Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userGalaxy properties from J-PAS narrow-band photometry
107
0
0.0
(
0
)
Added by
Alfredo Mej\\'ia-Narv\\'aez
Publication date
2017
fields
Physics
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
We study the consistency of the physical properties of galaxies retrieved from SED-fitting as a function of spectral resolution and signal-to-noise ratio (SNR). Using a selection of physically motivated star formation histories, we set up a control sample of mock galaxy spectra representing observations of the local universe in high-resolution spectroscopy, and in 56 narrow-band and 5 broad-band photometry. We fit the SEDs at these spectral resolutions and compute their corresponding the stellar mass, the mass- and luminosity-weighted age and metallicity, and the dust extinction. We study the biases, correlations, and degeneracies affecting the retrieved parameters and explore the r^ole of the spectral resolution and the SNR in regulating these degeneracies. We find that narrow-band photometry and spectroscopy yield similar trends in the physical properties derived, the former being considerably more precise. Using a galaxy sample from the SDSS, we compare more realistically the results obtained from high-resolution and narrow-band SEDs (synthesized from the same SDSS spectra) following the same spectral fitting procedures. We use results from the literature as a benchmark to our spectroscopic estimates and show that the prior PDFs, commonly adopted in parametric methods, may introduce biases not accounted for in a Bayesian framework. We conclude that narrow-band photometry yields the same trend in the age-metallicity relation in the literature, provided it is affected by the same biases as spectroscopy; albeit the precision achieved with the latter is generally twice as large as with the narrow-band, at SNR values typical of the different kinds of data.
rate research
Read More
Our aim in this work is to answer, using simulated narrow-band photometry data, the following general question: What can we learn about galaxies from these new generation cosmological surveys? For instance, can we estimate stellar age and metallicity distributions? Can we separate star-forming galaxies from AGN? Can we measure emission lines, nebular abundances and extinction? With what precision? To accomplish this, we selected a sample of about 300k galaxies with good S/N from the SDSS and divided them in two groups: 200k objects and a template library of 100k. We corrected the spectra to $z = 0$ and converted them to filter fluxes. Using a statistical approach, we calculated a Probability Distribution Function (PDF) for each property of each object and the library. Since we have the properties of all the data from the {sc starlight}-SDSS database, we could compare them with the results obtained from summaries of the PDF (mean, median, etc). Our results shows that we retrieve the weighted average of the log of the galaxy age with a good error margin ($sigma approx 0.1 - 0.2$ dex), and similarly for the physical properties such as mass-to-light ratio, mean stellar metallicity, etc. Furthermore, our main result is that we can derive emission line intensities and ratios with similar precision. This makes this method unique in comparison to the other methods on the market to analyze photometry data and shows that, from the point of view of galaxy studies, future photometric surveys will be much more useful than anticipated.
The impending Javalambre Physics of the accelerating universe Astrophysical Survey (J-PAS) will be the first wide-field survey of $gtrsim$ 8500 deg$^2$ to reach the `stage IV category. Because of the redshift resolution afforded by 54 narrow-band filters, J-PAS is particularly suitable for cluster detection in the range z$<$1. The photometric redshift dispersion is estimated to be only $sim 0.003$ with few outliers $lesssim$ 4% for galaxies brighter than $isim23$ AB, because of the sensitivity of narrow band imaging to absorption and emission lines. Here we evaluate the cluster selection function for J-PAS using N-body+semi-analytical realistic mock catalogues. We optimally detect clusters from this simulation with the Bayesian Cluster Finder, and we assess the completeness and purity of cluster detection against the mock data. The minimum halo mass threshold we find for detections of galaxy clusters and groups with both $>$80% completeness and purity is $M_h sim 5 times 10^{13}M_{odot}$ up to $zsim 0.7$. We also model the optical observable, $M^*_{rm CL}$-halo mass relation, finding a non-evolution with redshift and main scatter of $sigma_{M^*_{rm CL} | M_{rm h}}sim 0.14 ,dex$ down to a factor two lower in mass than other planned broad-band stage IV surveys, at least. For the $M_{rm h} sim 1 times 10^{14}M_{odot}$ Planck mass limit, J-PAS will arrive up to $zsim 0.85$ with a $sigma_{M^*_{rm CL} | M_{rm h}}sim 0.12 , dex$. Therefore J-PAS will provide the largest sample of clusters and groups up to $zsim 0.8$ with a mass calibration accuracy comparable to X-ray data.
We present a mock catalogue for the Physics of the Accelerating Universe Survey (PAUS) and use it to quantify the competitiveness of the narrow band imaging for measuring spectral features and galaxy clustering. The mock agrees with observed number count and redshift distribution data. We demonstrate the importance of including emission lines in the narrow band fluxes. We show that PAUCam has sufficient resolution to measure the strength of the 4000AA{} break to the nominal PAUS depth. We predict the evolution of a narrow band luminosity function and show how this can be affected by the OII emission line. We introduce new rest frame broad bands (UV and blue) that can be derived directly from the narrow band fluxes. We use these bands along with D4000 and redshift to define galaxy samples and provide predictions for galaxy clustering measurements. We show that systematic errors in the recovery of the projected clustering due to photometric redshift errors in PAUS are significantly smaller than the expected statistical errors. The galaxy clustering on two halo scales can be recovered quantatively without correction, and all qualitative trends seen in the one halo term are recovered. In this analysis mixing between samples reduces the expected contrast between the one halo clustering of red and blue galaxies and demonstrates the importance of a mock catalogue for interpreting galaxy clustering results. The mock catalogue is available on request at https://cosmohub.pic.es/home.
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 CIGALE. We use CFHTLS broad-band and PAUS narrow-band photometry for a flux-limited ($mathrm{i}<22.5$) sample of galaxies spanning the redshift range $mathrm{0<z<1.0}$. 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.
J-PAS will soon start imaging 8000 deg2 of the northern sky with its unique set of 56 filters (R $sim$ 60). Before, we observed 1 deg2 on the AEGIS field with an interim camera with all the J-PAS filters. With this data (miniJPAS), we aim at proving the scientific potential of J-PAS to identify and characterize the galaxy populations with the goal of performing galaxy evolution studies across cosmic time. Several SED-fitting codes are used to constrain the stellar population properties of a complete flux-limited sample (rSDSS <= 22.5 AB) of miniJPAS galaxies that extends up to z = 1. We find consistent results on the galaxy properties derived from the different codes, independently of the galaxy spectral-type or redshift. For galaxies with SNR>=10, we estimate that the J-PAS photometric system allows to derive stellar population properties with a precision that is equivalent to that obtained with spectroscopic surveys of similar SNR. By using the dust-corrected (u-r) colour-mass diagram, a powerful proxy to characterize galaxy populations, we find that the fraction of red and blue galaxies evolves with cosmic time, with red galaxies being $sim$ 38% and $sim$ 18% of the whole population at z = 0.1 and z = 0.5, respectively. At all redshifts, the more massive galaxies belong to the red sequence and these galaxies are typically older and more metal rich than their counterparts in the blue cloud. Our results confirm that with J-PAS data we will be able to analyze large samples of galaxies up to z $sim$ 1, with galaxy stellar masses above of log(M$_*$/M$_{odot}$) $sim$ 8.9, 9.5, and 9.9 at z = 0.3, 0.5, and 0.7, respectively. The SFH of a complete sub-sample of galaxies selected at z $sim$ 0.1 with log(M$_*$/M$_{odot}$) > 8.3 constrain the cosmic evolution of the star formation rate density up to z $sim$ 3 in good agreement with results from cosmological surveys.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
