adsabs/AstroCLIMB huggingface dataset:
Paper: The Large-scale Anisotropy and Flux (de)magnification of Ultrahigh-energy Cosmic Rays in the Galactic Magnetic Field
Authors: Teresa Bister, Glennys R. Farrar, Michael Unger
Figure caption: Combined constraints on the the source number density n  s  and EGMF parameter ﹩{\beta }_{\mathrm{EGMF}}\equiv B/\mathrm{nG}\,\sqrt{{L}_{c}/\mathrm{Mpc}}﹩. Taken from T. Bister & G. R. Farrar (2024; Figure 11), the gray filled contours with the intensity bar at the top show the number of simulations out of 1000 total, using the JF12-full model for the GMF, that have both a sufficiently large dipole and higher multipole moments small enough to be compatible with the 99% isotropic expectations as found for the data. The navy, light-blue, red, and green contours indicate the regions encompassing 1 (dotted), 20 (dashed), and 100 (solid) simulations that fulfill both criteria for the base, neCL, nebCor, and twistX models. Characteristic estimates of the number densities of some steady source candidates are shown with vertical lines: Milky Way–like galaxies (C. J. Conselice et al. 2016), low-luminosity AGNs (L. C. Ho 2008), star-forming galaxies (C. Gruppioni et al. 2013), starburst galaxies (C. Gruppioni et al. 2013; K. Murase & M. Fukugita 2019), high-luminosity AGNs (P. N. Best & T. M. Heckman 2012; C. Gruppioni et al. 2013), and blazars (Ajello et al. 2013). Indicative loci of transient source candidates are shown with rotated lines (long gamma-ray bursts; D. Wanderman & T. Piran 2010), tidal disruption events (TDEs; S. van Velzen & G. R. Farrar 2014; I. Andreoni et al. 2022), and black hole–neutron star mergers (Abbott et al. 2023); see T. Bister & G. R. Farrar (2024) for more details.
Paper: The Large-scale Anisotropy and Flux (de)magnification of Ultrahigh-energy Cosmic Rays in the Galactic Magnetic Field
Authors: Teresa Bister, Glennys R. Farrar, Michael Unger
Figure caption: Top row: the markers show the dipole and quadrupole moments, d and Q, in the limit of continuous source number density (n  s  = ∞ ) for the various GMF models. The black markers indicate the data 1σ uncertainty regions for the dipole (G. Golup 2023) and quadrupole (L. Caccianiga et al. 2023). Second–sixth row: when the density of sources is finite, cosmic variance in the source locations leads to variations of the dipole and quadrupole amplitude, here indicated by the error bar showing the inner 68% of the distribution (for one realization of the model with l  c  = 60 pc). For 10−5 Mpc−3 ≲ n  s  ≲ 10−3 Mpc−3, both the  UF23 dipole and quadrupole moments agree with the data within 1σ for all models.
Paper: The Large-scale Anisotropy and Flux (de)magnification of Ultrahigh-energy Cosmic Rays in the Galactic Magnetic Field
Authors: Teresa Bister, Glennys R. Farrar, Michael Unger
Figure caption: Dipole direction dependence on the extragalactic flux, for different energy thresholds in Galactic coordinates: the thin markers indicate the predicted dipole directions for the LSS model (T. Bister & G. R. Farrar 2024) for selected GMF models. The respective thicker markers of the same form show the dipole direction prediction when the LSS illumination map is replaced by a smooth dipole with the same magnitude and direction—demonstrating the sensitivity of the observed dipole direction to the inhomogeneities in the illumination map. The black contours represent the 1σ and 2σ uncertainty domains of the measured dipole (G. Golup 2023).
Paper: The Large-scale Anisotropy and Flux (de)magnification of Ultrahigh-energy Cosmic Rays in the Galactic Magnetic Field
Authors: Teresa Bister, Glennys R. Farrar, Michael Unger
Figure caption: Combined magnification maps (as in Figure 4) for the JF12 model with the different random fields used in this work (JF12-regular, JF12-full with l  c  = 30 pc, and JF12-Planck with l  c  = 60 pc, the latter with two variations), illustrating the sensitivity of the magnification to the random field and—by comparing to Figure 4—the general differences between the JF12 and  UF23 coherent models as a function of rigidity. The color bar displays the magnification range in directions where all combinations of JF12 and random models agree; for the white area there is no consensus among the models. The directions of source candidates are indicated by stars, and the marker size is proportional to 1/distance.
Paper: Swiftly Chasing Gravitational Waves across the Sky in Real Time
Authors: Aaron Tohuvavohu, Jamie A. Kennea, Christopher J. Roberts, James DeLaunay, Samuele Ronchini, S. Bradley Cenko, Becca Ewing, Ryan Magee, Cody Messick, Surabhi Sachdev, Leo P. Singer
Figure caption: Cumulative distribution of the angular separation between the highest-probability pixel in a sky map and the true location for different truncation frequencies. An observer with a telescope of a given FOV radius can easily read off when to make a slew decision, depending on their risk posture and response time to the target. The BAT FOV is oblong, but its semiminor axis is 40°, thus guaranteeing coverage of the true position >60% of the time, if pointed successfully at the highest-probability location from the 29 Hz (∼–60 s) sky map.
Paper: The Large-scale Anisotropy and Flux (de)magnification of Ultrahigh-energy Cosmic Rays in the Galactic Magnetic Field
Authors: Teresa Bister, Glennys R. Farrar, Michael Unger
Figure caption: Dipole amplitude dependence on the extragalactic flux: the thin markers indicate the predicted dipole amplitude for the LSS model (T. Bister & G. R. Farrar 2024) for selected GMF models. The respective thicker markers of the same form show the dipole amplitude prediction when the LSS illumination map is replaced by a smooth dipole with the same magnitude and direction—demonstrating the sensitivity of the observed dipole amplitude to the inhomogeneities in the illumination map. The black markers represent the measured dipole amplitude and its 1σ uncertainty (G. Golup 2023).
Paper: Swiftly Chasing Gravitational Waves across the Sky in Real Time
Authors: Aaron Tohuvavohu, Jamie A. Kennea, Christopher J. Roberts, James DeLaunay, Samuele Ronchini, S. Bradley Cenko, Becca Ewing, Ryan Magee, Cody Messick, Surabhi Sachdev, Leo P. Singer
Figure caption: GW localization sky maps at different truncation frequencies (premerger times) for a 1.4–1.2 M ⊙ merger at 50 Mpc. This example clearly shows the highest-probability mode shifting between three locations in the sky, separated by ∼180°. In this case, a slew decision made on information from the earliest sky map could unknowingly result in looking at the wrong part of the sky.
Paper: The Large-scale Anisotropy and Flux (de)magnification of Ultrahigh-energy Cosmic Rays in the Galactic Magnetic Field
Authors: Teresa Bister, Glennys R. Farrar, Michael Unger
Figure caption: (a)–(m) Magnification maps for rigidity ﹩{ \mathcal R }=5\,\mathrm{EV}﹩ (as in Figure 3) for various GMF models including also variations of the random field. Contours indicating the extragalactic directions with large flux predicted by the LSS model (panel (n)) are shown in red. (n) The E > 8 EeV illumination map calculated from the LSS model (T. Bister & G. R. Farrar 2024), showing the flux at the edge of the Galaxy.
Paper: The Polar Vortex Hypothesis: Evolving, Spectrally Distinct Polar Regions Explain Short- and Long-term Light-curve Evolution and Color–Inclination Trends in Brown Dwarfs and Giant Exoplanets
Authors: Nguyen Fuda, Dániel Apai
Figure caption:  Overview of our atmosphere model. The model is composed of an ultracool atmosphere with spectral types corresponding to two circulation modes: jet dominated in the equator/midlatitudes and vortex dominated in the poles. Sonora Diamondback cloudy spectra are assigned to the bands, and less cloudy spectra are assigned to the poles. We considered three scenarios: a null hypothesis scenario, “No Vortex,” where the poles are spectrally indistinguishable from the ambient atmosphere; (2) “Evolving Vortex,” where the polar region is spectrally distinct, and where short-period change on rotational timescale comes from the equator/midlatitudes and long-period change comes from the pole; “Stationary Vortex,” where the polar region is spectrally distinct, but all temporal change comes from the equator/midlatitudes.
Paper: The Polar Vortex Hypothesis: Evolving, Spectrally Distinct Polar Regions Explain Short- and Long-term Light-curve Evolution and Color–Inclination Trends in Brown Dwarfs and Giant Exoplanets
Authors: Nguyen Fuda, Dániel Apai
Figure caption: Panels (a), (b) Modeled variability amplitude–inclination trends for (a) short-duration (10 hr, 2 rotations) and (b) long-duration simulated data (60 hr, 12 rotations). Spitzer 3.6 μm (few rotations) variability data from J. M. Vos et al. (2020) are overplotted in panel (a). Panels (c), (d) Modeled [J − K  s ] color–inclination for (c) short-duration and (d) long-duration simulated data. Spitzer color anomaly data from J. M. Vos et al. (2017) are overplotted. Both the “Evolving Vortex” and “Stationary Vortex” scenarios could explain the color anomaly vs. inclination trend. The “No Vortex” scenario does not explain the data.
Paper: The Polar Vortex Hypothesis: Evolving, Spectrally Distinct Polar Regions Explain Short- and Long-term Light-curve Evolution and Color–Inclination Trends in Brown Dwarfs and Giant Exoplanets
Authors: Nguyen Fuda, Dániel Apai
Figure caption: Flux evolution and spectral ratio for the“No Vortex” (panels (A), (B)), “Evolving Vortex” (panels (C), (D)), and “Stationary Vortex” (panels (E), (F)) scenarios. The spectral ratio is defined as the ratio of spectra at maximum and minimum flux: ﹩{\mathrm{Spectra}}_{\max }/{\mathrm{Spectra}}_{\min }﹩. For “Evolving Vortex,” the amplitude of flux variation is higher at the pole-on viewing angle. In contrast, both “Stationary Vortex” and “No Vortex” have higher flux amplitude equator-on. This shows that the latitudes where the long-period components are located will affect the observed flux amplitude vs. inclination trend.
Paper: The Polar Vortex Hypothesis: Evolving, Spectrally Distinct Polar Regions Explain Short- and Long-term Light-curve Evolution and Color–Inclination Trends in Brown Dwarfs and Giant Exoplanets
Authors: Nguyen Fuda, Dániel Apai
Figure caption: The single-pressure brightness models of the atmosphere, deconstructed of the region type: “Ambient,” “Bands,” and “Polar.” The coverage fraction of each region with the full disk is shown. The projected area of each region type changes with inclination, which also changes their fractional contribution to the hemisphere-integrated spectra and photometry.
Paper: The Polar Vortex Hypothesis: Evolving, Spectrally Distinct Polar Regions Explain Short- and Long-term Light-curve Evolution and Color–Inclination Trends in Brown Dwarfs and Giant Exoplanets
Authors: Nguyen Fuda, Dániel Apai
Figure caption: Plots of J − H color (a), (b) and wavelength-averaged spectral ratio (c), (d) with inclination for each simulated scenario over short-duration (10 hr) and long-duration (60 hr) monitoring. The spectral ratios (defined as ﹩{\mathrm{Spectra}}_{\max }/{\mathrm{Spectra}}_{\min }﹩) are averaged over 0.9–2.6 μm. The shaded regions show ±1σ values from 10 phase-randomized iterations.
Paper: The Polar Vortex Hypothesis: Evolving, Spectrally Distinct Polar Regions Explain Short- and Long-term Light-curve Evolution and Color–Inclination Trends in Brown Dwarfs and Giant Exoplanets
Authors: Nguyen Fuda, Dániel Apai
Figure caption: Analytical variability amplitude vs. inclination prediction for atmospheres with long-term variability from the polar region and short-term modulation from the low and midlatitudes.
Paper: Polycyclic Aromatic Hydrocarbon Emission in the Central Regions of Three Seyferts and the Implication for Underlying Feedback Mechanisms
Authors: Lulu Zhang, Ismael García-Bernete, Chris Packham, Fergus R. Donnan, Dimitra Rigopoulou, Erin K. S. Hicks, Ric I. Davies, Taro T. Shimizu, Almudena Alonso-Herrero, Cristina Ramos Almeida, Miguel Pereira-Santaella, Claudio Ricci, Andrew J. Bunker, Mason T. Leist, David J. Rosario, Santiago García-Burillo, Laura Hermosa Muñoz, Francoise Combes, Masatoshi Imanishi, Alvaro Labiano, Donaji Esparza-Arredondo, Enrica Bellocchi, Anelise Audibert, Lindsay Fuller, Omaira González-Martín, Sebastian Hönig, Takuma Izumi, Nancy A. Levenson, Enrique López-Rodríguez, Daniel Rouan, Marko Stalevski, Martin J. Ward
Figure caption: Diagnostic diagram of PAH band ratios 11.3/7.7 vs. 6.2/7.7 μm for the 3″ × 3″ (∼500 pc) apertures as illustrated in Figure 1. The red rectangles, blue star, and slate-gray hexagons represent the measurements of apertures in ESO137-G034, MCG-05-23-016, and NGC 3081, respectively, where points with a black dot pertain to the innermost aperture (i.e., aperture 1) of each target, and other apertures are number coded the same as in Figure 1. The gray contours marked by ”SF” represent the PAH band ratio distribution of 185 spatially resolved spaxels in 29 SF galaxies measured by L. Zhang et al. (2022). The open small circles indicate the PAH band ratios of 83 Seyferts with the measurements of all the three PAH features available from the literature (i.e., J. D. T. Smith et al. 2007; M. J. O’Dowd et al. 2009; A. M. Diamond-Stanic & G. H. Rieke 2010; J. F. Gallimore et al. 2010; D. A. Sales et al. 2010; PAH measurements of upper limits are excluded). The filled small circles indicate the PAH band ratios of 11 low-redshift quasars with all the three PAH features detected by Y. Xie & L. C. Ho (2022). The upward and downward small triangles, respectively, indicate the PAH band ratios of 29 giant H II regions in 3 Local Group galaxies measured by V. Lebouteiller et al. (2011) and 14 BCDs measured by L. K. Hunt et al. (2010) and V. Lebouteiller et al. (2011). The gray grids represent model predictions of PAH band ratios by D. Rigopoulou et al. (2024), respectively, for neutral (top grid, marked by “+”) and 70% ionized (bottom grid, marked by “×”) PAHs of different sizes (i.e., with carbon number N C = 20−400 from the right boundary to the left boundary of each grid) in the interstellar radiation field (ISRF; the top boundary of each grid) and the 103 × ISRF (the bottom boundary of each grid).
Paper: Polycyclic Aromatic Hydrocarbon Emission in the Central Regions of Three Seyferts and the Implication for Underlying Feedback Mechanisms
Authors: Lulu Zhang, Ismael García-Bernete, Chris Packham, Fergus R. Donnan, Dimitra Rigopoulou, Erin K. S. Hicks, Ric I. Davies, Taro T. Shimizu, Almudena Alonso-Herrero, Cristina Ramos Almeida, Miguel Pereira-Santaella, Claudio Ricci, Andrew J. Bunker, Mason T. Leist, David J. Rosario, Santiago García-Burillo, Laura Hermosa Muñoz, Francoise Combes, Masatoshi Imanishi, Alvaro Labiano, Donaji Esparza-Arredondo, Enrica Bellocchi, Anelise Audibert, Lindsay Fuller, Omaira González-Martín, Sebastian Hönig, Takuma Izumi, Nancy A. Levenson, Enrique López-Rodríguez, Daniel Rouan, Marko Stalevski, Martin J. Ward
Figure caption:                         Top panel: the residual emission-line spectrum after subtracting the best-fit model (i.e., the red curve in the middle panel) from the MIRI/MRS spectrum. From the left to the right, the short lines in the top indicate the positions of [Fe II] 5.34, [Fe VIII] 5.45, [Mg VII] 5.50, [Mg V] 5.61, H2                      S(6), H2                      S(5), [Ar II] 6.985, [Na III] 7.32, Pfα, [Ne VI] 7.65, [Fe VII] 7.815, [Ar V] 7.90, H2                      S(4), [Ar III] 8.99, [Fe VII] 9.53, H2                      S(3), [S IV] 10.51, H2                      S(2), Huα, [Ne II] 12.81, [Ar V] 13.10, [Ne V] 14.32, [Ne III] 15.555, and H2                      S(1) emission lines. Middle panel: illustration of the multicomponent fitting for PAH measurements (see Section 2.2). The gray curve is the observed MIRI/MRS spectrum with emission lines masked. The red curve gives the best-fit model with the shaded region indicating the corresponding 1σ posterior distribution. The blue curve is the summation of all continuum components (i.e., stellar and dust continuum), and these green curves are Drude profiles representing individual PAH features. Bottom panel: the residual PAH spectrum (i.e., the black curve) after subtracting all continuum components (i.e., the blue curve in the middle panel) from the emission-line masked MIRI/MRS spectrum. As in the middle panel, these green curves are Drude profiles representing individual PAH features, and the magenta curve is the summation of all green curves, i.e., the modeled PAH spectrum. From the left to the right, the short lines in the top indicate the positions of PAH complexes around 6.2, 7.7, 8.6, 11.3, and 12.7 μm. Note that all x-axes and the y-axis of the middle panel are in logarithmic scale, while y-axes of the top and bottom panels are in linear scale. The same plots for all apertures studied here are available from Figure A1 in the Appendix.
Paper: Polycyclic Aromatic Hydrocarbon Emission in the Central Regions of Three Seyferts and the Implication for Underlying Feedback Mechanisms
Authors: Lulu Zhang, Ismael García-Bernete, Chris Packham, Fergus R. Donnan, Dimitra Rigopoulou, Erin K. S. Hicks, Ric I. Davies, Taro T. Shimizu, Almudena Alonso-Herrero, Cristina Ramos Almeida, Miguel Pereira-Santaella, Claudio Ricci, Andrew J. Bunker, Mason T. Leist, David J. Rosario, Santiago García-Burillo, Laura Hermosa Muñoz, Francoise Combes, Masatoshi Imanishi, Alvaro Labiano, Donaji Esparza-Arredondo, Enrica Bellocchi, Anelise Audibert, Lindsay Fuller, Omaira González-Martín, Sebastian Hönig, Takuma Izumi, Nancy A. Levenson, Enrique López-Rodríguez, Daniel Rouan, Marko Stalevski, Martin J. Ward
Figure caption: Diagnostic diagrams of ionized emission-line ratios as (a) [Ne V]/[Ne II] vs. [Ne III]/[Ne II], (b) [O IV]/[Ne II] vs. [Ne III]/[Ne II], and (c) [S IV]/[Ne II] vs. [Ne III]/[Ne II] for apertures in the three targets with markers the same as in Figure 3. The reddish, greenish, and purplish contours in each panel correspond to the model calculations for AGN, fast radiative shocks (including the shock precursor), and H II regions, respectively, with each contour containing 30%, 60%, and 90% of the model results from the inside to the outside.
Paper: Polycyclic Aromatic Hydrocarbon Emission in the Central Regions of Three Seyferts and the Implication for Underlying Feedback Mechanisms
Authors: Lulu Zhang, Ismael García-Bernete, Chris Packham, Fergus R. Donnan, Dimitra Rigopoulou, Erin K. S. Hicks, Ric I. Davies, Taro T. Shimizu, Almudena Alonso-Herrero, Cristina Ramos Almeida, Miguel Pereira-Santaella, Claudio Ricci, Andrew J. Bunker, Mason T. Leist, David J. Rosario, Santiago García-Burillo, Laura Hermosa Muñoz, Francoise Combes, Masatoshi Imanishi, Alvaro Labiano, Donaji Esparza-Arredondo, Enrica Bellocchi, Anelise Audibert, Lindsay Fuller, Omaira González-Martín, Sebastian Hönig, Takuma Izumi, Nancy A. Levenson, Enrique López-Rodríguez, Daniel Rouan, Marko Stalevski, Martin J. Ward
Figure caption: Illustration of coverages of the JWST/MRS observations (white dashed rectangles for channel 1 field of view) and relative positions of the 3″ × 3″ apertures (colored rectangles with corresponding numbers) of our targets, with HST/WFC3 F673N or F606W (MCG-05-23-016) band imaging as the background. A scale bar of 500 pc is in the top right and a compass is in the bottom right of each panel.
Paper: Polycyclic Aromatic Hydrocarbon Emission in the Central Regions of Three Seyferts and the Implication for Underlying Feedback Mechanisms
Authors: Lulu Zhang, Ismael García-Bernete, Chris Packham, Fergus R. Donnan, Dimitra Rigopoulou, Erin K. S. Hicks, Ric I. Davies, Taro T. Shimizu, Almudena Alonso-Herrero, Cristina Ramos Almeida, Miguel Pereira-Santaella, Claudio Ricci, Andrew J. Bunker, Mason T. Leist, David J. Rosario, Santiago García-Burillo, Laura Hermosa Muñoz, Francoise Combes, Masatoshi Imanishi, Alvaro Labiano, Donaji Esparza-Arredondo, Enrica Bellocchi, Anelise Audibert, Lindsay Fuller, Omaira González-Martín, Sebastian Hönig, Takuma Izumi, Nancy A. Levenson, Enrique López-Rodríguez, Daniel Rouan, Marko Stalevski, Martin J. Ward
Figure caption: The correlation normalized by PAH 7.7 μm emission between H2 rotational emission and (a) atomic hydrogen Pfα emission and (b) atomic hydrogen Huα emission, with markers the same as in Figure 3.
Paper: Polycyclic Aromatic Hydrocarbon Emission in the Central Regions of Three Seyferts and the Implication for Underlying Feedback Mechanisms
Authors: Lulu Zhang, Ismael García-Bernete, Chris Packham, Fergus R. Donnan, Dimitra Rigopoulou, Erin K. S. Hicks, Ric I. Davies, Taro T. Shimizu, Almudena Alonso-Herrero, Cristina Ramos Almeida, Miguel Pereira-Santaella, Claudio Ricci, Andrew J. Bunker, Mason T. Leist, David J. Rosario, Santiago García-Burillo, Laura Hermosa Muñoz, Francoise Combes, Masatoshi Imanishi, Alvaro Labiano, Donaji Esparza-Arredondo, Enrica Bellocchi, Anelise Audibert, Lindsay Fuller, Omaira González-Martín, Sebastian Hönig, Takuma Izumi, Nancy A. Levenson, Enrique López-Rodríguez, Daniel Rouan, Marko Stalevski, Martin J. Ward
Figure caption: Diagnostic diagram of H2 S(0−3)/PAH 7.7 and H2 S(3)/H2 S(1) ratios for apertures in the three targets with markers the same as in Figure 3. The horizontal dashed line shows the upper limit of the H2 S(0−3)/PAH 7.7 ratio given by the photodissociation region models adopted by P. Guillard et al. (2012), and the horizontal arrow indicates the direction of increasing H2 temperature.
Paper: Polycyclic Aromatic Hydrocarbon Emission in the Central Regions of Three Seyferts and the Implication for Underlying Feedback Mechanisms
Authors: Lulu Zhang, Ismael García-Bernete, Chris Packham, Fergus R. Donnan, Dimitra Rigopoulou, Erin K. S. Hicks, Ric I. Davies, Taro T. Shimizu, Almudena Alonso-Herrero, Cristina Ramos Almeida, Miguel Pereira-Santaella, Claudio Ricci, Andrew J. Bunker, Mason T. Leist, David J. Rosario, Santiago García-Burillo, Laura Hermosa Muñoz, Francoise Combes, Masatoshi Imanishi, Alvaro Labiano, Donaji Esparza-Arredondo, Enrica Bellocchi, Anelise Audibert, Lindsay Fuller, Omaira González-Martín, Sebastian Hönig, Takuma Izumi, Nancy A. Levenson, Enrique López-Rodríguez, Daniel Rouan, Marko Stalevski, Martin J. Ward
Figure caption: Fitting results of H2 rotational emission lines assuming a continuous power-law distribution of temperature T for apertures in the three targets with markers the same as in Figure 3. The ranges of the best-fit temperature distribution index n and low-end temperature T  l  for ESO137-G034 and the other two targets are indicated above and below the fitting curves, respectively.
Paper: Polycyclic Aromatic Hydrocarbon Emission in the Central Regions of Three Seyferts and the Implication for Underlying Feedback Mechanisms
Authors: Lulu Zhang, Ismael García-Bernete, Chris Packham, Fergus R. Donnan, Dimitra Rigopoulou, Erin K. S. Hicks, Ric I. Davies, Taro T. Shimizu, Almudena Alonso-Herrero, Cristina Ramos Almeida, Miguel Pereira-Santaella, Claudio Ricci, Andrew J. Bunker, Mason T. Leist, David J. Rosario, Santiago García-Burillo, Laura Hermosa Muñoz, Francoise Combes, Masatoshi Imanishi, Alvaro Labiano, Donaji Esparza-Arredondo, Enrica Bellocchi, Anelise Audibert, Lindsay Fuller, Omaira González-Martín, Sebastian Hönig, Takuma Izumi, Nancy A. Levenson, Enrique López-Rodríguez, Daniel Rouan, Marko Stalevski, Martin J. Ward
Figure caption: Diagnostic diagram of (a) [Fe II]/Pfα and (b) [Fe II]/Huα vs. H2 S(3)/H2 S(1) for apertures in the three targets, with markers the same as in Figure 3.