Redshift Estimates Research Articles

The 3HSP catalogue of extreme and high-synchrotron peaked blazars

Aims. High-synchrotron peaked blazars (HSPs or HBLs) play a central role in very high-energy (VHE) γ-ray astronomy, and likely in neutrino astronomy. Currently, the largest compilation of HSP blazars, the 2WHSP sample, includes 1691 sources, but it is not complete in the radio or in the X-ray band. In order to provide a larger and more accurate set of HSP blazars that is useful for future statistical studies and to plan for VHE/TeV observations, we present the 3HSP catalogue, the largest sample of extreme and high-synchrotron peaked (EHSP; HSP) blazars and blazar candidates. Methods. We implemented several ways to improve the size and the completeness of the 2WHSP catalogue and reduced the selection biases to be taken into consideration in population studies. By discarding the IR constraint and relaxing the radio–IR and IR–X-ray slope criteria, we were able to select more sources with νpeak close to the 1015 Hz threshold and objects where the host galaxy dominates the flux. The selection of extra sources now commences with a cross-matching between radio and X-ray surveys, applying a simple flux ratio cut. We also considered Fermi-LAT catalogues to find reasonable HSP-candidates that are detected in the γ-ray band but are not included in X-ray or radio source catalogues. The new method, and the use of newly available multi-frequency data, allowed us to add 395 sources to the sample, to remove 73 2WHSP sources that were previously flagged as uncertain and could not be confirmed as genuine HSP blazars, and to update parameters obtained by fitting the synchrotron component. Results. The 3HSP catalogue includes 2013 sources, 88% of which with a redshift estimation, a much higher percentage than in any other list of HSP blazars. All new γ-ray detections are described in the First and Second Brazil ICRANet γ-ray blazar catalogues (1BIGB & 2BIGB) also taking into account the 4FGL list of γ-ray sources published by the Fermi Large Area Telescope (Fermi-LAT) team. Moreover, the cross-matching between the 2WHSP, 2FHL HSP, and IceCube neutrino positions suggests that HSPs are likely counterparts of neutrino events, which implies the 3HSP catalogue is also useful in that respect. The 3HSP catalogue shows improved completeness compared to its predecessors, the 1WHSP and 2WHSP catalogues, and follows the track of their increasing relevance for VHE astronomy.

A new strategy for estimating photometric redshifts of quasars

Based on the SDSS and SDSS-WISE quasar datasets, we put forward two schemes to estimate the photometric redshifts of quasars. Our schemes are based on the idea that the samples are firstly classified into subsamples by a classifier and then a photometric redshift estimation of different subsamples is performed by a regressor. Random Forest is adopted as the core algorithm of the classifiers, while Random Forest and kNN are applied as the key algorithms of regressors. The samples are divided into two subsamples and four subsamples, depending on the redshift distribution. The performances based on different samples, different algorithms and different schemes are compared. The experimental results indicate that the accuracy of photometric redshift estimation for the two schemes generally improves to some extent compared to the original scheme in terms of the percents in and and mean absolute error. Only given the running speed, kNN shows its superiority to Random Forest. The performance of Random Forest is a little better than or comparable to that of kNN with the two datasets. The accuracy based on the SDSS-WISE sample outperforms that based on the SDSS sample no matter by kNN or by Random Rorest. More information from more bands is considered and helpful to improve the accuracy of photometric redshift estimation. Evidently, it can be found that our strategy to estimate photometric redshift is applicable and may be applied to other datasets or other kinds of objects. Only talking about the percent in , there is still large room for further improvement in the photometric redshift estimation.

Reconstructing large-scale structure with neutral hydrogen surveys

Upcoming 21-cm intensity surveys will use the hyperfine transition in emission to map out neutral hydrogen in large volumes of the universe. Unfortunately, large spatial scales are completely contaminated with spectrally smooth astrophysical foregrounds which are orders of magnitude brighter than the signal. This contamination also leaks into smaller radial and angular modes to form a foreground wedge, further limiting the usefulness of 21-cm observations for different science cases, especially cross-correlations with tracers that have wide kernels in the radial direction. In this paper, we investigate reconstructing these modes within a forward modeling framework. Starting with an initial density field, a suitable bias parameterization and non-linear dynamics to model the observed 21-cm field, our reconstruction proceeds by {combining} the likelihood of a forward simulation to match the observations (under given modeling error and a data noise model) {with the Gaussian prior on initial conditions and maximizing the obtained posterior}. For redshifts z=2 and 4, we are able to reconstruct 21cm field with cross correlation, rc > 0.8 on all scales for both our optimistic and pessimistic assumptions about foreground contamination and for different levels of thermal noise. The performance deteriorates slightly at z=6. The large-scale line-of-sight modes are reconstructed almost perfectly. We demonstrate how our method also provides a technique for density field reconstruction for baryon acoustic oscillations, outperforming standard methods on all scales. We also describe how our reconstructed field can provide superb clustering redshift estimation at high redshifts, where it is otherwise extremely difficult to obtain dense spectroscopic samples, as well as open up a wealth of cross-correlation opportunities with projected fields (e.g. lensing) which are restricted to modes transverse to the line of sight.

Can redshift errors bias measurements of the Hubble Constant?

ABSTRACT Redshifts have been so easy to measure for so long that we tend to neglect the fact that they too have uncertainties and are susceptible to systematic error. As we strive to measure cosmological parameters to better than 1 per cent it is worth reviewing the accuracy of our redshift measurements. Surprisingly small systematic redshift errors, as low as 10−4, can have a significant impact on the cosmological parameters we infer, such as H0. Here, we investigate an extensive (but not exhaustive) list of ways in which redshift estimation can go systematically astray. We review common theoretical errors, such as adding redshifts instead of multiplying by (1 + z); using v = cz; and using only cosmological redshift in the estimates of luminosity and angular diameter distances. We consider potential observational errors, such as rest wavelength precision, air to vacuum conversion, and spectrograph wavelength calibration. Finally, we explore physical effects, such as peculiar velocity corrections, galaxy internal velocities, gravitational redshifts, and overcorrecting within a bulk flow. We conclude that it would be quite easy for small systematic redshift errors to have infiltrated our data and be impacting our cosmological results. While it is unlikely that these errors are large enough to resolve the current H0 tension, it remains possible, and redshift accuracy may become a limiting factor in near future experiments. With the enormous efforts going into calibrating the vertical axis of our plots (standard candles, rulers, clocks, and sirens) we argue that it is now worth paying a little more attention to the horizontal axis (redshifts).

Morpho-photometric redshifts

ABSTRACT Machine learning (ML) is one of two standard approaches (together with SED fitting) for estimating the redshifts of galaxies when only photometric information is available. ML photo-z solutions have traditionally ignored the morphological information available in galaxy images or partly included it in the form of hand-crafted features, with mixed results. We train a morphology-aware photometric redshift machine using modern deep learning tools. It uses a custom architecture that jointly trains on galaxy fluxes, colours, and images. Galaxy-integrated quantities are fed to a Multi-Layer Perceptron (MLP) branch, while images are fed to a convolutional (convnet) branch that can learn relevant morphological features. This split MLP-convnet architecture, which aims to disentangle strong photometric features from comparatively weak morphological ones, proves important for strong performance: a regular convnet-only architecture, while exposed to all available photometric information in images, delivers comparatively poor performance. We present a cross-validated MLP-convnet model trained on 130 000 SDSS-DR12 (Sloan Digital Sky Survey – Data Release 12) galaxies that outperforms a hyperoptimized Gradient Boosting solution (hyperopt+XGBoost), as well as the equivalent MLP-only architecture, on the redshift bias metric. The fourfold cross-validated MLP-convnet model achieves a bias δz/(1 + z) = −0.70 ± 1 × 10−3, approaching the performance of a reference ANNZ2 ensemble of 100 distinct models trained on a comparable data set. The relative performance of the morphology-aware and morphology-blind models indicates that galaxy morphology does improve ML-based photometric redshift estimation.

HELP: a catalogue of 170 million objects, selected at 0.36–4.5 μm, from 1270 deg2 of prime extragalactic fields

ABSTRACT We present an optical to near-infrared (NIR) selected astronomical catalogue covering 1270 deg2. This is the first attempt to systematically combine data from 23 of the premier extragalactic survey fields – the product of a vast investment of telescope time. The fields are those imaged by the Herschel Space Observatory that form the Herschel Extragalactic Legacy Project (HELP). Our catalogue of 170 million objects is constructed by a positional cross-match of 51 public surveys. This high-resolution optical, NIR, and mid-infrared catalogue is designed for photometric redshift estimation, extraction of fluxes in lower resolution far-infrared maps, and spectral energy distribution modelling. It collates, standardizes, and provides value added derived quantities including corrected aperture magnitudes and astrometry correction over the Herschel extragalactic wide fields for the first time. $grizy$ fluxes are available on all fields with g-band data reaching $5\sigma$ point-source depths in a 2 arcsec aperture of 23.5, 24.4, and 24.6 (AB) mag at the 25th, 50th, and 75th percentiles, by area covered, across all HELP fields. It has K or $K_s$ coverage over 1146 deg2 with depth percentiles of 20.2, 20.4, and 21.0 mag, respectively. The IRAC Ch 1 band is available over 273 deg2 with depth percentiles of 17.7, 21.4, and 22.2 mag, respectively. This paper defines the ‘masterlist’ objects for the first data release (DR1) of HELP. This large sample of standardized total and corrected aperture fluxes, uniform quality flags, and completeness measures provides large well-understood statistical samples over the full Herschel extragalactic sky.

Developing a unified pipeline for large-scale structure data analysis with angular power spectra – I. The importance of redshift-space distortions for galaxy number counts

ABSTRACT We develop a cosmological parameter estimation code for (tomographic) angular power spectra analyses of galaxy number counts, for which we include, for the first time, redshift-space distortions (RSDs) in the Limber approximation. This allows for a speed-up in computation time, and we emphasize that only angular scales where the Limber approximation is valid are included in our analysis. Our main result shows that a correct modelling of RSD is crucial not to bias cosmological parameter estimation. This happens not only for spectroscopy-detected galaxies, but even in the case of galaxy surveys with photometric redshift estimates. Moreover, a correct implementation of RSD is especially valuable in alleviating the degeneracy between the amplitude of the underlying matter power spectrum and the galaxy bias. We argue that our findings are particularly relevant for present and planned observational campaigns, such as the Euclid satellite or the Square Kilometre Array, which aim at studying the cosmic large-scale structure and trace its growth over a wide range of redshifts and scales.

Quasi-stellar object redshift estimates from optical, near-infrared, and ultraviolet colours

A simple estimate of the photometric redshift would prove invaluable to forthcoming continuum surveys on the next generation of large radio telescopes, as well as mitigating the existing bias towards the most optically bright sources. While there is a well-known correlation between the near-infrared K-band magnitude and redshift for galaxies, we find the K − z relation to break down for samples dominated by quasi-stellar objects. We hypothesise that this is due to the additional contribution to the near-infrared flux by the active galactic nucleus, and, as such, the K-band magnitude can only provide a lower limit to the redshift in the case of active galactic nuclei, which will dominate the radio surveys. From a large optical dataset, we find a tight relationship between the rest-frame (U − K)/(W2 − FUV) colour ratio and spectroscopic redshift over a sample of 17 000 sources, spanning z ≈ 0.1−5. Using the observed-frame ratios of (U − K)/(W2 − FUV) for redshifts of z ≲ 1, (I − W2)/(W3 − U) for 1 ≲ z ≲ 3, and (I − W2.5)/(W4 − R) for z ≳ 3, where W2.5 is the λ = 8.0 μm magnitude and the appropriate redshift ranges are estimated from the W2 (4.5 μm) magnitude, we find this to be a robust photometric redshift estimator for quasars. We suggest that the rest-frame U − K colour traces the excess flux from the AGN over this wide range of redshifts, although the W2 − FUV colour is required to break the degeneracy.

MAGPHYS+photo-z: Constraining the Physical Properties of Galaxies with Unknown Redshifts

Abstract We present an enhanced version of the multiwavelength spectral modeling code MAGPHYS that allows the estimation of galaxy photometric redshift and physical properties (e.g., stellar mass, star formation rate, dust attenuation) simultaneously, together with robust characterization of their uncertainties. The self-consistent modeling over ultraviolet to radio wavelengths in MAGPHYS+photo-z is unique compared to standard photometric redshift codes. The broader wavelength consideration is particularly useful for breaking certain degeneracies in color versus redshift for dusty galaxies with limited observer-frame ultraviolet and optical data (or upper limits). We demonstrate the success of the code in estimating redshifts and physical properties for over 4000 infrared-detected galaxies at 0.4 < z < 6.0 in the COSMOS field with robust spectroscopic redshifts. We achieve high photo-z precision ( ), high accuracy (i.e., minimal offset biases; median(Δz/(1 + z spec)) ≲ 0.02), and low catastrophic failure rates (η ≃ 4%) over all redshifts. Interestingly, we find that a weak 2175 Å absorption feature in the attenuation curve models is required to remove a subtle systematic z phot offset ( ) that occurs when this feature is not included. As expected, the accuracy of derived physical properties in MAGPHYS+photo-z decreases strongly as redshift uncertainty increases. The all-in-one treatment of uncertainties afforded with this code is beneficial for accurately interpreting physical properties of galaxies in large photometric data sets. Finally, we emphasize that MAGPHYS+photo-z is not intended to replace existing photo-z codes, but rather offers flexibility to robustly interpret physical properties when spectroscopic redshifts are unavailable. The MAGPHYS+photo-z code is publicly available online.

A Comparison of Photometric Redshift Techniques for Large Radio Surveys

Future radio surveys will generate catalogs of tens of millions of radio sources, for which redshift estimates will be essential to achieve many of the science goals. However, spectroscopic data will be available for only a small fraction of these sources, and in most cases even the optical and infrared photometry will be of limited quality. Furthermore, radio sources tend to be at higher redshift than most optical sources (most radio surveys have a median redshift greater than 1) and so a significant fraction of radio sources hosts differ from those for which most photometric redshift templates are designed. We therefore need to develop new techniques for estimating the redshifts of radio sources. As a starting point in this process, we evaluate a number of machine-learning techniques for estimating redshift, together with a conventional template-fitting technique. We pay special attention to how the performance is affected by the incompleteness of the training sample and by sparseness of the parameter space or by limited availability of ancillary multiwavelength data. As expected, we find that the quality of the photometric-redshift degrades as the quality of the photometry decreases, but that even with the limited quality of photometry available for all-sky-surveys, useful redshift information is available for the majority of sources, particularly at low redshift. We find that a template-fitting technique performs best in the presence of high-quality and almost complete multi-band photometry, especially if radio sources that are also X-ray emitting are treated separately, using specific templates and priors. When we reduced the quality of photometry to match that available for the EMU all-sky radio survey, the quality of the template-fitting degraded and became comparable to some of the machine-learning methods. Machine learning techniques currently perform better at low redshift than at high redshift, because of incompleteness of the currently available training data at high redshifts.

Preliminary Results of Using k-nearest-neighbor Regression to Estimate the Redshift of Radio-selected Data Sets**Released on 2018 June 1.

In the near future, all-sky radio surveys are set to produce catalogues of tens of millions of sources with limited multiwavelength photometry. Spectroscopic redshifts will only be possible for a small fraction of these new-found sources. In this paper, we provide the first in-depth investigation into the use of k-nearest-neighbor (kNN) regression for the estimation of redshift of these sources. We use Australia Telescope Large Area Survey (ATLAS) radio data, combined with Spitzer Wide-Area Infrared Extragalactic Survey infrared, Dark Energy Survey optical, and Australian Dark Energy Survey spectroscopic survey data. We then reduce the depth of photometry to match what is expected from the upcoming Evolutionary Map of the Universe survey, testing against both data sets. To examine the generalization of our methods, we test one of the subfields of ATLAS against the other. We achieve an outlier rate of ∼10% across all tests, showing that the kNN regression algorithm is an acceptable method of estimating redshift, and would perform better given a sample training set with uniform redshift coverage.

Impact of foregrounds on H i intensity mapping cross-correlations with optical surveys

ABSTRACT The future of precision cosmology could benefit from cross-correlations between intensity maps of unresolved neutral hydrogen (H i) and more conventional optical galaxy surveys. A major challenge that needs to be overcome is removing the 21cm foreground emission that contaminates the cosmological H i signal. Using N-body simulations, we simulate H i intensity maps and optical catalogues that share the same underlying cosmology. Adding simulated foreground contamination and using state-of-the-art reconstruction techniques, we investigate the impacts that 21cm foregrounds and other systematics have on these cross-correlations. We find that the impact a Fast Independent Component Analysis 21cm foreground clean has on the cross-correlations with spectroscopic optical surveys with well-constrained redshifts is minimal. However, problems arise when photometric surveys are considered: We find that a redshift uncertainty σz ≥ 0.04 causes significant degradation in the cross-power spectrum signal. We diagnose the main root of these problems, which relates to arbitrary amplitude changes along the line of sight in the intensity maps caused by the foreground clean and suggest solutions that should be applicable to real data. These solutions involve a reconstruction of the line-of-sight temperature means using the available overlapping optical data along with an artificial extension to the H i data through redshift to address edge effects. We then put these solutions through a further test in a mock experiment that uses a clustering-based redshift estimation technique to constrain the photometric redshifts of the optical sample. We find that with our suggested reconstruction, cross-correlations can be utilized to make an accurate prediction of the optical redshift distribution.

Optical follow-up study of 32 high-redshift galaxy cluster candidates from Planck with the William Herschel Telescope

Abstract The Planck satellite has detected cluster candidates via the Sunyaev Zel’dovich (SZ) effect, but the optical follow-up required to confirm these candidates is still incomplete, especially at high redshifts and for SZ detections at low significance. In this work, we present our analysis of optical observations obtained for 32 Planck cluster candidates using ACAM on the 4.2-m William Herschel Telescope. These cluster candidates were pre-selected using SDSS, WISE, and Pan-STARRS images to likely represent distant clusters at redshifts z ≳ 0.7. We obtain photometric redshift and richness estimates for all of the cluster candidates from a red-sequence analysis of r-, i-, and z-band imaging data. In addition, long-slit observations allow us to measure the redshifts of a subset of the clusters spectroscopically. The optical richness is often lower than expected from the inferred SZ mass when compared to scaling relations previously calibrated at low redshifts. This likely indicates the impact of Eddington bias and projection effects or noise-induced detections, especially at low-SZ significance. Thus, optical follow-up not only provides redshift measurements, but also an important independent verification method. We find that 18 (7) of the candidates at redshifts z > 0.5 (z > 0.8) are at least half as rich as expected from scaling relations, thereby clearly confirming these candidates as massive clusters. While the complex selection function of our sample due to our pre-selection hampers its use for cosmological studies, we do provide a validation of massive high-redshift clusters particularly suitable for further astrophysical investigations.

A Decade of Gamma-Ray Bursts Observed by Fermi-LAT: The Second GRB Catalog

Abstract The Large Area Telescope (LAT) aboard the Fermi spacecraft routinely observes high-energy emission from gamma-ray bursts (GRBs). Here we present the second catalog of LAT-detected GRBs, covering the first 10 yr of operations, from 2008 to 2018 August 4. A total of 186 GRBs are found; of these, 91 show emission in the range 30–100 MeV (17 of which are seen only in this band) and 169 are detected above 100 MeV. Most of these sources were discovered by other instruments (Fermi/GBM, Swift/BAT, AGILE, INTEGRAL) or reported by the Interplanetary Network (IPN); the LAT has independently triggered on four GRBs. This catalog presents the results for all 186 GRBs. We study onset, duration, and temporal properties of each GRB, as well as spectral characteristics in the 100 MeV–100 GeV energy range. Particular attention is given to the photons with the highest energy. Compared with the first LAT GRB catalog, our rate of detection is significantly improved. The results generally confirm the main findings of the first catalog: the LAT primarily detects the brightest GBM bursts, and the high-energy emission shows delayed onset as well as longer duration. However, in this work we find delays exceeding 1 ks and several GRBs with durations over 10 ks. Furthermore, the larger number of LAT detections shows that these GRBs not only cover the high-fluence range of GBM-detected GRBs but also sample lower fluences. In addition, the greater number of detected GRBs with redshift estimates allows us to study their properties in both the observer and rest frames. Comparison of the observational results with theoretical predictions reveals that no model is currently able to explain all results, highlighting the role of LAT observations in driving theoretical models.

Cluster Cosmology Constraints from the 2500 deg2 SPT-SZ Survey: Inclusion of Weak Gravitational Lensing Data from Magellan and the Hubble Space Telescope

Abstract We derive cosmological constraints using a galaxy cluster sample selected from the 2500 deg2 SPT-SZ survey. The sample spans the redshift range 0.25 < z < 1.75 and contains 343 clusters with SZ detection significance ξ > 5. The sample is supplemented with optical weak gravitational lensing measurements of 32 clusters with 0.29 < z < 1.13 (from Magellan and Hubble Space Telescope) and X-ray measurements of 89 clusters with 0.25 < z < 1.75 (from Chandra). We rely on minimal modeling assumptions: (i) weak lensing provides an accurate means of measuring halo masses, (ii) the mean SZ and X-ray observables are related to the true halo mass through power-law relations in mass and dimensionless Hubble parameter E(z) with a priori unknown parameters, and (iii) there is (correlated, lognormal) intrinsic scatter and measurement noise relating these observables to their mean relations. We simultaneously fit for these astrophysical modeling parameters and for cosmology. Assuming a flat νΛCDM model, in which the sum of neutrino masses is a free parameter, we measure Ωm = 0.276 ± 0.047, σ 8 = 0.781 ± 0.037, and σ 8(Ωm/0.3)0.2 = 0.766 ±0.025. The redshift evolutions of the X-ray Y X–mass and M gas–mass relations are both consistent with self-similar evolution to within 1σ. The mass slope of the Y X–mass relation shows a 2.3σ deviation from self-similarity. Similarly, the mass slope of the M gas–mass relation is steeper than self-similarity at the 2.5σ level. In a νwCDM cosmology, we measure the dark energy equation-of-state parameter w = −1.55 ± 0.41 from the cluster data. We perform a measurement of the growth of structure since redshift z ∼ 1.7 and find no evidence for tension with the prediction from general relativity. This is the first analysis of the SPT cluster sample that uses direct weak-lensing mass calibration and is a step toward using the much larger weak-lensing data set from DES. We provide updated redshift and mass estimates for the SPT sample.

Cosmological lensing ratios with DES Y1, SPT, and Planck

ABSTRACTCorrelations between tracers of the matter density field and gravitational lensing are sensitive to the evolution of the matter power spectrum and the expansion rate across cosmic time. Appropriately defined ratios of such correlation functions, on the other hand, depend only on the angular diameter distances to the tracer objects and to the gravitational lensing source planes. Because of their simple cosmological dependence, such ratios can exploit available signal-to-noise ratio down to small angular scales, even where directly modelling the correlation functions is difficult. We present a measurement of lensing ratios using galaxy position and lensing data from the Dark Energy Survey, and CMB lensing data from the South Pole Telescope and Planck, obtaining the highest precision lensing ratio measurements to date. Relative to the concordance ΛCDM model, we find a best-fitting lensing ratio amplitude of A = 1.1 ± 0.1. We use the ratio measurements to generate cosmological constraints, focusing on the curvature parameter. We demonstrate that photometrically selected galaxies can be used to measure lensing ratios, and argue that future lensing ratio measurements with data from a combination of LSST and Stage-4 CMB experiments can be used to place interesting cosmological constraints, even after considering the systematic uncertainties associated with photometric redshift and galaxy shear estimation.

Representation learning for automated spectroscopic redshift estimation

Context. Determining the radial positions of galaxies up to a high accuracy depends on the correct identification of salient features in their spectra. Classical techniques for spectroscopic redshift estimation make use of template matching with cross-correlation. These templates are usually constructed from empirical spectra or simulations based on the modeling of local galaxies. Aims. We propose two new spectroscopic redshift estimation schemes based on new learning techniques for galaxy spectra representation, using either a dictionary learning technique for sparse representation or denoising autoencoders. We investigate how these representations impact redshift estimation. Methods. We first explored dictionary learning to obtain a sparse representation of the rest-frame galaxy spectra modeling both the continuum and line emissions. As an alternative, denoising autoencoders were considered to learn non-linear representations from rest-frame emission lines extracted from the data. In both cases, the redshift was then determined by redshifting the learnt representation and selecting the redshift that gave the lowest approximation error among the tested values. Results. These methods have been tested on realistic simulated galaxy spectra, with photometry modeled after the Large Synoptic Survey Telescope (LSST) and spectroscopy reproducing properties of the Sloan Digital Sky Survey (SDSS). They were compared to Darth Fader, a robust technique extracting line features and estimating redshift through eigentemplates cross-correlations. We show that both dictionary learning and denoising autoencoders provide improved accuracy and reliability across all signal-to-noise (S/N) regimes and galaxy types. Furthermore, the former is more robust at high noise levels; the latter is more accurate on high S/N regimes. Combining both estimators improves results at low S/N. Conclusions. The representation learning framework for spectroscopic redshift analysis introduced in this work offers high performance in feature extraction and redshift estimation, improving on a classical eigentemplates approach. This is a necessity for next-generation galaxy surveys, and we demonstrate a successful application in realistic simulated survey data.

The quasars’ redshift estimation method based on piecewise Gaussian fitting

To solve the problem that high-redshift and broad emission lines weaken the quasar discovery and observation severely, a new redshift calculation method based on piecewise Gaussian fitting is proposed. The denoised and normalized spectrum is divided into two regions, peak and non-peak, by mean square error threshold segmentation first. Then, the non-peak region spectrum is applied to fit the continuous spectrum, removal of which gains access to the residual spectrum. And, the peak of each segment in the residual spectrum is precisely fitted by single-peak Gaussian fitting to replace the original multi-peak Gaussian fitting. Finally, through matching the accurate peak value with the stationary template, the redshift value is acquired. Compared with traditional methods, the method proposed improves the precision of continuous spectrum fitting and redshift calculation. The effectiveness and accuracy of this method have been verified by experiments based on the Sloan Digital Sky Survey data.

The Sloan Digital Sky Survey Reverberation Mapping Project: Sample Characterization

Abstract We present a detailed characterization of the 849 broad-line quasars from the Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) project. Our quasar sample covers a redshift range of 0.1 < z < 4.5 and is flux-limited to i PSF < 21.7 without any other cuts on quasar properties. The main sample characterization includes: (1) spectral measurements of the continuum and broad emission lines for individual objects from the coadded first-season spectroscopy in 2014, (2) identification of broad and narrow absorption lines in the spectra, and (3) optical variability properties for continuum and broad lines from multi-epoch spectroscopy. We provide improved systemic redshift estimates for all quasars and demonstrate the effects of the signal-to-noise ratio on the spectral measurements. We compile measured properties for all 849 quasars along with supplemental multi-wavelength data for subsets of our sample from other surveys. The SDSS-RM sample probes a diverse range in quasar properties and shows well-detected continuum and broad-line variability for many objects from first-season monitoring data. The compiled properties serve as the benchmark for follow-up work based on SDSS-RM data. The spectral fitting tools are made public along with this work.

Mock galaxy shape catalogues in the Subaru Hyper Suprime-Cam Survey

Abstract We use the full-sky ray-tracing weak lensing simulations to generate 2268 mock catalogues for the Subaru Hyper Suprime-Cam (HSC) survey first-year shear catalogue. Our mock catalogues take into account various effects as in the real data: the survey footprints, inhomogeneous angular distribution of source galaxies, statistical uncertainties in photometric redshift (photo-z) estimate, variations in the lensing weight, and the statistical noise in galaxy shape measurements including both intrinsic shapes and the measurement errors. We then utilize our mock catalogues to evaluate statistical uncertainties expected in measurements of cosmic shear two-point correlations ξ± with tomographic redshift information for the HSC survey. We develop a quasi-analytical formula for the Gaussian sample variance properly taking into account the number of source pairs in the survey footprints. The standard Gaussian formula significantly overestimates or underestimates the mock results by 50 per cent level. We also show that different photo-z catalogues or the six disconnected fields, rather than a consecutive geometry, cause variations in the covariance by ${\sim } 5{{\ \rm per\ cent}}$. The mock catalogues enable us to study the chi-square distribution for ξ±. We find the wider distribution than that naively expected for the distribution with the degrees of freedom of data vector used. Finally, we propose a method to include non-zero multiplicative bias in mock shape catalogue and show that the non-zero multiplicative bias can change the effective shape noise in cosmic shear analyses. Our results suggest an importance of estimating an accurate form of the likelihood function (and therefore the covariance) for robust cosmological parameter inference from the precise measurements.