adsabs/AstroCLIMB huggingface dataset:
Paper: A Large (≈ 1 pc) Contracting Envelope Around the Prestellar Core L1544 
Authors: Elena Redaelli, Ana Chacón-Tanarro, Paola Caselli, Mario Tafalla, Jaime E. Pineda, Silvia Spezzano, Olli Sipilä
Figure caption: The red curve shows the synthetic spectrum of HCO+ (1–0) obtained with a model with n env = 50 cm−3, X env(HCO+) = 10−8, and otherwise identical to that used to produce the rightmost panel of Figure 7. The black histogram shows the observed spectrum at the dust peak of L1544.
Paper: A Large (≈ 1 pc) Contracting Envelope Around the Prestellar Core L1544 
Authors: Elena Redaelli, Ana Chacón-Tanarro, Paola Caselli, Mario Tafalla, Jaime E. Pineda, Silvia Spezzano, Olli Sipilä
Figure caption: Synthetic spectra of HCO+ (1–0) obtained with MOLLIE for the physical model with the extended 1.0 pc envelope with a volume density of n env = 27 cm−3, at three distinct infall velocities, from left to right: V env = 0 (static envelope, magenta histogram), V env = −0.025  km s−1 (light-blue histogram), and V env = −0.05 km s−1 (red histogram). The observed spectrum is shown with a black histogram and gray shadow.
Paper: A Large (≈ 1 pc) Contracting Envelope Around the Prestellar Core L1544 
Authors: Elena Redaelli, Ana Chacón-Tanarro, Paola Caselli, Mario Tafalla, Jaime E. Pineda, Silvia Spezzano, Olli Sipilä
Figure caption: The observed HC18O+ (1–0) spectrum is shown with the black histogram (taken from Redaelli et al. 2019). The blue and red histograms show the synthetic spectra obtained with MOLLIE using the chemical model with external A V = 2 and A V = 5, respectively.
Paper: Dust Rings and Cavities in the Protoplanetary Disks around HD 163296 and DoAr 44
Authors: Harrison Leiendecker, Hannah Jang-Condell, Neal J. Turner, Adam D. Myers
Figure caption: (a) GPI observation showing scattered light from the surface of the inner ring, taken from Monnier et al. (2017). (b) Synthetic scattered-light image of the best-fitting model. We apply a mask to the central region (shown in gray). The approximate stellar location is marked with a red circle. The GPI data were not used to determine the best-fit model, so the brightness of the outer ring and the ring locations are different between the model and data.
Paper: Dust Rings and Cavities in the Protoplanetary Disks around HD 163296 and DoAr 44
Authors: Harrison Leiendecker, Hannah Jang-Condell, Neal J. Turner, Adam D. Myers
Figure caption: Observations of HD 163296 (top) and DoAr 44 (bottom). Thermal emission images (1.3 mm) are shown on the left with a red scale, and polarized scattered-light images (J band and H band) are both shown on the right with a blue scale. Both of the thermal emission data were taken with ALMA (Andrews et al. 2018; Cieza et al. 2021). The J-band data for HD 163296 are from Gemini Planet Imager (Monnier et al. 2017). The H-band data for DoAr 44 are from SPHERE (Avenhaus et al. 2018). The two disks demonstrate some of the variety of appearances ring-like substructure may have in disks.
Paper: Dust Rings and Cavities in the Protoplanetary Disks around HD 163296 and DoAr 44
Authors: Harrison Leiendecker, Hannah Jang-Condell, Neal J. Turner, Adam D. Myers
Figure caption: Azimuthal variation of normalized intensity of the rings around HD 163296 observed with ALMA. The curves were calculated by taking the peak surface brightness for each ring at every angle. The results are normalized to compare the relative deviations between different rings. Each ring observation is plotted in color, and the corresponding best-fitting model is depicted in dashed black lines. The uncertainty of the observations is plotted as colored shading. The outer ring shows a more distinct deviation from our model predictions.
Paper: Dust Rings and Cavities in the Protoplanetary Disks around HD 163296 and DoAr 44
Authors: Harrison Leiendecker, Hannah Jang-Condell, Neal J. Turner, Adam D. Myers
Figure caption: Top: temperature map of the best-fitting model of HD 163296. The scattering surface of the disk, as determined by the model, is displayed as a dashed red line. Labeled isotherms are represented with dotted white lines. The very low density region in the upper left corner (displayed in white) does not conform to our model assumptions of well-mixed dust and thermal equilibrium between dust and gas. Therefore, the temperature cannot be properly calculated by our model in this region. Bottom: midplane temperature of the model compared to other studies (the temperature from Guidi et al. 2022 is not well constrained in the dust gaps). Our model ring locations are marked with vertical lines.
Paper: Dust Rings and Cavities in the Protoplanetary Disks around HD 163296 and DoAr 44
Authors: Harrison Leiendecker, Hannah Jang-Condell, Neal J. Turner, Adam D. Myers
Figure caption: Schematic showing the temperature map from Figure 5 and the lines of sight to the near (solid) and far side (dashed) of the rings in the model. The temperature map has been cropped to just below the disk surface, and the contour labels have been removed for clarity. Labels are placed at 60, 100, and 140 au on the right-hand side. The inner ring (orange) is warmer along the line of sight to the near side, while the outer ring (cyan) is warmer along the line of sight to the far side. This creates the respective asymmetries on the near and far sides of the disk in Figure 6.
Paper: Dust Rings and Cavities in the Protoplanetary Disks around HD 163296 and DoAr 44
Authors: Harrison Leiendecker, Hannah Jang-Condell, Neal J. Turner, Adam D. Myers
Figure caption: (a) ALMA image of the two rings in HD 163296, taken from Andrews et al. (2018). (b) Thermal emission at 1.3 mm from our best-fitting model. The masks we applied to the inner disk and the region containing the asymmetric arc are shown in gray in both images. The approximate stellar location is marked with a red circle. An ellipse marks the beam size in the upper right of the ALMA observation.
Paper: Dust Rings and Cavities in the Protoplanetary Disks around HD 163296 and DoAr 44
Authors: Harrison Leiendecker, Hannah Jang-Condell, Neal J. Turner, Adam D. Myers
Figure caption: Top: dust surface density of the best-fitting model to the ALMA observation of HD 163296. Middle: surface brightness of ALMA observation with shaded errors and best-fitting model at 1.3 mm. Bottom: surface brightness of GPI observation with shaded errors and the model in J band.
Paper: Creating the Radius Gap without Mass Loss
Authors: Eve J. Lee, Amalia Karalis, Daniel P. Thorngren
Figure caption: Left: final gas mass for each core mass. We see the steep rise in M gas for ﹩{M}_{\mathrm{core}}\lesssim {M}_{\oplus }﹩ from the isothermal limit and a slow rise in M gas up to ﹩{M}_{\mathrm{core}}\sim 10{M}_{\oplus }﹩ from accretion by cooling. After a brief sharp rise from runaway cooling, we see a plateau in M gas from global disk accretion. The uptick in M gas at ∼50M ⊕ arises from the gas accretion onto these massive cores being always limited by global disk accretion whose rate is significantly higher at early times. Middle: corresponding radius (at 3 Gyr) of the M gas curves shown on the left. Right: histogram of radius for log-uniform ﹩{M}_{\mathrm{core}}﹩ distribution (unfilled histogram) and for cores drawn from Equation (14) with δ = 0.3, and M break = 4M ⊕ (filled histogram).
Paper: Creating the Radius Gap without Mass Loss
Authors: Eve J. Lee, Amalia Karalis, Daniel P. Thorngren
Figure caption: Comparison of radius conversion methods between the analytic scheme of Lee & Connors (2021, blue solid), extrapolating the grid of Lopez & Fortney (2014, green; hereafter LF14) and the grid presented in this paper (orange solid). The analytic scheme does not take into account the self-gravity of the envelope and therefore overestimates the radius at ﹩{M}_{\mathrm{gas}}/{M}_{\mathrm{core}}\,\gtrsim 0.1﹩. LF14 grid only extends up to ﹩{M}_{\mathrm{gas}}/{M}_{\mathrm{core}}\sim 0.25﹩ (region covered by the grid plotted in solid; extrapolation in dashed). Using the radius calculation presented in this work, we see a slight downturn in the radius at ﹩{M}_{\mathrm{gas}}/{M}_{\mathrm{core}}\sim 300﹩ (equivalent to ∼5M jup) as we approach the brown dwarf regime.
Paper: Creating the Radius Gap without Mass Loss
Authors: Eve J. Lee, Amalia Karalis, Daniel P. Thorngren
Figure caption: Radius distribution of 5000 planets (evaluated at 3 Gyr) for bottom-heavy (δ = −0.3) and top-heavy (δ = 0.3) core mass distributions with M break = 4M ⊕ with a cutoff in the low-mass end ﹩{M}_{{\rm{c}},\min }﹩ at 0.3M ⊕ (top) and 0.5M ⊕ (bottom). While both distributions consistently produce a gap at ∼1–2 R ⊕ and a peak at ∼2–3 R ⊕, the radius peak of the δ = −0.3 is sharper and is shifted slightly toward lower radius. Plotted in dashed lines is the correction to the radius distribution accounting for the variance in core density (see text for more detail). We have rescaled the data points of Hsu et al. (2019) for better comparison.
Paper: Creating the Radius Gap without Mass Loss
Authors: Eve J. Lee, Amalia Karalis, Daniel P. Thorngren
Figure caption: Same as Figure 8 at orbital periods of 30 days for different level of disk gas depletion at the time of gas accretion. On the right panel, we plot the histogram of the radius of 1000 model planets from 5 to 64 days with the data from Hsu et al. (2019; same range of orbital periods) plotted in black circles, rescaled for better comparison with the models. The chosen range of orbital periods maximizes the number of data points that can be plotted (i.e., actual measurements of occurrence rate rather than upper limits).
Paper: Creating the Radius Gap without Mass Loss
Authors: Eve J. Lee, Amalia Karalis, Daniel P. Thorngren
Figure caption: The location of radius gap evaluated at an orbital period of 30 days for each stellar mass. In general, the gap shifts to larger radii around more massive stars for both bottom-heavy (δ = −0.3) and top-heavy (δ = 0.3) distributions. The best-fit scaling relationship between the gap radius R gap and the stellar mass M ⋆ for both populations agrees with the measurement by Berger et al. (2020) (﹩{R}_{\mathrm{gap}}\propto {M}_{\star }^{{0.26}_{-0.16}^{+0.21}}﹩) and that by Petigura et al. (2022) (﹩{R}_{\mathrm{gap}}\propto {M}_{\star }^{{0.18}_{-0.07}^{+0.08}}﹩) within 1σ.
Paper: Creating the Radius Gap without Mass Loss
Authors: Eve J. Lee, Amalia Karalis, Daniel P. Thorngren
Figure caption: Radius-period distribution of Hsu et al. (2019) data (top) and from the accretion model (bottom). Overplotted in the bottom two panels are the best power-law fits to the shape of the radius gap.
Paper: Creating the Radius Gap without Mass Loss
Authors: Eve J. Lee, Amalia Karalis, Daniel P. Thorngren
Figure caption: Distribution of small planet densities computed using the masses and radii drawn from NASA Exoplanet Archive (2022), downloaded 2022 August 21 2022. We filter for planets smaller than 2R ⊕ and 10M ⊕ and for those with mass and radius error estimates that are within 30%.
Paper: Creating the Radius Gap without Mass Loss
Authors: Eve J. Lee, Amalia Karalis, Daniel P. Thorngren
Figure caption: Radius vs. core mass for varying initial envelope mass fraction ﹩{M}_{\mathrm{gas},\mathrm{init}}/{M}_{\mathrm{core}}﹩ and orbital periods. Plotted in dark lines are the radii after photoevaporation over 3 Gyr whereas plotted in light lines are the radii from pure thermal evolution over 3 Gyr without mass loss. To the right of each family of lines (different line styles), we indicate their corresponding ﹩{M}_{\mathrm{gas},\mathrm{init}}/{M}_{\mathrm{core}}﹩.
Paper: Creating the Radius Gap without Mass Loss
Authors: Eve J. Lee, Amalia Karalis, Daniel P. Thorngren
Figure caption: Radius-period distribution for primordial population thermally evolved to 3 Gyr (top) and for those undergone photoevaporative mass loss for 3 Gyr (bottom). The underyling core mass distribution follows δ = 0.3, and M break = 4M ⊕.
Paper: Observed Rate Variations in Superflaring G-type Stars
Authors: James Crowley, Michael S. Wheatland, Kai Yang
Figure caption: Left: Bayesian blocks determination of flaring rate (blue), bootstrap mean flaring rate and uncertainty (orange and light orange, respectively), and flares (black) for TIC 394030788 over years 2 (top) and 4 (bottom) of TESS observations. Right: the detected change in activity from the optimal block representation (blue), the bootstrap mean flaring rate (orange), flares (black), and the 1000 individual bootstrap samples (green).
Paper: Observed Rate Variations in Superflaring G-type Stars
Authors: James Crowley, Michael S. Wheatland, Kai Yang
Figure caption: Top: an excerpt of the light curve of TIC 364588501, showing the raw data (blue) and the background model calculated using the nonlinear iterative filtering technique (orange line). Several flare candidates are highlighted in red, with their peaks marked with crosses. Bottom: the same light curve after the background model is subtracted.
Paper: Observed Rate Variations in Superflaring G-type Stars
Authors: James Crowley, Michael S. Wheatland, Kai Yang
Figure caption: Average flaring rate (total flares divided by observation time) of analyzed stars vs. the total number of flares detected. Stars with detected variations in their flaring rate are highlighted in red. The size of each marker is indicative of how many sectors the star was observed for. The lower limit (solid line) is the minimum possible flaring rate for a star, corresponding to observation for the maximum number of sectors possible (26). The histogram in the right panel shows the distribution of rates across the sample of stars.
Paper: Observed Rate Variations in Superflaring G-type Stars
Authors: James Crowley, Michael S. Wheatland, Kai Yang
Figure caption: A flare on TIC 364588501, depicting the process for identifying flare candidates. The black horizontal bar indicates the minimum flux required for each point in the flare candidate, and the red horizontal bar indicates the minimum flux required when including the contribution of the photometric error of each data point (shown as black error bars). The points in red were selected as the flare candidate following this procedure. The peak of the flare (vertical line) is taken to be the data point with the maximum flux.
Paper: Observed Rate Variations in Superflaring G-type Stars
Authors: James Crowley, Michael S. Wheatland, Kai Yang
Figure caption: Bayesian blocks determination of flaring rate (blue), bootstrap mean flaring rate and uncertainty (red and orange, respectively) and flares (black) for TIC 364588501 over years 1 (top) and 3 (bottom) of TESS observations. The left-hand axis indicates the rates determined by the Bayesian blocks and bootstrap methods, and the right-hand axis gives the flare energies.
Paper: Observed Rate Variations in Superflaring G-type Stars
Authors: James Crowley, Michael S. Wheatland, Kai Yang
Figure caption: The amplitude–FWHM–recovery rate surface of TIC 364588501 over all sectors, after 443,300 injected and recovered flares. The contour of 75% recovery rate is shown in red. Observed flares are shown as black dots, however some observed flares had FWHMs above 1 hr. These flares are not shown. Sampling is incomplete toward the edges due to the use of a log-normal distribution of amplitudes.
Paper: Observed Rate Variations in Superflaring G-type Stars
Authors: James Crowley, Michael S. Wheatland, Kai Yang
Figure caption: Bayesian blocks determination of flaring rate (blue), as well as the individual bootstrap samples (green) for TIC 382575967 over years 1 (top) and 3 (bottom) of TESS observations.
Paper: Deflection of O2 + Ion Flow by Magnetic Fields in the Martian Ionosphere
Authors: Shibang Li, Haoyu Lu, Jinbin Cao, Jun Cui, Chenling Zhou, James A. Wild, Guokan Li, Yun Li
Figure caption: Magnetic elevation angle (also called inclination angle) in the horizontal plane at 350 km, (a) based on the dayside MAVEN Magnetometer level 2 data and overlapped with isomagnetic lines of the crustal field of G110 model, (b) plotted from simulation with the G110 crustal field model and overlapped with its isomagnetic lines, (c) plotted from simulation with the ESD model and overlapped with its isomagnetic lines.
Paper: Deflection of O2 + Ion Flow by Magnetic Fields in the Martian Ionosphere
Authors: Shibang Li, Haoyu Lu, Jinbin Cao, Jun Cui, Chenling Zhou, James A. Wild, Guokan Li, Yun Li
Figure caption: Distributions of variables resulting from simulation with ESD model at 350 km. (a) Magnetic elevation angle in latitude from −30° to −60° and longitude from 160° to 200°. (b) Magnetic elevation angle, (c) eastward velocity, (d) eastward EM forces, along the white line of Figure 5(a) at latitude of −50°. Orange and blue highlights represent the outward and inward magnetic field regions, respectively.
Paper: Deflection of O2 + Ion Flow by Magnetic Fields in the Martian Ionosphere
Authors: Shibang Li, Haoyu Lu, Jinbin Cao, Jun Cui, Chenling Zhou, James A. Wild, Guokan Li, Yun Li
Figure caption: Dayside southern hemisphere distribution of positive (a) and negative (b) total EM F  φ  in latitude from 0° to −90° and longitude from 90° to 270° at an altitude of 350 km accompanied by red and blue dashed contour lines of 10° and −10° magnetic inclination angles separately, resulting from simulation with the G110 crustal field model.
Paper: Deflection of O2 + Ion Flow by Magnetic Fields in the Martian Ionosphere
Authors: Shibang Li, Haoyu Lu, Jinbin Cao, Jun Cui, Chenling Zhou, James A. Wild, Guokan Li, Yun Li
Figure caption: Dayside distribution of ﹩{{\rm{O}}}_{2}^{+}﹩ ion velocity vector (black anchor) at 350 km, resulting from simulation without the crustal field model.
Paper: Deflection of O2 + Ion Flow by Magnetic Fields in the Martian Ionosphere
Authors: Shibang Li, Haoyu Lu, Jinbin Cao, Jun Cui, Chenling Zhou, James A. Wild, Guokan Li, Yun Li
Figure caption: Total strength of magnetic field in the horizontal plane at 350 km, (a) based on the dayside MAVEN Magnetometer level 2 data and overlapped with isomagnetic lines of crustal field of the G110 model, (b) plotted from simulation with the G110 crustal field model and overlapped with its isomagnetic lines, (c) plotted from simulation with the ESD model and overlapped with its isomagnetic lines.
Paper: Deflection of O2 + Ion Flow by Magnetic Fields in the Martian Ionosphere
Authors: Shibang Li, Haoyu Lu, Jinbin Cao, Jun Cui, Chenling Zhou, James A. Wild, Guokan Li, Yun Li
Figure caption: Magnetic elevation angle in the longitude–latitude plane at 350 km from results of simulations with the ESD model. Black anchor represents the dayside velocity vector of ﹩{{\rm{O}}}_{2}^{+}﹩.
Paper: Deflection of O2 + Ion Flow by Magnetic Fields in the Martian Ionosphere
Authors: Shibang Li, Haoyu Lu, Jinbin Cao, Jun Cui, Chenling Zhou, James A. Wild, Guokan Li, Yun Li
Figure caption: Magnetic field topology around Mars in the case with the ESD model.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: The standard AGN SED model at z = 2 (solid blue line, normalized by the MIPS 24 μm detection limit and plotted in λ F  λ  units). We show examples of variations with the different obscuration levels in the X-ray (N H = 1022, 1023, 1024 cm−2) or in the UV to mid-IR (A  V  = 1, 5, 20). The default AGN model is assumed to be radio-quiet (solid lines), and we also show the far-IR to radio SED of the radio-loud case as a dashed green line. A radio-quiet AGN template without obscuration at z = 0 is also presented for comparison (dotted blue line). The median 5σ detection limits of various surveys are also denoted as filled circles (X-ray data from Chandra in light blue, optical to mid-IR SED photometry data used in this work in black, radio data from VLA in red, and planned JADES and MIRI-HUDF observations in magenta and green, respectively). See text for details.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: Sizes of the AGN samples selected with different methods and the source intersections in the full AGN sample, visualized with the UpSet technique. The sample intersections of AGNs selected with different methods are plotted as a matrix. Each row corresponds to one selection method, and the bar charts on the left show the size of the AGN identified with this method. Each column corresponds to a possible intersection: the filled-in cells indicate which selection method is part of the intersection. The lines connecting the filled-in cells show in which direction the plots should be read. The bar charts on the top give the size of the AGN sample identified with the corresponding intersection of various selection techniques. We only show subsets with sample size greater than 4 ( ≳ 4% of the whole sample). We highlight the subsets relevant to mid-IR SED selections in red, where we expect that the numbers will be increased significantly with the upcoming JWST surveys of this field.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: SFG IR luminosity, L SF,IR, derived from our SED fitting vs. the 3 GHz radio luminosity, L 3GHz, for our radio sample. We show radio-quiet AGNs, radio-loud AGNs, and galaxies in blue, red, and green circles. Adopting the Kennicutt (1998) star formation law, we converted the L SF,IR to SFR and denote the corresponding values with gray horizontal lines. (Note: for some objects with L SF,IR ≲ 1044 erg s−1, the SED constraints are not good enough to constrain the galaxy IR luminosity.)
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: AGN light fraction as a function of rest-frame wavelength in our SED-identified AGN. Optical SED AGNs are shown in blue, and mid-IR SED AGNs are shown in orange. We denote the AGN fractional detection limit with a thick green line, above which the existence of an AGN can be confirmed by our selection criteria once the wavelength coverage is sufficient. See text for details.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: Comparison of AGN bolometric luminosity measurements from the X-ray and SED analysis. We denote [otype_sed], [mtype_sed], and other AGNs with blue, red, and gray circles, respectively. The dashed black line represents the 1:1 relation. The blue and magenta shaded regions indicate where the X-ray or SED L bol estimations are not useful.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: Radar diagrams showing the fraction of sources to which each AGN selection can be applied and the fraction of AGNs that each selection identifies. These numbers are calculated for the whole AGN sample and the AGN samples detected in the radio, X-ray, mid-IR, or none of the above. On the bottom left panel, we show that the AGN sample overlaps for sources in our sample that are detected in radio, X-ray, or mid-IR.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: The redshift and luminosity distribution of GOODS-S AGNs identified in this work. We have denoted radio-detected and radio-undetected AGNs in orange and blue. Sources with spectroscopic redshifts and photometric redshifts are shown as circles and crosses, respectively.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption:  L AGN,bol detection limits as a function of redshift for different photometric bands in X-ray (top), optical to mid-IR (middle), and radio (bottom), under the assumption that the emission is coming purely from the AGN.