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Start Over Subject surveys Validation Level 2
801. Hawaii Trails Project
ID:
ivo://CDS.VizieR/J/A+A/505/1297
Title:
Hawaii Trails Project
Short Name:
J/A+A/505/1297
Date:
21 Oct 2021
Publisher:
CDS
Description:
The mysterious solar system object 133P/(7968) Elst-Pizarro is dynamically asteroidal, yet displays recurrent comet-like dust emission. Two scenarios were hypothesized to explain this unusual behavior: (1) 133P is a classical comet from the outer solar system that has evolved onto a main-belt orbit, or (2) 133P is a dynamically ordinary main-belt asteroid on which subsurface ice has recently been exposed. If (1) is correct, the expected rarity of a dynamical transition onto an asteroidal orbit implies that 133P could be alone in the main belt. In contrast, if (2) is correct, other icy main-belt objects should exist and could also exhibit cometary activity. Believing 133P to be a dynamically ordinary, yet icy main-belt asteroid, I set out to test the primary prediction of the hypothesis: that 133P-like objects should be common and could be found by an appropriately designed observational survey.
802. HDBSCAN star, galaxy, QSO classification
ID:
ivo://CDS.VizieR/J/A+A/633/A154
Title:
HDBSCAN star, galaxy, QSO classification
Short Name:
J/A+A/633/A154
Date:
21 Oct 2021
Publisher:
CDS
Description:
Classification will be an important first step for upcoming surveys that will detect billions of new sources such as LSST and Euclid, as well as DESI, 4MOST and MOONS. The application of traditional methods of model fitting and colour-colour selections will face significant computational constraints, while machine-learning (ML) methods offer a viable approach to tackle datasets of that volume. While supervised learning methods can perform very well for classification tasks, the creation of representative and accurate training sets is a resource and time consuming task. We present a viable alternative using an unsupervised ML method to separate stars, galaxies and QSOs using photometric data. The heart of our work uses HDBSCAN to find the star, galaxy and QSO clusters in a multidimensional colour space. We optimized the hyperparameters and input attributes of three separate HDBSCAN runs, each to select a particular object class, and thus treat the output of each separate run as a binary classifier. We subsequently consolidate the output to give our final classifications, optimized on their F1 scores. We explore the use of Random Forest and PCA as part of the pre-processing stage for feature selection and dimensionality reduction. Using our dataset of ~50000 spectroscopically labelled objects we obtain an F1 score of 98.9, 98.9 and 93.13 respectively for star, galaxy and QSO selection using our unsupervised learning method. We find that careful attribute selection is a vital part of accurate classification with HDBSCAN. We applied our classification to a subset of the SDSS spectroscopic catalogue and demonstrate the potential of our approach in correcting misclassified spectra useful for DESI and 4MOST. Finally, we create a multiwavelength catalogue of 2.7 million sources using the KiDS, VIKING and ALLWISE surveys and publish corresponding classifications and photometric redshifts.
803. HDF flanking fields and related data
ID:
ivo://CDS.VizieR/J/ApJ/481/673
Title:
HDF flanking fields and related data
Short Name:
J/ApJ/481/673
Date:
21 Oct 2021
Publisher:
CDS
Description:
File flanking.dat contains Unpublished Catalogue of Galaxies identified by the DEEP Team in the Flanking Fields. This is the source catalogue that Vogt et al. (1997ApJ...479L.121V), Phillips et al. (1997ApJ...489..543P), Guzman et al. (1997ApJ...489..559G), and Mendez & Guzman (1998A&A...333..106M) used to select objects. The photometry in this catalogue was carried out using circular apertures of 3 arcsec diameter, as described by Phillips et al. (1997ApJ...489..543P). These will present small differences (~0.12mag, rms) relative to published values for the sample of 51 compact galaxies that were analysed by Phillips et al. (1997ApJ...489..543P) and Guzman et al. (1997ApJ...489..559G). This is because for the papers, the I(814) magnitudes were recalculated using elliptical apertures to 8 arcsec. The differences should only be significant in the case of galaxies with larger apparent sizes or with elongated shapes.
804. HDF-N Caltech faint galaxy redshift survey. X.
ID:
ivo://CDS.VizieR/J/ApJ/538/29
Title:
HDF-N Caltech faint galaxy redshift survey. X.
Short Name:
J/ApJ/538/29
Date:
21 Oct 2021
Publisher:
CDS
Description:
A redshift survey has been carried out in the region of the Hubble Deep Field North using the Low Resolution Imaging Spectrograph (LRIS) at the Keck Observatory. The resulting redshift catalog, which contains 671 entries, is a compendium of our own data together with published LRIS/Keck data.
805. HDFN SCUBA Super-map. III
ID:
ivo://CDS.VizieR/J/MNRAS/358/149
Title:
HDFN SCUBA Super-map. III
Short Name:
J/MNRAS/358/149
Date:
21 Oct 2021
Publisher:
CDS
Description:
We present a new submillimetre (submm) super-map in the Hubble Deep Field North (HDF-N) region (Great Observatories Origins Deep Survey North, GOODS-N, field), containing 40 statistically robust sources at 850um. This map contains additional data, and several new sources, including one of the brightest blank-sky extragalactic submm sources ever detected. We have used the Advanced Camera for Surveys (ACS) Hubble Space Telescope (HST) images and ground-based near-infrared (IR) observations from the Great Observatories Origins Deep Survey (GOODS), along with deep radio observations, to develop a systematic approach for counterpart identification. With the depth achieved by this survey, optical counterparts have been found for all the radio-detected (RD) submm sources.
806. HEAO 1A
ID:
ivo://nasa.heasarc/skyview/heao1a
Title:
HEAO 1A
Short Name:
HEAO1A
Date:
25 Apr 2025
Publisher:
NASA/GSFC HEASARC
Description:
These data were generated at the HEASARC in 1994. Certain gaps and streaks in the image have been fixed by interpolating over the the gap. Typically these gaps are no more than a pixel or two wide. A brief description of the satellite and the data analysis follows. The map used in <i> SkyView </i> is the map designated <tt> 322_15_tot_ecl_samp.img</tt> in the <a href=ftp://legacy.gsfc.nasa.gov/heao1/data/a2/maps/heasarc_med_hed> HEASARC FTP area</a>. Many other maps are available. These differ in epoch, resolution, energy band, coordinate system and projection, and sampling methods. Details are given in the README file in the archive. <p> See Allen, Jahoda, and Whitlock (1994) for full details about the available maps, their processing, and methods for converting the map intensities into familiar physical units. Provenance: NASA, HEASARC. This is a service of NASA HEASARC.
807. HeCS-red: Hectospec surveys of redMaPPer clusters
ID:
ivo://CDS.VizieR/J/ApJ/862/172
Title:
HeCS-red: Hectospec surveys of redMaPPer clusters
Short Name:
J/ApJ/862/172
Date:
21 Oct 2021
Publisher:
CDS
Description:
We use dense redshift surveys to explore the properties of galaxy clusters selected from the redMaPPer catalog. Our new survey, Hectospec Cluster Survey of red-sequence-selected clusters (HeCS-red), includes 10589 new or remeasured redshifts from MMT/Hectospec observations of 27 redMaPPer clusters at redshifts z=0.08-0.25 with large estimated richnesses (richness estimate {lambda}>64). Our spectra confirm that each candidate cluster corresponds to a large overdensity in redshift space. The redMaPPer photometric redshifts have a slight bias toward higher redshifts. We measure the relation between velocity dispersion {sigma}p and {lambda}. The relation shows intrinsic scatter of 24% (and a range of 2x) in velocity dispersion at fixed richness. We extend our analysis to HeCS-red-ext, a sample that includes several clusters selected by X-ray flux or Sunyaev-Zeldovich signal. The heterogeneous sample of 121 clusters in HeCS-red-ext shows similar intrinsic scatter in the {sigma}p-{lambda} relation as the HeCS-red sample, but the range of {sigma}p at fixed richness increases to 3x. We evaluate the membership probability estimates Pmem for individual galaxies provided by redMaPPer. The spectroscopic membership fraction is larger than Pmem for 0.05<=P_mem_<=0.7; conversely, the spectroscopic membership fraction is smaller than P_mem_ at P_mem_>=0.8. We compare spectroscopic richness estimates with redMaPPer richness estimates and find good agreement on average, but a range of a factor of two in spectroscopic richness at fixed redMaPPer richness. Overall, within the high-richness and low-redshift cut of our sample, spectroscopically estimated parameters such as velocity dispersion correlate well with photometric richness estimates, although the relations contain substantial scatter.
808. Hectospec Cluster Survey (HeCS)
ID:
ivo://CDS.VizieR/J/ApJ/767/15
Title:
Hectospec Cluster Survey (HeCS)
Short Name:
J/ApJ/767/15
Date:
21 Oct 2021
Publisher:
CDS
Description:
The infall regions of galaxy clusters represent the largest gravitationally bound structures in a {Lambda}CDM universe. Measuring cluster mass profiles into the infall regions provides an estimate of the ultimate mass of these halos. We use the caustic technique to measure cluster mass profiles from galaxy redshifts obtained with the Hectospec Cluster Survey (HeCS), an extensive spectroscopic survey of galaxy clusters with MMT/Hectospec. We survey 58 clusters selected by X-ray flux at 0.1<z<0.3. The survey includes 22680 unique MMT/Hectospec redshifts for individual galaxies; 10145 of these galaxies are cluster members. For each cluster, we acquired high signal-to-noise spectra for ~200 cluster members and a comparable number of foreground/background galaxies. The cluster members trace out infall patterns around the clusters. The members define a very narrow red sequence. We demonstrate that the determination of velocity dispersion is insensitive to the inclusion of bluer members (a small fraction of the cluster population). We apply the caustic technique to define membership and estimate the mass profiles to large radii. The ultimate halo mass of clusters (the mass that remains bound in the far future of a {Lambda}CDM universe) is on average (1.99+/-0.11)M_200_, a new observational cosmological test in essential agreement with simulations. Summed profiles binned in M_200_ and in L_X_demonstrate that the predicted Navarro-Frenk-White form of the density profile is a remarkably good representation of the data in agreement with weak lensing results extending to large radius. The concentration of these summed profiles is also consistent with theoretical predictions.
809. Hectospec survey of SZ clusters (HeCS-SZ)
ID:
ivo://CDS.VizieR/J/ApJ/819/63
Title:
Hectospec survey of SZ clusters (HeCS-SZ)
Short Name:
J/ApJ/819/63
Date:
21 Oct 2021
Publisher:
CDS
Description:
We estimate cluster masses and velocity dispersions for 123 clusters from optical spectroscopy to compare the Sunyaev-Zeldovich (SZ) mass proxy and dynamical masses. Our new survey, HeCS-SZ (Hectospec Cluster Survey of SZ-selected clusters), includes 7721 new or remeasured redshifts from MMT/Hectospec observations of 21 SZ-selected clusters at redshifts z=0.05-0.20. We supplement the Hectospec data with spectra from the Sloan Digital Sky Survey (SDSS) and cluster data from the Cluster Infall Regions in SDSS project and the Hectospec Cluster Survey, our Hectospec survey of clusters selected by X-ray flux. We measure the scaling relation between velocity dispersion and SZ mass estimates from the integrated Compton parameter for an SZ-complete sample of 83 clusters. The observed relation agrees very well with a simple virial scaling from mass (based on SZ) to velocity dispersion. The SZ mass estimates (calibrated with hydrostatic X-ray mass estimates) are not significantly biased compared to dynamical mass estimates under the assumption of small velocity bias of galaxies compared to dark matter particles. Significant mass bias in SZ mass estimates could relieve tension between cosmological results from Planck SZ cluster counts and Planck CMB data. In principle, SZ mass bias and velocity bias of galaxies could conspire to yield good agreement, but the required velocity bias is {sigma}_galaxy_~0.77{sigma}_DM_, outside the range of recent models of velocity bias in the literature. More likely, SZ mass bias and velocity bias are both small, and the tension between SZ cluster counts and CMB data requires another explanation.
810. Heidelberg InfraRed Optical Cluster Survey, HIROCS
ID:
ivo://CDS.VizieR/J/A+A/513/A15
Title:
Heidelberg InfraRed Optical Cluster Survey, HIROCS
Short Name:
J/A+A/513/A15
Date:
21 Oct 2021
Publisher:
CDS
Description:
We describe a survey for distant clusters of galaxies that identified clusters as local overdensities in the 3D galaxy distribution. Optical and near-IR imaging in B, R, i, z, and H are used to derive photometric redshifts for objects as faint as m*+1 at a redshift of 1.5. We outline the astrometric and photometric data reduction. The 3D cluster search, based on the photometric redshifts, is described.

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