adsabs/AstroCLIMB huggingface dataset:
Paper: BASS. XXXIII. Swift-BAT Blazars and Their Jets through Cosmic Time
Authors: L. Marcotulli, M. Ajello, C. M. Urry, V. S. Paliya, M. Koss, K. Oh, G. Madejski, Y. Ueda, M. Baloković, B. Trakhtenbrot, F. Ricci, C. Ricci, D. Stern, F. Harrison, M. C. Powell
Figure caption: Best-fit to the de-evolved XLF (ϕ(L, 0), red data points) using various values of the kinematic Doppler factor distribution index (p parameter). Higher values of p (p > 5) can more likely be attributed to the EC process in the jet, while lower values are associated with the SSC process. As can be seen, for p > 7, the XLF is predicted to show a break around the lowest-luminosity bin of our sample (L ∼ 1044 erg s−1), while for lower values of p, this break would happen at L < 1042 erg s−1. From our best fits, we are not able to discern which values best representing the population of these jets, though the range p = [5, 7] seems to be the more favorable overall (see details in Section 7.1).
Paper: BASS. XXXIII. Swift-BAT Blazars and Their Jets through Cosmic Time
Authors: L. Marcotulli, M. Ajello, C. M. Urry, V. S. Paliya, M. Koss, K. Oh, G. Madejski, Y. Ueda, M. Baloković, B. Trakhtenbrot, F. Ricci, C. Ricci, D. Stern, F. Harrison, M. C. Powell
Figure caption: Log-likelihood results (C, see Equation (13)) for the BAT FSRQs using the MPDE model fixing the position of the z peak = [3, 5]. It can be noticed how the fit values reach a minimum for a peak occurring at z peak = 4.3–4.4, confirming that the luminous BAT FSRQ population peaks at z > 4.
Paper: A Multiscale Picture of the Magnetic Field and Gravity from a Large-scale Filamentary Envelope to Core-accreting Dust Lanes in the High-mass Star-forming Region W51
Authors: Patrick M. Koch, Ya-Wen Tang, Paul T. P. Ho, Pei-Ying Hsieh, Jia-Wei Wang, Hsi-Wei Yen, Ana Duarte-Cabral, Nicolas Peretto, Yu-Nung Su
Figure caption: Top to bottom panels: polarized emission I  p , polarization percentage p, and polarization percentage vs. Stokes I, normalized by ﹩{I}_{\max }﹩, for W51 e2 (left column) and W51 e8 (right column). The red solid lines in the bottom panels are the best-fit power laws with indices −0.81 (e2) and −0.77 (e8). The maps display overgridded data for a sharper visualization. The data in the bottom panels are extracted from maps gridded to only half of the synthesized beam resolution.
Paper: A Multiscale Picture of the Magnetic Field and Gravity from a Large-scale Filamentary Envelope to Core-accreting Dust Lanes in the High-mass Star-forming Region W51
Authors: Patrick M. Koch, Ya-Wen Tang, Paul T. P. Ho, Pei-Ying Hsieh, Jia-Wei Wang, Hsi-Wei Yen, Ana Duarte-Cabral, Nicolas Peretto, Yu-Nung Su
Figure caption: Self-similar structures on two different scales, envelope-to-core scale (Section 5.1.1; left column) and local-collapsing-core scale (Section 5.1.3; right column), in their detected magnetic field morphologies (red segments, top row) and their gravitational vector fields (black arrows, bottom row). Green boxes mark the self-similar structures. On the envelope-to-core scale between e8 and e2, the gravitational field starts to be deflected in the north of e8, gradually pointing more toward e2. The more massive e2 core mostly displays an azimuthally symmetric gravitational field. This systematic deflection toward the more massive local center is seen again on smaller scales when zooming in between the cores e2-W and e2-E, e2-NW and e2-E/e2-W, and e8-S and e8-N. The B-field morphology shows a characteristic feature where the field segments are bent away from the less massive core and straightened toward the more massive local center. These recurring structures point at a multiscale collapse-within-collapse scenario that leaves its imprints both in the B-field and the gravitational vector field.
Paper: A Multiscale Picture of the Magnetic Field and Gravity from a Large-scale Filamentary Envelope to Core-accreting Dust Lanes in the High-mass Star-forming Region W51
Authors: Patrick M. Koch, Ya-Wen Tang, Paul T. P. Ho, Pei-Ying Hsieh, Jia-Wei Wang, Hsi-Wei Yen, Ana Duarte-Cabral, Nicolas Peretto, Yu-Nung Su
Figure caption: Histograms of polarization percentages for W51 e2 and e8. Averages, median values, and standard deviations are 2.8%, 2.3%, and 2.0% for e2, and 3.1%, 2.4%, and 2.5% for e8. Maximum and minimum polarizations are 14% and 0.13% for e2 and 23% and 0.27% for e8.
Paper: Critical Mach Numbers for Magnetohydrodynamic Shocks with Accelerated Particles and Waves
Authors: J. Martin Laming
Figure caption: Left: schematic diagram of shock propagation in the pressure–velocity space for γ  G  = γ CR = 5/3, M = 1.972. Gas pressure P  G  is plotted on the y-axis, and velocity on the x-axis. Cosmic ray pressure P CR = 0 delineates the third side of the triangle as shown. The Hugoniot is represented by the two thick vertical lines at u 1 (upstream) and u 2 (downstream), and the reflected Hugoniot runs from the intersection of the downstream Hugoniot and the sonic line and the intersection of the upstream Hugoniot and the P CR = 0 line. The dotted curve shows the trajectory of plasma with a nonzero P CR, following the adiabatic gas law from its initial position until it hits the reflected Hugoniot, and then making the shock jump to the downstream Hugoniot. Right: schematic diagram of shock propagation in the pressure–velocity space with cosmic rays trapped at the shock, i.e., with zero cosmic ray energy flux. The Hugoniot is now the curve shown, and coincides with the reflected Hugoniot.
Paper: Near-infrared Extragalactic Background Light Fluctuations on Nonlinear Scales
Authors: Yun-Ting Cheng, James J. Bock
Figure caption: Top: fraction of IGL intensity from z < 1.4 galaxies in H12 model as a function of masking threshold m th at 1 (blue), 3 (green), and 5 (red) μm. The masking threshold is defined at 1 μm for all three wavelengths, and the corresponding masking depth at other wavelengths is derived by the abundance matching technique (Cheng & Chang 2022). Bottom: fraction of IGL power spectrum from linear clustering and Poisson fluctuations at ℓ = 103 from z < 1.4 galaxies. We use the power spectrum model from Cheng & Chang (2022) built from the H12 IGL model.
Paper: Near-infrared Extragalactic Background Light Fluctuations on Nonlinear Scales
Authors: Yun-Ting Cheng, James J. Bock
Figure caption: MICECAT luminosity function at z = 0.2 in the Euclid NISP Y band (black), and the M  r  < −18 population (red) used in this work. Error bars give the sample variance of the 140 deg2 of MICECAT data we used in this study. The blue line shows a model of luminosity function at the same wavelength and redshift from H12, fitting a Schechter function to observed galaxy counts. The MICECAT luminosity function on the faint end shows an excess above the model, and thus we discard all M  r  > −18 sources in our analysis.
Paper: X-Ray Sources in the SSA22 Chandra Field
Authors: Brandon T. Radzom, A. J. Taylor, A. J. Barger, L. L. Cowie
Figure caption: The L  X  distribution of the full X-ray sample with rough classifications included. Violet triangles correspond to BLAGNs while filled green circles correspond to non-BLAGN (note that both populations are X-ray AGNs). Empty green circles represent non-BLAGNs that are also not AGNs and gray “x” marks trace sources that have no spectroscopic classification. Sources with photzs are highlighted by orange diamonds. The vertical dashed gray lines represent the redshift intervals over which we choose to construct our AGN XLFs, while the horizontal dotted black line corresponds to the AGN luminosity cut.
Paper: X-Ray Sources in the SSA22 Chandra Field
Authors: Brandon T. Radzom, A. J. Taylor, A. J. Barger, L. L. Cowie
Figure caption: The solid angle distribution for detected 2–8 keV fluxes. The gray dotted line represents the best-fit flux sensitivity border according to our log-linear fit of Equation (3), while the red dashed line corresponds to the circular solid angle traced out by the ﹩\theta =10^{\prime} ﹩ cutoff mark. As hard X-ray fluxes fall below ∼ 2 × 10−15 erg s−1 cm−2, we see that detections are increasingly biased toward the beam center.
Paper: X-Ray Sources in the SSA22 Chandra Field
Authors: Brandon T. Radzom, A. J. Taylor, A. J. Barger, L. L. Cowie
Figure caption: Top panel: the rest-frame 2–8 keV XLF for the 33 BLAGNs (violet triangles) and 61 non-BLAGNs (green circles) in our sample, constructed over the same redshift intervals and overplotted with our AGN XLF (0.25 ≤ z < 4). Vertical and horizontal axes share identical ranges. Bottom panel: the fraction of spectroscopically classified AGNs (94/155) in our AGN XLF sample that are BLAGNs, by redshift interval. Error bars are 1σ uncertainties derived from Monte Carlo simulations with 106 Poissonian trials per bin.
Paper: X-Ray Sources in the SSA22 Chandra Field
Authors: Brandon T. Radzom, A. J. Taylor, A. J. Barger, L. L. Cowie
Figure caption: The rest-frame 2–8 keV XLF for 155 AGNs in our SSA22 sample (black squares), split into three redshift intervals spanning 0.25 ≤ z < 4. We overplot data from Figure 7 of A15 for overlapping redshift intervals (shown as green, blue, red, or orange). In the high-redshift interval, we also plot the XLF excluding protocluster candidates (gray transparent squares). Vertical and horizontal axes share identical ranges. Our results are consistent with those of A15 to within 1σ.
Paper: Near-infrared Extragalactic Background Light Fluctuations on Nonlinear Scales
Authors: Yun-Ting Cheng, James J. Bock
Figure caption: Fraction of the MICECAT IGL from M  r  < −18 galaxies as a function of redshift. The galaxies fainter than M r = −18 only constitute ∼10% of the IGL at z ≲ 0.5, and this fraction decreases to zero at z ≳ 1.
Paper: X-Ray Sources in the SSA22 Chandra Field
Authors: Brandon T. Radzom, A. J. Taylor, A. J. Barger, L. L. Cowie
Figure caption: Redshift distribution for the X-ray sources in our updated SSA22 catalog. Speczs are traced by the solid black line, while photzs from LePHARE are traced by the orange dashed line.
Paper: Updated Low-temperature Gas Opacities with ÆSOPUS 2.0
Authors: Paola Marigo, Bernhard Aringer, Léo Girardi, Alessandro Bressan
Figure caption: Differences in effective temperature caused by using either ÆSOPUS 1.0 (blue lines) or ÆSOPUS 2.0 (magenta lines) opacities in red giant models. The reference solar composition is MBS22. Left panel: RGB tracks predicted on the H-R diagram with Z = 0.001 and 0.017 and M  i  ranging from 0.8 to 1.6 M ⊙ (with a mass step of 0.2 M ⊙). Right panel: predicted effective temperature as a function of increasing photospheric C/O in a TP-AGB star (top) and difference ΔT eff between the two ÆSOPUS versions (bottom). The selected stellar parameters and frequency grid size are indicated. See text for more details.
Paper: Updated Low-temperature Gas Opacities with ÆSOPUS 2.0
Authors: Paola Marigo, Bernhard Aringer, Léo Girardi, Alessandro Bressan
Figure caption: Rosseland mean opacity and major opacity sources as a function of temperature T and for three values of R. The adopted composition is assumed to have Z = 0.0165, X = 0.7, and the metal abundances scaled to solar following AGSS09. In the left panels, as indicated in the legends, the three curves correspond to different opacity calculations. The insets zoom in on the most pronounced opacity variations for temperatures below about 2240 K. Except for the lowest-density case (top panels with ﹩\mathrm{log}(R)=-8﹩), where Thomson e− scattering dominates the opacity, the differences are primarily due to different water absorption line lists and the line broadening scheme used. Right panels: contributions to the total Rosseland mean opacity from various opacity sources, as derived from AESOPUS 2.0 calculations shown in the left panel. Each curve corresponds to ﹩\mathrm{log}({\kappa }_{{\rm{R}}})-\mathrm{log}({\kappa }_{{\rm{R}}}^{i,\mathrm{off}})﹩, where κ R is the full opacity including all opacity sources considered here, and ﹩{\kappa }_{{\rm{R}}}^{i,\mathrm{off}}﹩ is the reduced opacity obtained by excluding the specific absorbing species. See the text for more details.
Paper: Updated Low-temperature Gas Opacities with ÆSOPUS 2.0
Authors: Paola Marigo, Bernhard Aringer, Léo Girardi, Alessandro Bressan
Figure caption: Comparison of Rosseland mean opacities across the entire extension of a typical table, assuming X = 0.7 and Z = 0.0165. Top panels: differences between ÆSOPUS 2.0 and ÆSOPUS 1.0, mainly due to the updates and expansion of molecular absorption. Solar compositions from MBS22; left) and (AAG21; right) are assumed. Contour levels map a 0.05 dex difference in ﹩\mathrm{log}({\kappa }_{{\rm{R}}})﹩. Bottom panels: differences caused by the choice of solar mixture. Comparison is made between GS98 and MBS22 (left) or AAG21 and MBS22 (right). Version ÆSOPUS 2.0 is adopted. The grid of contour levels is distributed every 0.02 dex difference in ﹩\mathrm{log}({\kappa }_{{\rm{R}}})﹩.
Paper: Updated Low-temperature Gas Opacities with ÆSOPUS 2.0
Authors: Paola Marigo, Bernhard Aringer, Léo Girardi, Alessandro Bressan
Figure caption: Differences in Rosseland mean opacities between the reference frequency grid with n OSgrid = 5365 points and two test cases with n OSgrid = 2358 and 1458 (top and bottom panels, respectively). The chemical composition assumes X = 0.7, Z = 0.0165, with scaled-solar elemental abundances according to (MBS22). Left panels: maps of opacity differences across the whole R–T extension of a typical table. Contour levels are distributed every 0.01 dex in ﹩{\rm{\Delta }}\mathrm{log}({\kappa }_{{\rm{R}}})﹩. Right panels: distribution of opacity differences with respect to the reference frequency grid calculated over the entire sample of N tot = 1273 opacity values in the table.
Paper: TPHO: A Time-dependent Photoionization Model for AGN Outflows 
Authors: Daniele Rogantini, Missagh Mehdipour, Jelle Kaastra, Elisa Costantini, Anna Juráňová, Erin Kara
Figure caption: Recombination timescale as a function of the density of plasma in photoionization equilibrium. In the top panels, we show the recombination timescale of the oxygen (left) and iron (right) ions for plasma with an ionization parameter of ﹩\mathrm{log}\xi =2﹩. We show only the ions which have a relative concentration larger than 10−6. In the bottom panels, we display the recombination timescales of the H-like ion of oxygen (left) and iron (right) for a grid of ionization parameters.
Paper: Updated Low-temperature Gas Opacities with ÆSOPUS 2.0
Authors: Paola Marigo, Bernhard Aringer, Léo Girardi, Alessandro Bressan
Figure caption: Effective temperature predicted by the integration of a red giant’s model atmosphere. The test is designed to assess the sensitivity to the frequency grid size used to compute κ R. Top panel: effective temperature of a TP-AGB star with L = 104 L ⊙ and increasing photospheric C/O using n OSgrid = 5365 (solid line) or 1458 (dotted line). Bottom panel: difference in effective temperature between atmospheric integrations using the two frequency grids. Both frequency distributions are extracted following the Helling & Jørgensen (1998) OS optimization prescriptions.
Paper: Updated Low-temperature Gas Opacities with ÆSOPUS 2.0
Authors: Paola Marigo, Bernhard Aringer, Léo Girardi, Alessandro Bressan
Figure caption: ÆSOPUS 2.0 Rosseland mean opacity as a function of temperature, with ﹩\mathrm{log}(R)=-3﹩. The adopted chemical composition is defined by X = 0.7 and Z = Z ⊙ according to various compilations of the solar mixture (see Table 3). As highlighted in the inset, the largest differences occur at ﹩\mathrm{log}(T/{\rm{K}})\lesssim 3.4﹩, where water absorption dominates the opacity.
Paper: Updated Low-temperature Gas Opacities with ÆSOPUS 2.0
Authors: Paola Marigo, Bernhard Aringer, Léo Girardi, Alessandro Bressan
Figure caption: Number densities of H2O, CN, and H− as a function of temperature for two R parameter values. ÆSOPUS 2.0 predictions are shown for three solar mixtures, namely, GS98, AAG21, and MBS22.
Paper: Identifying the 3FHL Catalog. VI. Swift Observations of 3FHL Unassociated Objects with Source Classification via Machine Learning
Authors: S. Joffre, R. Silver, M. Rajagopal, M. Ajello, N. Torres-Albà, A. Pizzetti, S. Marchesi, A. Kaur
Figure caption: Multiple X-ray counterpart candidates for 3FHL J0319.2-7045 imaged in 0.3−10 keV. SWIFT J032009-704535 (bottom) and SWIFT J032007-704320 (top) are labeled with corresponding circular uncertainty regions. SWIFT J032009-704535 lies ﹩\sim 1.3^{\prime} ﹩ and SWIFT J032007-704320 ﹩\sim 1.5^{\prime} ﹩ from the edge of the 3FHL region. Multiwavelength data help to confirm that the brighter SWIFT J032009-704535 detection is most likely our corresponding X-ray counterpart.
Paper: Identifying the 3FHL Catalog. VI. Swift Observations of 3FHL Unassociated Objects with Source Classification via Machine Learning
Authors: S. Joffre, R. Silver, M. Rajagopal, M. Ajello, N. Torres-Albà, A. Pizzetti, S. Marchesi, A. Kaur
Figure caption: Swift−XRT image of 3FHL J1127.8+3615 in 0.3−10 keV energy range. Although the 4FGL was able to significantly reduce the 95% uncertainty region for this gamma-ray detection, both X-ray counterpart candidates fall outside of this region. Both SWIFT J112759+362033 (left) and SWIFT J112741+362051 (right) make persuasive blazar candidates. Due to the vicinity of the 4FGL uncertainty region, J112759+362033 was selected as the counterpart candidate.
Paper: Identifying the 3FHL Catalog. VI. Swift Observations of 3FHL Unassociated Objects with Source Classification via Machine Learning
Authors: S. Joffre, R. Silver, M. Rajagopal, M. Ajello, N. Torres-Albà, A. Pizzetti, S. Marchesi, A. Kaur
Figure caption: Image field for 3FHL J0121.8+3808 in the 0.3–10 keV energy range. No significant detections were determined to fall within the 3FHL uncertainty region for 3FHL J0121.8+3808. The XRT uncertainty regions are denoted in purple. J012206+380445 (upper source) and J012219+380801 (lower source) comprise our two counterpart candidates. A previous gamma-ray burst detection led to this field having greater counts on the eastern side of the field, possibly requiring additional time to distinguish a source within the 3FHL region.
Paper: Identifying the 3FHL Catalog. VI. Swift Observations of 3FHL Unassociated Objects with Source Classification via Machine Learning
Authors: S. Joffre, R. Silver, M. Rajagopal, M. Ajello, N. Torres-Albà, A. Pizzetti, S. Marchesi, A. Kaur
Figure caption: Gamma-ray photon index vs. gamma-ray flux (10 GeV–1 TeV) from the 3FHL catalog. Blue points and red Xs represent the distribution of known blazar types (BL Lac and FSRQ, respectively). The green triangles correspond to Galactic sources. The stars denote our unassociated sources, most of which fall in regions dominated by known blazars. The average known blazar photon index is designated by the blue solid line. The green dashed line is the average photon index of Galactic sources.
Paper: Identifying the 3FHL Catalog. VI. Swift Observations of 3FHL Unassociated Objects with Source Classification via Machine Learning
Authors: S. Joffre, R. Silver, M. Rajagopal, M. Ajello, N. Torres-Albà, A. Pizzetti, S. Marchesi, A. Kaur
Figure caption: Swift−XRT image of 3FHL J1626.3-4915 field taken in 0.3−10 keV energy range. SWIFT J162703-491231 (upper left) and SWIFT J162609-491746 (lower right) both constitute X-ray counterparts for this field. Their corresponding pointing uncertainty regions (in purple) are plotted along with the 95% uncertainty regions for the 3FHL and 4FGL.
Paper: Identifying the 3FHL Catalog. VI. Swift Observations of 3FHL Unassociated Objects with Source Classification via Machine Learning
Authors: S. Joffre, R. Silver, M. Rajagopal, M. Ajello, N. Torres-Albà, A. Pizzetti, S. Marchesi, A. Kaur
Figure caption: Swift−XRT image of 3FHL J0233.0+3742 field. In purple, we show SWIFT J023308+374158 (center) and SWIFT J023256+373843 (bottom right) with corresponding uncertainty regions. The 3FHL and 4FGL 95% uncertainty regions are plotted in green and red, respectively. Image energy range is 0.3−10.0 keV.
Paper: Identifying the 3FHL Catalog. VI. Swift Observations of 3FHL Unassociated Objects with Source Classification via Machine Learning
Authors: S. Joffre, R. Silver, M. Rajagopal, M. Ajello, N. Torres-Albà, A. Pizzetti, S. Marchesi, A. Kaur
Figure caption: Plot of X-ray photon index vs. X-ray flux (0.3–10 keV) for 3FHL known blazars and Galactic sources. The blue line indicates the average photon index of known blazars, while the green dashed line is for Galactic sources. Stars designate the unassociated sources analyzed in this work.
Paper: Deep Learning–based Fast Spectral Inversion of Hα and Ca II 8542 Line Spectra
Authors: Kyoung-Sun Lee, Jongchul Chae, Eunsu Park, Yong-Jae Moon, Hannah Kwak, Kyuhyoun Cho
Figure caption: Temporal variation of the Doppler velocity (v 0), the temperature of hydrogen, and the nonthermal velocity at the upper chromosphere of the superpenumbral fibril in the AR, determined from the DNN and MLSI.
Paper: Deep Learning–based Fast Spectral Inversion of Hα and Ca II 8542 Line Spectra
Authors: Kyoung-Sun Lee, Jongchul Chae, Eunsu Park, Yong-Jae Moon, Hannah Kwak, Kyuhyoun Cho
Figure caption: Temporal variations of the Doppler velocity (v 0), the temperature of hydrogen, and the nonthermal velocity at the upper chromosphere of the network feature in the QR, determined from the DNN and MLSI.
Paper: VERTICO. IV. Environmental Effects on the Gas Distribution and Star Formation Efficiency of Virgo Cluster Spirals
Authors: Vicente Villanueva, Alberto D. Bolatto, Stuart Vogel, Tobias Brown, Christine D. Wilson, Nikki Zabel, Sara Ellison, Adam R. H. Stevens, María Jesús Jiménez Donaire, Kristine Spekkens, Mallory Tharp, Timothy A. Davis, Laura C. Parker, Ian D. Roberts, Dhruv Basra, Alessandro Boselli, Barbara Catinella, Aeree Chung, Luca Cortese, Bumhyun Lee, Adam Watts
Figure caption: Stacked molecular gas (Σmol; blue solid line) and stellar (Σ⋆; orange solid line) surface densities, in units of M ⊙ pc−2, as a function of galactocentric radius, in units of r 25, for the 38 VERTICO galaxies analyzed in this work (sorted by H I-Class). The shaded blue area is the Σmol uncertainty. The brown dotted line is the SFR surface density, ΣSFR. The purple dashed line is the atomic gas surface density derived from H I moment 0 maps at 15″   resolution from the VIVA survey. The gray shaded area is the region within the stellar effective radius R  e,⋆. The green dashed and red dashed lines represent the best-fit exponential profiles for Σmol and Σ⋆, respectively, when an exponential fit was appropriate. The vertical dashed lines correspond to r gal = 3 kpc.
Paper: VERTICO. IV. Environmental Effects on the Gas Distribution and Star Formation Efficiency of Virgo Cluster Spirals
Authors: Vicente Villanueva, Alberto D. Bolatto, Stuart Vogel, Tobias Brown, Christine D. Wilson, Nikki Zabel, Sara Ellison, Adam R. H. Stevens, María Jesús Jiménez Donaire, Kristine Spekkens, Mallory Tharp, Timothy A. Davis, Laura C. Parker, Ian D. Roberts, Dhruv Basra, Alessandro Boselli, Barbara Catinella, Aeree Chung, Luca Cortese, Bumhyun Lee, Adam Watts
Figure caption: Left: comparison between the stellar (l ⋆) and molecular (l mol) scale lengths, computed by fitting exponential profiles to the respective surface densities as a function of galactocentric radius. The colored circles correspond to 33 VERTICO galaxies with Σmol > 1 M ⊙ pc−2 for all the annuli within 0.25r 25, color-coded by H I-Class from Yoon et al. (2017). The blue solid line is the OLS linear bisector fit (forced through the origin) for them, and the red dashed−dotted and green dashed lines illustrate the 1:1 scaling and the OLS linear bisector fit for EDGE-CALIFA galaxies (Villanueva et al. 2021), respectively. The “r  p ” value noted corresponds to the Pearson correlation parameter. Right: the molecular, R  e,mol, vs. stellar, R  e,⋆, effective radii, which enclose 50% of the total molecular gas and stellar masses, respectively, for the 38 VERTICO galaxies analyzed in this work. Conventions are as in the left panel.