Redshift Catalog Research Articles

A Photometric Redshift Catalogue of Galaxies from the DESI Legacy Imaging Surveys DR10

The large-scale measurement of galaxy redshifts holds significant importance for cosmological research, as well as for understanding the formation and evolution of galaxies. This study utilizes a known sample obtained by cross-correlating the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys DR10 galaxy catalog with various galaxy catalogs from different spectroscopic surveys. The methods Easy and Accurate Photometric Redshifts from Yale (EAZY) and CatBoost are employed to estimate redshifts. In the case of EAZY, the known sample is used solely for testing, while CatBoost utilizes it for both training and testing purposes. The known sample is categorized into different subsamples based on various classification methods. Several CatBoost regression models are trained and optimized using these subsamples. By comparing the performance of different methods and models, it is observed that the two-step and two-part models outperform the one-step model, with further enhancements achieved through the combination of the two-step and two-part models. Based on the findings from all experiments, we propose a photometric redshift estimation workflow designed to facilitate the photometric redshift measurement of all galaxies within the DESI Legacy Imaging Surveys DR10. Consequently, a photometric redshift catalog has been released, comprising a total of 1,533,107,988 galaxies. Among these, 312,960,837 galaxies have reliable redshift estimates, determined using the CatBoost algorithm, with magnitude limits set at g > 24.0, r > 23.4, and z > 22.5. For galaxies with g, r, and z magnitudes exceeding these thresholds, the photometric redshifts estimated by EAZY can be employed as a reference.

FASHI: A Search for Extragalactic OH Megamasers with FAST

The FAST All Sky H i survey (FASHI) is broader in frequency band and sky volume, and deeper in detection sensitivity than the Arecibo Legacy Fast ALFA survey. To efficiently expand the sample of OH megamasers (OHMs), whose strongest line has a rest frequency of 1667.35903 MHz, we directly matched the IRAS Point Source Catalog Redshift (PSCz) catalog with the corresponding FASHI data cube. From 145 PSCz sources already covered by FASHI, we obtained 27 OHMs with a detection rate of 18.6%, including 9 previously known and 18 new ones, within a redshift range of 0.14314 ≲ z OH ≲ 0.27656. We also measured the hyperfine ratio of nine OHMs between the 1667 and 1665 MHz lines. The ratio ranges from 1.32 to 15.22, with an average of R 1667:1665 = 4.74. In a fit to the L OH versus L FIR relation, we have logLOH=(1.57±0.10)logLFIR−(15.80±1.19) , which is almost the same as derived from previous observations. As expected, since the OHM sample was selected by cross correlation with the IRAS-selected PSCz, our detected OHMs are (ultra)luminous infrared galaxies ((U)LIRGs). However, not all (U)LIRGs have detectable OH emission, suggesting that the OH emission may be triggered within a specific stage of the merger or can only be seen in specific orientations. In general, FAST, with its 19-beam array and Ultra-Wide Bandwidth receiver, will be a powerful tool for observing more OHMs and unraveling their mystery in the future.

Deeper than DEEP: a spectroscopic survey of z > 3 Ly α emitters in the Extended Groth Strip

ABSTRACT We present a spectroscopic survey of Ly α emitters in the Extended Groth Strip (EGS) field, targeting the regime near the Epoch of Reionization. Using Keck/DEep Imaging Multi-Object Spectrograph, we observed 947 high-z candidates with photometric redshifts from 3 < zphot < 7 and down to an H-band (Hubble Space Telescope/Wide Field Camera 3 F160W) magnitude limit of <27.5. Observations were taken over the course of eight nights, with integration times ranging from 4 to 7.8 h. Our survey secured 137 unique redshifts, 126 of which are Ly α emitters at 2.8 < z < 6.3 with a mean redshift of $\overline{z} = 4.3$. We provide a comprehensive redshift catalogue for our targets, as well as the reduced one- and two-dimensional spectra for each object. These observations will provide an important auxiliary data set for the JWST Directors Discretionary Early Release Science programme the Cosmic Evolution Early Release Science Survey, which recently completed near- and mid-infrared imaging and spectroscopy of galaxies in the EGS field.

Bright submillimeter galaxies do trace galaxy protoclusters

There is controversy in the literature regarding whether distant, massive, and dusty starbursts selected at (sub)millimeter wavelengths can trace galaxy overdensities. We thus performed the first systematic search for distant protoclusters around a homogeneously selected sample of 12 spectroscopically confirmed submillimeter galaxies (SMGs) at z ∼ 1.2 − 5.3, which we selected from the GOODS-N field. We applied the well-established Poisson probability method (PPM) to search for megaparsec-scale overdensities around these SMGs, using three different photometric redshift catalogs. We robustly detect galaxy overdensities for 11 out of the 12 SMGs (i.e., 92%±8%), distributed over eight large-scale protoclusters. We confirm all three previously discovered protoclusters, and we detect five new ones around the SMGs SMM J123634 (z = 1.225), ID.19 (z = 2.047), SMM J123607 (z = 2.487), SMM J123606 (z = 2.505), and GN10 (z = 5.303). A wavelet-based analysis of the protocluster fields shows that the SMGs are located in protocluster cores with a complex morphology (compact, filamentary, or clumpy) and an average size of ∼(0.4 − 1) Mpc. By comparing the PPM results obtained using the three redshift catalogs independently, each of which trace different galaxy populations and redshift ranges, we speculate that we are possibly witnessing a transitioning phase at z ≳ 4 for the galaxy population of protoclusters. While z ≲ 4 protoclusters appear to be populated by dusty galaxies, those at the highest redshifts, z ∼ 5, are detected as overdensities of Lyman α emitters or Lyman break galaxies. Further investigation with larger samples is required to reach a definitive conclusion. We also find a good correlation between the molecular (H2) gas mass of the SMGs and the significance of the associated overdensity. To explain the overall phenomenology, we suggest that galaxy interactions in dense environments likely triggered the starburst and gas-rich phase of the SMGs. Altogether, our findings support the scenario that SMGs are excellent tracers of distant protoclusters. The ones presented in this work are excellent targets for the James Webb Space Telescope. Similarly, future surveys with forthcoming facilities (e.g., Euclid and LSST) can be tuned to detect even larger samples of distant protoclusters.

YOLO–CL: Galaxy cluster detection in the SDSS with deep machine learning

Galaxy clusters are powerful probes for cosmological models. Next-generation, large-scale optical and infrared surveys are poised to reach unprecedented depths and, thus, they require highly complete and pure cluster catalogs, with a well-defined selection function. We have developed a new cluster detection algorithm named YOLO for CLuster detection (YOLO–CL), which is a modified version of the state-of-the-art object detection deep convolutional network named You only look once (YOLO) that has been optimized for the detection of galaxy clusters. We trained YOLO–CL on the red-sequence Matched-filter Probabilistic Percolation (redMaPPer) cluster catalog, based on Sloan Digital Sky Survey (SDSS) color images. We find that YOLO–CL detects 95–98% of the redMaPPer clusters, with a purity of 95–98%, that is calculated by applying the network to SDSS blank fields. When compared to the Meta-Catalog of X-Ray Detected Clusters of Galaxies 2021 (MCXC2021) X-ray catalog in the SDSS footprint, YOLO–CL recovers all clusters at LX ≳ 2–3 × 1044 erg s−1, M500 ≳ 2–3 × 1014M⊙, R500≳0.75–0.8 Mpc and 0.4 ≲ z ≲ 0.6. When compared to the redMaPPer detection of the same MCXC2021 clusters, we find that YOLO–CL is more complete than redMaPPer, which means that the neural network has indeed improved the cluster detection efficiency of its training sample. In fact, YOLO–CL detects ~98% of the MCXC2021 clusters with an X-ray surface brightness of IX,500 ≳ 20 × 10−15 erg s−1 cm−2 arcmin−2 at 0.2 ≲ z ≲ 0.6 and ~100% of the MCXC2021 clusters with IX,500 ≳ 30 × 10−15 erg s−1 cm−2 arcmin−2 at 0.3 ≲ z ≲ 0.6; while redMaPPer detects ~98% of the MCXC2021 clusters with IX,500 ≳ 55 × 10−15 erg s−1 cm−2 arcmin−2 at 0.2 ≲ z ≲ 0.6 and ~100% of the MCXC2021 clusters with IX,500 ≳ 20 × 10−15 erg s−1 cm−2 arcmin−2 at 0.5 ≲ z ≲ 0.6. The YOLO–CL selection function is approximately constant with redshift, with respect to the MCXC2021 cluster X-ray surface brightness. YOLO–CL exhibits a high level of performance when compared to traditional detection algorithms applied to SDSS. Deep learning networks display a strong advantage over traditional galaxy cluster detection techniques because they do not require the galaxy’s photometric and photometric redshift catalogs. This eliminates systematic uncertainties that may be introduced during source detections and photometry, as well as photometric redshift measurements. Our results show that YOLO–CL is an efficient alternative to traditional cluster detection methods. In general, this work shows that it is worth exploring the performance of deep convolution networks for future cosmological cluster surveys, such as the Rubin/Legacy Survey of Space and Time (Rubin/LSST), Euclid, and Roman Space Telescope surveys.

The GLASS-JWST Early Release Science Program. III. Strong-lensing Model of Abell 2744 and Its Infalling Regions

Abstract We present a new high-precision, JWST-based, strong-lensing model for the galaxy cluster Abell 2744 at z = 0.3072. By combining the deep, high-resolution JWST imaging from the Grism Lens Amplified Survey from Space–JWST and Ultradeep NIRSpec and NIRCam Observations before the Epoch of Reionization programs and a Director’s Discretionary Time program, with newly obtained Very Large Telescope/Multi Unit Spectroscopic Explorer (MUSE) data, we identify 32 multiple images from 11 background sources lensed by two external subclusters at distances of ∼160″ from the main cluster. The new MUSE observations enable the first spectroscopic confirmation of a multiple-image system in the external clumps. Moreover, the reanalysis of the spectrophotometric archival and JWST data yields 27 additional multiple images in the main cluster. The new lens model is constrained by 149 multiple images (∼66% more than in our previous model) covering an extended redshift range between 1.03 and 9.76. The subhalo mass component of the cluster includes 177 member galaxies down to m F160W = 21, of which 163 are spectroscopically confirmed. Internal velocity dispersions are measured for 85 members. The new lens model is characterized by a remarkably low scatter between the predicted and observed positions of the multiple images (0.″43). This precision is unprecedented given the large multiple-image sample, the complexity of the cluster mass distribution, and the large modeled area. The improved precision and resolution of the cluster total mass distribution provides a robust magnification map over a ∼30 arcmin2 area, which is critical for inferring the intrinsic physical properties of the highly magnified, high-z sources. The lens model and the new MUSE redshift catalog are released with this publication.

An IllustrisTNG view of the caustic technique for galaxy cluster mass estimation

The TNG300-1 run of the IllustrisTNG simulations includes 1697 clusters of galaxies with M200c > 1014 M⊙ covering the redshift range 0.01 − 1.04. We built mock spectroscopic redshift catalogs of simulated galaxies within these clusters and applied the caustic technique to estimate the cumulative cluster mass profiles. We computed the total true cumulative mass profile from the 3D simulation data, calculated the ratio of caustic mass to total 3D mass as a function of cluster-centric distance, and identified the radial range where this mass ratio is roughly constant. The ratio of 3D to caustic mass on this plateau defines ℱβ. The filling factor, ℱβ = 0.41 ± 0.08, is constant on a plateau that covers a wide cluster-centric distance range, (0.6 − 4.2) R200c. This calibration is insensitive to redshift. The calibrated caustic mass profiles are unbiased, with an average uncertainty of 23%. At R200c, the average MC/M3D = 1.03 ± 0.22; at 2 R200c, the average MC/M3D = 1.02 ± 0.23. Simulated galaxies are unbiased tracers of the mass distribution. IllustrisTNG is a broad statistical platform for application of the caustic technique to large samples of clusters with spectroscopic redshifts for ≳200 members in each system. These observations will allow extensive comparisons with weak-lensing masses and will complement other techniques for measuring the growth rate of structure in the Universe.

The SSA22 H i Tomography Survey (SSA22-HIT). I. Data Set and Compiled Redshift Catalog

We conducted a deep spectroscopic survey, named SSA22-HIT, in the SSA22 field with the DEep Imaging MultiObject Spectrograph (DEIMOS) on the Keck telescope, designed to tomographically map high-z H i gas through analysis of Lyα absorption in background galaxies’ spectra. In total, 198 galaxies were spectroscopically confirmed at 2.5 < z < 6 with a few low-z exceptions in the 26 × 15 arcmin2 area, of which 148 were newly determined in this study. Our redshift measurements were merged with previously confirmed redshifts available in the 34 × 27 arcmin2 area of the SSA22 field. This compiled catalog containing 730 galaxies of various types at z > 2 is useful for various applications, and it is made publicly available. Our SSA22-HIT survey has increased by approximately twice the number of spectroscopic redshifts of sources at z > 3.2 in the observed field. From a comparison with publicly available redshift catalogs, we show that our compiled redshift catalog in the SSA22 field is comparable to those among major extragalactic survey fields in terms of a combination of wide area and high surface number density of objects at z > 2. About 40% of the spectroscopically confirmed objects in SSA22-HIT show reasonable quality of spectra in the wavelengths shorter than Lyα when a sufficient amount of smoothing is adopted. Our data set enables us to make the H i tomographic map at z ≳ 3, which we present in a parallel study.

The first large catalogue of spectroscopic redshifts in Webb’s first deep field, SMACS J0723.3−7327

ABSTRACT We present a spectroscopic redshift catalogue of the SMACS J0723.3−7327 field (‘Webb’s First Deep Field’) obtained from JWST/NIRISS grism spectroscopy and supplemented with JWST/NIRSpec and VLT/MUSE redshifts. The catalogue contains a total of 190 sources with secure spectroscopic redshifts, including 156 NIRISS grism redshifts, 123 of which are for sources whose redshifts were previously unknown. These new grism redshifts are secured with two or more spectroscopic features (64 sources), or with a single spectral feature whose identity is secured from the object’s nine-band photometric redshift (59 sources). These are complemented with 17 NIRSpec and 48 MUSE redshifts, including six new NIRSpec redshifts identified in this work. In addition to the zcl = 0.39 cluster galaxy redshifts (for which we provide ∼40 new NIRISS absorption-line redshifts), we also find three prominent galaxy overdensities at higher redshifts – at z = 1.1, z = 1.4, and z = 2.0 – that were until now not seen in the JWST/NIRSpec and VLT/MUSE data. The paper describes the characteristics of our spectroscopic redshift sample and the methodology we have employed to obtain it. Our redshift catalogue is made available to the community at https://niriss.github.io/smacs0723.

Upper limits on transmitter rate of extragalactic civilizations placed by Breakthrough Listen observations

ABSTRACT The Search for Extra-Terrestrial Intelligence (SETI) has been conducted for over 60 yr, yet no technosignatures have been identified. Previous studies have focused on stars in our Galaxy, with few searches in the extragalactic Universe despite a larger volume being available. Civilizations capable of harvesting energy from a star or a galaxy are classified as KII or KIII on the Kardashev scale, respectively. Technosignatures from such advanced civilizations would be extremely luminous and detectable by current radio telescopes, even from distant galaxies. To explore the frontier of extragalactic SETI, we investigate the likely prevalence of extragalactic civilizations possessing a radio transmitter, known as the transmitter rate, based on observational results from the Breakthrough Listen (BL) observations. We calculated the transmitter rate by considering the background galaxies in the field of view of target stars in BL observations. We used a statistical method to derive the total mass of stars in those background galaxies from a galaxy stellar mass function. Our statistical method suggests that less than one in hundreds of trillions of extragalactic civilizations within 969 Mpc possess a radio transmitter above 7.7 × 1026 W of power, assuming one civilization per one-solar-mass stellar system. Additionally, we cross-matched the BL survey fields with the WISE × SuperCOSMOS Photometric Redshift Catalogue and compared with the statistical method. Our result sets the strictest limits to date on the transmitter rate at such high-power levels, emphasizing the high efficiency of searching for radio transmitters in galaxies and the rarity of technologically advanced civilizations in our Universe.

A newly identified galaxy group thanks to tidal streams of intragroup light

Context. In the accretion-driven growth scenario, part of the intracluster light is formed in the group environment. Aims. We report the serendipitous discovery of a group of galaxies with signs of diffuse light in the foreground of the known galaxy cluster MACS J0329−0211 at z ∼ 0.45. Methods. Our investigation began with the detection of diffuse light streams around a pair of bright galaxies in the southeastern region of a Suprime-Cam image of the galaxy cluster MACS J0329-0211. Our analysis is based on the extended CLASH-VLT redshift catalog and on new spectroscopic data obtained ad hoc with the Italian Telescopio Nazionale Galileo. We use the density reconstruction method to analyze the redshift distribution of the galaxies in the region around the galaxy pair. We also use available photometric and X-ray data to better characterize the properties of the group. Results. Thanks to the large amount of redshift data collected in this region, we have been able to discover the existence of a group of galaxies, here called GrG J0330−0218, which is associated with the pair of galaxies. These are the two brightest group galaxies (BGG1 and BGG2). We extracted 41 group members from the redshift catalog and estimate a mean redshift z = 0.1537 and a line-of-sight velocity dispersion σv ∼ 370 km s−1. In the phase-space diagram, the distribution of the galaxies of GrG J0330-0218 follows the characteristic trumpet-shaped pattern, which is related to the escape velocity of galaxy clusters, suggesting that the group is a virialized structure. Under this assumption, the mass of the group is M200 ∼ 6 × 1013 M⊙. We also measured a mass-to-light ratio of ∼130 M⊙/L⊙ and a luminosity fraction of diffuse light of ∼20% within 0.5 R200. Conclusions. We conjecture that galaxy pairs that are surrounded by diffuse light, probably due to tidal interactions, can serve as signposts for groups.

Neural networks optimized by genetic algorithms in cosmology

The applications of artificial neural networks in the cosmological field have shone successfully during the past decade, this is due to their great ability of modeling large amounts of datasets and complex nonlinear functions. However, in some cases, their use still remains controversial because their ease of producing inaccurate results when the hyperparameters are not carefully selected. In this paper, to find the optimal combination of hyperparameters to artificial neural networks, we propose to take advantage of the genetic algorithms. As a proof of the concept, we analyze three different cosmological cases to test the performance of the architectures achieved with the genetic algorithms and compare them with the standard process, consisting of a grid with all possible configurations. First, we carry out a model-independent reconstruction of the distance modulus using a type Ia supernovae compilation. Second, the neural networks learn to infer the equation of state for the quintessence model, and finally with the data from a combined redshift catalog the neural networks predict the photometric redshift given six photometric bands (urgizy). We found that the genetic algorithms improve considerably the generation of the neural network architectures, which can ensure more confidence in their physical results because of the better performance in the metrics with respect to the grid method.

The MUSEHubbleUltra Deep Field surveys: Data release II

We present the second data release of the MUSEHubbleUltra-Deep Field surveys, which includes the deepest spectroscopic survey ever performed. The MUSE data, with their 3D content, amazing depth, wide spectral range, and excellent spatial and medium spectral resolution, are rich in information. Their location in theHubbleultra-deep field area, which benefits from an exquisite collection of ancillary panchromatic information, is a major asset. This update of the first release incorporates a new 141-h adaptive-optics-assisted MUSE eXtremely Deep Field (MXDF; 1 arcmin diameter field of view) in addition to the reprocessed 10-h mosaic (3 × 3 arcmin2) and the single 31-h deep field (1 × 1 arcmin2). All three data sets were processed and analyzed homogeneously using advanced data reduction and analysis methods. The 3σpoint-source flux limit of an unresolved emission line reaches 3.1 × 10−19and 6.3 × 10−20 erg s−1 cm−2at 10- and 141-h depths, respectively. We have securely identified and measured the redshift of 2221 sources, an increase of 41% compared to the first release. With the exception of eight stars, the collected sample consists of 25 nearby galaxies (z &lt; 0.25), 677 [O II] emitters (z= 0.25 − 1.5), 201 galaxies in the MUSE redshift desert range (z = 1.5 − 2.8), and 1308 Lyαemitters (z = 2.8 − 6.7). This represents an order of magnitude more redshifts than the collection of all spectroscopic redshifts obtained before MUSE in theHubbleultra-deep field area (i.e., 2221 versus 292). At high redshift (z &gt; 3), the difference is even more striking, with a factor of 65 increase (1308 versus 20). We compared the measured redshifts against three published photometric redshift catalogs and find the photo-z accuracy to be lower than the constraints provided by photo-z fitting codes. Eighty percent of the galaxies in our final catalog have an HST counterpart. These galaxies are on average faint, with a median ABF775Wmagnitude of 25.7 and 28.7 for the [O II] and Lyαemitters, respectively. Fits of their spectral energy distribution show that these galaxies tend to be low-mass star-forming galaxies, with a median stellar mass of 6.2 × 108 M⊙and a median star-formation rate of 0.4 M⊙yr−1. We measured the completeness of our catalog with respect to HST and found that, in the deepest 141-h area, 50% completeness is achieved for an AB magnitude of 27.6 and 28.7 (F775W) atz= 0.8 − 1.6 andz = 3.2 − 4.5, respectively. Twenty percent of our catalog, or 424 galaxies, have no HST counterpart. The vast majority of these new sources are high equivalent-widthz &gt; 2.8 Lyαemitters that are detected by MUSE thanks to their bright and asymmetric broad Lyαline. We release advanced data products, specific software, and a web interface to select and download data sets.

Hierarchical Bayesian Inference of Photometric Redshifts with Stellar Population Synthesis Models

We present a Bayesian hierarchical framework to analyze photometric galaxy survey data with stellar population synthesis (SPS) models. Our method couples robust modeling of spectral energy distributions with a population model and a noise model to characterize the statistical properties of the galaxy populations and real observations, respectively. By self-consistently inferring all model parameters, from high-level hyperparameters to SPS parameters of individual galaxies, one can separate sources of bias and uncertainty in the data. We demonstrate the strengths and flexibility of this approach by deriving accurate photometric redshifts for a sample of spectroscopically confirmed galaxies in the COSMOS field, all with 26-band photometry and spectroscopic redshifts. We achieve a performance competitive with publicly released photometric redshift catalogs based on the same data. Prior to this work, this approach was computationally intractable in practice due to the heavy computational load of SPS model calls; we overcome this challenge by the addition of neural emulators. We find that the largest photometric residuals are associated with poor calibration for emission-line luminosities and thus build a framework to mitigate these effects. This combination of physics-based modeling accelerated with machine learning paves the path toward meeting the stringent requirements on the accuracy of photometric redshift estimation imposed by upcoming cosmological surveys. The approach also has the potential to create new links between cosmology and galaxy evolution through the analysis of photometric data sets.

Morpheus Reveals Distant Disk Galaxy Morphologies with JWST: The First AI/ML Analysis of JWST Images

The dramatic first images with JWST demonstrated its power to provide unprecedented spatial detail for galaxies in the high-redshift universe. Here, we leverage the resolution and depth of the JWST Cosmic Evolution Early Release Science Survey data in the Extended Groth Strip to perform pixel-level morphological classifications of galaxies in JWST F150W imaging using the Morpheus deep-learning framework for astronomical image analysis. By cross-referencing with existing photometric redshift catalogs from the Hubble Space Telescope (HST) CANDELS survey, we show that JWST images indicate the emergence of disk morphologies before z ∼ 2 and with candidates appearing as early as z ∼ 5. By modeling the light profile of each object and accounting for the JWST point-spread function, we find the high-redshift disk candidates have exponential surface brightness profiles with an average Sérsic index 〈n〉 = 1.04 and >90% displaying “disky” profiles (n < 2). Comparing with prior Morpheus classifications in CANDELS we find that a plurality of JWST disk galaxy candidates were previously classified as compact based on the shallower HST imagery, indicating that the improved optical quality and depth of the JWST helps to reveal disk morphologies that were hiding in the noise. We discuss the implications of these early disk candidates on theories for cosmological disk galaxy formation.

Searching for γ-ray Emission from Binary Black-Hole Mergers Detected in LIGO/Virgo O3 Run

We conduct searches for γ-ray emission from the binary black-hole (BBH) mergers reported in the Gravitational-Wave Candidate Event Database (GraceDB). The γ-ray data are from the all-sky survey of the Large-Area Telescope (LAT) onboard the Fermi Gamma-ray Space Telescope (Fermi), which allows searches for events of given time durations in large sky areas. The Two-Micron All-Sky Survey Photometric Redshift Catalog (2MPZ) is used for target selection, from which galaxy sources within the 90% credible areas and the distance ranges given by the gravitational-wave (GW) detections are determined. Excluding those BBH cases with large credible areas and/or dense fields (containing too many 2MPZ sources), searches for short transient events over the time duration of from −1 to 100 days of a trigger time for seven BBH mergers are conducted. We find two candidate short flaring events in the field of the GW event S200311bg and one in that of S190408an. However, the flaring events all have low significance (after considering the trial factor), and the third one appears off the position of the target galaxy. We discuss one of them from the first field that is detected in different short time-bin data and suggest that it is possibly a real flare arising from a radio galaxy. More such studies for the near-future GW detection run are planned, for which we will adjust our search strategy to be more effective and target flares of various time scales.

First JWST observations of a gravitational lens

We present our lens mass model of SMACS J0723.3−7327, the first strong gravitational lens observed by the James Webb Space Telescope (JWST). We use data from the Hubble Space Telescope and the Multi Unit Spectroscopic Explorer (MUSE) to build our ‘pre-JWST’ lens model and then refine it with newly available JWST near-infrared imaging in our JWST model. To reproduce the positions of all multiple lensed images with good accuracy, the adopted mass parameterisation consists of one cluster-scale component, accounting mainly for the dark matter distribution, the galaxy cluster members, and an external shear component. The pre-JWST model has, as constraints, 19 multiple images from six background sources, of which four have secure spectroscopic redshift measurements from this work. The JWST model has more than twice the number of constraints: 30 additional multiple images from another 11 lensed sources. Both models can reproduce the multiple image positions very well, with a δrms of 0.​​″39 and 0.​​″51 for the pre-JWST and JWST models, respectively. The total mass estimates within a radius of 128 kpc (roughly the Einstein radius) are 7.9−0.2+0.3 × 1013 M⊙ and 8.7−0.2+0.2 × 1013 M⊙ for the pre-JWST and JWST models, respectively. We predict with our mass models the redshifts of the newly detected JWST sources, which is crucial information, especially for systems without spectroscopic measurements, for further studies and follow-up observations. Interestingly, one family detected with JWST is found to be at a very high redshift, z &gt; 7.5 (68% confidence level), and with one image that has a lensing magnification of |μ| = 9.5−0.8+0.9, making it an interesting case for future studies. The lens models, including magnification maps and redshifts estimated from the model, are made publicly available, along with the full spectroscopic redshift catalogue from MUSE.

Type Ia supernova Hubble diagrams with host galaxy photometric redshifts

Systematic uncertainties associated to type Ia supernova (SN Ia) Hubble diagrams from photometrically selected samples using photometric SN host galaxy redshifts are investigated. The host redshift uncertainties and the contamination by core-collapse SNe are both addressed. As a test case, we use the 3-year photometric SN Ia sample of the SuperNova Legacy Survey (SNLS), consisting of 437 objects between 0.1 and 1.05 in redshift with 4.7% contamination. We combine this sample with non-SNLS objects of the spectroscopic sample from the joint analysis (JLA) of the SDSS-II and SNLS collaborations, consisting of 501 objects mostly below 0.4 in redshift. We study two options for the origin of the redshifts of the photometric sample, either provided entirely from the host photometric redshift catalogue used in the selection or a mixed origin where around 75% of the sample can be assigned spectroscopic redshifts from dedicated measurements or external catalogues. Using light curve simulations subject to the same photometric selection as data, we study the impact of photometric redshift uncertainties and contamination on flatΛCDM fits to Hubble diagrams from such combined samples. Our primary finding is that photometric redshifts and contamination lead to biased cosmological parameters. The magnitude of the bias is found to be similar for both redshift options. This bias can be largely accounted for if photometric redshift uncertainties and contamination are taken into account when computing the SN magnitude bias correction due to selection effects. To reduce the residual cosmological bias, we explore two methods to propagate redshift uncertainties into the cosmological likelihood computation, either by refitting photometric redshifts along with cosmology or by sampling the redshift resolution function. Redshift refitting fails at correcting the cosmological bias whatever the redshift origin, while sampling slightly reduces it in both cases. Finally, for actual data, we find compatible results with those from the JLA diagram for mixed photometric and spectroscopic redshifts, while the full photometric option is biased upwards, but consistent with JLA when all statistical and systematic uncertainties are included.

X-Ray Redshifts of Obscured Chandra Source Catalog Active Galactic Nuclei

We have computed obscured active galactic nuclei (AGN) redshifts using the XZ method, adopting a broad treatment in which we employed a wide-ranging data set and worked primarily at the XZ counts sensitivity threshold, culminating with a redshift catalog containing 121 sources that lack documented redshifts. We considered 363 obscured AGN from the Chandra Source Catalog Release 2.0, 59 of which were selected using multiwavelength criteria while 304 were X-ray selected. One third of the data set had crossmatched spectroscopic or photometric redshifts. These sources, dominated by low-z and low-N H AGN, were supplemented by 1000 simulations to form a data set for testing the XZ method. We used a multilayer perceptron neural network to examine and predict cases in which XZ fails to reproduce the known redshift, yielding a classifier that can identify and discard poor redshift estimates. This classifier demonstrated a statistically significant ∼3σ improvement over the existing XZ redshift information gain filter. We applied the machine-learning model to sources with no documented redshifts, resulting in the 121 source new redshift catalog, all of which were X-ray selected. Our neural network’s performance suggests that nearly 90% of these redshift estimates are consistent with hypothetical spectroscopic or photometric measurements, strengthening the notion that redshifts can be reliably estimated using only X-rays, which is valuable to current and future missions such as Athena. We have also identified a possible Compton-thick candidate that warrants further investigation.

Simulated catalogs and maps of radio galaxies at millimeter wavelengths in Websky

We present simulated millimeter-wavelength maps and catalogs of radio galaxies across the full sky that trace the nonlinear clustering and evolution of dark matter halos from the Websky simulation at z < 4.6 and M halo > 1012 m ⊙/h, and the accompanying framework for generating a new sample of radio galaxies from any halo catalog of positions, redshifts, and masses. Object fluxes are generated using a hybrid approach that combines (1) existing astrophysical halo models of radio galaxies from the literature to determine the positions and rank-ordering of the observed fluxes with (2) empirical models from the literature based on fits to the observed distribution of flux densities and (3) spectral indices drawn from an empirically-calibrated frequency-dependent distribution. The resulting population of radio galaxies is in excellent agreement with the number counts, polarization fractions, and distribution of spectral slopes from the data from observations at millimeter wavelengths from 20-200 GHz, including Planck, ALMA, SPT, and ACT. Since the radio galaxies are correlated with the existing cosmic infrared background (CIB), Compton-y (tSZ), and CMB lensing maps from Websky, our model makes new predictions for the cross-correlation power spectra and stacked profiles of radio galaxies and these other components. These simulations will be important for unbiased analysis of a wide variety of observables that are correlated with large-scale structure, such as gravitational lensing and SZ clusters.