adsabs/AstroCLIMB huggingface dataset:
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: The distribution of redshift and luminosity distance for each type, shown as normalized density with respect to distance modulus. Labels with asterisks are events that are not further classified as any subtype of this parent type, i.e., “unspecified” events in Table 2. Luminous events, like SNe Ia and SLSNe, are generally populated at the higher-redshift side. Meanwhile, relative to their parent types, luminous subtypes (e.g., Ia-91T, Ia CSM, and Ibn) are usually at the higher-redshifts side, while faint subtypes (e.g., Ia-91bg, Ia-02cx, and Ca-rich) are usually at lower redshifts. However, the different distributions cannot be fully attributed to the classical Malmquist bias. Some types require detailed observations (e.g., densely sampled light curves, spectra) to be classified, implicitly biasing them to lower redshifts. Also, our transients are compiled from various surveys and spontaneous discoveries that do not share the same detection efficiencies.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Year of discovery vs. redshift of our transient events, color-coded with the decl. angle. The time axis is stretched so that transients are uniformly distributed, and the vertical axis is in uniform scale of the cosmological distance modulus. The transient sample is a mixture of shallow, wide-field surveys and deep, high-redshift surveys with limited sky coverage. There exists a low-redshift, spatially scattered component peaked at z ≃ 0.05, with another higher redshift, spatially more localized component around z ≃ 0.5. Consequently, the redshift or luminosity distance distribution of our events is double-peaked, as illustrated in Figure 3.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Top: equatorial coordinates of transients in Lambert cylindrical equal-area projection. Colors indicate their redshifts, and gray points are events without redshifts. The dashed and dotted lines trace ecliptic and Galactic planes, respectively. The fields of several deep supernova surveys are clearly visible, but they only contribute a limited fraction of events. Large-area surveys discover most events. Bottom: similar to the top panel, but showing Galactic coordinates instead. The discovery dates of events are color-coded with uniform number density over the color axis. Gray points indicate events without discovery dates. The dashed and dotted lines trace equatorial and ecliptic planes, respectively. The timespans of major deep supernova surveys, particularly the SDSS-II supernova survey near the equatorial plane, are clearly visible.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: The general procedure to compile host properties for transient events. For events with known hosts, we resolve host names in NED and SIMBAD to obtain the best-available host coordinates and search the coordinates in external catalogs. The catalog sources that correspond to our known hosts are selected with a multi-catalog cross-matching process to avoid mismatching. For events without hosts reported, we search the transient coordinates in external catalogs with larger cone radii, cross-match all nearby catalog sources with a similar approach, and identify the most likely host candidates within cross-matched groups using a trained ranking function. The subsections are indicated on each block.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: The accuracy of host cross-identification with our default ranking functions, using redshift-dependent variables (red) or not (blue). The four panels here show the dependence of accuracy on transient redshift, transient-host angular offset, transient type, and host optical-NIR magnitude. Except for the panel of transient type, we split the sample into bins of equal number counts along the axis of interest and plot the per-bin accuracy at the median value of the bin. We estimate the accuracy in two separate ways. With the sample of known hosts (i.e., the training set), we calculated the average accuracy using tenfold cross-validation, where the standard deviations are indicated as error bars. For the sample of new hosts, we estimated an empirical accuracy with a visual inspection, defined as the fraction of visually identified hosts that are also chosen by our algorithm. Vertical error bars outline the range of accuracy due to the uncertain cases (Appendix J.2). We plot the distribution of both samples as shaded areas in each subpanel. The densities are over the logarithmic axis for redshift and transient-host angular offset, so the histogram area corresponds to the sample size. For the dependence on redshift, we also plot the subset of points without redshift, in the gray shaded area of the first panel.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Examples of incorrectly identified hosts from cross-validation of known hosts and visual inspection of new hosts. Each panel shows a field centered at the transient event, with the event name and angular scale of 5″ indicated at the corners. Inside the search radius of each event (dotted circle), the best host (either previously reported or visually identified) and algorithm-identified host are highlighted with red and orange crosses, and other cross-matched sources are marked with white circles. Each row here represents a common failure mode: (1) inevitable confusion of multiple likely host candidates in the field, in which the true host could be ambiguous even for visual identification; (2) the true host is located beyond the search radius due to an exceptionally large transient-host offset; (3) part of a well-resolved, nearby large galaxy is identified as the host, instead of its main component; and (4) another cross-matched object, either nearby or far in the background, is erroneously identified as the host at higher ranks. Events at lower redshifts are more susceptible to the second and third cases.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Examples of cross-matching catalog sources using astrometric tolerances and connectivity of objects. Each panel here shows the color composite image of a host galaxy on the left side, with transient name, redshift, and 1″ angular scale (red bar) indicated. The cross-matched catalog sources are plotted with various symbols on the right side, and a zoom-in view of the red circle (radius indicated) centered at the host. To cross-match objects, the distances of catalog sources are normalized by their pairwise astrometric tolerances and then compared to their thresholds of connectivity (Section 3.2). Connected pairs under this criteria are indicated as gray lines, and groups of interconnected catalog sources are further labeled as cross-matched objects. For clarity, we only zoom into the host here, while other catalog sources in the search radius are also cross-matched into groups in the same way. These panels are randomly selected near redshifts 0.02, 0.05, 0.1, 0.2, 0.5, and 1, where the upper six panels are known hosts, and the lower six panels are new hosts with our algorithm (Section 3.4). The cross-matching algorithm we developed is effective yet flexible for most hosts, while more complex cases are discussed in Appendix G.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Star-galaxy separation using Gaia astrometric excess noise (ϵ) and its statistical significance (σϵ), illustrated with a cross-matched example of Gaia and MzLS/BASS. Sources are classified into “point” (PSF) or “extended” (EXP, DEV, COMP, REX) by DESI-LS pipeline morphological types, and further separated into “bright” or “faint” groups by Gaia G-band magnitude of 19. DESI-LS use G < 19 and ﹩{\mathrm{log}}_{10}\epsilon \lt 0.5﹩ (vertical dashed line) as their criterion for astrometric point sources, which is independent of their morphological classification. To improve the effectiveness at fainter magnitudes while ensuring the purity of point sources, we use a magnitude-independent selection cut (solid line) that aligns with the gap that separates pointlike and extended sources in this plane.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Top: the angular transient-host distances in our database, including both known host galaxies and newly identified hosts. Thermonuclear (Ia) and core-collapse (CC) supernovae are plotted separately with orange and blue dots. Angular distances matching 1 kpc and 6.5 kpc (average deprojected physical distance) are outlined in dashed and solid gray lines, respectively. Bottom: the deprojected physical distance of transient-host pairs (in kiloparsecs), with similar symbols as in the top panel. Physical distance matching 1″ angular scale (typical position accuracy of galaxy coordinates) is indicated in gray dashed line. The angular distance mainly follows the cosmological angular diameter distance, where most events happen within 1 and 10 kpc. Converted to the physical distances, we find little or no redshift dependence of transient-host distance, with an average value of 6.5 kpc.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Redshift and luminosity distance distributions of transients with host properties available in each external catalog, shown as normalized densities with respect to distance modulus. The top two rows show the distribution for events with confirmed known hosts and newly identified candidates, while other rows show subsets of all hosts (confirmed and newly identified) with data in the external catalog available, as indicated at the left side. Here the distributions mainly reflect the depth of external catalogs, where deeper surveys like GALEX MIS and DES have more higher-redshift events than those shallow surveys (e.g., SkyMapper). The double-peaked redshift distribution of transients is clear in the known hosts.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Fractional converge of host properties within each data set, for each major transient type. The fractions of events with valid redshift, known hosts, or newly identified hosts are also indicated in three separate columns. The fractional coverage accounted here primarily reflects the coverage of a catalog in sky area and depth. Wide-area sky surveys, including PS1, WISE, SDSS, and SuperCOSMOS, have generally better coverage over almost all transient types. The depth or sensitivity of a catalog may also have a nonnegligible effect on the availability. Furthermore, transient subtypes that require detailed follow-up to identify have relatively complete host properties as they are usually biased to lower redshifts.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: The photometric magnitude (AB) distribution of known hosts and newly identified hosts in our external catalogs, grouped by their nominal photometric bands. In each panel, the photometric band is indicated at the upper right corner, while the catalog and number count of valid values are listed in the legend. Histogram heights are scaled to the highest peak in each photometric band. We applied a signal-to-noise cut of 5 for a fair comparison. Vega magnitudes are converted to the AB system using the zero-points in Jarrett et al. (2011). Note that deep optical catalogs with substantial coverage in the northern hemisphere have prominent double-peaked magnitude distributions. These events are mostly at higher redshifts, rather than in fainter hosts at lower redshifts.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: The procedure to access value-added catalogs and survey catalogs for host properties. For each event, we determine the coordinate to search (host or transient coordinate) and the search radius based on the availability of information in our transient data sources. Whenever possible, we search host coordinates resolved using VACs or as provided in the transient data set, instead of the transient coordinate. When searching a transient coordinate, to optimize the chance of covering the true host, we determine the search radius using transient redshift if available. In the absence of transient redshift, the error circle is also used for GRBs.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Finding the best astrometric tolerances for external catalogs using Monte Carlo sampling. The results here show a Monte Carlo sample of 200,000 points, optimized for an objective function with a constant power index of 0.618 for the scaling function, as discussed in Appendix F. We use a fixed axis range of (0″, 3″) for all subpanels, including marginalized distributions and two-dimensional projections of the sample. The best-overall astrometric tolerances, determined by searching the peak of marginalized distribution using a Gaussian kernel of 0″.125, are indicated with blue lines. The detailed values are listed in Table 5.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Top: the improvement of connectivity after tuning the matching threshold. We count the number of valid pairs (Npair) using the adjusted matching threshold and compare it to the number of valid pairs matched under unity threshold (Npair,unity). Their ratio represents the improvement of cross-matching after per-field fine-tuning of the matching threshold. The solid line shows the moving median of Npair/Npair,unity, while the thin lines show the corresponding 25%–75%. Bottom: histogram of the locally adjusted matching threshold. More than half of the fields are cross-matched using a default unity matching threshold (gray zone), so we only show the distribution for those with different matching thresholds.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Three quality control metrics of cross-matching for known and newly identified hosts. For cross-matched objects in a group, we calculate their average distance to the group centroid (mean offset, d), the axis ratio (semimajor to minor) of covariance ellipse (σa/σb), and the number of directly connected pairs to the maximal number of allowed connections (i.e., degree of connectivity). We split our hosts into three subgroups of nearly equal sizes per their number of cross-matched catalog objects (N). The dark and light contours in each panel enclose 50% and 95% of the hosts in each subgroup, while hosts outside 95% contours are plotted as individual points. The top and right sides of each panel show the cumulative histograms of each metric for each subgroup. Properly matched groups are expected to be compact (low d) and isotropic (σa/σb near unity), in which catalog objects are adequately connected (high degree of connectivity). Cross-matched groups with extreme values, like large d and σa/σb, or very low degree of connectivity, should be used with care.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Top: cross-matching catalog sources in fields with nearby large galaxies. Two examples here are PS16fdq (left) and SNhunt124 (right). The spiral arms, bright clumps, and extended outskirts of nearby large galaxies are often broken into individual sources when the object detection algorithm is not tailored toward such situations. Nearby large galaxies with low surface brightness, flat light profile, or irregular morphology may also have significant catalog-to-catalog offsets in source coordinates. Consequently, their compiled host properties are subject to incompleteness or mismatching. Even the cross-matched substructures may interfere with the identification of new hosts. Bottom: cross-matching catalog sources with non-optimal astrometric tolerances or matching thresholds. Examples here are SN2017hdn (left) and SDSS-II SN 15822 (right). The cross-matched groups in both cases contain at least two distinct objects, which are glued into a single group either due to large scatter of source coordinates or by a few bridging sources. Such groups can be excluded by their extreme values of connectivity and mean offset. We illustrate the connectivity of catalog sources in selected groups with zoom-in panels, where the panel sizes are indicated at lower left corners. Red dashed circles indicate cross-matched groups with spanning distances above 1″.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: Accuracy of the ranking function estimated using the training sample, averaged over standard tenfold cross-validation. We show the dependence of accuracy on transient redshift, transient-host angular offset, transient type, and host optical-NIR magnitudes in four separate panels. Except for the panel of transient type, we divide the sample into equal-sized bins over the axis of interest and plot the per-bin accuracy at the median value of each bin. Each curve shows the accuracy of a feature set. For clarity, the accuracy curves of redshift-dependent feature sets (with “_z” suffix) and redshift-independent feature sets are grouped into two separate subpanels. Some feature sets rely on certain source properties that are not always available for those known hosts. We estimate the accuracy using the subset of known hosts with the relevant features available and outline the fraction of true hosts with relevant parameters available in the bottom subpanels. Specifically, in the panel of transient redshift, we plot the accuracy of events without redshift in the gray shaded area, if applicable.
Paper: Linking Extragalactic Transients and Their Host Galaxy Properties: Transient Sample, Multiwavelength Host Identification, and Database Construction
Authors: Yu-Jing Qin, Ann Zabludoff, Marina Kisley, Yuantian Liu, Iair Arcavi, Kobus Barnard, Peter Behroozi, K. Decker French, Curtis McCully, and Nirav Merchant
Figure caption: The decision tree of visual inspection for transients with known and properly cross-matched hosts (Appendix J.1) and transients with newly identified hosts (Appendix J.2). For transients with known hosts, we assign “OK” or “Failed” based on the results of cross-matching. If there is clearly a better host than the reported one, we also flag the case and mark the “alternative host” in the image. If we cannot determine if the indicated host is successfully cross-matched and if any better host exists, we consider this an “Unclear” case and set flags for the detailed reasons. For events with new hosts, if the algorithm chose the unique best host in the images, we consider the case “OK.” If the algorithm chose one likely host while there are other equally possible hosts, we consider this a “Confusing” case. If the algorithm missed the best host in the radius, we consider the case a “Failed” one and then manually reassign the host if we can. However, if the best host is outside the radius, we group the case under “Other.” If no group has been cross-matched near the event, the case falls into “No Group.” Finally, similar to the case of known hosts, if we cannot determine the best host from the image, we consider the case “Unclear” with appropriate flags indicating the detailed reason.