adsabs/AstroCLIMB huggingface dataset:
Paper: Examining AGN UV/Optical Variability beyond the Simple Damped Random Walk
Authors: Weixiang Yu, Gordon T. Richards, Michael S. Vogeley, Jackeline Moreno, Matthew J. Graham
Figure caption: Distribution of σ DHO, τ perturb, and σ  ϵ  as a function of rest wavelength (λ RF). The color gives the photometric band from which the best-fit parameters are obtained. The black points in the middle and bottom panels mark the median values in bins centered at the corresponding λ RF; the error bars have been made twice as large for better visibility. Top: the contours show the 85% mass for each band. σ DHO follows an overall monotonic relation with λ RF; the solid line shows the best linear fit. Middle: τ perturb increases with λ RF longward of ≈2500 Å; the solid line shows the best linear fit to the median values with λ RF > 2500 Å. Bottom: σ  ϵ  decreases with λ RF shortward of ≈2500 Å; the solid line shows the best linear fit to the median values with λ RF < 2500 Å.
Paper: Examining AGN UV/Optical Variability beyond the Simple Damped Random Walk
Authors: Weixiang Yu, Gordon T. Richards, Michael S. Vogeley, Jackeline Moreno, Matthew J. Graham
Figure caption: A comparison between the output DHO parameters obtained on simulated light curves and the true input; only simulations of overdamped DHOs are shown. Two versions of the output parameters are shown: the first one (orange) is the original MAP best fit, and the second one (blue) has the linear correction applied. The correction is determined from modeling the difference between the output and the input parameters in the form of Δlog(X) = log(X Output)–log(X Input), as a function of the temporal sampling and photometric accuracy of the light curves. Row one: scatter plots comparing the output DHO parameters (y-axis) with the input parameters (x-axis). Solid diagonal lines show a one-to-one correspondence. Row two: histograms showing the difference between the output DHO parameters and the input. The vertical dashed lines mark an offset of zero, meaning that the output is in perfect agreement with the input. Row three: the difference between the (corrected) output parameters and the input parameters as a function of the input parameters.
Paper: Examining AGN UV/Optical Variability beyond the Simple Damped Random Walk
Authors: Weixiang Yu, Gordon T. Richards, Michael S. Vogeley, Jackeline Moreno, Matthew J. Graham
Figure caption: DHO fits for realistically simulated SDSS S82 light curves; the input model parameters are drawn from the distribution shown in the top two panels of Figure 3. The DHO fits that are identified as good using the algorithm described at the beginning of Section 4.1 are color-coded by the difference between their best-fit log(ω 0) and the input. Identified bad fits that were simulated as overdamped DHOs are shown using gray dots and those simulated as underdamped DHOs are shown using magenta crosses. The orange dashed line marks a T QPO of 1 day. The cyan dashed–dotted line shows the cut used to remove the bad fits associated with the daily observing cadence (surrounding the orange dashed line). The red contour outlines the distribution of the input DHO parameters.
Paper: Examining AGN UV/Optical Variability beyond the Simple Damped Random Walk
Authors: Weixiang Yu, Gordon T. Richards, Michael S. Vogeley, Jackeline Moreno, Matthew J. Graham
Figure caption: MCMC posterior distributions for DHO parameters: α 1, α 2, β 0, β 1, and τ perturb. Shown are DHO fits for g-band light curves. Left: a selected example showing a bimodal distribution; this example has a bimodality index of 7.25. Right: a selected example showing a posterior distribution with a single mode; this example has a bimodality index of 1.31.
Paper: Examining AGN UV/Optical Variability beyond the Simple Damped Random Walk
Authors: Weixiang Yu, Gordon T. Richards, Michael S. Vogeley, Jackeline Moreno, Matthew J. Graham
Figure caption: DHO amplitude (σ DHO) and emission-line properties. Left: distribution of quasars in the EV1 parameter space, with the color showing the mean σ DHO of objects in the corresponding bins; a trend of increasing σ DHO toward the upper left corner is clearly shown. Right: distribution of quasars in the C IV parameter space, with the color showing the mean σ DHO of objects in the corresponding bins; a trend of increasing σ DHO with decreasing C IV blueshift and increasing C IV EQW is shown.
Paper: Examining AGN UV/Optical Variability beyond the Simple Damped Random Walk
Authors: Weixiang Yu, Gordon T. Richards, Michael S. Vogeley, Jackeline Moreno, Matthew J. Graham
Figure caption: Quasars with − 1.1  < log(L/L edd) <   − 0.9 in the r perturb, σ  ϵ  parameter space. A trend of decreasing L bol toward the upper right corner is clearly shown.
Paper: Constraining the Physical Properties of Stellar Coronal Mass Ejections with Coronal Dimming: Application to Far-ultraviolet Data of ϵ Eridani
Authors: R. O. Parke Loyd, James Paul Mason, Meng Jin, Evgenya L. Shkolnik, Kevin France, Allison Youngblood, Jackie Villadsen, Christian Schneider, Adam C. Schneider, Joe Llama, Tahina Ramiaramanantsoa, Tyler Richey-Yowell
Figure caption: Example of coronal dimming from a solar coronal mass ejection (CME). The upper panels show images from the Solar Dynamics Observatory (SDO; Pesnell et al. 2012) Atmospheric Imaging Assembly (AIA; Lemen et al. 2012) in the 171 Å band, dominated by coronal emission from Fe IX. The second two panels in the series are differenced from the first to highlight changes in flux. Below the images is a disk-integrated (“Sun-as-a-star”) lightcurve from the SDO Extreme ultraviolet Variability Experiment (EVE; Woods et al. 2012), also of emission from the Fe IX line at 171 Å, from Mason et al. (2014). In this example, a flare-associated CME produces transient coronal dimmings that show up in the disk-integrated lightcurve as a drop in coronal emission, indicating that a CME occurred.
Paper: NuSTAR Observations of AGNs with Low Observed X-Ray to [O III] Luminosity Ratios: Heavily Obscured AGNs or Turned-off AGNs?
Authors: M. Lynne Saade, Murray Brightman, Daniel Stern, Matthew A. Malkan, Javier A. García
Figure caption: Observed 2–10 keV X-ray luminosity vs. [O III] luminosity for the nine Seyfert 2 galaxies in our sample. The 12 μm sample is based on data from Malkan et al. (2017). The solid red line shows the mean L 2–10 vs. L [O III] relation for the Seyfert 1 galaxies in the 12 μm sample (Equation (1)). The dashed red line is the same line shifted by an order of magnitude down in observed 2–10 keV X-ray luminosity. The nine galaxies of the sample are labeled as blue squares. NGC 5953 is plotted as an open square as it had no NuSTAR data available, and so was left out of the final sample. The L 2–10 vs. L [O III] relation for Seyferts from Berney et al. (2015) is plotted in dark cyan for comparison, with the shaded region corresponding to its rms scatter of 0.59 dex.
Paper: NuSTAR Observations of AGNs with Low Observed X-Ray to [O III] Luminosity Ratios: Heavily Obscured AGNs or Turned-off AGNs?
Authors: M. Lynne Saade, Murray Brightman, Daniel Stern, Matthew A. Malkan, Javier A. García
Figure caption: Zoomed-in and re-scaled Chandra image of NGC 3627 highlighting and labeling the plethora of off-nuclear point sources (small red circles) within the larger 40″ radius NuSTAR beam. The ULX M66 X-1 is visible to the southeast (green circle).
Paper: NuSTAR Observations of AGNs with Low Observed X-Ray to [O III] Luminosity Ratios: Heavily Obscured AGNs or Turned-off AGNs?
Authors: M. Lynne Saade, Murray Brightman, Daniel Stern, Matthew A. Malkan, Javier A. García
Figure caption: Unfolded spectrum and best-fit model for NGC 1386. Black, red, green, and blue denote Chandra data (ObsIDs 4076, 12289, 13185, and 13257). Cyan and magenta denote FPMA and FPMB data for NuSTAR observation 60001063002. Yellow and orange denote FPMA and FPMB for NuSTAR observation 60201024002.
Paper: NuSTAR Observations of AGNs with Low Observed X-Ray to [O III] Luminosity Ratios: Heavily Obscured AGNs or Turned-off AGNs?
Authors: M. Lynne Saade, Murray Brightman, Daniel Stern, Matthew A. Malkan, Javier A. García
Figure caption: Chandra (left; ObsID: 9548) and NuSTAR FPMA (right) images of NGC 3627. The larger, 40″ radius red circle denotes the NuSTAR extraction region for the AGN, while the smaller red circle denotes the Chandra extraction region for the AGN. The ULX M66 X-1 is highlighted with a green circle (3.″75 diameter in Chandra; 40″ radius in NuSTAR). M66 X-1 dominates the NuSTAR image, while the AGN is not clearly detected by NuSTAR.
Paper: NuSTAR Observations of AGNs with Low Observed X-Ray to [O III] Luminosity Ratios: Heavily Obscured AGNs or Turned-off AGNs?
Authors: M. Lynne Saade, Murray Brightman, Daniel Stern, Matthew A. Malkan, Javier A. García
Figure caption: Chandra (ObsID: 13257) and NuSTAR (ObsID: 60201024002) FPMA images of NGC 1386. The larger, 40″ radius circle denotes the NuSTAR extraction region, while the smaller circles denote the Chandra extraction regions. Five extranuclear point sources were visible in the Chandra observations, though all were sufficiently faint (i.e., <10% the flux of the nucleus) to be ignored in the AGN spectral analysis.
Paper: Constraining the Physical Properties of Stellar Coronal Mass Ejections with Coronal Dimming: Application to Far-ultraviolet Data of ϵ Eridani
Authors: R. O. Parke Loyd, James Paul Mason, Meng Jin, Evgenya L. Shkolnik, Kevin France, Allison Youngblood, Jackie Villadsen, Christian Schneider, Adam C. Schneider, Joe Llama, Tahina Ramiaramanantsoa, Tyler Richey-Yowell
Figure caption: 2017 March epoch, MCMC chains from the fit to the Fe XII data in Figure 11. Symbols are the pre-flare flux, F pre (10−15 erg s−1 cm−2); CME acceleration, a (m s−2); dimming depth, ﹩{\delta }_{\max }﹩ (relative units); and the white noise hyperparameter, σ (relative units).
Paper: Constraining the Physical Properties of Stellar Coronal Mass Ejections with Coronal Dimming: Application to Far-ultraviolet Data of ϵ Eridani
Authors: R. O. Parke Loyd, James Paul Mason, Meng Jin, Evgenya L. Shkolnik, Kevin France, Allison Youngblood, Jackie Villadsen, Christian Schneider, Adam C. Schneider, Joe Llama, Tahina Ramiaramanantsoa, Tyler Richey-Yowell
Figure caption: 2017 August epoch, MCMC chains from the fit to the Fe XII data in Figure 13. Symbols are the pre-flare flux, F pre (10−15 erg s−1 cm−2); CME acceleration, a (m s−2); dimming depth, ﹩{\delta }_{\max }﹩ (relative units); and the white noise hyperparameter, σ (relative units).
Paper: Constraining the Physical Properties of Stellar Coronal Mass Ejections with Coronal Dimming: Application to Far-ultraviolet Data of ϵ Eridani
Authors: R. O. Parke Loyd, James Paul Mason, Meng Jin, Evgenya L. Shkolnik, Kevin France, Allison Youngblood, Jackie Villadsen, Christian Schneider, Adam C. Schneider, Joe Llama, Tahina Ramiaramanantsoa, Tyler Richey-Yowell
Figure caption: 2017 August epoch, MCMC chains from the fit to the Fe XXI data in Figure 13. Symbols are the pre-flare flux, F pre (10−15 erg s−1 cm−2); CME acceleration, a (m s−2); dimming depth, ﹩{\delta }_{\max }﹩ (relative units); and the white noise hyperparameter, σ (relative units).
Paper: Extremely Low-mass White Dwarf Stars Observed in Gaia DR2 and LAMOST DR8
Authors: Kun Wang, 坤 王, Péter Németh, Yangping Luo, 杨平 罗, Xiaodian Chen, 孝钿 陈, Qingquan Jiang, 青权 蒋, Xingmei Cao, 星梅 曹
Figure caption: Best model-atmosphere fits to the 16 LAMOST spectra of 12 stars in the ELM survey. The black and red lines are the observed and synthetic spectra, respectively. The residuals are shown as dark gray lines. The vertical blue lines mark the locations of the Ca II K (3934.8 Å), the Mg I (5167 Å), and the Na I D (5895.6 Å) absorption lines. The target name and the best-fitting atmospheric parameters are given for each LAMOST spectrum.
Paper: Extremely Low-mass White Dwarf Stars Observed in Gaia DR2 and LAMOST DR8
Authors: Kun Wang, 坤 王, Péter Németh, Yangping Luo, 杨平 罗, Xiaodian Chen, 孝钿 陈, Qingquan Jiang, 青权 蒋, Xingmei Cao, 星梅 曹
Figure caption: Upper panel: comparisons of the atmospheric parameters measured by XTGRID with LAMOST spectra and results of Brown et al. (2020b) for the 12 known ELM WDs. We plot the same object with the same color in each of the upper panels. The dashed lines are the 1:1 ratios. Lower panel: atmospheric parameters of three ELM WDs derived from two different fits to the same three MMT spectra (Warren R. Brown, private communication; Brown et al. 2020b). Our spectral fitting results and parameter values from Brown et al. (2020b) are shown as blue and red points, respectively.
Paper: Extremely Low-mass White Dwarf Stars Observed in Gaia DR2 and LAMOST DR8
Authors: Kun Wang, 坤 王, Péter Németh, Yangping Luo, 杨平 罗, Xiaodian Chen, 孝钿 陈, Qingquan Jiang, 青权 蒋, Xingmei Cao, 星梅 曹
Figure caption:  T eff vs. logg diagram of all the 188 LAMOST spectra. Evolutionary tracks from Althaus et al. (2013) for low-mass WDs with 0.17M ☉ < M < 0.44M ☉ are overplotted. The magenta dots mark the selected ELM WD candidates that fall in the red box with effective temperatures of 8800 K ≤ T eff ≤ 25,000 K and surface gravities of 4.5 ≤ logg ≤ 7.2. The yellow dots represent the hot subdwarf stars identified by Luo et al. (2021).
Paper: Extremely Low-mass White Dwarf Stars Observed in Gaia DR2 and LAMOST DR8
Authors: Kun Wang, 坤 王, Péter Németh, Yangping Luo, 杨平 罗, Xiaodian Chen, 孝钿 陈, Qingquan Jiang, 青权 蒋, Xingmei Cao, 星梅 曹
Figure caption: Comparison between the Gaia parallaxes and our spectrophotometric parallax estimates. Red dashed lines represent the 3:1, 1:1, and 1:3 parallax ratio lines. The marker colors indicate the effective temperatures of the objects.
Paper: Extremely Low-mass White Dwarf Stars Observed in Gaia DR2 and LAMOST DR8
Authors: Kun Wang, 坤 王, Péter Németh, Yangping Luo, 杨平 罗, Xiaodian Chen, 孝钿 陈, Qingquan Jiang, 青权 蒋, Xingmei Cao, 星梅 曹
Figure caption: Gaia color–magnitude diagram showing ELM WD candidates selected from the Gaia DR2. The blue points indicate the 5762 ELM WD candidates reported by Pelisoli & Vos (2019), whereas the red dots represent 136 of 5762 objects with LAMOST spectra. We also show in grey the Gaia 100 pc clean sample (sample C in Lindegren et al. 2018) for reference, similar to Pelisoli & Vos (2019).
Paper: The Missing Satellite Problem outside of the Local Group. II. Statistical Properties of Satellites of Milky Way–like Galaxies
Authors: Masashi Nashimoto, Masayuki Tanaka, Masashi Chiba, Kohei Hayashi, Yutaka Komiyama, Takashi Okamoto
Figure caption: The number of detected satellites vs. host halo mass and magnitude of the brightest satellite. The open circles are the secure satellites with M  V  < −12.1 around the binary (red: N7332 and N3245) and isolated (black: others) host galaxy. In the right panels, N5470 is excluded because N5470 has no secure satellite. The gray circles show the satellite galaxies outside the LG detected by the SAGA survey (Mao et al. 2021). The number of satellite galaxies is corrected for completeness. The green and yellow circles represent the MW and M31, respectively. We assume that both galaxies have a halo mass of ∼1.5 × 1012 M ⊙ (McConnachie 2012).
Paper: The Missing Satellite Problem outside of the Local Group. II. Statistical Properties of Satellites of Milky Way–like Galaxies
Authors: Masashi Nashimoto, Masayuki Tanaka, Masashi Chiba, Kohei Hayashi, Yutaka Komiyama, Takashi Okamoto
Figure caption: Measured properties of the candidates around N5866. The circles are the candidates after the initial Source Extractor cuts (Section 3.1). The solid lines represent each parameter cut. The blue circles are the objects that satisfy all the criteria.
Paper: The Missing Satellite Problem outside of the Local Group. II. Statistical Properties of Satellites of Milky Way–like Galaxies
Authors: Masashi Nashimoto, Masayuki Tanaka, Masashi Chiba, Kohei Hayashi, Yutaka Komiyama, Takashi Okamoto
Figure caption: Cumulative luminosity function of the detected dwarf galaxies and MW satellites (red line; McConnachie 2012). The black line includes only the secure satellites, while the gray line includes both secure and possible satellites. The error bars represent the standard deviation among the nine host galaxies. Note that the completeness correction (see Section 3.5) is applied here. The blue curve is the double Schechter function provided by Wang et al. (2021), which is estimated by higher-redshift dwarf galaxies.
Paper: The Missing Satellite Problem outside of the Local Group. II. Statistical Properties of Satellites of Milky Way–like Galaxies
Authors: Masashi Nashimoto, Masayuki Tanaka, Masashi Chiba, Kohei Hayashi, Yutaka Komiyama, Takashi Okamoto
Figure caption: SBF distance vs. magnitude for candidate objects around N5866. The shaded region is the extent of the SBF distance cut. Blue (gray) circles represent the objects satisfying (not satisfying) the SBF distance criteria.
Paper: The Missing Satellite Problem outside of the Local Group. II. Statistical Properties of Satellites of Milky Way–like Galaxies
Authors: Masashi Nashimoto, Masayuki Tanaka, Masashi Chiba, Kohei Hayashi, Yutaka Komiyama, Takashi Okamoto
Figure caption: Surface brightness vs. magnitude for all detected sources around N5866. The solid lines represent the surface brightness and magnitude cuts. The blue (gray) circles represent objects that satisfy (do not satisfy) the surface brightness, magnitude, and axial ratio criteria and are outside the masked regions.
Paper: The Missing Satellite Problem outside of the Local Group. II. Statistical Properties of Satellites of Milky Way–like Galaxies
Authors: Masashi Nashimoto, Masayuki Tanaka, Masashi Chiba, Kohei Hayashi, Yutaka Komiyama, Takashi Okamoto
Figure caption: Spatial distribution of the dwarf galaxies. The red and blue circles represent the secure and possible dwarf galaxies, respectively. The green shaded circles and boxes show the masked regions. The white circle is the virial radius of the host galaxy. Note that the virial radius of N5866 is outside of the field of view. The white solid and dashed lines represent the central galaxy’s major and minor axis, respectively.
Paper: Global Modeling of Nebulae with Particle Growth, Drift, and Evaporation Fronts. II. The Influence of Porosity on Solids Evolution
Authors: Paul R. Estrada, Jeffrey N. Cuzzi, Orkan M. Umurhan
Figure caption: Total solids surface density for the sa2g, sa4g, and sa5g (dashed curves) and fa2g, fa4g, and fa5g (solid curves) models after 0.5 Myr. Peaks in Σsolids can be associated with solids enhancement outside EFs. Also plotted in gray are the fiducial models for direct comparison.
Paper: Global Modeling of Nebulae with Particle Growth, Drift, and Evaporation Fronts. II. The Influence of Porosity on Solids Evolution
Authors: Paul R. Estrada, Jeffrey N. Cuzzi, Orkan M. Umurhan
Figure caption: Distribution of Stokes numbers associated with the evolution of the particle mass distributions for the compact (sa3g) and fractal (fa3g) fiducial growth models shown in Figure 2. Stokes numbers of the distribution are indicated by the color map at the right, and labeled (gray) curves of constant St are plotted to aid in visualization. As noted in the text, the more rapid growth of fractal particles beyond the snowline leads to more massive, and higher St particles by 105 yr compared to compact growth (middle panels). Note that outside of 200–400 au, even small grains have very large St ≫ 1 making them essentially unaffected by radial drift. The total mass fraction is very low so growth times are exceedingly long. With careful inspection, one can see the outline of the water ice EF (e.g., ∼4 au at 0.5 Myr), as well as the outline of m  λ  in the fractal growth case (by reference, the dotted brown curves in Figure 2; the reader may find it easier to view this on-screen and magnified).
Paper: Global Modeling of Nebulae with Particle Growth, Drift, and Evaporation Fronts. II. The Influence of Porosity on Solids Evolution
Authors: Paul R. Estrada, Jeffrey N. Cuzzi, Orkan M. Umurhan
Figure caption: Comparison of models with α t = 10−2 for both compact (top panels) and fractal (bottom panels) growth at, from left to right, 104, 105, and 5 × 105 yr. Plotted in each panel is a snapshot of the particle mass distribution as a function of semimajor axis. First and third rows: particle solids mass volume density per bin of width Δm. Second and fourth rows: Stokes numbers. The particle size distributions for models sa2g and fa2g after 0.5 Myr can be seen in Appendix A.
Paper: Global Modeling of Nebulae with Particle Growth, Drift, and Evaporation Fronts. II. The Influence of Porosity on Solids Evolution
Authors: Paul R. Estrada, Jeffrey N. Cuzzi, Orkan M. Umurhan
Figure caption: Comparison of models with α t = 10−4 for both compact (top panels) and fractal (bottom panels) growth at, from left to right, 104, 105, and 5 × 105 yr. Plotted in each panel is a snapshot of the particle mass distribution as a function of semimajor axis. First and third rows: particle solids mass volume density per bin of width Δm. Second and fourth rows: Stokes numbers. Though it is more apparent in the compact particle models, the St of particles outside the snowline tend to be relatively constant over a large radial extent in Paper I. For these models, the water snowline is located near ∼3 au after 0.5 Myr. The particle size distributions for models sa4g and fa4g after 0.5 Myr can be seen in Appendix A.
Paper: Global Modeling of Nebulae with Particle Growth, Drift, and Evaporation Fronts. II. The Influence of Porosity on Solids Evolution
Authors: Paul R. Estrada, Jeffrey N. Cuzzi, Orkan M. Umurhan
Figure caption: Metallicity Z for the compact model sa3g (dashed curves) and fractal model fa3g (solid curves) at the same times given in Figure 2 as a function of semimajor axis. The sharp decrease in the total solids surface density outside the snowline (located at ∼4 au after 0.5 Myr) and beyond seen in Figure 3 (right panel) is reflected more strongly here as an order of magnitude drop in Z compared to the initial disk metallicity of ﹩\bar{Z}\simeq 0.014﹩.
Paper: Global Modeling of Nebulae with Particle Growth, Drift, and Evaporation Fronts. II. The Influence of Porosity on Solids Evolution
Authors: Paul R. Estrada, Jeffrey N. Cuzzi, Orkan M. Umurhan
Figure caption: Pressure gradient β as a function of semimajor axis after 0.5 Myr for all models discussed thus far. Solid curves correspond to fractal models, and dashed to compact growth models. The blue curve corresponds to the MMSN nebula. Though the gradient shows considerable variation in the most inner disk regions, at no point is β < 0, so appreciable pressure bumps do not develop over the simulation time of these models.
Paper: Global Modeling of Nebulae with Particle Growth, Drift, and Evaporation Fronts. II. The Influence of Porosity on Solids Evolution
Authors: Paul R. Estrada, Jeffrey N. Cuzzi, Orkan M. Umurhan
Figure caption: Rosseland (solid curves) and Planck (dashed curves) mean opacities as a function of semimajor axis and at the same times as the compact (left panel) and fractal (right panel) growth simulations shown in Figure 2. In both cases, the decrease in opacity outside the snowline (4–5 au) is due to larger particles and material drifting inward and lowering the local effective Z. However, the fractal case retains much more mass in the outer disk from ≳40–100 au.
Paper: Global Modeling of Nebulae with Particle Growth, Drift, and Evaporation Fronts. II. The Influence of Porosity on Solids Evolution
Authors: Paul R. Estrada, Jeffrey N. Cuzzi, Orkan M. Umurhan
Figure caption: Midplane temperature profiles after 0.5 Myr for all models discussed thus far. Solid curves correspond to fractal models, and solid curves to compact models. The blue curve corresponds to the MMSN nebula.
Paper: Global Modeling of Nebulae with Particle Growth, Drift, and Evaporation Fronts. II. The Influence of Porosity on Solids Evolution
Authors: Paul R. Estrada, Jeffrey N. Cuzzi, Orkan M. Umurhan
Figure caption: Comparison of models with α t = 10−5 for both compact (top panel) and fractal (bottom panes) growth at 5 × 105 yr. Plotted in each panel is a snapshot of the particle mass distribution as a function of semimajor axis. Descriptions are the same as in Figure 2.