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Register a new userTesting the accuracy of 3D-HST photometric redshift estimates as reference samples for deep weak lensing studies
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Siti Fatimah Raihan
Publication date
2020
fields
Physics
and research's language is
English
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Accurate weak lensing mass estimates of clusters are needed in order to calibrate mass proxies for the cosmological exploitation of galaxy cluster surveys. Such measurements require accurate knowledge of the redshift distribution of the weak lensing source galaxies. In this context, we investigate the accuracy of photometric redshifts (photo-$z$s) computed by the 3D-HST team for the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey fields, which provide a relevant photometric reference data set for deep weak lensing studies. Through the comparison to spectroscopic redshifts and photo-$z$s based on very deep data from the Hubble Ultra Deep Field, we identify catastrophic redshift outliers in the 3D-HST/CANDELS catalogue. These would significantly bias weak lensing results if not accounted for. We investigate the cause of these outliers and demonstrate that the interpolation of spectral energy distribution (SED) templates and a well-selected combination of photometric data can reduce the net impact for weak lensing studies.
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The 3D-HST and CANDELS programs have provided WFC3 and ACS spectroscopy and photometry over ~900 square arcminutes in five fields: AEGIS, COSMOS, GOODS-North, GOODS-South, and the UKIDSS UDS field. All these fields have a wealth of publicly available imaging datasets in addition to the HST data, which makes it possible to construct the spectral energy distributions (SEDs) of objects over a wide wavelength range. In this paper we describe a photometric analysis of the CANDELS and 3D-HST HST imaging and the ancillary imaging data at wavelengths 0.3um to 8um. Objects were selected in the WFC3 near-IR bands, and their SEDs were determined by carefully taking the effects of the point spread function in each observation into account. A total of 147 distinct imaging datasets were used in the analysis. The photometry is made available in the form of six catalogs: one for each field, as well as a master catalog containing all objects in the entire survey. We also provide derived data products: photometric redshifts, determined with the EAZY code, and stellar population parameters determined with the FAST code. We make all the imaging data that were used in the analysis available, including our reductions of the WFC3 imaging in all five fields. 3D-HST is a spectroscopic survey with the WFC3 and ACS grisms, and the photometric catalogs presented here constitute a necessary first step in the analysis of these grism data. All the data presented in this paper are available through the 3D-HST website.
We present a study of photometric redshift accuracy in the 3D-HST photometric catalogs, using 3D-HST grism redshifts to quantify and dissect trends in redshift accuracy for galaxies brighter than $H_{F140W}<24$ with an unprecedented and representative high-redshift galaxy sample. We find an average scatter of $0.0197pm0.0003(1+z)$ in the Skelton et al. (2014) photometric redshifts. Photometric redshift accuracy decreases with magnitude and redshift, but does not vary monotonically with color or stellar mass. The 1-$sigma$ scatter lies between $0.01-0.03$(1+z) for galaxies of all masses and colors below $z<2.5$ (for $H_{F140W}{<}24$), with the exception of a population of very red ($U-V > 2$), dusty star-forming galaxies for which the scatter increases to $sim0.1(1+z)$. Although the overall photometric redshift accuracy for quiescent galaxies is better than for star-forming galaxies, scatter depends more strongly on magnitude and redshift than on galaxy type. We verify these trends using the redshift distributions of close pairs and extend the analysis to fainter objects, where photometric redshift errors further increase to $sim0.046(1+z)$ at $H_{F160W}=26$. We demonstrate that photometric redshift accuracy is strongly filter-dependent and quantify the contribution of multiple filter combinations. We evaluate the widths of redshift probability distribution functions and find that error estimates are underestimated by a factor of $sim1.1-1.6$, but that uniformly broadening the distribution does not adequately account for fitting outliers. Finally, we suggest possible applications of these data in planning for current and future surveys and simulate photometric redshift performance in the LSST, DES, and combined DES and VHS surveys.
In order for Wide-Field Infrared Survey Telescope (WFIRST) and other Stage IV dark energy experiments (e.g., Large Synoptic Survey Telescope; LSST, and Euclid) to infer cosmological parameters not limited by systematic errors, accurate redshift measurements are needed. This accuracy can be met by using spectroscopic subsamples to calibrate the photometric redshifts for the full sample. In this work we employ the Self Organizing Map (SOM) spectroscopic sampling technique, to find the minimal number of spectra required for the WFIRST weak lensing calibration. We use galaxies from the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) to build the LSST+WFIRST lensing analog sample of ~36 k objects and train the LSST+WFIRST SOM. We find that 26% of the WFIRST lensing sample consists of sources fainter than the Euclid depth in the optical, 91% of which live in color cells already occupied by brighter galaxies. We demonstrate the similarity between faint and bright galaxies as well as the feasibility of redshift measurements at different brightness levels. Our results suggest that the spectroscopic sample acquired for calibration to the Euclid depth is sufficient for calibrating the majority of the WFIRST color-space. For the spectroscopic sample to fully represent the synthetic color-space of WFIRST, we recommend obtaining additional spectroscopy of ~0.2-1.2 k new sources in cells occupied by mostly faint galaxies. We argue that either the small area of the CANDELS fields and the small overall sample size or the large photometric errors might be the reason for no/less bright galaxies mapped to these cells. Acquiring the spectra of these sources will confirm the above findings and will enable the comprehensive calibration of the WFIRST color-redshift relation.
Obtaining accurate distributions of galaxy redshifts is a critical aspect of weak lensing cosmology experiments. One of the methods used to estimate and validate redshift distributions is apply weights to a spectroscopic sample so that their weighted photometry distribution matches the target sample. In this work we estimate the textit{selection bias} in redshift that is introduced in this procedure. We do so by simulating the process of assembling a spectroscopic sample (including observer-assigned confidence flags) and highlight the impacts of spectroscopic target selection and redshift failures. We use the first year (Y1) weak lensing analysis in DES as an example data set but the implications generalise to all similar weak lensing surveys. We find that using colour cuts that are not available to the weak lensing galaxies can introduce biases of $Delta~zsim0.015$ in the weighted mean redshift of different redshift intervals. To assess the impact of incompleteness in spectroscopic samples, we select only objects with high observer-defined confidence flags and compare the weighted mean redshift with the true mean. We find that the mean redshift of the DES Y1 weak lensing sample is typically biased at the $Delta~z=0.005-0.05$ level after the weighting is applied. The bias we uncover can have either sign, depending on the samples and redshift interval considered. For the highest redshift bin, the bias is larger than the uncertainties in the other DES Y1 redshift calibration methods, justifying the decision of not using this method for the redshift estimations. We discuss several methods to mitigate this bias.
Weak lensing surveys are emerging as an important tool for the construction of mass selected clusters of galaxies. We evaluate both the efficiency and completeness of a weak lensing selection by combining a dense, complete redshift survey, the Smithsonian Hectospec Lensing Survey (SHELS), with a weak lensing map from the Deep Lens Survey (DLS). SHELS includes 11,692 redshifts for galaxies with R < 20.6 in the four square degree DLS field; the survey is a solid basis for identifying massive clusters of galaxies with redshift z < 0.55. The range of sensitivity of the redshift survey is similar to the range for the DLS convergence map. Only four the twelve convergence peaks with signal-to-noise > 3.5 correspond to clusters of galaxies with M > 1.7 x 10^14 solar masses. Four of the eight massive clusters in SHELS are detected in the weak lensing map yielding a completeness of roughly 50%. We examine the seven known extended cluster x-ray sources in the DLS field: three can be detected in the weak lensing map, three should not be detected without boosting from superposed large-scale structure, and one is mysteriously undetected even though its optical properties suggest that it should produce a detectable lensing signal. Taken together, these results underscore the need for more extensive comparisons among different methods of massive cluster identification.
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