adsabs/AstroCLIMB huggingface dataset:
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Summary of observations and model fits to the 2019 June 5 (MIRC-X) epoch data. In the top panels, data points are denoted with triangles with 1σ error bars included. Measurements (and fits) in the wave band closest to 1.6 μm are drawn with full opacity whereas measurements in other wave bands are partially transparent to minimize the “confusion-limit” of the figure. In the top left panel, visibility amplitude is shown rather than the measured (and fit to) square visibility to assist the reader in visually distinguishing the halo/disk/star relative flux contributions; the residuals, plotted immediately below, are for square visibility. In the bottom-left panel, the total uv coverage of the epoch is shown together with the minimum-area [Löwner] ellipse enclosing all of the points; this ellipse is used to derive an approximate “beam size” according to λ/2B along the major and minor axes, as depicted by the purple ellipse in the bottom-left corner of the lower-right panel.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Parametric model (fifth-order) fits of all analyzed epochs, with the orbital position of a point on a 43.6 day circular trajectory at a radius of 0.13 au superimposed in cyan. The green contours denote the regions in the reconstructed disk image where the surface brightness is within 90% of its peak value. The blue lines denote the best-fit error-ellipses to the green contours, which are reported in Table 3 and used to fit the cyan orbit. Note that the analytic best-fit model solution for July 13 still places a considerable amount of flux in the vicinity of the expected orbital position, despite the fact that this region is not the dominant source of disk emission in that particular epoch.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Best-fit azimuthally modulated rings for each epoch at 1.6 μm. The orientation of the inner disk was fixed to match the outer disk orientation, but the ring size, and amplitude and phase of sinusoidal variations were free parameters. Each column represents a single epoch of data; each row represents the maximum sinusoidal order used in the fit. For all epochs, models beyond fifth order do not show significant qualitative deviation with the addition of subsequent higher-order sinusoids.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Images reconstructed of the HD 163296 inner disk via OITOOLS.jl. A clear, moving, localized flux excess is recovered near the putative dust sublimation rim. We emphasize that while these images do provide a general sense of the inner geometry, and that the presence and rough position of the localized spot is corroborated by traditional model fitting methods, other “whispy” features seen in these images are likely artifacts of the image reconstruction process given the sparse interferometric Fourier coverage rather than real, physical disk features.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: The total ﹩{\chi }_{\nu }^{2}﹩ value (top panel) and ﹩{\chi }_{\nu }^{2}﹩ contributions of the square visibility (middle) and closure phase (bottom) components of the analytic modeling fits. The addition of additional azimuthal orders beyond 3–5 has little effect on the final fit for all epochs.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Summary of observations and model fits to the 2019 June 6 (MIRC-X) epoch data. See the caption in Figure 8 for an explanation of what is depicted in the panels.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Image reconstructions of all analyzed epochs with orbital parameter extraction diagnostics overplotted (see Figure 6 for description).
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Summary of observations and model fits to the 2019 June 8 (MIRC-X in polarimetric mode) epoch data. See the caption in Figure 8 for an explanation of what is depicted in the panels.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Summary of observations and model fits to the 2019 June 9 (MIRC-X and PIONIER) epoch data. See the caption in Figure 8 for an explanation of what is depicted in the panels.
Paper: Comet 289P/Blanpain: Near-perihelion Activity and the Phoenicids
Authors: Toshihiro Kasuga
Figure caption: Nucleus radius versus perihelion-normalized NGA of 289P (blue symbol) and comparison with those of well-studied short-period comets (yellow symbols). The dashed red line indicates the trend found by fitting from the latter data, which is Halley type (1P and 55P), Encke type (2P, 87P, and 147P), and JFCs (4P, 6P, 7P, 8P, 9P, 10P, 19P, 21P, 22P, 24P, 26P, 43P, 65P, 67P, 76P, 81P, 96P, 103P, and 106P).
Paper: Comet 289P/Blanpain: Near-perihelion Activity and the Phoenicids
Authors: Toshihiro Kasuga
Figure caption: Relationship between JFC nucleus radius and fractional active area, fA. The fA of 289P is estimated near its perihelion, despite being among the lowest in JFCs, comparable to the inactive state of 169P.
Paper: Deep Learning-based Identification of CP1 and CP2 Stars from LAMOST DR11
Authors: ZhiWei Lu, Xiaoming Kong, YaTao Zhang, ZhenPing Yi, Meng Liu
Figure caption: The Teff, ﹩\mathrm{log}﹩g, [Fe/H] distribution of CP1 stars, in which the blue part is our newly found CP1 stars, the red part is all the CP1 stars known in previous literature (L.-H. Shang et al. 2022; X.-m. Tian et al. 2023; and H.-F. Yang et al. 2024), and the green part is the CP1 stars (including previous literature and our discovery).
Paper: Deep Learning-based Identification of CP1 and CP2 Stars from LAMOST DR11
Authors: ZhiWei Lu, Xiaoming Kong, YaTao Zhang, ZhenPing Yi, Meng Liu
Figure caption: The Teff, ﹩\mathrm{log}﹩g, [Fe/H] distribution of CP2 stars, in which the blue part is our newly found CP2 stars, the red part is all the CP2 stars known in previous literature (L.-H. Shang et al. 2022; F. Shi et al. 2023; H.-F. Yang et al. 2024), and the green part is the CP2 stars (including previous literature and our discovery).
Paper: Deep Learning-based Identification of CP1 and CP2 Stars from LAMOST DR11
Authors: ZhiWei Lu, Xiaoming Kong, YaTao Zhang, ZhenPing Yi, Meng Liu
Figure caption: Architecture of the ODCNNnet model. The arrows represent the data flow direction within the network.
Paper: Lux: A Generative, Multioutput, Latent-variable Model for Astronomical Data with Noisy Labels
Authors: Danny Horta, Adrian M. Price-Whelan, David W. Hogg, Melissa K. Ness, Andrew R. Casey
Figure caption: A comparison of APOGEE spectra (black lines) and predicted spectra from Lux (navy and cyan lines) for six stars (each panel is for one star). We use Lux to predict stellar spectra in two ways. First, we use the stellar labels for each star to infer latent representations (zn) for the test objects, and then use the model to transform latent vectors to stellar flux (navy lines). Then, as a self-test of the model, we use the spectral fluxes for each star to infer latent representations again and transform back to spectral fluxes (cyan lines). The six stars chosen are from the high-SNR fiend RGB-test sample: 2M00204904-7133587, 2M00055986+6850184, 2M00002926+5737333, 2M00101602+0154424, 2M00052512+5642535, and 2M01233689+6233205). Each row includes stars with either similar ﹩{T}_{{\rm{eff}}},\mathrm{log}\,g﹩, or [Fe/H]. These results demonstrate that Lux is able to accurately predict (and impute) stellar spectra for test objects across a wide range of stellar parameter space, either when using the stellar labels or stellar spectra in the test set.
Paper: Lux: A Generative, Multioutput, Latent-variable Model for Astronomical Data with Noisy Labels
Authors: Danny Horta, Adrian M. Price-Whelan, David W. Hogg, Melissa K. Ness, Andrew R. Casey
Figure caption: Graphical model of Lux. Here, ℓ represents labels, f represents flux, z are the latent variables, A and B represent the matrices that project the latent variables into stellar labels and stellar fluxes, respectively, s is the vector of scatter terms at every pixel to account for underestimated uncertainties in the flux measurements, and σℓ and σf represent the uncertainties in the labels and flux, respectively. See Section 3.1 for details.
Paper: Lux: A Generative, Multioutput, Latent-variable Model for Astronomical Data with Noisy Labels
Authors: Danny Horta, Adrian M. Price-Whelan, David W. Hogg, Melissa K. Ness, Andrew R. Casey
Figure caption: Reduced χ2 value for all stars in the validation/test set using the stellar fluxes. The median value (dotted line) is 1.07. These stellar fluxes are generated from the latent vectors inferred from the stellar spectra themselves. ﹩{\chi }_{{\rm{r}}}^{2}﹩ is computed as χ2 divided by the number of pixels in the spectrum. The majority of our test objects yield a ﹩{\chi }_{{\rm{r}}}^{2}﹩ around unity, indicating that the Lux model is a good fit and the extent of the match between the observed (APOGEE) stellar spectra and estimates from the Lux model are in accord with the error variance.
Paper: Lux: A Generative, Multioutput, Latent-variable Model for Astronomical Data with Noisy Labels
Authors: Danny Horta, Adrian M. Price-Whelan, David W. Hogg, Melissa K. Ness, Andrew R. Casey
Figure caption: A flowchart summarizing the optimization scheme for our application of the linear Lux model to APOGEE data, described in Section 4.2.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: We remind the reader that a CLEAN algorithm was not used in the image reconstruction procedure (owing to the impossibility of direct visibility phase measurement in the infrared through Earth’s atmosphere). Nevertheless, a “dirty beam” map still may still provide some readers with insights related to interferometric resolution (size of the “primary beam,” compare to the beam size in Figures 8–15) as well as a vague qualitative notion of the liable morphology of imaging artifacts.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Summary of observations and model fits to the 2019 July 20 (MIRC-X and PIONIER) epoch data. See the caption in Figure 8 for an explanation of what is depicted in the panels.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Summary of observations and model fits to the 2019 July 10 (PIONIER only) epoch data. See the caption in Figure 8 for an explanation of what is depicted in the panels.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Summary of observations and model fits to the 2019 June 10 (MIRC-X in polarimetric mode) epoch data. See the caption in Figure 8 for an explanation of what is depicted in the panels.
Paper: The Dynamic Inner Disk of a Planet-forming Star
Authors: Benjamin R. Setterholm, John D. Monnier, Fabien Baron, Jaehan Bae, Jacques Kluska, Stefan Kraus, Nuria Calvet, Noura Ibrahim, Evan Rich, Narsireddy Anugu, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Cyprien Lanthermann, Gail Schaefer
Figure caption: Summary of observations and model fits to the 2019 July 13 (MIRC-X) epoch data. See the caption in Figure 8 for an explanation of what is depicted in the panels.
Paper: Open-source High-resolution Exoplanet Atmosphere Retrievals with POSEIDON
Authors: Ruizhe Wang, Ryan J. MacDonald, Neale P. Gibson, Nikole K. Lewis
Figure caption: Panel 1: The observation injected with an enhanced signal (to be seen by eye for demonstration purposes). In this paper, red color theme is used for emission spectroscopy (left column) and blue is used for transmission spectroscopy (right column). Panel 2 left: Red consists of the background contribution from star, noise, and instrumental effects. Fp are injected planet signals at different phases. They highlight the wavelength-shifting nature of planet signals. Panel 2 right and Panel 3 left: Injected data after filtering. We can clearly see the shifting lines in the residuals. This is to be compared with the filtered models during retrieval. Panel 3 right: Vertical slices of panel 2 right at selected wavelengths. Each wavelength channel is a noisy light curve with continuum 1, where the deeper transit depths are from the absorption features. Panel 4 left: Example of a noiseless, idealistic data consisting of stellar flux and shifting planetary flux only. Panel 4 right: Injected models after filtering. This is to be compared with the residual data during retrieval. Panel 5 left: The stellar flux and shifting planetary flux of the noiseless data shown in panel 4 left. Panel 5 right: Unit-less visualization of data and model at different stages. The similarity between filtered models and filtered data shows the effectiveness of our filtering process.
Paper: Open-source High-resolution Exoplanet Atmosphere Retrievals with POSEIDON
Authors: Ruizhe Wang, Ryan J. MacDonald, Neale P. Gibson, Nikole K. Lewis
Figure caption: Upper: Detection significance as a function of Kp and ΔVsys. White dashed lines indicate the literature values and the marker denotes the location of the peak signal. Lower: Cross-correlation value divided by the standard deviation per row, as a function of phase and radial velocity in planet rest frame. The slope of the trail is approximately Kp. Phase-folding the matrix assuming a Kp would yield a single row of the Kp-Vsys map. Left (reddish) is the cross-correlation result applying emission spectroscopy to WASP-77Ab with a template model containing H2O, CO. Right (blueish) is the cross-correlation result applying transmission spectroscopy to WASP-121b with a template model containing all species detected in the retrieval (Fe, Cr, V, Mg).
Paper: Open-source High-resolution Exoplanet Atmosphere Retrievals with POSEIDON
Authors: Ruizhe Wang, Ryan J. MacDonald, Neale P. Gibson, Nikole K. Lewis
Figure caption: Results of the retrieval for the IGRINS WASP-77Ab data. See Appendix Figure 13 for full corner plots. Blue lines are median retrieved values from M. R. Line et al. (2021). Note that fixing planet radius and the choice of filtering methods can slightly offset the results.
Paper: Open-source High-resolution Exoplanet Atmosphere Retrievals with POSEIDON
Authors: Ruizhe Wang, Ryan J. MacDonald, Neale P. Gibson, Nikole K. Lewis
Figure caption: Detection significance (S/N) versus number of PCA iterations. Unlike C. J. Cheverall et al. (2023), we do not find that detection strengths decay as more principal components are removed, nor do we find a significant advantage for one approach over the others. We therefore use 10 iterations throughout our analysis. A data-driven approach, which halts the iterations when the variance of the residuals plateau, provides a similar number.
Paper: Open-source High-resolution Exoplanet Atmosphere Retrievals with POSEIDON
Authors: Ruizhe Wang, Ryan J. MacDonald, Neale P. Gibson, Nikole K. Lewis
Figure caption: Upper panel: The raw UVES observation of WASP-121b. Middle Panel: The observation after blaze correction. The transmission features of the planet are buried under the background and noise. Lower panel: Residual after filtering.
Paper: Open-source High-resolution Exoplanet Atmosphere Retrievals with POSEIDON
Authors: Ruizhe Wang, Ryan J. MacDonald, Neale P. Gibson, Nikole K. Lewis
Figure caption: Upper panel: Example transmission spectra shifted according to planet velocities at each phase weighted by the transit shape. Notice out-of-transit spectra are equal to 1. Lower panel: Removing the transit shape by dividing the median of wavelength for each phase.
Paper: Open-source High-resolution Exoplanet Atmosphere Retrievals with POSEIDON
Authors: Ruizhe Wang, Ryan J. MacDonald, Neale P. Gibson, Nikole K. Lewis
Figure caption: Detection significance (S/N) versus the size of the square mask used when calculating the standard deviation of the CCF map. The standard deviation is calculated after clipping values outside 3σ for the blue curve, in addition to applying the square mask centered at the expected velocity.
Paper: Open-source High-resolution Exoplanet Atmosphere Retrievals with POSEIDON
Authors: Ruizhe Wang, Ryan J. MacDonald, Neale P. Gibson, Nikole K. Lewis
Figure caption: Upper panel: The reduced IGRINS observation of WASP-77Ab. The flux at each phase is calibrated to the same level. The emission signal of WASP-77Ab is buried under the background and noise. Lower panel: Residual after removing the first four principal components. The residual should be a good representation of the signal.
Paper: Open-source High-resolution Exoplanet Atmosphere Retrievals with POSEIDON
Authors: Ruizhe Wang, Ryan J. MacDonald, Neale P. Gibson, Nikole K. Lewis
Figure caption: Example high-resolution transmission and emission forward models. Left: Emergent flux with ﹩\mathrm{log}{X}_{{{\rm{H}}}_{2}{\rm{O}}}=-6﹩. Right: Transmission spectrum with ﹩\mathrm{log}{X}_{{\rm{Fe}}}=-6﹩. Models scaled by α = 2 and models with doubled abundances are over-plotted for comparison. Models convolved by a Gaussian kernel with width 3 are also plotted.
Paper: Origins of Super Jupiters: TOI-2145b has a Moderately Eccentric and Nearly Aligned Orbit
Authors: Jiayin Dong, Ashley Chontos, George Zhou, Gudmundur Stefansson, Songhu Wang, Chelsea X. Huang, Arvind F. Gupta, Samuel Halverson, Shubham Kanodia, Jacob K. Luhn, Suvrath Mahadevan, Andrew Monson, Jaime A. Alvarado-Montes, Joe P. Ninan, Paul Robertson, Arpita Roy, Christian Schwab, Jason T. Wright
Figure caption: Mass and orbital properties of the innermost warm Jupiter in low-disk-mass and high-disk-mass scenarios. TOI-2145b is labeled as a red cross. Both planets born in a low-mass disk followed by collisions and in a high-mass disk followed by scatterings could explain the current properties of TOI-2145b.
Paper: Origins of Super Jupiters: TOI-2145b has a Moderately Eccentric and Nearly Aligned Orbit
Authors: Jiayin Dong, Ashley Chontos, George Zhou, Gudmundur Stefansson, Songhu Wang, Chelsea X. Huang, Arvind F. Gupta, Samuel Halverson, Shubham Kanodia, Jacob K. Luhn, Suvrath Mahadevan, Andrew Monson, Jaime A. Alvarado-Montes, Joe P. Ninan, Paul Robertson, Arpita Roy, Christian Schwab, Jason T. Wright
Figure caption: Same as Figure 2 but for the NEID’s second RM-effect visit on 2023 July 6.
Paper: Origins of Super Jupiters: TOI-2145b has a Moderately Eccentric and Nearly Aligned Orbit
Authors: Jiayin Dong, Ashley Chontos, George Zhou, Gudmundur Stefansson, Songhu Wang, Chelsea X. Huang, Arvind F. Gupta, Samuel Halverson, Shubham Kanodia, Jacob K. Luhn, Suvrath Mahadevan, Andrew Monson, Jaime A. Alvarado-Montes, Joe P. Ninan, Paul Robertson, Arpita Roy, Christian Schwab, Jason T. Wright
Figure caption: Spin–orbit coupling factor ϵ ⋆1 between TOI-2145 and TOI-2145b given different perturber properties. Here, we assume a stellar rotation rate of 5 days. The dashed line corresponds to ϵ ⋆1 = 0.1. Perturbers above the line are unlikely to excite the mutual inclination of the inner planet due to spin–orbit coupling.
Paper: CO Isotopologue-derived Molecular Gas Conditions and CO-to-H2 Conversion Factors in M51
Authors: Jakob den Brok, María J. Jiménez-Donaire, Adam Leroy, Eva Schinnerer, Frank Bigiel, Jérôme Pety, Glen Petitpas, Antonio Usero, Yu-Hsuan Teng, Pedro Humire, Eric W. Koch, Erik Rosolowsky, Karin Sandstrom, Daizhong Liu, Qizhou Zhang, Sophia Stuber, Mélanie Chevance, Daniel A. Dale, Cosima Eibensteiner, Ina Galić, Simon C. O. Glover, Hsi-An Pan, Miguel Querejeta, Rowan J. Smith, Thomas G. Williams, David J. Wilner, Valencia Zhang
Figure caption: Analysis of the CO-to-H2 conversion factor. (Left panel) The non-LTE-derived ﹩{\alpha }_{{}^{12}\mathrm{CO}(1-0)}﹩ correlated with the 12CO(1–0) line dispersion. The red line indicates a regression fit. For reference, we also indicate the Y.-H. Teng et al. (2023) and Y.-H. Teng et al. (2024) regression fits (after accounting for differences in the assumed CO-to-H2 abundance values) with the blue- and orange-dashed lines, which were obtained using a sample of three barred and 12 nearby star-forming galaxies, respectively. (Right panel) The non-LTE-derived ﹩{\alpha }_{{}^{12}\mathrm{CO}(1-0)}﹩ correlated with the observed 13CO-to-12CO ratio, ﹩{R}_{10}^{13/12}﹩. The red line again shows a regression fit to the measurements of M51.