494,00 galaxies in the D10-COSMOS field and $\sim$230,000 galaxies from the GAMA survey. By combining an AGN component with a flexible star formation and metallicity implementation, we obtain estimates for the AGN luminosities, stellar masses, star formation histories, and metallicity histories for each of our galaxies. We find that ProSpect can identify AGN components in 91 per cent of galaxies pre-selected as containing AGN through narrow-emission line ratios and the presence of broad lines. Our ProSpect-derived AGN luminosities show close agreement with luminosities derived for X-ray selected AGN using both the X-ray flux and previous SED fitting results. We show that incorporating the flexibility of an AGN component when fitting the SEDs of galaxies with no AGN has no significant impact on the derived galaxy properties. However, in order to obtain accurate estimates of the stellar properties of AGN host galaxies, it is crucial to include an AGN component in the SED fitting process. We use our derived AGN luminosities to map the evolution of the AGN luminosity function for $0<z<2$ and find good agreement with previous measurements and predictions from theoretical models.

astro-ph.GA↗

arXiv2021

The PAU Survey: Measurement of Narrow-band galaxy properties with Approximate Bayesian Computation

Narrow-band imaging surveys allow the study of the spectral characteristics of galaxies without the need of performing their spectroscopic follow-up. In this work, we forward-model the Physics of the Accelerating Universe Survey (PAUS) narrow-band data. The aim is to improve the constraints on the spectral coefficients used to create the galaxy spectral energy distributions (SED) of the galaxy population model in Tortorelli et al. 2020. In that work, the model parameters were inferred from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) data using Approximate Bayesian Computation (ABC). This led to stringent constraints on the B-band galaxy luminosity function parameters, but left the spectral coefficients only broadly constrained. To address that, we perform an ABC inference using CFHTLS and PAUS data. This is the first time our approach combining forward-modelling and ABC is applied simultaneously to multiple datasets. We test the results of the ABC inference by comparing the narrow-band magnitudes of the observed and simulated galaxies using Principal Component Analysis, finding a very good agreement. Furthermore, we prove the scientific potential of the constrained galaxy population model to provide realistic stellar population properties by measuring them with the SED fitting code \textsc{CIGALE}. We use CFHTLS broad-band and PAUS narrow-band photometry for a flux-limited ($\mathrm{i}<22.5$) sample of galaxies up to redshift $\mathrm{z \sim 0.8}$. We find that properties like stellar masses, star-formation rates, mass-weighted stellar ages and metallicities are in agreement within errors between observations and simulations. Overall, this work shows the ability of our galaxy population model to correctly forward-model a complex dataset such as PAUS and the ability to reproduce the diversity of galaxy properties at the redshift range spanned by CFHTLS and PAUS.

astro-ph.GA↗

arXiv2021

Deep Extragalactic VIsible Legacy Survey (DEVILS): SED Fitting in the D10-COSMOS Field and the Evolution of the Stellar Mass Function and SFR-$M_\star$ relation

We present catalogues of stellar masses, star formation rates, and ancillary stellar population parameters for galaxies spanning $0 2.6$, we see evidence of a bend in the relation at low redshifts ($z<0.45$). This suggests evolution in both the normalisation and shape of the SFR-$M_\star$ 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.

astro-ph.GA↗

arXiv2021

The PAU Survey: Intrinsic alignments and clustering of narrow-band photometric galaxies

We present the first measurements of the projected clustering and intrinsic alignments (IA) of galaxies observed by the Physics of the Accelerating Universe Survey (PAUS). With photometry in 40 narrow optical passbands ($450\rm{nm}-850\rm{nm}$), the quality of photometric redshift estimation is $σ_{z} \sim 0.01(1 + z)$ for galaxies in the $19\,\rm{deg}^{2}$ Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) W3 field, allowing us to measure the projected 3D clustering and IA for flux-limited, faint galaxies ($i < 22.5$) out to $z\sim0.8$. To measure two-point statistics, we developed, and tested with mock photometric redshift samples, `cloned' random galaxy catalogues which can reproduce data selection functions in 3D and account for photometric redshift errors. In our fiducial colour-split analysis, we made robust null detections of IA for blue galaxies and tentative detections of radial alignments for red galaxies ($\sim1-3σ$), over scales of $0.1-18\,h^{-1}\rm{Mpc}$. The galaxy clustering correlation functions in the PAUS samples are comparable to their counterparts in a spectroscopic population from the Galaxy and Mass Assembly survey, modulo the impact of photometric redshift uncertainty which tends to flatten the blue galaxy correlation function, whilst steepening that of red galaxies. We investigate the sensitivity of our correlation function measurements to choices in the random catalogue creation and the galaxy pair-binning along the line of sight, in preparation for an optimised analysis over the full PAUS area.

astro-ph.GA↗

arXiv2021

Deep Extragalactic VIsible Legacy Survey (DEVILS): Stellar Mass Growth by Morphological Type since $z = 1$

Using high-resolution Hubble Space Telescope imaging data, we perform a visual morphological classification of $\sim 36,000$ galaxies at $z < 1$ in the DEVILS/COSMOS region. As the main goal of this study, we derive the stellar mass function (SMF) and stellar mass density (SMD) sub-divided by morphological types. We find that visual morphological classification using optical imaging is increasingly difficult at $z > 1$ as the fraction of irregular galaxies and merger systems (when observed at rest-frame UV/blue wavelengths) dramatically increases. We determine that roughly two-thirds of the total stellar mass of the Universe today was in place by $z \sim 1$. Double-component galaxies dominate the SMD at all epochs and increase in their contribution to the stellar mass budget to the present day. Elliptical galaxies are the second most dominant morphological type and increase their SMD by $\sim 2.5$ times, while by contrast, the pure-disk population significantly decreases by $\sim 85\%$. According to the evolution of both high- and low-mass ends of the SMF, we find that mergers and in-situ evolution in disks are both present at $z < 1$, and conclude that double-component galaxies are predominantly being built by the in-situ evolution in disks (apparent as the growth of the low-mass end with time), while mergers are likely responsible for the growth of ellipticals (apparent as the increase of intermediate/high-mass end).

astro-ph.GA↗

arXiv2021

GAMA/DEVILS: Constraining the cosmic star-formation history from improved measurements of the 0.3-2.2 micron Extragalactic Background Light

We present a revised measurement of the optical extragalactic background light (EBL), based on the contribution of resolved galaxies to the integrated galaxy light (IGL). The cosmic optical background radiation (COB), encodes the light generated by star-formation, and provides a wealth of information about the cosmic star formation history (CSFH). We combine wide and deep galaxy number counts from the Galaxy And Mass Assembly survey (GAMA) and Deep Extragalactic VIsible Legacy Survey (DEVILS), along with the Hubble Space Telescope (HST) archive and other deep survey datasets, in 9 multi-wavelength filters to measure the COB in the range from 0.35 micron to 2.2 micron. We derive the luminosity density in each band independently and show good agreement with recent and complementary estimates of the optical-EBL from very high-energy (VHE) experiments. Our error analysis suggests that the IGL and Gamma-ray measurements are now fully consistent to within ~10%, suggesting little need for any additional source of diffuse light beyond the known galaxy population. We use our revised IGL measurements to constrain the cosmic star-formation history, and place amplitude constraints on a number of recent estimates. As a consistency check, we can now demonstrate convincingly, that the CSFH, stellar mass growth, and the optical-EBL provide a fully consistent picture of galaxy evolution. We conclude that the peak of star-formation rate lies in the range 0.066-0.076 Msol/yr/Mpc^3 at a lookback time of 9.1 to 10.9 Gyrs.

astro-ph.CO↗

arXiv2020

The PAU Survey: An improved photo-$z$ sample in the COSMOS field

We present -- and make publicly available -- accurate and precise photometric redshifts in the ACS footprint from the COSMOS field for objects with $i_{\mathrm{AB}}\leq 23$. The redshifts are computed using a combination of narrow band photometry from PAUS, a survey with 40 narrow bands spaced at $100Å$ intervals covering the range from $4500Å$ to $8500Å$, and 26 broad, intermediate, and narrow bands covering the UV, visible and near infrared spectrum from the COSMOS2015 catalogue. We introduce a new method that models the spectral energy distributions (SEDs) as a linear combination of continuum and emission line templates and computes its Bayes evidence, integrating over the linear combinations. The correlation between the UV luminosity and the OII line is measured using the 66 available bands with the zCOSMOS spectroscopic sample, and used as a prior which constrains the relative flux between continuum and emission line templates. The flux ratios between the OII line and $\mathrm{H}_α$, $\mathrm{H}_β$ and $\mathrm{OIII}$ are similarly measured and used to generate the emission line templates. Comparing to public spectroscopic surveys via the quantity $Δ_z\equiv(z_{\mathrm{photo}}-z_{\mathrm{spec}})/(1+z_{\mathrm{spec}})$, we find the photometric redshifts to be more precise than previous estimates, with $σ_{68}(Δ_z) \approx (0.003, 0.009)$ for galaxies at magnitude $i_{\mathrm{AB}}\sim18$ and $i_{\mathrm{AB}}\sim23$, respectively, which is $3\times$ and $1.66\times$ tighter than COSMOS2015. Additionally, we find the redshifts to be very accurate on average, yielding a median of the $Δ_z$ distribution compatible with $|\mathrm{median}(Δ_z)|\leq0.001$ at all redshifts and magnitudes considered. Both the added PAUS data and new methodology contribute significantly to the improved results.

astro-ph.GA↗

arXiv2020

The PAU Survey: Background light estimation with deep learning techniques

In any imaging survey, measuring accurately the astronomical background light is crucial to obtain good photometry. This paper introduces BKGnet, a deep neural network to predict the background and its associated error. BKGnet has been developed for data from the Physics of the Accelerating Universe Survey (PAUS), an imaging survey using a 40 narrow-band filter camera (PAUCam). Images obtained with PAUCam are affected by scattered light: an optical effect consisting of light multiply that deposits energy in specific detector regions contaminating the science measurements. Fortunately, scattered light is not a random effect, but it can be predicted and corrected for. We have found that BKGnet background predictions are very robust to distorting effects, while still being statistically accurate. On average, the use of BKGnet improves the photometric flux measurements by 7% and up to 20% at the bright end. BKGnet also removes a systematic trend in the background error estimation with magnitude in the i-band that is present with the current PAU data management method. With BKGnet, we reduce the photometric redshift outlier rate

astro-ph.IM↗