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Paper: Oxygen Abundance Throughout the Dwarf Starburst Galaxy IC 10
Authors: Maren Cosens, Shelley A. Wright, Karin Sandstrom, Lee Armus, Norman Murray, Jordan N. Runco, Sanchit Sabhlok, James Wiley
Figure caption: Oxygen abundance and uncertainty determined via the direct method for individual H II regions in IC 10 where SNR[O III]4363 > 3 (a) and with the outlier region M16c left out of the comparison (b). The data point for each region is filled based on the star formation rate (SFR) determined in Paper I, with H II regions containing or adjacent to a W-R star outlined in cyan. The vertical axis is sorted by region ID. The assignment of these IDs is based on their location, so adjacent regions on this plot are near each other in IC 10. The mean and 1σ deviation of the distribution are shown by the solid and dashed vertical lines, respectively. As this distribution is not Gaussian, the IQR is shown by the gray shaded region. As can be seen by the spread of oxygen abundances and how many regions fall outside of the IQR, the ISM throughout IC 10 may not be well mixed overall, though regions within ∼100 pc of each other are. This is true even with the outlier M16c left out of the comparison, with 4/11 regions outside of the IQR.
Paper: Oxygen Abundance Throughout the Dwarf Starburst Galaxy IC 10
Authors: Maren Cosens, Shelley A. Wright, Karin Sandstrom, Lee Armus, Norman Murray, Jordan N. Runco, Sanchit Sabhlok, James Wiley
Figure caption: Comparison of the oxygen abundance determined for IC 10's H II regions from the direct (horizontal axis) and indirect methods (vertical axis) for regions with SNR[O III] 4363 > 3 in the integrated spectrum. The lower branches of the indirect methods are denoted by triangles pointed down and the upper branches by upward pointing triangles. The points corresponding to the KK04 calibration are colored in cyan, with the PT05 calibration corresponding to the yellow points. The filled black points are the medians for each calibration and branch. The dashed gray line indicates the one-to-one line. There is not a clear “best” strong line method calibration for which the indirect oxygen abundance matches the value or span of abundances from the direct method. The upper and lower branches bracket the values measured with the direct method regardless of the calibration used, and the span of values probed by each branch/calibration is less than that found with the direct method in all cases.
Paper: Oxygen Abundance Throughout the Dwarf Starburst Galaxy IC 10
Authors: Maren Cosens, Shelley A. Wright, Karin Sandstrom, Lee Armus, Norman Murray, Jordan N. Runco, Sanchit Sabhlok, James Wiley
Figure caption: Maps of the estimated oxygen abundance throughout our KCWI observations of IC 10 using the KK04 (left) and PT05 (right) strong line calibrations. Only spaxels with SNR[O II] > 3 are included. The outlines of the H II regions identified in Paper I are shown in light blue. The locations of spectroscopically confirmed W-R stars are shown with white Xs and unconfirmed with white +s. Potential chemical enrichment from these W-R stars is discussed in Section 4.3. These maps show the well-known systematic offset between the KK04 and PT05 calibrations as well as the differing results of the upper and lower branches of the same calibration. The upper branches show higher abundance outside of the H II regions while the opposite is seen with the lower branches. This illustrates the need for caution in the interpretation of these indirect abundance metrics when applied to the DIG where the physical conditions are likely to be different than in H II regions for which the calibrations were developed.
Paper: Oxygen Abundance Throughout the Dwarf Starburst Galaxy IC 10
Authors: Maren Cosens, Shelley A. Wright, Karin Sandstrom, Lee Armus, Norman Murray, Jordan N. Runco, Sanchit Sabhlok, James Wiley
Figure caption: Properties which show evidence of a possible correlation with the gas-phase oxygen abundance (﹩12+\mathrm{log}({\rm{O}}/{\rm{H}})﹩) when the outlier region M16c is removed. The region radius is shown in the top left, luminosity on the top right, velocity dispersion on the bottom left, and dynamical mass on the bottom right. The Spearman rank coefficients are included on the plots and provide an indication of how likely a correlation between the two parameters is. The strongest (still moderate) correlation is between oxygen abundance and dynamical mass—though the latter is dependent on r and σ as seen in Equation (9).
Paper: Oxygen Abundance Throughout the Dwarf Starburst Galaxy IC 10
Authors: Maren Cosens, Shelley A. Wright, Karin Sandstrom, Lee Armus, Norman Murray, Jordan N. Runco, Sanchit Sabhlok, James Wiley
Figure caption: [O II]/Hβ  ratio as a function of [O III] 5007 Å luminosity (left), 12 + log(O/H) determined via the direct method (center), and extinction measured from the Hγ/Hβ line ratio (right). Lower L [O III] and ﹩12+\mathrm{log}({\rm{O}}/{\rm{H}})﹩ are weakly correlated with increasing [O II]/Hβ, but higher extinction is quite strongly correlated with increasing [O II]/Hβ. Fewer H II regions are included in the center plot due to requirement that SNR[O III]4363 > 3.
Paper: Oxygen Abundance Throughout the Dwarf Starburst Galaxy IC 10
Authors: Maren Cosens, Shelley A. Wright, Karin Sandstrom, Lee Armus, Norman Murray, Jordan N. Runco, Sanchit Sabhlok, James Wiley
Figure caption: Histogram of direct metallicity for each H II region in IC 10 with SNR[O III] 4363 > 3. The H II regions associated with a known or newly detected candidate W-R star are shown in cyan while those without a nearby W-R star are shown by the black hatched region. There does not appear to be any clear correlation between H II regions associated with a W-R star and gas-phase oxygen abundance.
Paper: Oxygen Abundance Throughout the Dwarf Starburst Galaxy IC 10
Authors: Maren Cosens, Shelley A. Wright, Karin Sandstrom, Lee Armus, Norman Murray, Jordan N. Runco, Sanchit Sabhlok, James Wiley
Figure caption: Integrated spectra of each H II region with a signal-to-noise ratio (SNR) of SNR[O III] 4363 > 3, shown here after reddening correction, DIG subtraction, and continuum subtraction. The error spectra are shown by the gray shading while the emission line fits are shown with the dashed cyan line. All spectra are normalized to the [O III] 5007 Å line for ease of comparison. The insets show a zoom-in view of the fit to Hγ and [O III] 4363 Å to illustrate the clear detection of the faint auroral line.
Paper: Walking the Line: Young Stars on the Boundary of the Epsilon Cha and Lower Centaurus Crux Associations
Authors: Attila Varga, Joel H. Kastner, D. Annie Dickson-Vandervelde, Alex Binks
Figure caption: Eight sample VOSA SED fits from among the fits for our 54 new candidates. Observed photometry from Gaia DR3, 2MASS, and WISE is presented as blue points, where the horizontal bars indicate the passbands. The best-fit BT-SETTL models are shown in black, with red points indicating the synthetic model photometry used in the fitting process. The top row shows four stars with no measurable infrared excess; the bottom row shows a sample of four stars with significant infrared excess, as indicated by the light blue highlighted regions.
Paper: Walking the Line: Young Stars on the Boundary of the Epsilon Cha and Lower Centaurus Crux Associations
Authors: Attila Varga, Joel H. Kastner, D. Annie Dickson-Vandervelde, Alex Binks
Figure caption: Left: initial positional selection of our ECA candidates. Stars indicated in blue are those selected to lie within a 70° by 12° box centered on R.A. 180°, decl. −74°, and with parallaxes between 8.9 < π < 11. The positions of previously identified ECA members and candidates are indicated in green. Right: Proper motion candidate selection. Filtered stars, again indicated in blue, are those with PMs between R.A. (PMRA) −44 and −37 mas yr−1, and PMs in decl. (PMDEC) between −20 and +10 mas yr−1. Proper motions of previously identified ECA members and candidates are again indicated in green. In both panels, gray points indicate the background sample of stars from Gaia DR3 around and within our regions of interest.
Paper: Walking the Line: Young Stars on the Boundary of the Epsilon Cha and Lower Centaurus Crux Associations
Authors: Attila Varga, Joel H. Kastner, D. Annie Dickson-Vandervelde, Alex Binks
Figure caption: Left: complete sample of ∼1600 stars satisfying initial RA and DEC search criteria (gray points). Blue points are stars that satisfy selection criteria for proper motion and distance from the empirical isochrone. Red X’s are stars rejected on the basis of astrometric excess noise. Blue shading indicates the region used to select sample stars with ages close to the DV+21 5–8 Myr isochrone, shown as the blue curve. Middle: Comparison between the final sample meeting all candidate criteria (yellow star markers) and bona fide candidates from DV+21 in green. Right: same final sample now compared with stars from the LCC subgroup A0 from B. Goldman et al. (2018; teal diamonds).
Paper: Walking the Line: Young Stars on the Boundary of the Epsilon Cha and Lower Centaurus Crux Associations
Authors: Attila Varga, Joel H. Kastner, D. Annie Dickson-Vandervelde, Alex Binks
Figure caption: Heliocentric velocities shown in all three directions. The LCC subgroups from G+18 in different shades of blue, and bona fide ECA members (DV+21) in green. New candidates stars are in yellow. LCC A0 subgroup stars are in blue diamonds.
Paper: Walking the Line: Young Stars on the Boundary of the Epsilon Cha and Lower Centaurus Crux Associations
Authors: Attila Varga, Joel H. Kastner, D. Annie Dickson-Vandervelde, Alex Binks
Figure caption: Heliocentric positions of our sample as yellow stars, the LCC subgroups from G+18 in different shades of blue, and bona fide ECA members in green. Our sample shows new stars scattered around the ECA core as well as around the A0 subgroup. We also recovered existing ECA and A0 stars.
Paper: Walking the Line: Young Stars on the Boundary of the Epsilon Cha and Lower Centaurus Crux Associations
Authors: Attila Varga, Joel H. Kastner, D. Annie Dickson-Vandervelde, Alex Binks
Figure caption: Left: the sky position and tangential velocity vectors of the new ECA candidates (Section 2.1 and Table 1), LCC A0 subgroup, and previous ECA members. Right: the tangential velocity vectors of the the new ECA candidates, LCC A0 subgroup, and previous ECA members.
Paper: Walking the Line: Young Stars on the Boundary of the Epsilon Cha and Lower Centaurus Crux Associations
Authors: Attila Varga, Joel H. Kastner, D. Annie Dickson-Vandervelde, Alex Binks
Figure caption: HR diagram positions of our new ECA candidates (yellow stars) overlaid with BT-SETTL model isochrones for 5, 8, and 10 Myr (left) and SPOTS model isochrones, with a spot-filling factor of f = 0.34, for 5, 8, and 11 Myr (right).
Paper: Walking the Line: Young Stars on the Boundary of the Epsilon Cha and Lower Centaurus Crux Associations
Authors: Attila Varga, Joel H. Kastner, D. Annie Dickson-Vandervelde, Alex Binks
Figure caption: Age distribution for the new ECA candidates. Blue bars shows stellar ages obtained with the BT-SETTL model. Orange bars show ages obtained from the SPOTS model adopting a filling factor of f = 0.34.
Paper: Walking the Line: Young Stars on the Boundary of the Epsilon Cha and Lower Centaurus Crux Associations
Authors: Attila Varga, Joel H. Kastner, D. Annie Dickson-Vandervelde, Alex Binks
Figure caption: BT-SETTLE best-fit temperatures and derived spectral types (M. J. Pecaut & E. E. Mamajek 2013) for new sample candidates (yellow), LCC A0 members (teal) and ECA members (green).
Paper: Walking the Line: Young Stars on the Boundary of the Epsilon Cha and Lower Centaurus Crux Associations
Authors: Attila Varga, Joel H. Kastner, D. Annie Dickson-Vandervelde, Alex Binks
Figure caption: Infrared excesses, E(K  s  − W3) vs. E(K  s  − W4), for all new candidate stars; stars with the largest excesses are highlighted (with symbols as indicated in the legend). Background colors indicate IR-excess-based disk classifications as detailed in M. J. Pecaut & E. E. Mamajek (2016).
Paper: Walking the Line: Young Stars on the Boundary of the Epsilon Cha and Lower Centaurus Crux Associations
Authors: Attila Varga, Joel H. Kastner, D. Annie Dickson-Vandervelde, Alex Binks
Figure caption: Comparisons of age distributions of new ECA candidates (dark blue) with previously identified ECA members (green; top plot) and with LCC A0 stars (teal; bottom plot). All ages are derived using BT-SETTL model isochrones.
Paper: UVIT Study of the MAgellanic Clouds (U-SMAC). II. A Far-UV Catalog of the Small Magellanic Cloud: Morphology and Kinematics of Young Stellar Population
Authors: Sipra Hota, Annapurni Subramaniam, Prasanta K. Nayak, Smitha Subramanian
Figure caption: VPDs of four young populations. Distributions of PMRA and PMDec are shown at the top and right-hand side. Gaussian (sum) is shown in red for all panels, while Gaussian 1 and Gaussian 2 are shown in black and blue, respectively, in (a) and (d). Gray points represent the SMC FUV stars.
Paper: UVIT Study of the MAgellanic Clouds (U-SMAC). II. A Far-UV Catalog of the Small Magellanic Cloud: Morphology and Kinematics of Young Stellar Population
Authors: Sipra Hota, Annapurni Subramaniam, Prasanta K. Nayak, Smitha Subramanian
Figure caption: (a) FUV–optical CMD of the SMC sources. The main-sequence branch is shown within a red polygon. (b) Polygons on the optical CMD of the SMC sources representing different populations of the SMC (see right-hand panel of their Figure 2, Gaia Collaboration et al. et al. 2021a). The locations of Young 1, Young 2, Young 3, and BL stars on FUV–optical and IR CMDs are shown in panels (c), (d), (e), and (f), respectively. The error bars (median value) for FUV magnitude and FUV–optical color are shown in black for the FUV–optical CMDs. Gray points are the SMC FUV sources.
Paper: UVIT Study of the MAgellanic Clouds (U-SMAC). II. A Far-UV Catalog of the Small Magellanic Cloud: Morphology and Kinematics of Young Stellar Population
Authors: Sipra Hota, Annapurni Subramaniam, Prasanta K. Nayak, Smitha Subramanian
Figure caption: Surface density distribution (KDE; kernel width = 0.1 deg) of the SMC. The color bar represents the density in the unit of deg−2. The black ellipse and circle represent the inner SMC Wing and shell-like structure, respectively.
Paper: UVIT Study of the MAgellanic Clouds (U-SMAC). II. A Far-UV Catalog of the Small Magellanic Cloud: Morphology and Kinematics of Young Stellar Population
Authors: Sipra Hota, Annapurni Subramaniam, Prasanta K. Nayak, Smitha Subramanian
Figure caption: Spatial distribution of PMRA of four young populations.
Paper: UVIT Study of the MAgellanic Clouds (U-SMAC). II. A Far-UV Catalog of the Small Magellanic Cloud: Morphology and Kinematics of Young Stellar Population
Authors: Sipra Hota, Annapurni Subramaniam, Prasanta K. Nayak, Smitha Subramanian
Figure caption: Panels (a) and (b) represent the spatial distribution of probable FUV stars of the SMC and the MW obtained from different methods under two distinct conditions: without RUWE constraints and with a RUWE < 1.4, respectively.
Paper: UVIT Study of the MAgellanic Clouds (U-SMAC). II. A Far-UV Catalog of the Small Magellanic Cloud: Morphology and Kinematics of Young Stellar Population
Authors: Sipra Hota, Annapurni Subramaniam, Prasanta K. Nayak, Smitha Subramanian
Figure caption: PM distribution of the four young populations. Gaussian 1 (G1), Gaussian 2 (G2), and their sum (G1 + G2) curves are shown in blue, magenta, and red, respectively.
Paper: UVIT Study of the MAgellanic Clouds (U-SMAC). II. A Far-UV Catalog of the Small Magellanic Cloud: Morphology and Kinematics of Young Stellar Population
Authors: Sipra Hota, Annapurni Subramaniam, Prasanta K. Nayak, Smitha Subramanian
Figure caption: VPDs of four dense and inner Wing regions of Young 1 and BL stars. Distributions of PMRA and PMDec are shown at the top and right-hand side, respectively.
Paper: UVIT Study of the MAgellanic Clouds (U-SMAC). II. A Far-UV Catalog of the Small Magellanic Cloud: Morphology and Kinematics of Young Stellar Population
Authors: Sipra Hota, Annapurni Subramaniam, Prasanta K. Nayak, Smitha Subramanian
Figure caption: (a) The FUV magnitude distribution and (b) completeness in percentage for seven UVIT observed SMC fields with different exposure times. The black-dotted line represents 90% of completeness.
Paper: UVIT Study of the MAgellanic Clouds (U-SMAC). II. A Far-UV Catalog of the Small Magellanic Cloud: Morphology and Kinematics of Young Stellar Population
Authors: Sipra Hota, Annapurni Subramaniam, Prasanta K. Nayak, Smitha Subramanian
Figure caption: Surface density distribution (KDE; kernel width = 0.1 deg) of Young 1, Young 2, Young 3, and BL populations in (a), (b), (c), and (d), respectively. The color bar represents the density in units of deg−2. Dashed polygons mark four distinct dense regions named east, NE, center, and SW. The labeling in panel (a) is consistent across all panels.
Paper: Correcting Turbulence-induced Errors in Fiber Positioning for the Dark Energy Spectroscopic Instrument
Authors: E. F. Schlafly, J. Guy, K. Honscheid, S. Kent, S. E. Koposov, J. Aguilar, S. Ahlen, S. Bailey, D. Brooks, T. Claybaugh, K. Dawson, P. Doel, K. Fanning, D. P. Finkbeiner, A. Font-Ribera, J. E. Forero-Romero, S. Gontcho A Gontcho, G. Gutierrez, D. Kirkby, T. Kisner, A. Kremin, M. Landriau, J. Lasker, L. Le Guillou, M. E. Levi, A. de la Macorra, P. Martini, A. Meisner, R. Miquel, J. Moustakas, G. Niz, F. Prada, G. Rossi, E. Sanchez, M. Schubnell, R. Sharples, D. Sprayberry, G. Tarlé, B. A. Weaver, H. Zou
Figure caption: An example of turbulence-induced variations in the measured positions of fibers as seen by the Fiber-View Camera (FVC) in DESI. Arrows point from the average position over a long series of exposures to the measured position in a particular exposure. The rms variation ﹩\sigma =\sqrt{\langle {x}^{2}+{y}^{2}\rangle }﹩ of 7.7 μm is given in the upper right-hand corner, and an arrow of length 10 μm is shown for comparison in the upper left-hand corner. Red circles show the locations of stationary points which we will use to correct turbulence.
Paper: Correcting Turbulence-induced Errors in Fiber Positioning for the Dark Energy Spectroscopic Instrument
Authors: E. F. Schlafly, J. Guy, K. Honscheid, S. Kent, S. E. Koposov, J. Aguilar, S. Ahlen, S. Bailey, D. Brooks, T. Claybaugh, K. Dawson, P. Doel, K. Fanning, D. P. Finkbeiner, A. Font-Ribera, J. E. Forero-Romero, S. Gontcho A Gontcho, G. Gutierrez, D. Kirkby, T. Kisner, A. Kremin, M. Landriau, J. Lasker, L. Le Guillou, M. E. Levi, A. de la Macorra, P. Martini, A. Meisner, R. Miquel, J. Moustakas, G. Niz, F. Prada, G. Rossi, E. Sanchez, M. Schubnell, R. Sharples, D. Sprayberry, G. Tarlé, B. A. Weaver, H. Zou
Figure caption: Fiber positioning performance for DESI. The blue, orange, and green regions show the range between the 16th and 84th percentiles for DESI positioning accuracy over roughly 10,000 DESI positioning sequences. Darks, biases, and other exposures that do not involve a positioning loop are not used. Absent any correction, the blue region shows that we would obtain typical precision of 7.3 μm. We, however, fit for the turbulence in each image (orange), which contributes most of the variance. The final positioning errors after correction for turbulence (green) have typical values of 3.5 μm. Dashed horizontal lines show the median rms positioning error over all of the exposures.
Paper: Correcting Turbulence-induced Errors in Fiber Positioning for the Dark Energy Spectroscopic Instrument
Authors: E. F. Schlafly, J. Guy, K. Honscheid, S. Kent, S. E. Koposov, J. Aguilar, S. Ahlen, S. Bailey, D. Brooks, T. Claybaugh, K. Dawson, P. Doel, K. Fanning, D. P. Finkbeiner, A. Font-Ribera, J. E. Forero-Romero, S. Gontcho A Gontcho, G. Gutierrez, D. Kirkby, T. Kisner, A. Kremin, M. Landriau, J. Lasker, L. Le Guillou, M. E. Levi, A. de la Macorra, P. Martini, A. Meisner, R. Miquel, J. Moustakas, G. Niz, F. Prada, G. Rossi, E. Sanchez, M. Schubnell, R. Sharples, D. Sprayberry, G. Tarlé, B. A. Weaver, H. Zou
Figure caption: The correlation between positioning offsets along the direction of separation (Ψ∥, longitudinal) and perpendicular to it (Ψ⊥, transverse). The quantity ﹩\tfrac{d}{{dr}}(r{{\rm{\Psi }}}_{\perp })﹩ is shown by a dashed line and should match Ψ∥ if the turbulence is sourced by a scalar field. There is good agreement at small separations though the agreement becomes worse at large separations; see text for discussion. The shaded regions correspond to the 16th–84th percentile of the correlation function at each separation over the 400 images considered, while the solid lines give the average.
Paper: Correcting Turbulence-induced Errors in Fiber Positioning for the Dark Energy Spectroscopic Instrument
Authors: E. F. Schlafly, J. Guy, K. Honscheid, S. Kent, S. E. Koposov, J. Aguilar, S. Ahlen, S. Bailey, D. Brooks, T. Claybaugh, K. Dawson, P. Doel, K. Fanning, D. P. Finkbeiner, A. Font-Ribera, J. E. Forero-Romero, S. Gontcho A Gontcho, G. Gutierrez, D. Kirkby, T. Kisner, A. Kremin, M. Landriau, J. Lasker, L. Le Guillou, M. E. Levi, A. de la Macorra, P. Martini, A. Meisner, R. Miquel, J. Moustakas, G. Niz, F. Prada, G. Rossi, E. Sanchez, M. Schubnell, R. Sharples, D. Sprayberry, G. Tarlé, B. A. Weaver, H. Zou
Figure caption: The positioning accuracy as a function of the number of positioners used to measure the turbulence for a variety of different turbulence correction schemes. Even when only 30 positioners are available to probe the turbulence, turbulence-induced errors can be reduced by half for DESI, even with a simple correction scheme. Using a Gaussian process and taking advantage of the curl-free nature of the turbulence field provides the best performance (gradwavefront), though when a large number of turbulence probes are available (e.g., for DESI) the improvement with respect to the independent scheme is negligible.
Paper: Correcting Turbulence-induced Errors in Fiber Positioning for the Dark Energy Spectroscopic Instrument
Authors: E. F. Schlafly, J. Guy, K. Honscheid, S. Kent, S. E. Koposov, J. Aguilar, S. Ahlen, S. Bailey, D. Brooks, T. Claybaugh, K. Dawson, P. Doel, K. Fanning, D. P. Finkbeiner, A. Font-Ribera, J. E. Forero-Romero, S. Gontcho A Gontcho, G. Gutierrez, D. Kirkby, T. Kisner, A. Kremin, M. Landriau, J. Lasker, L. Le Guillou, M. E. Levi, A. de la Macorra, P. Martini, A. Meisner, R. Miquel, J. Moustakas, G. Niz, F. Prada, G. Rossi, E. Sanchez, M. Schubnell, R. Sharples, D. Sprayberry, G. Tarlé, B. A. Weaver, H. Zou
Figure caption: Three examples of turbulence. Each column corresponds to a different exposure and therefore realization of the turbulence-induced position offsets. The top row shows the measurements; the middle row shows the turbulence derived using the DESI turbulence algorithm; and the bottom row shows the residuals. The turbulence modeling explains most of the variation and is able to reduce the residuals to roughly 2 μm. The rms displacement is given in the upper right-hand corner of each panel, and a 10 μm scale bar is shown in the upper left-hand corner.
Paper: The MDW Hα Sky Survey: Data Release 0
Authors: Noor Aftab, Xunhe (Andrew) Zhang, David R. Mittelman, Dennis di Cicco, Sean Walker, David H. Sliski, Julia Homa, Colin Holm-Hansen, Mary Putman, David Schiminovich, Arne Henden, Gary Walker
Figure caption: Above: a 2D histogram for (MDWHα  − Pan − STARRS1 r ), using the entire DR0 catalog. Below: a similar histogram of all (MDWHα  − IGAPSHα ) values for the subset of the DR0 catalog with matched IGAPS sources. In both figures, we see DR0 sources with slightly lower magnitudes near the field middles (a difference of ∼−0.25). We also notice a tendency for our DR0 sources in the field corners to have lower magnitudes than Pan-STARRS1 (differences up to ∼−2). We suspect these offsets are related to the patterns of larger separation distances in catalog matching, which could imply mismatches, as discussed in Figure 6.