adsabs/AstroCLIMB huggingface dataset:
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: The γ posterior distributions for fitting the fiducial stream-track observations with (purple) and without (blue) a RV measurement in ΦPL with σtrack = 1 kpc. Adding a RV to the fit shifts the posterior distribution closer to the truth.
Paper: The End of the Road for Far-infrared Reddening Maps? Evidence for Reddening Errors Driven by Changes in Polycyclic Aromatic Hydrocarbon Abundance
Authors: Dennis Lee, Brandon S. Hensley, Tzu-Ching Chang, Olivier Doré
Figure caption: Left: PAH dust grain size from the astrodust+PAH dust grain model (B. S. Hensley & B. T. Draine 2023) as a function of effective radius a. The solid black line indicates the initial PAH size distribution (ΔMPAH/MPAH,init = 0). Distributions with increased PAH mass due to accretion with ΔMPAH/MPAH,init = 1, 5, and 10 are plotted as dotted, dashed–dotted, and dashed black lines, respectively. Right: change in extinction and emission as a function of increasing PAH mass (ΔMPAH/MPAH,init). The changes in various extinction properties are shown as dashed lines while the emission at various wavelengths is shown as solid lines. As PAH mass grows, the emission at 100 μm and at 350 μm (857 GHz) is only weakly sensitive to the resulting increase in E(B − V), while the emission at 3.3 μm and in the WISE W3 band at 12 μm is highly responsive. The process of PAH growth by accretion results in the loss of the relatively small PAH population that is responsible for the 3.3 μm emission. This results in a decrease in emission with increasing PAH mass fraction. The WISE W3 band emission at 12 μm largely originates from the comparatively larger PAHs. Unlike the emission at 3.3 μm, emission in this band increases with increasing PAH mass fraction as accretion progresses.
Paper: The End of the Road for Far-infrared Reddening Maps? Evidence for Reddening Errors Driven by Changes in Polycyclic Aromatic Hydrocarbon Abundance
Authors: Dennis Lee, Brandon S. Hensley, Tzu-Ching Chang, Olivier Doré
Figure caption: Galaxy density per deg2 of the DESI ELG_LOP galaxy sample selected using various reddening maps. The galaxy density is median subtracted to emphasize the degree of uniformity. The Ursa Major cloud can be seen clearly in the underestimates of the galaxy sample maps obtained using the SFD, Planck-857, and MF15 maps. On the other hand, the galaxy samples created using the DESI and Gaia reddening maps generally show less spatial correlation with the Ursa Major cloud. The WISE W3, while still showing some spatial correlation, shows comparatively less when compared to the SFD, Planck-857, and MF15 maps.
Paper: The End of the Road for Far-infrared Reddening Maps? Evidence for Reddening Errors Driven by Changes in Polycyclic Aromatic Hydrocarbon Abundance
Authors: Dennis Lee, Brandon S. Hensley, Tzu-Ching Chang, Olivier Doré
Figure caption: Top: difference between the SFD and DESI reddening maps in the shared footprint. The black outline indicates the Ursa Major region where SFD underestimates the extinction compared to DESI. Bottom: a zoom in of the difference the SFD and DESI reddening maps is shown on the left. Also shown are the E(B − V) (center) and RV (right) as measured by Gaia for the Ursa Major region. The SFD reddening map underestimates the extinction in the Ursa Major region where the value of RV is lower.
Paper: The End of the Road for Far-infrared Reddening Maps? Evidence for Reddening Errors Driven by Changes in Polycyclic Aromatic Hydrocarbon Abundance
Authors: Dennis Lee, Brandon S. Hensley, Tzu-Ching Chang, Olivier Doré
Figure caption: Median-subtracted ELG_LOP galaxy sample density vs. qPAH for each reddening map. The Pearson correlation coefficient r is also shown. Both the SFD and Planck-857 reddening maps produce galaxy samples that are strongly correlated with qPAH.
Paper: The End of the Road for Far-infrared Reddening Maps? Evidence for Reddening Errors Driven by Changes in Polycyclic Aromatic Hydrocarbon Abundance
Authors: Dennis Lee, Brandon S. Hensley, Tzu-Ching Chang, Olivier Doré
Figure caption: Posterior distributions for the contributions from the mid-infrared and the far-infrared to AB and AV. ﹩{A}_{V}^{{\rm{MIR}}}﹩ and ﹩{A}_{B}^{{\rm{MIR}}}﹩ are in units of magnitudes per MJy sr−1, while ﹩{A}_{V}^{{\rm{FIR}}}﹩ and ﹩{A}_{B}^{{\rm{FIR}}}﹩ are in units of magnitudes per E(B − V) magnitude. The median of the marginal distributions and the upper and lower quantiles are shown.
Paper: Inferring the Magnetic Field Configuration of an ICME From the In Situ Observations at Different Points
Authors: Dongwei Mao, Chenglong Shen, Yutian Chi, Junyan Liu, Mengjiao Xu, Zhihui Zhong, Zhiyong Zhang, Can Wang, Yuming Wang
Figure caption: Interplanetary magnetic field (IMF) and solar wind data of Event1 at STA. The variables are transferred to a new coordinate system related with RTN coordinate. The x-axis and y-axis are along the −R and −T directions of RTN, and the z-axis remains in the same direction of N. From top to bottom, the panels display total IMF, z component of IMF, latitudinal angle of IMF, longitudinal angle of IMF, bulk solar wind speed, number density of protons, and proton temperature (Tp, black curve) along with the ratio of proton temperature and experimental temperature calculated from solar wind speed (Tp/Texp, red curve; I. G. Richardson & H. V. Cane 1995) and plasma β. Black vertical lines refer to the beginning and ending of the ICME, and blue curves show the flux rope fitting results.
Paper: Prestellar Cores in Turbulent Clouds: Observational Perspectives on Structure, Kinematics, and Lifetime
Authors: Sanghyuk Moon, Eve C. Ostriker
Figure caption: The average duration that prestellar cores spend above each central density bin, obtained by taking the ratio of the number of prestellar cores above each bin to the number of Class II YSOs, multiplied by the reference timescale of ΔtII = 2 Myr. The individual cloud names are annotated on top of each panel. Two dashed lines mark tff and 10tff.
Paper: Inferring the Magnetic Field Configuration of an ICME From the In Situ Observations at Different Points
Authors: Dongwei Mao, Chenglong Shen, Yutian Chi, Junyan Liu, Mengjiao Xu, Zhihui Zhong, Zhiyong Zhang, Can Wang, Yuming Wang
Figure caption: The observations and MFCI model calculation results of the example event at VEX. Panels from top to bottom are total IMF strength, z component of IMF in the VSO coordinate, latitudinal angle of IMF, longitudinal angle of IMF, and the distance from the spacecraft to Venus surface. Black curves show the in situ data from VEX and data when VEX was inside the magnetosphere are excluded. Red curves show the IMF estimation from the MFCI model, and sky blue curves show the ensemble results obtained by sampling input parameters in Table 1. Shadowed parts show the duration of the ICME from in situ data.
Paper: Inferring the Magnetic Field Configuration of an ICME From the In Situ Observations at Different Points
Authors: Dongwei Mao, Chenglong Shen, Yutian Chi, Junyan Liu, Mengjiao Xu, Zhihui Zhong, Zhiyong Zhang, Can Wang, Yuming Wang
Figure caption: The position of VEX (blue diamond), STEREO-A (red diamond), and the Sun (golden circle) at the time of event1 and the flux rope axis direction (blue and red arrows) at both spacecraft. The x-axis is along the Sun–STEREO-A line, and the z-axis is along the N-axis of RTN coordinate at STEREO-A. Panel (a) shows the projection in the x–y plane, and panel (b) in the y–z plane. A longitudinal separation of ﹩10\mathop{.}\limits^{^\circ }6﹩ lies between the spacecraft.
Paper: Inferring the Magnetic Field Configuration of an ICME From the In Situ Observations at Different Points
Authors: Dongwei Mao, Chenglong Shen, Yutian Chi, Junyan Liu, Mengjiao Xu, Zhihui Zhong, Zhiyong Zhang, Can Wang, Yuming Wang
Figure caption: A sketch of the Magnetic Field Configuration Inferring (MFCI) model. Four panels show the stages of the model. Green rectangles represent the input and output data; blue ones represent the time of arrival (ToA) and duration evolution part; and yellow ones represent the flux rope parameter evolution part. Input ICME parameters include flux rope parameters and time of arrival at 1 au (shown in Table 1), and the evolution is calculated with self-similar expansion and drag-based model separately.
Paper: Prestellar Cores in Turbulent Clouds: Observational Perspectives on Structure, Kinematics, and Lifetime
Authors: Sanghyuk Moon, Eve C. Ostriker
Figure caption: Similar to Figure 14, but using the average density derived from the “deconvolved” (solid) and observed (dashed) RFWHM as reported in the HGBS catalog.
Paper: Inferring the Magnetic Field Configuration of an ICME From the In Situ Observations at Different Points
Authors: Dongwei Mao, Chenglong Shen, Yutian Chi, Junyan Liu, Mengjiao Xu, Zhihui Zhong, Zhiyong Zhang, Can Wang, Yuming Wang
Figure caption: A sketch of the position of observers at the time of Event1, generated with the website Solar-Mach (J. Gieseler et al. 2023). The longitude of observers are in Stonyhurst coordinates.
Paper: Inferring the Magnetic Field Configuration of an ICME From the In Situ Observations at Different Points
Authors: Dongwei Mao, Chenglong Shen, Yutian Chi, Junyan Liu, Mengjiao Xu, Zhihui Zhong, Zhiyong Zhang, Can Wang, Yuming Wang
Figure caption: A sketch of the geometric relations between the spacecraft trajectory and the flux rope.
Paper: Extreme Geomagnetic Storm on the Early Earth Induced by Corotating Interaction Regions from the Young Sun
Authors: Dibyendu Sur, Vladimir S. Airapetian
Figure caption: Cases of northern hemispheric integrated energy fluxes from precipitating electrons during (a) a period of high proton density, and (b) a period of high stellar wind speed.
Paper: Extreme Geomagnetic Storm on the Early Earth Induced by Corotating Interaction Regions from the Young Sun
Authors: Dibyendu Sur, Vladimir S. Airapetian
Figure caption: Northern hemispheric polar cap boundary during periods of lower and higher dynamic pressure and positive and negative stellar magnetic field By, as obtained from SWMF simulation.
Paper: Extreme Geomagnetic Storm on the Early Earth Induced by Corotating Interaction Regions from the Young Sun
Authors: Dibyendu Sur, Vladimir S. Airapetian
Figure caption: (a) Hemispherically integrated Joule heating rates as obtained from SWMF simulation. (b) Correlation of dynamic pressure and northern hemispherically integrated Joule heating rates.
Paper: Extreme Geomagnetic Storm on the Early Earth Induced by Corotating Interaction Regions from the Young Sun
Authors: Dibyendu Sur, Vladimir S. Airapetian
Figure caption: (a) Integrated energy flux from SWMF (RCM) electron precipitation in the northern hemisphere during periods of high dynamic pressure. Corresponding FAC (b), and ionospheric height-integrated Hall and Pedersen conductances (c) and (d) are also shown.
Paper: Extreme Geomagnetic Storm on the Early Earth Induced by Corotating Interaction Regions from the Young Sun
Authors: Dibyendu Sur, Vladimir S. Airapetian
Figure caption: SYMH as obtained from SWMF simulation.
Paper: Extreme Geomagnetic Storm on the Early Earth Induced by Corotating Interaction Regions from the Young Sun
Authors: Dibyendu Sur, Vladimir S. Airapetian
Figure caption: (a) SWMF current density in the planetary magnetosphere at the XY plane (b) Temporal variations of total SYMH and SYMH driven by the RCM ring current.
Paper: Extreme Geomagnetic Storm on the Early Earth Induced by Corotating Interaction Regions from the Young Sun
Authors: Dibyendu Sur, Vladimir S. Airapetian
Figure caption: Integrated energy flux from SWMF electron precipitation in the northern hemisphere during a period of positive stellar magnetic field Bz and low By with high proton density, dynamic pressure, and stellar wind speed.
Paper: Extreme Geomagnetic Storm on the Early Earth Induced by Corotating Interaction Regions from the Young Sun
Authors: Dibyendu Sur, Vladimir S. Airapetian
Figure caption: Temporal variations of CPCP from the main simulation and simulation2 (from viscous interaction only) alongside the dynamic pressure.
Paper: Extreme Geomagnetic Storm on the Early Earth Induced by Corotating Interaction Regions from the Young Sun
Authors: Dibyendu Sur, Vladimir S. Airapetian
Figure caption: CPCP as obtained from SWMF simulation.
Paper: Characterizing the Star Cluster Populations in Stephan’s Quintet Using HST and JWST Observations
Authors: P. Aromal, S. C. Gallagher, K. Fedotov, N. Bastian, U. Lisenfeld, J. C. Charlton, P. N. Appleton, J. Braine, K. E. Johnson, P. Tzanavaris, B. H. C. Emonts, A. Togi, C. K. Xu, P. Guillard, L. Barcos-Muñoz, L. J. Smith, I. S. Konstantopoulos
Figure caption: The total intensity (moment 0) map of CO(2–1) molecular emission obtained with ACA (B. H. C. Emonts et al. 2025), overlaid on the spatial distribution of young SCCs (τ < 107 yr) across the field, color coded by region of interest. The SCCs whose ages shifted to <107 yr after including NIR photometry (from initial HST-based estimates of >108 yr) are highlighted with star symbols, outlined in white for clarity. The contour levels start at 0.4 Jy beam−1 × km s−1 and increase by a factor ﹩\sqrt{2}﹩. The background is the HST WFC3 image taken in the V606 filter (K. Fedotov et al. 2011).
Paper: ML-driven Strong Lens Discoveries: Down to θE﹩\,\sim \,0\mathop{.}\limits^{\unicode{x02033}}03﹩ and Mhalo < 1011M⊙
Authors: Ethan Silver, R. Wang, Xiaosheng Huang, Adam S. Bolton, Christopher J. Storfer, S. Banka
Figure caption: Correctly classified lenses for Model 3 (JWST-small) (﹩0\mathop{.}\limits^{^{\prime\prime} }02\lt {\theta }_{{\rm{E}}}\lt 0\mathop{.}\limits^{^{\prime\prime} }15﹩), or true positives. Four examples are shown, with one system in each row. The four columns show (A) the full image seen by the ResNet, (B) the image with the lens light removed, (C) the image with the lens light and environmental galaxies removed (i.e., just the lensed source), and (D) the original unlensed source. The white crosshairs show the location of the lens. With the lens light removed, one sometimes (e.g., for the systems in the second and third rows) can see a small “dimple” (essentially, a small Einstein ring) in the second and third columns. On the left, for each image, we show the Einstein radius, the lens and source redshifts, the halo and stellar masses for the lensing galaxy as well as the projected mass within θE (﹩{M}_{{\theta }_{{\rm{E}}}}﹩), and the probability assigned by the ResNet. Note that for the system in the third row, the projected mass within θE is nearly 2 orders of magnitude smaller than that for the lensed SN Zwicky.
Paper: ML-driven Strong Lens Discoveries: Down to θE﹩\,\sim \,0\mathop{.}\limits^{\unicode{x02033}}03﹩ and Mhalo < 1011M⊙
Authors: Ethan Silver, R. Wang, Xiaosheng Huang, Adam S. Bolton, Christopher J. Storfer, S. Banka
Figure caption: These four panels illustrate the numbers we forecast for low-mass lenses (Mhalo < 1011M⊙) that are detectable. The top row shows histograms of the overall forecast of lens numbers (using the methods from Section 2), as a function of Einstein radius. The top-left panel shows ﹩0\mathop{.}\limits^{^{\prime\prime} }02\lt {\theta }_{{\rm{E}}}\lt 1\mathop{.}\limits^{^{\prime\prime} }50﹩ and the top-right panel shows the zoom-in on the range ﹩0\mathop{.}\limits^{^{\prime\prime} }02\lt {\theta }_{{\rm{E}}}\lt 0\mathop{.}\limits^{^{\prime\prime} }15﹩. The bottom-left and -right panels show the fractions and numbers, respectively, of lenses with Mhalo < 1011M⊙ that are detectable by Model 3 (JWST-small) at a 0.96 probability threshold (with zero false positives). Note that for the lower-right panel, the forecast numbers from Method A contribute minimally to this category, as expected.
Paper: ML-driven Strong Lens Discoveries: Down to θE﹩\,\sim \,0\mathop{.}\limits^{\unicode{x02033}}03﹩ and Mhalo < 1011M⊙
Authors: Ethan Silver, R. Wang, Xiaosheng Huang, Adam S. Bolton, Christopher J. Storfer, S. Banka
Figure caption: Precision and recall for Model 3 (JWST-small) as a function of probability threshold, with selected values shown in Table 7 below. The solid lines show the performance on the original validation set, using Type 1 non-lenses. For actual searches for these low-mass lenses, the more relevant metrics are the dotted lines, showing the performance on the original validation set with Type 2 non-lenses (see Section 3.1.2). Because only the non-lenses differ, the recall is identical for the Type 1 and Type 2 non-lenses. Note that at these very high precisions, there are a very small number of false positives, so the jumps in precision are caused by individual false positives being removed.
Paper: ML-driven Strong Lens Discoveries: Down to θE﹩\,\sim \,0\mathop{.}\limits^{\unicode{x02033}}03﹩ and Mhalo < 1011M⊙
Authors: Ethan Silver, R. Wang, Xiaosheng Huang, Adam S. Bolton, Christopher J. Storfer, S. Banka
Figure caption: Performance of Model 3 (JWST-small) with ﹩0\mathop{.}\limits^{^{\prime\prime} }02\lt {\theta }_{{\rm{E}}}\lt 0\mathop{.}\limits^{^{\prime\prime} }15﹩ as a function of Einstein radius, at a threshold of 0.5. The columns at ﹩{\theta }_{{\rm{E}}}=0\mathop{.}\limits^{^{\prime\prime} }0﹩ correspond to non-lenses. Therefore, on the left plot, the column at ﹩{\theta }_{{\rm{E}}}=0\mathop{.}\limits^{^{\prime\prime} }0﹩ shows the fraction of non-lenses misclassified as lenses, and the other columns show the fraction of lenses misclassified as non-lenses.
Paper: ML-driven Strong Lens Discoveries: Down to θE﹩\,\sim \,0\mathop{.}\limits^{\unicode{x02033}}03﹩ and Mhalo < 1011M⊙
Authors: Ethan Silver, R. Wang, Xiaosheng Huang, Adam S. Bolton, Christopher J. Storfer, S. Banka
Figure caption: Incorrectly classified lenses for Model 3 (JWST-small) (﹩0\mathop{.}\limits^{^{\prime\prime} }02\lt {\theta }_{{\rm{E}}}\lt 0\mathop{.}\limits^{^{\prime\prime} }15﹩), or lenses misclassified as non-lenses (false negatives). The arrangement of the columns and the information shown on the left are the same as for Figure 15. In these cases, the ResNet probabilities are all below the threshold (0.5).
Paper: ML-driven Strong Lens Discoveries: Down to θE﹩\,\sim \,0\mathop{.}\limits^{\unicode{x02033}}03﹩ and Mhalo < 1011M⊙
Authors: Ethan Silver, R. Wang, Xiaosheng Huang, Adam S. Bolton, Christopher J. Storfer, S. Banka
Figure caption: Incorrectly classified non-lenses for Model 3 (JWST-small) (﹩0\mathop{.}\limits^{^{\prime\prime} }02\lt {\theta }_{{\rm{E}}}\lt 0\mathop{.}\limits^{^{\prime\prime} }15﹩), or non-lenses misclassified as lenses (false positives). The arrangement of the columns and the information shown on the left are nearly the same as for Figure 15: here, there are three columns: (A) the full image seen by the ResNet, (B) the image with the light of the overlapping galaxy removed, and (C) the image with the overlapping galaxy light and environmental galaxies removed (i.e., just the source). Here, the white crosshairs show the location of the overlapping galaxy. These are non-lenses, so θE = 0.
Paper: ML-driven Strong Lens Discoveries: Down to θE﹩\,\sim \,0\mathop{.}\limits^{\unicode{x02033}}03﹩ and Mhalo < 1011M⊙
Authors: Ethan Silver, R. Wang, Xiaosheng Huang, Adam S. Bolton, Christopher J. Storfer, S. Banka
Figure caption: The forecast mass distribution of halos with ﹩0\mathop{.}\limits^{^{\prime\prime} }02\lt {\theta }_{{\rm{E}}}\lt 0\mathop{.}\limits^{^{\prime\prime} }15﹩. Note that these histograms make it clear that the condition of Mhalo < 1011M⊙ essentially implies ﹩0\mathop{.}\limits^{^{\prime\prime} }02\lt {\theta }_{{\rm{E}}}\lt 0\mathop{.}\limits^{^{\prime\prime} }05﹩. However, the inverse is not true: there are many systems with θE in that smallest bin, but the lens halo mass is >1011M⊙.
Paper: ML-driven Strong Lens Discoveries: Down to θE﹩\,\sim \,0\mathop{.}\limits^{\unicode{x02033}}03﹩ and Mhalo < 1011M⊙
Authors: Ethan Silver, R. Wang, Xiaosheng Huang, Adam S. Bolton, Christopher J. Storfer, S. Banka
Figure caption: Two examples of simulated systems (in the context of Model 3 (JWST-small)) with a similar Einstein radius around ﹩0\mathop{.}\limits^{^{\prime\prime} }03﹩. The left system has a low mass, and the right system has a mass almost 2 orders of magnitude larger. This is because the left system has a redshift configuration that is much more favorable to lensing than the right system.
Paper: ML-driven Strong Lens Discoveries: Down to θE﹩\,\sim \,0\mathop{.}\limits^{\unicode{x02033}}03﹩ and Mhalo < 1011M⊙
Authors: Ethan Silver, R. Wang, Xiaosheng Huang, Adam S. Bolton, Christopher J. Storfer, S. Banka
Figure caption: AUC and loss curves for Model 3 (JWST-small) with ﹩0\mathop{.}\limits^{^{\prime\prime} }02\lt {\theta }_{{\rm{E}}}\lt 0\mathop{.}\limits^{^{\prime\prime} }15﹩. For the non-lenses, light for the foreground galaxy is included in the simulation. This makes the training more challenging (see Section 3.1.2).
Paper: Measuring the Two-dimensional Thermal Structures of Protoplanetary Disks
Authors: Anna J. Fehr, Sean M. Andrews
Figure caption: The left panel shows an example full model resolution channel map from the CO J = 2–1 emission cube. The white line shows the major axis. The top-right panel shows the radial intensity profile of the front surface along the major axis, with dashed lines at r1 and r2 (where the intensity is half the maximum intensity) and rK (the radius where the projected Keplerian velocity is equal to the channel velocity). The three panels on the bottom right show the spectrum of the front surface at the pixels corresponding to r1, rK, and r2, relative to the velocity of the example channel. The spectrum at rK peaks at the channel velocity, while the channel velocity has half the maximum intensity at r1 and r2 (the channel velocity is vpeak ± vFWHM/2).
Paper: Measuring the Two-dimensional Thermal Structures of Protoplanetary Disks
Authors: Anna J. Fehr, Sean M. Andrews
Figure caption: Surfaces extracted using disksurf from the J = 2–1 emission cubes of CO, 13CO, and C18O. The black dashed lines show the true τ = 2/3 surface, the blue points show the binned surface points and standard deviations extracted from the convolved, noiseless cube, and the orange points are the same for the convolved, noisy (rms = 2 mJy beam−1) cube. The gray ellipses show the projected beam size (﹩0\mathop{.}\limits^{^{\prime\prime} }1﹩ on the sky).
Paper: Measuring the Two-dimensional Thermal Structures of Protoplanetary Disks
Authors: Anna J. Fehr, Sean M. Andrews
Figure caption: The extracted radial temperature profile (top panel) and azimuthal temperature profiles in annuli (bottom panels) for the CO J = 2–1 emission cube. In the top panel, the orange lines and points show the azimuthally averaged brightness temperature, while the blue shows the brightness temperature along the major axis. The lines show extractions from the noiseless cubes, while the points are extracted from the noisy cubes. The black dashed line shows the gas temperature at the τ = 2/3 surface, and the shaded gray region shows where τ < 5. In the bottom panels, the light-orange line shows the azimuthal average, and the blue points are along the major axis.
Paper: Measuring the Two-dimensional Thermal Structures of Protoplanetary Disks
Authors: Anna J. Fehr, Sean M. Andrews
Figure caption: Results of the vertical temperature inference using accurate emission surfaces and radial temperature profiles with nominal uncertainties. The leftmost column shows the median inferred temperatures, the second column shows σT/Tgas (precision), the third column shows ΔT/σT (accuracy), and the rightmost column shows ΔT. The solid black lines show the emission surfaces included in each inference.
Paper: Measuring the Two-dimensional Thermal Structures of Protoplanetary Disks
Authors: Anna J. Fehr, Sean M. Andrews
Figure caption: The model τlos = 2/3 surfaces (left panel) and corresponding radial temperature profiles along those surfaces (right panel) for the J = 1–0, 2–1, and 3–2 emission lines. In this model, the CO emission surfaces are all proximate to the CO photodissociation surface, while the isotopologue surfaces span a range of elevations.