Photometric Redshift Catalogue Research Articles

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.

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.

The MUSE Hubble Ultra Deep Field surveys: Data release II

We present the second data release of the MUSE Hubble Ultra-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 the Hubble ultra-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 3σ point-source flux limit of an unresolved emission line reaches 3.1 × 10−19 and 6.3 × 10−20 erg s−1 cm−2 at 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 < 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 Lyα emitters (z = 2.8 − 6.7). This represents an order of magnitude more redshifts than the collection of all spectroscopic redshifts obtained before MUSE in the Hubble ultra-deep field area (i.e., 2221 versus 292). At high redshift (z > 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 AB F775W magnitude of 25.7 and 28.7 for the [O II] and Lyα emitters, 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) at z = 0.8 − 1.6 and z = 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-width z > 2.8 Lyα emitters that are detected by MUSE thanks to their bright and asymmetric broad Lyα line. 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.

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.

Giant radio galaxies in the LOw-Frequency ARray Two-metre Sky Survey Boötes deep field

ABSTRACT Giant radio galaxies (GRGs) are radio galaxies that have projected linear extents of more than 700 kpc or 1 Mpc, depending on definition. We have carried out a careful visual inspection in search of GRGs of the Boötes LOw-Frequency ARray Deep Field image at 150 MHz. We identified 74 GRGs with a projected size larger than 0.7 Mpc of which 38 are larger than 1 Mpc. The resulting GRG sky density is about 2.8 (1.43) GRGs per square degree for GRGs with linear size larger than 0.7 (1) Mpc. We studied their radio properties and the accretion state of the host galaxies using deep optical and infrared survey data and determined flux densities for these GRGs from available survey images at both 54 MHz and 1.4 GHz to obtain integrated radio spectral indices. We show the location of the GRGs in the P–D diagram. The accretion mode on to the central black holes of the GRG hosts is radiatively inefficient suggesting that the central engines are not undergoing massive accretion at the time of the emission. Interestingly, 14 out of 35 GRGs for which optical spectra are available show a moderate star-formation rate (10–100 $\rm M_{\odot }\,yr^{-1}$). Based on the number density of optical galaxies taken from the Dark Energy Spectroscopic Instrument survey DR9 photometric redshift catalogue, we found no significant differences between the environments of GRGs and other radio galaxies, at least for redshift up to z = 0.7.

A systematic search for galaxy protocluster cores at the transition epoch of their star formation activity

ABSTRACT The redshift of z ∼ 1.5 is the transition epoch of protoclusters (PCs) from the star-forming phase into the quenching phase, and hence an appropriate era to investigate the build up of the quenched population. We define a ‘core’ as the most massive halo in a given PC, where environmental effects are likely to work most effectively, and search for cores at 1 &amp;lt; z &amp;lt; 1.5. We use a photometric redshift catalogue of a wide (effective area of ${\sim}22.2\, \mathrm{deg}^{2}$) and deep ($i\sim 26.8\, \mathrm{mag}$) optical survey with Subaru Hyper-Suprime Cam. Regarding galaxies with log (M*/M⊙) &amp;gt; 11.3 as the central galaxies of PC cores, we estimate their average halo mass by clustering analysis and find it to be log (Mh/M⊙) ∼ 13.7. An expected mass growth by the IllustrisTNG simulation and the observed overdensities around them suggest that the PC cores we find are progenitors of present-day clusters. Classifying our galaxy sample into red and blue galaxies, we calculate the stellar mass function (SMF) and the red galaxy fraction. The SMFs in the PC cores are more-top heavy than field, implying early high-mass galaxy formation and disruption of low-mass galaxies. We also find that the red fraction increases with stellar mass, consistent with stellar mass dependent environmental quenching recently found at z &amp;gt; 1. Interestingly, although the cores with red and blue centrals have similar halo masses, only those with red centrals show a significant red fraction excess compared to the field, suggesting a conformity effect. Some observational features of PC cores may imply that the conformity is caused by assembly bias.

Calibrating Photometric Redshift Measurements with the Multi-channel Imager (MCI) of the China Space Station Telescope (CSST)

The China Space Station Telescope (CSST) photometric survey aims to perform a high spatial resolution (∼0.″15) photometric imaging for the targets that cover a large sky area (∼17,500 deg2) and wide wavelength range (from NUV to NIR). It expects to explore the properties of dark matter, dark energy, and other important cosmological and astronomical areas. In this work, we evaluate whether the filter design of the Multi-channel Imager (MCI), one of the five instruments of the CSST, can provide accurate photometric redshift (photoz) measurements with its nine medium-band filters to meet the relevant scientific objectives. We generate the mock data based on the COSMOS photometric redshift catalog with astrophysical and instrumental effects. The application of upper limit information of low signal-to-noise ratio data is adopted in the estimation of photoz. We investigate the dependency of photoz accuracy on the filter parameters, such as band position and width. We find that the current MCI filter design can achieve good photoz measurements with accuracy σ z ≃ 0.017 and outlier fraction f c ≃ 2.2%. It can effectively improve the photoz measurements of the main CSST survey using the Survey Camera to an accuracy σ z ≃ 0.015 and outlier fraction f c ≃ 1.5%. This indicates that the original MCI filters are proper for the photoz calibration.

COSMOS2020: A Panchromatic View of the Universe to z ∼ 10 from Two Complementary Catalogs

Abstract The Cosmic Evolution Survey (COSMOS) has become a cornerstone of extragalactic astronomy. Since the last public catalog in 2015, a wealth of new imaging and spectroscopic data have been collected in the COSMOS field. This paper describes the collection, processing, and analysis of these new imaging data to produce a new reference photometric redshift catalog. Source detection and multiwavelength photometry are performed for 1.7 million sources across the 2 deg2 of the COSMOS field, ∼966,000 of which are measured with all available broadband data using both traditional aperture photometric methods and a new profile-fitting photometric extraction tool, The Farmer, which we have developed. A detailed comparison of the two resulting photometric catalogs is presented. Photometric redshifts are computed for all sources in each catalog utilizing two independent photometric redshift codes. Finally, a comparison is made between the performance of the photometric methodologies and of the redshift codes to demonstrate an exceptional degree of self-consistency in the resulting photometric redshifts. The i &lt; 21 sources have subpercent photometric redshift accuracy and even the faintest sources at 25 &lt; i &lt; 27 reach a precision of 5%. Finally, these results are discussed in the context of previous, current, and future surveys in the COSMOS field. Compared to COSMOS2015, it reaches the same photometric redshift precision at almost one magnitude deeper. Both photometric catalogs and their photometric redshift solutions and physical parameters will be made available through the usual astronomical archive systems (ESO Phase 3, IPAC-IRSA, and CDS).

Redshift identification of X-ray-selected active galactic nuclei in the J1030 field: searching for large-scale structures and high-redshift sources

We publicly release the spectroscopic and photometric redshift catalog of the sources detected withChandrain the field of thez= 6.3 quasar SDSS J1030+0525. This is currently the fifth-deepest extragalactic X-ray field, and reaches a 0.5–2 keV flux limit off0.5 − 2= 6 × 10−17erg s−1cm−2. Using two independent methods, we measure a photometric redshift for 243 objects, while 123 (51%) sources also have a spectroscopic redshift, 110 of which come from an INAF-Large Binocular Telescope (LBT) Strategic Program. We use the spectroscopic redshifts to determine the quality of the photometric ones, and find it to be in agreement with that of other X-ray surveys which used a similar number of photometric data points. In particular, we measure a sample normalized median absolute deviation ofσNMAD= 1.48 × median(||zphot − zspec||/(1 +zspec)) = 0.065. We use these new spectroscopic and photometric redshifts to study the properties of theChandraJ1030 field. We observe several peaks in our spectroscopic redshift distribution betweenz= 0.15 andz= 1.5, and find that the sources in each peak are often distributed across the wholeChandrafield of view. This confirms that X-ray-selected AGNs can efficiently track large-scale structures over physical scales of several megaparsecs. Finally, we computed theChandraJ1030z&gt; 3 number counts: while the spectroscopic completeness of our sample is limited at high redshift, our results point towards a potential source excess atz ≥ 4, which we plan to either confirm or reject in the near future with dedicated spectroscopic campaigns.

Interrelation of the Environment of Lyα Emitters and Massive Galaxies at 2 &lt; z &lt; 4.5

Abstract We present a comparison of the spatial distributions of Lyα emitters (LAEs) and massive star-forming and quiescent galaxies (SFGs and QGs) at 2 &lt; z &lt; 4.5. We use the photometric redshift catalog to select SFGs and QGs and an LAE catalog from intermediate/narrow bands obtained from the Subaru Telescope and Isaac Newton Telescope in the Cosmic Evolution Survey (COSMOS). We derive the auto-/cross-correlation signals of SFGs, QGs, and LAEs and the galaxy overdensity distributions at the position of them. Whereas the cross-correlation signals of SFGs and QGs are explained solely by their halo mass differences, those of SFGs and LAEs are significantly lower than those expected from their autocorrelation signals, suggesting that some additional physical processes are segregating these two populations. Such segregation of SFGs and LAEs becomes stronger for rest-frame ultraviolet faint LAEs (M UV &gt; −20). From the overdensity distributions, LAEs are located in less dense regions than SFGs and QGs, whereas SFGs and QGs tend to be in the same overdensity distributions. The different spatial distributions of LAEs compared to those of massive galaxies may be attributed to assembly bias or large amounts of neutral hydrogen gas associated with massive halos. These results reinforce the importance of exploring multiple galaxy populations in quantifying the intrinsic galaxy environment of the high-z universe.

Galaxy Clusters from the DESI Legacy Imaging Surveys. I. Cluster Detection

Abstract Based on the photometric redshift catalog of Zou et al., we apply a fast clustering algorithm to identify 540,432 galaxy clusters at z ≲ 1 in the DESI legacy imaging surveys, which cover a sky area of about 20,000 deg2. Monte Carlo simulations indicate that the false-detection rate of our detecting method is about 3.1%. The total masses of galaxy clusters are derived using a calibrated richness–mass relation that is based on the observations of X-ray emission and the Sunyaev and Zel’dovich effect. The median redshift and mass of our detected clusters are about 0.53 and 1.23 × 1014 M ⊙, respectively. Comparing with previous clusters identified using the data of the Sloan Digital Sky Survey; we can recognize most of them, especially those with high richness. Our catalog will be used for further statistical studies on galaxy clusters and environmental effects on galaxy evolution, etc.

A hierarchical clustering method for quantifying satellite abundance

ABSTRACT We present a new method for quantifying the abundance of satellites around field galaxies and in groups. The method is designed to work with samples such as photometric redshift catalogues, that do not have full spectroscopic coverage, but for which some redshift or distance information is available. It consists of identifying the galaxies most likely to be centrals, and using the clustering signal around them as a template to iteratively decompose the full population into satellite and central populations. Thus, it is similar to performing crowded-field photometry by using isolated stars to determine the point spread function of the image. The method does not identify individual satellites or centrals conclusively, but assigns a probability to each galaxy of being one or the other. Averaged over a large sample, it provides a statistical estimate of satellite abundance, even in crowded fields with large redshift uncertainties. We test the method using data from the COSMOS field, which includes a large set of local objects with accurate photometric redshifts. We measure satellite abundance as a function of central stellar or halo mass, as well as the satellite luminosity function, and find results consistent with previous studies, but extending over a broader range of central masses. We also consider a number of possible systematic uncertainties in the method, and show that they are generally smaller than our random errors. Having presented the method in this paper, we will use it to study the properties of the satellite populations in a forthcoming one.

The ALPINE-ALMA [CII] survey

Aims. We present the detailed characterisation of a sample of 56 sources serendipitously detected in ALMA band 7 as part of the ALMA Large Program to INvestigate CII at Early Times (ALPINE). These sources, detected in COSMOS and ECDFS, have been used to derive the total infrared luminosity function (LF) and to estimate the cosmic star formation rate density (SFRD) up to z ≃ 6. Methods. We looked for counterparts of the ALMA sources in all the available multi-wavelength (from HST to VLA) and photometric redshift catalogues. We also made use of deeper UltraVISTA and Spitzer source lists and maps to identify optically dark sources with no matches in the public catalogues. We used the sources with estimated redshifts to derive the 250 μm rest-frame and total infrared (8–1000 μm) LFs from z ≃ 0.5 to 6. Results. Our ALMA blind survey (860 μm flux density range: ∼0.3–12.5 mJy) allows us to further push the study of the nature and evolution of dusty galaxies at high-z, identifying luminous and massive sources to redshifts and faint luminosities never probed before by any far-infrared surveys. The ALPINE data are the first ones to sample the faint end of the infrared LF, showing little evolution from z ≃ 2.5 to z ≃ 6, and a “flat” slope up to the highest redshifts (i.e. 4.5 &lt; z &lt; 6). The SFRD obtained by integrating the luminosity function remains almost constant between z ≃ 2 and z ≃ 6, and significantly higher than the optical or ultra-violet derivations, showing a significant contribution of dusty galaxies and obscured star formation at high-z. About 14% of all the ALPINE serendipitous continuum sources are found to be optically and near-infrared (near-IR) dark (to a depth Ks ∼ 24.9 mag). Six show a counterpart only in the mid-IR and no HST or near-IR identification, while two are detected as [C II] emitters at z ≃ 5. The six HST+near-IR dark galaxies with mid-IR counterparts are found to contribute about 17% of the total SFRD at z ≃ 5 and to dominate the high-mass end of the stellar mass function at z &gt; 3.

Photometric redshifts for galaxies in the Subaru Hyper Suprime-Cam and unWISE and a catalogue of identified clusters of galaxies

ABSTRACT We first present a catalogue of photometric redshifts for 14.68 million galaxies derived from the 7-band photometric data of Hyper Suprime-Cam Subaru Strategic Program and the Wide-field Infrared Survey Explorer using the nearest-neighbour algorithm. The redshift uncertainty is about 0.024 for galaxies of z ≤ 0.7, and steadily increases with redshift to about 0.11 at z ∼ 2. From such a large data set, we identify 21 661 clusters of galaxies, among which 5537 clusters have redshifts z &amp;gt; 1 and 642 clusters have z &amp;gt; 1.5, significantly enlarging the high redshift sample of galaxy clusters. Cluster richness and mass are estimated, and these clusters have an equivalent mass of M500 ≥ 0.7 × 1014 M⊙. We find that the stellar mass of the brightest cluster galaxies (BCGs) in each richness bin does not significantly evolve with redshift. The fraction of star-forming BCGs increases with redshift, but does not depend on cluster mass.

A Statistical Standard Siren Measurement of the Hubble Constant from the LIGO/Virgo Gravitational Wave Compact Object Merger GW190814 and Dark Energy Survey Galaxies

Abstract We present a measurement of the Hubble constant H 0 using the gravitational wave (GW) event GW190814, which resulted from the coalescence of a 23 M ⊙ black hole with a 2.6 M ⊙ compact object, as a standard siren. No compelling electromagnetic counterpart has been identified for this event; thus our analysis accounts for thousands of potential host galaxies within a statistical framework. The redshift information is obtained from the photometric redshift (photo-z) catalog from the Dark Energy Survey. The luminosity distance is provided by the LIGO/Virgo gravitational wave sky map. Since this GW event has the second-smallest localization volume after GW170817, GW190814 is likely to provide the best constraint on cosmology from a single standard siren without identifying an electromagnetic counterpart. Our analysis uses photo-z probability distribution functions and corrects for photo-z biases. We also reanalyze the binary black hole GW170814 within this updated framework. We explore how our findings impact the H 0 constraints from GW170817, the only GW merger associated with a unique host galaxy. From a combination of GW190814, GW170814, and GW170817, our analysis yields (68% highest-density interval, HDI) for a prior in H 0 uniform between . The addition of GW190814 and GW170814 to GW170817 improves the 68% HDI from GW170817 alone by ∼18%, showing how well-localized mergers without counterparts can provide a significant contribution to standard siren measurements, provided that a complete galaxy catalog is available at the location of the event.

PS1-STRM: neural network source classification and photometric redshift catalogue for PS1 3π DR1

ABSTRACT The Pan-STARRS1 (PS1) 3π survey is a comprehensive optical imaging survey of three quarters of the sky in the grizy broad-band photometric filters. We present the methodology used in assembling the source classification and photometric redshift (photo-z) catalogue for PS1 3π Data Release 1, titled Pan-STARRS1 Source Types and Redshifts with Machine learning (PS1-STRM). For both main data products, we use neural network architectures, trained on a compilation of public spectroscopic measurements that has been cross-matched with PS1 sources. We quantify the parameter space coverage of our training data set, and flag extrapolation using self-organizing maps. We perform a Monte Carlo sampling of the photometry to estimate photo-z uncertainty. The final catalogue contains 2902 054 648 objects. On our validation data set, for non-extrapolated sources, we achieve an overall classification accuracy of $98.1{{\ \rm per\ cent}}$ for galaxies, $97.8{{\ \rm per\ cent}}$ for stars, and $96.6{{\ \rm per\ cent}}$ for quasars. Regarding the galaxy photo-z estimation, we attain an overall bias of 〈Δznorm〉 = 0.0005, a standard deviation of σ(Δznorm) = 0.0322, a median absolute deviation of MAD(Δznorm) = 0.0161, and an outlier fraction of $P\left(|\Delta z_{\mathrm{norm}}|\gt 0.15\right)=1.89{{\ \rm per\ cent}}$. The catalogue will be made available as a high-level science product via the Mikulski Archive for Space Telescopes.