adsabs/AstroCLIMB huggingface dataset:
Paper: The Power of High-precision Broadband Photometry: Tracing the Milky Way Density Profile with Blue Horizontal Branch Stars in the Dark Energy Survey
Authors: Fengqing Yu, 枫青 余, Ting S. Li, Joshua S. Speagle, 佳士 沈, Gustavo E. Medina, Sergey E. Koposov, Joss Bland-Hawthorn, Lara R. Cullinane, Gwendolyn M. Eadie, Denis Erkal, Geraint F. Lewis, Guilherme Limberg, Daniel B. Zucker
Figure caption: Same as Figure 3, but now highlighting the predicted BHB probability p BHB for individual stars as a function of g 0 magnitude. The model easily classifies BHBs at brighter magnitudes (g 0 < 19). The two sequences start to overlap at 19 < g 0 < 20. At the faintest magnitudes, the changing relative fraction of BHBs vs. BSs, in addition to larger photometric uncertainties, leads to a more ambiguous classification.
Paper: The Power of High-precision Broadband Photometry: Tracing the Milky Way Density Profile with Blue Horizontal Branch Stars in the Dark Energy Survey
Authors: Fengqing Yu, 枫青 余, Ting S. Li, Joshua S. Speagle, 佳士 沈, Gustavo E. Medina, Sergey E. Koposov, Joss Bland-Hawthorn, Lara R. Cullinane, Gwendolyn M. Eadie, Denis Erkal, Geraint F. Lewis, Guilherme Limberg, Daniel B. Zucker
Figure caption: A corner plot showing the marginal posterior probability distributions of the two parameters of our density profile estimated with dynesty. We see that the power-law index α and normalization coefficient A are well constrained, and they are correctly positively correlated since the total stellar count is constant.
Paper: Contour Analysis Tool: An Interactive Tool for Background and Morphology Analysis
Authors: Mark A. Hutchison, Christine M. Koepferl
Figure caption: Test of the background removal algorithm on a modified dipole function (Equation (1); top panels) and a synthetic map of a star-forming region (bottom panels). The panels on the left show the original, unperturbed images for each case. In the middle panels, images are perturbed from their original state with a known sinusoidal and/or linear gradient (see Equations (1) and (2)). The panels on the right show the result after applying the background removal to the perturbed images in an attempt to recover the original images on the left. While the algorithm effectively restores the morphology of high-density regions, many low-density features tend to be lost.
Paper: SDSS J0018-0939: A Clear Signature of Sub-Chandrasekhar Mass Type 1a Supernova
Authors: S. K. Jeena, Projjwal Banerjee
Figure caption: Same as Figure 2, but for stars COS 171, BD+80245, HE 0533-5340, and SMSS J034249-284216. The observational data adapted from A. McWilliam et al. (2018) for COS 171 and H. Reggiani et al. (2023) for BD+80245, HE 0533-5340, and SMSS J034249-284216.
Paper: SDSS J0018-0939: A Clear Signature of Sub-Chandrasekhar Mass Type 1a Supernova
Authors: S. K. Jeena, Projjwal Banerjee
Figure caption: Top: The observed elemental abundance pattern of SDSS J0018-0939 from W. Aoki et al. (2014) compared with the best-fit models from various scenarios: PISN (magenta dotted line), CCSN (black dashed line), 2CCSNe (cyan dashed line), CCSN+near-M Ch (red dashed–dotted line), CCSN+sub-M Ch (blue dashed–dotted line), and CCSN+PISN (green dashed line). Bottom: the fraction η for all elements produced by near-M Ch in CCSN+near-M Ch scenario (red), sub-M Ch in CCSN+sub-M Ch scenario (blue), and PISN in CCSN+PISN scenario (green).
Paper: Contour Analysis Tool: An Interactive Tool for Background and Morphology Analysis
Authors: Mark A. Hutchison, Christine M. Koepferl
Figure caption: Top: illustration of the effects of image processing on the four contours calculated by the code: unprocessed (left), smoothing (middle), and background removal (right). Bottom: normalized N-PDF for each panel in the top row, with vertical lines indicating the location of their respective LCCs. Smoothing primarily affects high-density signals while background removal affects low-density signals.
Paper: SDSS J0018-0939: A Clear Signature of Sub-Chandrasekhar Mass Type 1a Supernova
Authors: S. K. Jeena, Projjwal Banerjee
Figure caption: Theoretical elemental pattern relative to Fe from various sources. (a) PISN models of varying He core masses. (b) CCSN ejecta for  z  models of 10.1–30 M ⊙ without mixing and fallback, and have values of [Mg/Fe] ≲ 0.0. (c) SN 1a models, where the black solid line corresponds to a typical near-M Ch model, and the dotted and dashed–dotted lines represent sub-M Ch models with varied core and shell masses.
Paper: Contour Analysis Tool: An Interactive Tool for Background and Morphology Analysis
Authors: Mark A. Hutchison, Christine M. Koepferl
Figure caption: Example of how double masking can be used to disentangle individual cloud contributions to the N-PDF of a large cloud system. Left: region selected by the first Otsu contour mask. The colored lines collectively represent the LCC within this masked region, but are color-coded by cloud group to identify regions manually selected using the second mask. Right: N-PDF for the combined region as well as for the individual clouds. The slope of the combined N-PDF appears linear despite the individual contributions being slightly stepped.
Paper: Contour Analysis Tool: An Interactive Tool for Background and Morphology Analysis
Authors: Mark A. Hutchison, Christine M. Koepferl
Figure caption: Illustration of an intersecting contour that remains undetected due to the mask edge thickness being equivalent to a single cell width. Intersection detection involves mapping contour vertices to nearby grid points and identifying overlapping mask edges. A mask edge spanning two cells prevents diagonal gaps from forming, effectively mitigating false positives.
Paper: SDSS J0018-0939: A Clear Signature of Sub-Chandrasekhar Mass Type 1a Supernova
Authors: S. K. Jeena, Projjwal Banerjee
Figure caption: Same as Figure 3, but Al is neglected.
Paper: Full Stokes-vector Inversion of the Solar Mg II h and k Lines
Authors: Hao Li, Tanausú del Pino Alemán, Javier Trujillo Bueno
Figure caption: Same as Figure 6, but for a region in the quiet Sun with μ = 0.101 (see Figure 1).
Paper: Full Stokes-vector Inversion of the Solar Mg II h and k Lines
Authors: Hao Li, Tanausú del Pino Alemán, Javier Trujillo Bueno
Figure caption: Same as Figure 6, but for a region in the quiet Sun with μ = 0.563 (see Figure 1).
Paper: Learning the Universe: GalactISM Simulations of Resolved Star Formation and Galactic Outflows across Main-sequence and Quenched Galactic Environments
Authors: Sarah M. R. Jeffreson, Eve C. Ostriker, Chang-Goo Kim, Jindra Gensior, Greg L. Bryan, Timothy A. Davis, Lars Hernquist, Sultan Hassan
Figure caption: SFR surface density ΣSFR as a function of the total midplane pressure P tot (left) and as a function of the ISM weight ﹩{ \mathcal W }﹩ (right; see Section 5.2). Black dotted lines represent constant ratios of ΣSFR/P tot = 102, 103, and 104 km s−1. Only the cool–warm gas (T < 2 × 104 K) that is gravitationally unbound (α vir > 2) is included in the calculation. Filled data points represent median values over time for each simulated galaxy, measured within overlapping radial annuli of width 500 pc. For visual clarity, the corresponding interquartile ranges are shown at just one representative radius in each galaxy. The thick black line represents the best linear regression fit to these data points, excluding the dynamically suppressed galaxy (pink). The thick dashed line represents the corresponding best fit from the TIGRESS simulations (E. C. Ostriker & C.-G. Kim 2022). The gray contours represent the 40%–80%–95% levels of the observed galaxy sample from J. Sun et al. (2023), and the gray crosses represent average values across the gas disks of the ATLAS3D galaxy sample from T. A. Davis et al. (2014), also shown in Figure 2. We note that J. Sun et al. (2023) strictly measure ﹩{ \mathcal W }﹩ to obtain P tot, but we include these data in the left panel for readability.
Paper: Learning the Universe: GalactISM Simulations of Resolved Star Formation and Galactic Outflows across Main-sequence and Quenched Galactic Environments
Authors: Sarah M. R. Jeffreson, Eve C. Ostriker, Chang-Goo Kim, Jindra Gensior, Greg L. Bryan, Timothy A. Davis, Lars Hernquist, Sultan Hassan
Figure caption: Total midplane pressure P tot as a function of the midplane gas volume density n H and the epicyclic frequency κ for the cold+warm gas (T < 2 × 104 K) in our simulations, viewed in three different planes. The left panel shows the usual EOS (P tot vs. n H) for our simulated galaxies. The best-fit line to the Milky Way and NGC 300 (star-forming main-sequence) galaxy simulations is given by the solid black line, and the best fit to the TIGRESS simulations is indicated by the thick dashed line. Three isotherms of constant T = P tot/n H k B are given by gray dotted lines. Filled data points represent median values over time and azimuthal angle for each simulated galaxy, measured within overlapping radial annuli of width 500 pc. The gray transparent plane shows the best fit to all data, excluding the dynamically suppressed galaxy (pink).
Paper: Learning the Universe: GalactISM Simulations of Resolved Star Formation and Galactic Outflows across Main-sequence and Quenched Galactic Environments
Authors: Sarah M. R. Jeffreson, Eve C. Ostriker, Chang-Goo Kim, Jindra Gensior, Greg L. Bryan, Timothy A. Davis, Lars Hernquist, Sultan Hassan
Figure caption: Top row: the ISM weight ﹩{ \mathcal W }﹩ due to each component of the gravitational potential, as a function of the galactocentric radius, at the final analyzed time of each simulation. Middle row: comparison of the total midplane pressure (solid lines) and the total ISM weight (dashed lines), along with median values of the thermal midplane pressure (thin lines) as a function of galactocentric radius. Only the cool–warm gas (T < 2 × 104 K) that is gravitationally unbound (α vir > 2) is included in the calculation of the pressures and SFRs. Bottom row: comparison of the true SFR surface density ΣSFR (dotted lines) and the SFR surface density predicted by Equation (6). The bottom two rows are median values over time and azimuthal angle, and all shaded areas are the corresponding interquartile ranges.
Paper: Learning the Universe: GalactISM Simulations of Resolved Star Formation and Galactic Outflows across Main-sequence and Quenched Galactic Environments
Authors: Sarah M. R. Jeffreson, Eve C. Ostriker, Chang-Goo Kim, Jindra Gensior, Greg L. Bryan, Timothy A. Davis, Lars Hernquist, Sultan Hassan
Figure caption: SFR surface density ΣSFR as a function of the cold gas surface density ﹩{{\rm{\Sigma }}}_{\mathrm{HI}+{{\rm{H}}}_{2}}﹩ (left) and as a function of the molecular gas surface density ﹩{{\rm{\Sigma }}}_{{{\rm{H}}}_{2}}﹩ (right). Solid, dashed, and dotted lines represent depletion times of 108, 109, and 1010 Gyr, respectively. Filled data points represent median values over time for each simulated galaxy, measured within overlapping radial annuli of width 500 pc. For visual clarity, the corresponding interquartile ranges are shown at just one representative radius in each galaxy. The solid black line and shaded region represent the median and interquartile range of the SFR predicted by the model of V. Springel & L. Hernquist (2003). The model is applied to all of our high-resolution snapshots at once, where each snapshot is degraded to a 3D resolution of 80 pc—equal to the softening length used in TNG-50 (see Section 5.1). The blue and gray contours represent the 40%–80%–95% levels of the observed galaxy samples from F. Bigiel et al. (2008) and J. Sun et al. (2023), respectively, which assume a constant CO-to-H2 conversion factor.
Paper: Learning the Universe: GalactISM Simulations of Resolved Star Formation and Galactic Outflows across Main-sequence and Quenched Galactic Environments
Authors: Sarah M. R. Jeffreson, Eve C. Ostriker, Chang-Goo Kim, Jindra Gensior, Greg L. Bryan, Timothy A. Davis, Lars Hernquist, Sultan Hassan
Figure caption: Total midplane gas pressure P tot as a function of the ISM weight ﹩{ \mathcal W }﹩ for our six simulated galaxies. The dashed line represents the 1–1 relationship expected in dynamical equilibrium. Filled data points represent median values over time for each simulated galaxy, measured within overlapping radial annuli of width 500 pc. The Milky Way–like galaxy is represented by gray data points, the NGC 300–like galaxy by green data points, and the ETGs by the purple, pink, and orange data points. For visual clarity, the corresponding interquartile ranges are shown at just one representative radius in each galaxy.
Paper: The Interplay between the Disk and Corona of the Changing-look Active Galactic Nucleus 1ES 1927+654
Authors: Ruancun Li, Claudio Ricci, Luis C. Ho, Benny Trakhtenbrot, Erin Kara, Megan Masterson, Iair Arcavi
Figure caption: Comparison of the dimensionless mass accretion rate (﹩\dot{m}﹩) derived from the analysis of the final SED model (x-axis, Section 3.2.4) and the warm corona model (y-axis, Section 3.2.3). The black dashed line shows the 1:1 relation. The median difference (﹩{\rm{\Delta }}\mathrm{log}\dot{m}﹩) and standard deviation are given in the top-left corner.
Paper: Characteristics and Source Regions of Slow Alfvénic Solar Wind Observed by Parker Solar Probe
Authors: Tamar Ervin, Kai Jaffarove, Samuel T. Badman, Jia Huang, Yeimy J. Rivera, Stuart D. Bale
Figure caption: Box-plot overviews of compositional parameters for the 10 SASW and 5 FSW streams we modeled. The dashed vertical lines indicate the mean for the distribution with the corresponding color and the solid line shows the median. Panel (a): scaled proton density from SWEAP/SPAN-I. The dashed black line indicates typical 1 au solar-wind densities. Panel (b): proton mass flux (n 0 v 0 = (B 0/B  r )N  P  v  P ) calculated from in-situ observations and the photospheric footpoint field strength from modeling results. Panel (c): alpha abundance ratio (A He) using alpha and proton measurements from SWEAP/SPAN-I. Panel (d): normalized differential streaming speed (Δv  α p  /v A).
Paper: Characteristics and Source Regions of Slow Alfvénic Solar Wind Observed by Parker Solar Probe
Authors: Tamar Ervin, Kai Jaffarove, Samuel T. Badman, Jia Huang, Yeimy J. Rivera, Stuart D. Bale
Figure caption: Overview of parameters determined from PFSS modeling and the associated estimated footpoints for the FSW, SASW, and the CH-like and non-CH SASW subcategories. The box plot shows the inner quartile range (25%–75%) percentile and the solid line shows the median value. The dashed vertical lines show the mean of each parameter for the type of wind stream. Panels (a), (b), and (c) show the photospheric footpoint field strength (B 0), intensity at the footpoint from AIA 193 Å images, and expansion factor based on Equation (3) respectively.
Paper: Characteristics and Source Regions of Slow Alfvénic Solar Wind Observed by Parker Solar Probe
Authors: Tamar Ervin, Kai Jaffarove, Samuel T. Badman, Jia Huang, Yeimy J. Rivera, Stuart D. Bale
Figure caption: Overview of solar-wind velocity observations from the Wind 3DP instrument from 2004 to 2024. Panel (a): timeseries of solar-wind velocity from Wind at 1 au during the time period of this study. Panel (b): distribution of velocity measurements from 2004 to 2024 from Wind. Panel (c): distribution of velocity measurements during Solar Cycle 24 (2008 January–2019 December). Panel (d): distribution of velocity measurements from 2020 to 2023, covering the time period in this study. In panels (b)–(d), the dashed red and blue lines indicate the 500 km s−1 and 400 km s−1 speed cutoffs respectively. The legend shows the percentage of observations that fall above that threshold for each period.
Paper: Characteristics and Source Regions of Slow Alfvénic Solar Wind Observed by Parker Solar Probe
Authors: Tamar Ervin, Kai Jaffarove, Samuel T. Badman, Jia Huang, Yeimy J. Rivera, Stuart D. Bale
Figure caption: All usable E4–E14 data (see Section 3.1) is compiled into these normalized histograms of alpha-particle density (N  α ) against proton density (N  p ), each scaled by R 2. Particle measurements from the SPAN-I instrument aboard Parker/SWEAP show the alpha-to-proton abundance ratios. The dashed lines indicate the typical “high helium abundance” threshold of 0.045 and the “low abundance” boundary of 0.015 (J. C. Kasper et al. 2007, 2012). Panels (a), (b), and (c) plot the designated data for SSW, SASW, and FSW respectively.
Paper: Characteristics and Source Regions of Slow Alfvénic Solar Wind Observed by Parker Solar Probe
Authors: Tamar Ervin, Kai Jaffarove, Samuel T. Badman, Jia Huang, Yeimy J. Rivera, Stuart D. Bale
Figure caption: Normalized histograms comparing intensity values from many AIA images with intensity values sampled at the footpoints of the 10 identified and modeled SASW streams. The AIA images chosen are images at a 24 hr cadence for two weeks around each observation.
Paper: Characteristics and Source Regions of Slow Alfvénic Solar Wind Observed by Parker Solar Probe
Authors: Tamar Ervin, Kai Jaffarove, Samuel T. Badman, Jia Huang, Yeimy J. Rivera, Stuart D. Bale
Figure caption: Comparison of in-situ characteristics and footpoint estimates for the SASW stream spanning from 2020 September 27 12:00:00 to 2020 September 27 16:00:00 during E6.
Paper: Characteristics and Source Regions of Slow Alfvénic Solar Wind Observed by Parker Solar Probe
Authors: Tamar Ervin, Kai Jaffarove, Samuel T. Badman, Jia Huang, Yeimy J. Rivera, Stuart D. Bale
Figure caption: Comparison of in-situ characteristics and footpoint estimates for the SASW stream spanning from 2020 January 28 18:00:00 to 2020 January 29 01:00:00 during E4.
Paper: Characteristics and Source Regions of Slow Alfvénic Solar Wind Observed by Parker Solar Probe
Authors: Tamar Ervin, Kai Jaffarove, Samuel T. Badman, Jia Huang, Yeimy J. Rivera, Stuart D. Bale
Figure caption: Comparison of in-situ characteristics and footpoint estimates for the SASW stream spanning from 2020 June 6 06:00:00 to 2020 June 6 09:00:00 during E5.
Paper: Characteristics and Source Regions of Slow Alfvénic Solar Wind Observed by Parker Solar Probe
Authors: Tamar Ervin, Kai Jaffarove, Samuel T. Badman, Jia Huang, Yeimy J. Rivera, Stuart D. Bale
Figure caption: Comparison of in-situ characteristics and footpoint estimates for the SASW stream spanning from 2020 June 9 10:00:00 to 2020 June 9 22:00:00 during E5.
Paper: Poynting Flux of MHD Modes in Magnetic Solar Vortex Tubes
Authors: Samuel J. Skirvin, Viktor Fedun, Marcel Goossens, Suzana S. A. Silva, Gary Verth
Figure caption: Spatial profiles of the vertical component of the Poynting flux S  z  for the kink mode with m = 1 in a rotating magnetic flux tube at the same snapshot in time (t = 177 in arbitrary units). The background rotational flow profile is given by v 0,φ  = 0.1r such that the maximum amplitude of the rotational flow is 0.1. We display S  z  for varying amplitude ratios in the following range: (a) ﹩{v}_{0,\varphi }=100\hat{f}﹩, (b) ﹩{v}_{0,\varphi }=20\hat{f}﹩, (c) ﹩{v}_{0,\varphi }=10\hat{f}﹩, (d) ﹩{v}_{0,\varphi }=5\hat{f}﹩, (e) ﹩{v}_{0,\varphi }=2\hat{f}﹩, and (f) ﹩{v}_{0,\varphi }=\hat{f}﹩, where ﹩\hat{f}﹩ denotes the strength of the perturbation. The velocity vectors (background flow plus the perturbation) are scaled respectively for visualization purposes. The boundary of the flux tube is represented by the solid blue line, whereas the equilibrium location of the boundary is shown with the dashed red line.
Paper: Poynting Flux of MHD Modes in Magnetic Solar Vortex Tubes
Authors: Samuel J. Skirvin, Viktor Fedun, Marcel Goossens, Suzana S. A. Silva, Gary Verth
Figure caption: Spatial structure of the eigenfunctions (P  T , v  r , B  r , v  φ , and B  φ ) for the slow body kink mode (m = 1) normalized to 0.01 at r = a with k = 1.76 and ω = 1.69. The boundary of the magnetic flux tube with a background rotational flow is denoted by the dashed red line at r = 1.
Paper: Poynting Flux of MHD Modes in Magnetic Solar Vortex Tubes
Authors: Samuel J. Skirvin, Viktor Fedun, Marcel Goossens, Suzana S. A. Silva, Gary Verth
Figure caption: The vertical component of the Poynting flux S  z  for the slow body sausage mode in the presence of background rotational flow at a specific snapshot in time (t = 177 in arbitrary units). Panel (a) shows the case with amplitude ratio ﹩{v}_{0,\varphi }=20\hat{f}﹩, where ﹩\hat{f}﹩ denotes the strength of the perturbation, whereas panel (b) highlights the case with amplitude ratio ﹩{v}_{0,\varphi }=2\hat{f}﹩. The arrows denote the total velocity vector (background plus perturbation) and are scaled with the background flow amplitude, respectively. The boundary of the flux tube is represented by the solid blue line, whereas the equilibrium location of the boundary is shown with the dashed red line.
Paper: Poynting Flux of MHD Modes in Magnetic Solar Vortex Tubes
Authors: Samuel J. Skirvin, Viktor Fedun, Marcel Goossens, Suzana S. A. Silva, Gary Verth
Figure caption: Maximum value of S  z  computed using Equation (42) for (a) the sausage mode m = 0, (b) the kink mode m = 1, and (c) fluting mode m = 2 both with (black crosses) and without (blue crosses) the presence of a background rotational flow.
Paper: Poynting Flux of MHD Modes in Magnetic Solar Vortex Tubes
Authors: Samuel J. Skirvin, Viktor Fedun, Marcel Goossens, Suzana S. A. Silva, Gary Verth
Figure caption: Same as Figure 4 but for the linear superposition of the kink modes m = 1 and m = −1. Here, we assume that both modes have equal strength as one another.
Paper: Poynting Flux of MHD Modes in Magnetic Solar Vortex Tubes
Authors: Samuel J. Skirvin, Viktor Fedun, Marcel Goossens, Suzana S. A. Silva, Gary Verth
Figure caption: Same as Figure 4, but for the linear superposition of the modes m = 2 and m = −2. Here, we assume that both modes have equal strength as one another.
Paper: Poynting Flux of MHD Modes in Magnetic Solar Vortex Tubes
Authors: Samuel J. Skirvin, Viktor Fedun, Marcel Goossens, Suzana S. A. Silva, Gary Verth
Figure caption: Same as Figure 4 but for the m = −1 kink mode.
Paper: Poynting Flux of MHD Modes in Magnetic Solar Vortex Tubes
Authors: Samuel J. Skirvin, Viktor Fedun, Marcel Goossens, Suzana S. A. Silva, Gary Verth
Figure caption: Same as Figure 4, but for the m = −2 fluting mode.
Paper: Poynting Flux of MHD Modes in Magnetic Solar Vortex Tubes
Authors: Samuel J. Skirvin, Viktor Fedun, Marcel Goossens, Suzana S. A. Silva, Gary Verth
Figure caption: Same as Figure 4, but for the m = 2 fluting mode.
Paper: Cross-correlating Dark Sirens and Galaxies: Constraints on H 0 from GWTC-3 of LIGO–Virgo–KAGRA
Authors: Suvodip Mukherjee, Alex Krolewski, Benjamin D. Wandelt, Joseph Silk
Figure caption: Measurements of Hubble constant H 0 from GWTC-3 dark sirens, bright siren GW170817, and the combination of the two are shown along with the mean and the standard deviation on the measurements from Planck-2018 (Planck Collaboration et al. 2020) and SH0ES (A. G. Riess et al. 2022).
Paper: Cross-correlating Dark Sirens and Galaxies: Constraints on H 0 from GWTC-3 of LIGO–Virgo–KAGRA
Authors: Suvodip Mukherjee, Alex Krolewski, Benjamin D. Wandelt, Joseph Silk
Figure caption: Galaxy autocorrelations in different photometric redshift bins, with the default measurement (deprojecting Gaia stellar template and Schlegel–Finkbeiner–Davis dust map) in solid red, and measurement with no deprojection in dashed red. The model is shown in blue: the total model is in solid blue, which for WSC is the sum of the SuperCOSMOS plate template following N. Koukoufilippas et al. (2020; dashed blue) and ﹩{{bC}}_{{\ell }}^{{gg}}﹩ plus shot noise (dotted blue).
Paper: Cross-correlating Dark Sirens and Galaxies: Constraints on H 0 from GWTC-3 of LIGO–Virgo–KAGRA
Authors: Suvodip Mukherjee, Alex Krolewski, Benjamin D. Wandelt, Joseph Silk
Figure caption: The band-averaged cross-correlation power spectrum between GW sources and galaxies with a Δℓ = 15 bin width and Δz = 0.1 is shown for three different maps of the GW sources: Set-1 (GW190814), Set-2 (GW170818, GW1901412, GW190720_000836, GW2001129_065458, GW200311_115853), and Set-3 (GW190701_203306, GW200224_222234) composed from the selected eight events, as a function of the median value of the redshift bin.