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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Measurement of the photometric baryon acoustic oscillations with self-calibrated redshift distribution

ABSTRACT We use a galaxy sample derived from the Dark Energy Camera Legacy Survey Data Release 9 to measure the baryonic acoustic oscillations (BAO). The magnitude-limited sample consists of 10.6 million galaxies in an area of 4974 deg2 over the redshift range of [0.6, 1]. A key novelty of this work is that the true redshift distribution of the photo-z sample is derived from the self-calibration method, which determines the true redshift distribution using the clustering information of the photometric data alone. Through the angular correlation function in four tomographic bins, we constrain the BAO scale dilation parameter α to be 1.025 ± 0.033, consistent with the fiducial Planck cosmology. Alternatively, the ratio between the comoving angular diameter distance and the sound horizon, DM/rs, is constrained to be 18.94 ± 0.61 at the effective redshift of 0.749. We corroborate our results with the true redshift distribution obtained from a weighted spectroscopic sample, finding very good agreement. We have conducted a series of tests to demonstrate the robustness of the measurement. Our work demonstrates that the self-calibration method can effectively constrain the true redshift distribution in cosmological applications, especially in the context of photometric BAO measurement.

Astronomy & Astrophysics↗
DOE OSTI2020

Density weighted angular redshift fluctuations: a new cosmological observable

We propose the use of angular fluctuations in the galaxy redshift field as a new way to extract cosmological information in the Universe. This new probe $\delta z (\hat{\mathbf {n}})$ consists of the statistics of sky maps built by projecting redshifts under a Gaussian window of width σz centred upon a redshift zobs, and weighted by the galaxy density field. We compute the angular power spectrum of the $\delta z (\hat{\mathbf {n}})$ field in both numerical simulations and in linear perturbation theory. From these, we find that the $\delta z (\hat{\mathbf {n}})$ field (i) is sensitive to the underlying density and peculiar velocity fields; (ii) is highly correlated, at the $\gtrsim 60\, {{\ \rm per\ cent}}$ level, to the line-of-sight projected peculiar velocity field; (iii) for narrow windows (σz < 0.03), it is almost completely uncorrelated to the projected galaxy angular density field under the same redshift window; and (iv) it is largely unaffected by multiplicative and additive systematic errors on the observed number of galaxies that are redshift-independent over ~σz. We conclude that $\delta z (\hat{\mathbf {n}})$ is a simple and robust tomographic measure of the cosmic density and velocity fields, complementary to angular clustering, that will contribute to more complete exploitations of current and upcoming galaxy redshift surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Applying Information Theory to Design Optimal Filters for Photometric Redshifts

In this paper we apply ideas from information theory to create a method for the design of optimal filters for photometric redshift estimation. We show the method applied to a series of simple example filters in order to motivate an intuition for how photometric redshift estimators respond to the properties of photometric passbands. We then design a realistic set of six filters covering optical wavelengths that optimize photometric redshifts for z <= 2.3 and i < 25.3. We create a simulated catalog for these optimal filters and use our filters with a photometric redshift estimation code to show that we can improve the standard deviation of the photometric redshift error by 7.1% overall and improve outliers 9.9% over the standard filters proposed for the Large Synoptic Survey Telescope (LSST). We compare features of our optimal filters to the LSST and find that the LSST filters incorporate key features for optimal photometric redshift estimation. Finally, we describe how information theory can be applied to a range of optimization problems in astronomy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The Power of DESI for Photometric Redshift Calibration: A Case Study with KiDS-1000

Accurate redshift estimates are a critical requirement for weak lensing surveys and one of the main uncertainties in constraints on dark energy and large-scale cosmic structure. In this paper, we study the potential to calibrate photometric redshift (photo-z) distributions for gravitational lensing using the Dark Energy Spectroscopic Instrument (DESI). Since beginning its science operations in 2021, DESI has collected more than 50 million redshifts, adding about one million monthly. In addition to its large-scale structure samples, DESI has also acquired over 256k high-quality spectroscopic redshifts (spec-zs) in the COSMOS and XMM and VVDS fields. This is already a factor of 3 larger than previous spec-z calibration compilations in these two regions. Here, we explore calibrating photo-zs for the subset of KiDS-1000 galaxies that fall into joint self-organizing map (SOM) cells overlapping the DESI COSMOS footprint using the DESI COSMOS observations. Estimating the redshift distribution in KiDS-1000 with the new DESI data, we find broad consistency with previously published results while also detecting differences in the mean redshift in some tomographic bins with an average shifts of Delta Mean(z) = -0.028 in the mean and Delta Median(z) = +0.011 in the median across tomographic bins. However, we also find that incompleteness per SOM cell, i.e., groups of galaxies with similar colors and magnitudes, can modify n(z) distributions. Finally, we comment on the fact that larger photometric catalogs, aligned with the DESI COSMOS and DESI XMM and VVDS footprints, would be needed to fully exploit the DESI dataset and would extend the coverage to nearly eight times the area of existing 9-band photometry.

Blanco, Diana [UC, Santa Cruz; UC, Santa Cruz, Ins↗
DOE OSTI2025

The Tianlai-WIYN North Celestial Cap Redshift Survey

We present the results of a small, low redshift spectroscopic survey of galaxies within 3 degrees of the North Celestial Pole (NCP) selected using V-band photometry obtained from the North Celestial Cap Survey (NCCS) (Gorbikov & Brosch 2014). The purpose of the current survey is to create a redshift space template for 21 cm emission from neutral hydrogen with which to correlate radio line intensity observations by the Tianlai dish and cylinder interferometers. A total of 898 redshifts were obtained from the 2102 extended objects in the NCCS with m_V < 19 in the survey area. After accounting for extinction, the survey geometry and selection effects, the number density and clustering pattern of galaxies in the redshift catalog are consistent with other low redshift surveys. We were also able to identify 11 galaxy cluster candidates from this redshift catalog.

Ansari, Reza [AIM, Saclay]↗
DOE OSTI2024

High redshift LBGs from deep broadband imaging for future spectroscopic surveys

Lyman break galaxies (LBGs) are promising probes for clustering measurements at high redshift, z > 2, a region only covered so far by Lyman-α forest measurements. Here, in this paper, we investigate the feasibility of selecting LBGs by exploiting the existence of a strong deficit of flux shortward of the Lyman limit, due to various absorption processes along the line of sight. The target selection relies on deep imaging data from the HSC and CLAUDS surveys in the g, r, z and u bands, respectively, with median depths reaching 27 AB in all bands. The selections were validated by several dedicated spectroscopic observation campaigns with DESI. Visual inspection of spectra has enabled us to develop an automated spectroscopic typing and redshift estimation algorithm specific to LBGs. Based on these data and tools, we assess the efficiency and purity of target selections optimised for different purposes. Selections providing a wide redshift coverage retain 57% of the observed targets after spectroscopic confirmation with DESI, and provide an efficiency for LBGs of 83 ± 3%, for a purity of the selected LBG sample of 90 ± 2%. This would deliver a confirmed LBG density of ~ 620 deg$^{-2}$ in the range 2.3 < z < 3.5 for a r-band limiting magnitude r < 24.2. Selections optimised for high redshift efficiency retain 73% of the observed targets after spectroscopic confirmation, with 89 ± 4% efficiency for 97 ± 2% purity. This would provide a confirmed LBG density of ~ 470 deg$^{-2}$ in the range 2.8 < z < 3.5 for a r-band limiting magnitude r < 24.5.A preliminary study of the LBG sample 3d-clustering properties is also presented and used to estimate the LBG linear bias. A value of b$_{LBG}$ = 3.3 ± 0.2 (stat.) is obtained for a mean redshift of 2.9 and a limiting magnitude in r of 24.2, in agreement with results reported in the literature.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The impact of tomographic redshift bin width errors on cosmological probes

ABSTRACT Systematic errors in the galaxy redshift distribution n(z) can propagate to systematic errors in the derived cosmology. We characterize how the degenerate effects in tomographic bin widths and galaxy bias impart systematic errors on cosmology inference using observational data from the Deep Lens Survey. For this we use a combination of galaxy clustering and galaxy–galaxy lensing. We present two end-to-end analyses from the catalogue level to parameter estimation. We produce an initial cosmological inference using fiducial tomographic redshift bins derived from photometric redshifts, then compare this with a result where the redshift bins are empirically corrected using a set of spectroscopic redshifts. We find that the derived parameter S8 ≡ σ8(Ωm/.3)1/2 decreases from $0.841^{+0.062}_{-0.061}$ to $0.781^{0.061}_{0.054}$ upon correcting the n(z) errors in the second method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Deep learning methods for obtaining photometric redshift estimations from images

ABSTRACT Knowing the redshift of galaxies is one of the first requirements of many cosmological experiments, and as it is impossible to perform spectroscopy for every galaxy being observed, photometric redshift (photo-z) estimations are still of particular interest. Here, we investigate different deep learning methods for obtaining photo-z estimates directly from images, comparing these with ‘traditional’ machine learning algorithms which make use of magnitudes retrieved through photometry. As well as testing a convolutional neural network (CNN) and inception-module CNN, we introduce a novel mixed-input model that allows for both images and magnitude data to be used in the same model as a way of further improving the estimated redshifts. We also perform benchmarking as a way of demonstrating the performance and scalability of the different algorithms. The data used in the study comes entirely from the Sloan Digital Sky Survey (SDSS) from which 1 million galaxies were used, each having 5-filtre (ugriz) images with complete photometry and a spectroscopic redshift which was taken as the ground truth. The mixed-input inception CNN achieved a mean squared error (MSE) =0.009, which was a significant improvement ($30{{\ \rm per\ cent}}$) over the traditional random forest (RF), and the model performed even better at lower redshifts achieving a MSE = 0.0007 (a $50{{\ \rm per\ cent}}$ improvement over the RF) in the range of z < 0.3. This method could be hugely beneficial to upcoming surveys, such as Euclid and the Vera C. Rubin Observatory’s Legacy Survey of Space and Time (LSST), which will require vast numbers of photo-z estimates produced as quickly and accurately as possible.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Dark Energy Survey Year 3 results: redshift calibration of the MagLim lens sample from the combination of SOMPZ and clustering and its impact on cosmology

ABSTRACT We present an alternative calibration of the MagLim lens sample redshift distributions from the Dark Energy Survey (DES) first 3 yr of data (Y3). The new calibration is based on a combination of a self-organizing-map-based scheme and clustering redshifts to estimate redshift distributions and inherent uncertainties, which is expected to be more accurate than the original DES Y3 redshift calibration of the lens sample. We describe in detail the methodology, and validate it on simulations and discuss the main effects dominating our error budget. The new calibration is in fair agreement with the fiducial DES Y3 n(z) calibration, with only mild differences (<3σ) in the means and widths of the distributions. We study the impact of this new calibration on cosmological constraints, analysing DES Y3 galaxy clustering and galaxy–galaxy lensing measurements, assuming a Lambda cold dark matter cosmology. We obtain Ωm = 0.30 ± 0.04, σ8 = 0.81 ± 0.07, and S8 = 0.81 ± 0.04, which implies a ∼0.4σ shift in the Ω − S8 plane compared to the fiducial DES Y3 results, highlighting the importance of the redshift calibration of the lens sample in multiprobe cosmological analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Dark Energy Survey Year 6 results: Redshift calibration of the MagLim++ lens sample

In this work, we derive and calibrate the redshift distribution of the MagLim++ lens galaxy sample used in the Dark Energy Survey Year 6 (DES Y6) 3 x 2pt cosmology analysis. The 3 x 2pt analysis combines galaxy clustering from the lens galaxy sample and weak gravitational lensing. The redshift distributions are inferred using the SOMPZ method - a Self-Organizing Map framework that combines deep-field multi-band photometry, wide-field data, and a synthetic source injection ( B alrog) catalog. Key improvements over the DES Year 3 (Y3) calibration include a noise-weighted SOM metric, an expanded Balrog catalogue, and an improved scheme for propagating systematic uncertainties, which allows us to generate O(10 8 ) redshift realizations that collectively span the dominant sources of uncertainty. These realizations are then combined with independent clustering-redshift measurements via importance sampling. The resulting calibration achieves typical uncertainties on the mean redshift of 1-2%, corresponding to a 20-30% average reduction relative to DES Y3. We compress the n(z) uncertainties into a small number of orthogonal modes for use in cosmological inference. Marginalizing over these modes leads to only a minor degradation in cosmological constraints. Here, this analysis establishes the MagLim++ sample as a robust lens sample for precision cosmology with DES Y6 and provides a scalable framework for future surveys.

dark energy↗
DOE OSTI2024

Photometric redshifts probability density estimation from recurrent neural networks in the DECam local volume exploration survey data release 2

Photometric wide-field surveys are imaging the sky in unprecedented detail. These surveys face a significant challenge in efficiently estimating galactic photometric redshifts while accurately quantifying associated uncertainties. In this work, we address this challenge by exploring the estimation of Probability Density Functions (PDFs) for the photometric redshifts of galaxies across a vast area of 17,000 square degrees, encompassing objects with a median 5 σ point-source depth of g = 24.3, r = 23 . 9 , i = 23.5, and z = 22.8 mag. Our approach uses deep learning, specifically integrating a Recurrent Neural Network architecture with a Mixture Density Network, to leverage magnitudes and colors as input features for constructing photometric redshift PDFs across the whole DECam Local Volume Exploration (DELVE) survey sky footprint. Subsequently, we rigorously evaluate the reliability and robustness of our estimation methodology, gauging its performance against other well-established machine learning methods to ensure the quality of our redshift estimations. Our best results constrain photometric redshifts with the bias of − 0 . 0013 , a scatter of 0.0293, and an outlier fraction of 5.1%. These point estimates are accompanied by well-calibrated PDFs evaluated using diagnostic tools such as Probability Integral Transform and Odds distribution. We also address the problem of the accessibility of PDFs in terms of disk space storage and the time demand required to generate their corresponding parameters.We present a novel Autoencoder model that reduces the size of PDF parameter arrays to one-sixth of their original length, significantly decreasing the time required for PDF generation to one-eighth of the time needed when generating PDFs directly from the magnitudes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Constraining scale dependent growth with redshift surveys

Ongoing and future redshift surveys have the capability to measure the growth rate of large scale structure at the percent level over a broad range of redshifts, tightly constraining cosmological parameters. Beyond general relativity, however, the growth rate in the linear density perturbation regime can be not only redshift dependent but scale dependent, revealing important clues to modified gravity. We demonstrate that a fully model independent approach of binning the gravitational strength G eff (k,z) matches scalar-tensor results for the growth rate fσ 8 (k,z) to 0.02%–0.27% rms accuracy. For data of the quality of the Dark Energy Spectroscopic Instrument (DESI) we find the bin values can be constrained to 1.4%–28%. We also explore the general scalar-tensor form, constraining the amplitude and past and future scalaron mass/shape parameters. Perhaps most interesting is the strong complementarity of low redshift peculiar velocity data with DESI-like redshift space distortion measurements, enabling improvements up to a factor 6–7 on 2D joint confidence contour areas. Finally, we quantify some issues with gravity parametrizations that do not include all the key physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

The Completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: measurement of the BAO and growth rate of structure of the luminous red galaxy sample from the anisotropic power spectrum between redshifts 0.6 and 1.0

ABSTRACT We analyse the clustering of the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 16 luminous red galaxy sample (DR16 eBOSS LRG) in combination with the high redshift tail of the Sloan Digital Sky Survey III Baryon Oscillation Spectroscopic Survey Data Release 12 (DR12 BOSS CMASS). We measure the redshift space distortions (RSD) and also extract the longitudinal and transverse baryonic acoustic oscillation (BAO) scale from the anisotropic power spectrum signal inferred from 377 458 galaxies between redshifts 0.6 and 1.0, with the effective redshift of zeff = 0.698 and effective comoving volume of $2.72\, {\rm Gpc}^3$. After applying reconstruction, we measure the BAO scale and infer DH(zeff)/rdrag = 19.30 ± 0.56 and DM(zeff)/rdrag = 17.86 ± 0.37. When we perform an RSD analysis on the pre-reconstructed catalogue on the monopole, quadrupole, and hexadecapole we find, DH(zeff)/rdrag = 20.18 ± 0.78, DM(zeff)/rdrag = 17.49 ± 0.52 and fσ8(zeff) = 0.454 ± 0.046. We combine both sets of results along with the measurements in configuration space and report the following consensus values: DH(zeff)/rdrag = 19.77 ± 0.47, DM(zeff)/rdrag = 17.65 ± 0.30 and fσ8(zeff) = 0.473 ± 0.044, which are in full agreement with the standard ΛCDM and GR predictions. These results represent the most precise measurements within the redshift range 0.6 ≤ z ≤ 1.0 and are the culmination of more than 8 yr of SDSS observations.

Gil-Marín, Héctor↗
DOE OSTI2020

On the possibility of baryon acoustic oscillation measurements at redshift z > 7.6 with the Roman space telescope

ABSTRACT The Nancy Grace Roman Space Telescope (RST), with its field of view and high sensitivity will make surveys of cosmological large-scale structure possible at high redshifts. We investigate the possibility of detecting baryon acoustic oscillations (BAO) at redshifts z > 7.6 for use as a standard ruler. We use data from the hydrodynamic simulation bluetides in conjunction with the gigaparsec-scale Outer Rim simulation and a model for patchy reionization to create mock RST High Latitude Survey grism data for Lyman α emission line selected galaxies at redshifts z = 7.4 to z = 10, covering 2280 deg2. We measure the monopoles of galaxies in the mock catalogues and fit the BAO features. We find that for a line flux of $L = 7\times 10^{-17} \ {\rm erg\, s^{-1}\, cm}^{-2}$, the 5σ detection limit for the current design, the BAO feature is partially detectable (measured in three out of four survey quadrants analysed independently). The resulting root mean square error on the angular diameter distance to z = 7.7 is 7.9 ${{\ \rm per\ cent}}$. If we improve the detection sensitivity by a factor of two (i.e. $L = 3.5\times 10^{-17} \ {\rm erg\, s^{-1}\, cm}^{-2}$), the distance error reduces to $1.4{{\ \rm per\ cent}}$. We caution that many more factors are yet to be modelled, including dust obscuration, the damping wing due to the intergalactic medium, and low redshift interlopers. If these issues do not strongly affect the results, or different observational techniques (such as use of multiple lines) can mitigate them, RST, or similar instruments may be able to constrain the angular diameter distance to the high redshift universe.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Testing general relativity on cosmological scales at redshift z ∼ 1.5 with quasar and CMB lensing

ABSTRACT We test general relativity (GR) at the effective redshift $\bar{z} \sim 1.5$ by estimating the statistic EG, a probe of gravity, on cosmological scales $19 - 190\, h^{-1}{\rm Mpc}$. This is the highest redshift and largest scale estimation of EG so far. We use the quasar sample with redshifts 0.8 < z < 2.2 from Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 16 as the large-scale structure (LSS) tracer, for which the angular power spectrum $C_\ell ^{qq}$ and the redshift-space distortion parameter β are estimated. By cross-correlating with the Planck 2018 cosmic microwave background (CMB) lensing map, we detect the angular cross-power spectrum $C_\ell ^{\kappa q}$ signal at $12\, \sigma$ significance. Both jackknife resampling and simulations are used to estimate the covariance matrix (CM) of EG at five bins covering different scales, with the later preferred for its better constraints on the covariances. We find EG estimates agree with the GR prediction at $1\, \sigma$ level over all these scales. With the CM estimated with 300 simulations, we report a best-fitting scale-averaged estimate of $E_G(\bar{z})=0.30\pm 0.05$, which is in line with the GR prediction $E_G^{\rm GR}(\bar{z})=0.33$ with Planck 2018 CMB + BAO matter density fraction Ωm = 0.31. The statistical errors of EG with future LSS surveys at similar redshifts will be reduced by an order of magnitude, which makes it possible to constrain modified gravity models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The history of metal enrichment traced by X-ray observations of high-redshift galaxy clusters

ABSTRACT We present the analysis of deep X-ray observations of 10 massive galaxy clusters at redshifts 1.05 < z < 1.71, with the primary goal of measuring the metallicity of the intracluster medium (ICM) at intermediate radii, to better constrain models of the metal enrichment of the intergalactic medium. The targets were selected from X-ray and Sunyaev–Zel’dovich effect surveys, and observed with both the XMM–Newton and Chandra satellites. For each cluster, a precise gas mass profile was extracted, from which the value of r500 could be estimated. This allows us to define consistent radial ranges over which the metallicity measurements can be compared. In general, the data are of sufficient quality to extract meaningful metallicity measurements in two radial bins, r < 0.3r500 and 0.3 < r/r500 < 1.0. For the outer bin, the combined measurement for all 10 clusters, Z/Z⊙ = 0.21 ± 0.09, represents a substantial improvement in precision over previous results. This measurement is consistent with, but slightly lower than, the average metallicity of 0.315 solar measured at intermediate-to-large radii in low-redshift clusters. Combining our new high-redshift data with the previous low-redshift results allows us to place the tightest constraints to date on models of the evolution of cluster metallicity at intermediate radii. Adopting a power-law model of the form Z ∝ (1 + z)γ, we measure a slope $\gamma = -0.5^{+0.4}_{-0.3}$, consistent with the majority of the enrichment of the ICM having occurred at very early times and before massive clusters formed, but leaving open the possibility that some additional enrichment in these regions may have occurred since a redshift of 2.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Dark Energy Survey Y3 results: blending shear and redshift biases in image simulations

ABSTRACT As the statistical power of galaxy weak lensing reaches per cent level precision, large, realistic, and robust simulations are required to calibrate observational systematics, especially given the increased importance of object blending as survey depths increase. To capture the coupled effects of blending in both shear and photometric redshift calibration, we define the effective redshift distribution for lensing, nγ(z), and describe how to estimate it using image simulations. We use an extensive suite of tailored image simulations to characterize the performance of the shear estimation pipeline applied to the Dark Energy Survey (DES) Year 3 data set. We describe the multiband, multi-epoch simulations, and demonstrate their high level of realism through comparisons to the real DES data. We isolate the effects that generate shear calibration biases by running variations on our fiducial simulation, and find that blending-related effects are the dominant contribution to the mean multiplicative bias of approximately $-2{{\ \rm per\ cent}}$. By generating simulations with input shear signals that vary with redshift, we calibrate biases in our estimation of the effective redshift distribution, and demonstrate the importance of this approach when blending is present. We provide corrected effective redshift distributions that incorporate statistical and systematic uncertainties, ready for use in DES Year 3 weak lensing analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

QSO photometric redshifts using machine learning and neural networks

ABSTRACT The scientific value of the next generation of large continuum surveys would be greatly increased if the redshifts of the newly detected sources could be rapidly and reliably estimated. Given the observational expense of obtaining spectroscopic redshifts for the large number of new detections expected, there has been substantial recent work on using machine learning techniques to obtain photometric redshifts. Here, we compare the accuracy of the predicted photometric redshifts obtained from deep learning (DL) with the k-nearest neighbour (kNN) and the decision tree regression (DTR) algorithms. We find using a combination of near-infrared, visible, and ultraviolet magnitudes, trained upon a sample of Sloan Digital Sky Survey quasi-stellar objects, that the kNN and DL algorithms produce the best self-validation result with a standard deviation of σΔz = 0.24 (σΔz(norm) = 0.11). Testing on various subsamples, we find that the DL algorithm generally has lower values of σΔz, in addition to exhibiting a better performance in other measures. Our DL method, which uses an easy to implement off-the-shelf algorithm with neither filtering nor removal of outliers, performs similarly to other, more complex, algorithms, resulting in an accuracy of Δz < 0.1 up to z ∼ 2.5. Applying the DL algorithm trained on our 70 000 strong sample to other independent (radio-selected) data sets, we find σΔz ≤ 0.36 (σΔz(norm) ≤ 0.17) over a wide range of radio flux densities. This indicates much potential in using this method to determine photometric redshifts of quasars detected with the Square Kilometre Array.

Curran, S. J.↗