adsabs/AstroCLIMB huggingface dataset:
Paper: Characterization of the DART Ejecta Using Computer Modeling of the Ground-based and HST Photopolarimetric Data
Authors: Ludmilla Kolokolova, Johannes Markkanen, Quentin Ludet, Zuri Gray, Stefano Bagnulo, Cyrielle Opitom, Brian Murphy
Figure caption: Distribution of column density along the DART ejecta tail, shown as the number of particles per pixel (left) and the corresponding mass per pixel in kilograms (right).
Paper: Characterization of the DART Ejecta Using Computer Modeling of the Ground-based and HST Photopolarimetric Data
Authors: Ludmilla Kolokolova, Johannes Markkanen, Quentin Ludet, Zuri Gray, Stefano Bagnulo, Cyrielle Opitom, Brian Murphy
Figure caption: Simulated particle distances from the nucleus along the tail as a function of particle size on October 4. The particles were emitted at the time of the impact.
Paper: Formation and Evolution Simulations of Saturn, Including Composition Gradients and Helium Immiscibility
Authors: Peter Bodenheimer, David J. Stevenson, Jack J. Lissauer, Gennaro D'Angelo
Figure caption: Evolution of a model Saturn-mass planet up to just past the end of accretion. Time is given in years; masses are in Earth masses, as indicated. Mass MZ refers to the total heavy-element mass; mass MXY refers to the mass in hydrogen and helium; the total mass of the planet is Mp = MZ + MXY. The ends of the various phases are indicated by small circles, along with the time when the inner-core mass, Mc, stops increasing and the time when the accretion rate of heavy elements, ﹩{\dot{M}}_{Z}﹩, attains its maximum value. Note that some short-term sign variations in ﹩{\dot{M}}_{XY}﹩ are likely to be caused by minor numerical inaccuracies in the applied accretion procedure (see Section 2.5).
Paper: Formation and Evolution Simulations of Saturn, Including Composition Gradients and Helium Immiscibility
Authors: Peter Bodenheimer, David J. Stevenson, Jack J. Lissauer, Gennaro D'Angelo
Figure caption: For the same model as in Figure 3, the panels show: inner-core radius Rc in Earth radii (R⊕, solid line); outer radius Rp in units of R⊕ (short-dashed line); and the negative of the gravitational energy Eg, in units of 1040 erg (long dashed line). The luminosity, ﹩\mathrm{log}L/{L}_{\odot }﹩ (dashed–dotted line), is indicated on the right axes. Observed values of Rp and L are also indicated in the bottom panel (open circle and square).
Paper: Formation and Evolution Simulations of Saturn, Including Composition Gradients and Helium Immiscibility
Authors: Peter Bodenheimer, David J. Stevenson, Jack J. Lissauer, Gennaro D'Angelo
Figure caption: Structure of a model Saturn-mass planet at the end of Phase I. Quantities are plotted as a function of radius, as labeled. The interior temperature is indicated on the right axis. The mass fraction of heavy elements, Z, includes iron, silicates, and water. The thin vertical bars near the top left mark the outer boundaries of the inner and outer cores.
Paper: Formation and Evolution Simulations of Saturn, Including Composition Gradients and Helium Immiscibility
Authors: Peter Bodenheimer, David J. Stevenson, Jack J. Lissauer, Gennaro D'Angelo
Figure caption: Distributions of composition (mass fractions) at age 4.57 Gyr in a model of Jupiter used to calibrate the parametric temperature T1 in Equation (6). As a result of He rainout, the outer layers of the planet are (slightly) depleted in helium. Quantities, as labeled, are plotted as a function of radius.
Paper: A Pan-STARRS Search for Distant Planets: Part 1
Authors: Matthew J. Holman, Kevin J. Napier, Matthew J. Payne, Jacob A. Kurlander
Figure caption: Left: the sky-plane locations of all detections reported in a single GPC1 exposure. The colors highlight the sixty individual detectors. The 167,750 detections are distributed in rough proportion to the number of live pixels in each of the detectors. The 8 × 8 grid of cells within each detector is evident. Some cells are inactive. There is an excess of detections along the edges of each cell. The corners of the focal plane are rounded are due to a combination of vignetting and the deliberate placement of poor quality detectors near the edges of the field of view. The dotted blue circle, with an angular radius of 1﹩\mathop{.}\limits^{^\circ }﹩6, indicates the approximate GPC1 field of view. Right: the result of placing 4 × 105 synthetic detections uniformly within a circle with an angular radius of 1﹩\mathop{.}\limits^{^\circ }﹩6, centered on the exposure shown in Figure 3. The detections that fell in the inter- and intrachip gaps, on the “hot edges” or other regions that generate spurious detections, or on pixels that are flagged as bad in the static masks have been removed, following the filtering process described in Section 4. Roughly 68% of input detections remain after filtering.
Paper: A Pan-STARRS Search for Distant Planets: Part 1
Authors: Matthew J. Holman, Kevin J. Napier, Matthew J. Payne, Jacob A. Kurlander
Figure caption: The coverage of the Pan-STARRS1 data used in this search, from 2009 April 2 until 2017 November, shown in a Mollweide projection in equatorial coordinates (R.A. = 0° is at the center of the plot, with R.A. increasing to the left). The colors encode, with a linear scale, the number of exposures that cover the region, assuming a circular field of view with a 1﹩\mathop{.}\limits^{^\circ }﹩6 angular radius, ignoring the ∼68% fill factor. The 10 Medium Deep fields are shown for completeness. (Note that we skip any data from the Medium Deep fields, as well as from a few exposures for which the processing seems to have failed.) Each has thousands of exposures; we cap the maximum at 600 to keep those fields from dominating the color scale. The median number of exposures is ∼150. A fraction of the sky was not observed at all, and a few regions were observed more than ∼400 times. The center of the plot is 0 hr and 0°.
Paper: A Pan-STARRS Search for Distant Planets: Part 1
Authors: Matthew J. Holman, Kevin J. Napier, Matthew J. Payne, Jacob A. Kurlander
Figure caption: The number of detections per control object. The dashed blue line shows this distribution of candidate detections, i.e., those that fall within the field of view of an exposure. Of the 10,000 control objects, 8747 land within the circular boundary at least one exposure. Of those that hit at least one exposure, the median number of candidate detections is 154. The solid orange line shows the distribution of detections that remain after the filtering steps. As expected, the distribution is shifted to smaller numbers of detections, and the number of objects that go undetected is significantly larger. Of those that are detected in at least one exposure, the median number of detections is 43. The shapes and medians of the histograms depend upon the details of the control population, but the postfiltering histogram gives us a rough estimate of the expected number of detections for real objects.
Paper: A Pan-STARRS Search for Distant Planets: Part 1
Authors: Matthew J. Holman, Kevin J. Napier, Matthew J. Payne, Jacob A. Kurlander
Figure caption: Sky positions of our synthetic objects relative to F51 (Pan-STARRS1) on 2013 December 8 (approximately the midpoint of our data). The orientation is the same as in Figure 1. The green and black points represent objects that our simulator predicts would be recovered and missed, respectively. Note the strong spatial dependence introduced by the Galactic plane.
Paper: A Pan-STARRS Search for Distant Planets: Part 1
Authors: Matthew J. Holman, Kevin J. Napier, Matthew J. Payne, Jacob A. Kurlander
Figure caption: The detections in all the detectors shown in Figure 3, folded to match the repeated cell pattern: ﹩\bar{x}=x\, \% \,608,\bar{y}=y\, \% \,610﹩. The overabundance of detections at the borders of the cells is now even more evident. The horizontal and vertical lines indicate the area trimmed off in our processing. This eliminates ∼33% of the detections (most of which are false) and ∼6% of the detector area.
Paper: A Pan-STARRS Search for Distant Planets: Part 1
Authors: Matthew J. Holman, Kevin J. Napier, Matthew J. Payne, Jacob A. Kurlander
Figure caption: Of the 167,750 detections shown in Figure 3, only 10,050 remain after the removal of those that (1) fall in a noisy region of the focal plane, (2) are close to a bright star, or (3) coincide with a known stationary source. For this exposure, ∼94% of the detections are removed by one or more of these criteria.
Paper: A Pan-STARRS Search for Distant Planets: Part 1
Authors: Matthew J. Holman, Kevin J. Napier, Matthew J. Payne, Jacob A. Kurlander
Figure caption: On-sky density of the objects in the Planet Nine reference population that have not yet been ruled out by our survey (top) and by M. E. Brown et al. (2024, bottom). The orientation of each plot is the same as in Figure 1.
Paper: A Pan-STARRS Search for Distant Planets: Part 1
Authors: Matthew J. Holman, Kevin J. Napier, Matthew J. Payne, Jacob A. Kurlander
Figure caption: Calibration plot for our logistic regression model. The points on the x-axis are binned values of the predicted probability of a vector being linked, while the y-axis represents the fraction of the objects in that bin that were actually linked. The model, only deviates from perfect calibration by a few percent, indicating that it is justifiable to treat its predictions as probabilities.
Paper: A Pan-STARRS Search for Distant Planets: Part 1
Authors: Matthew J. Holman, Kevin J. Napier, Matthew J. Payne, Jacob A. Kurlander
Figure caption: Sky positions of our second set of synthetic objects relative to F51 (Pan-STARRS1) on 2013 December 8 (approximately the midpoint of our data). The orientation is the same as in Figure 1. The green and black points represent objects that our simulator predicts would be recovered and missed, respectively. Note the strong resemblance to Figure 6.
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Effective molecular residence times as a function of temperature. Activated surfaces (gray lines) have a range of desorption energies, and the harmonic average of these adsorption times is shown for adsorption endmember 1. Passivated surfaces (green) and ice (blue) have only a single desorption energy. The time of flight for a mean free path of 100 μm is shown for comparison (dashed line). On the lunar surface, the diffusion time is nearly always dominated by adsorption times, not by time of flight.
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Temperature and adsorbate profiles when the surface continually receives three monolayers of H2O per year. The adsorbate concentration increases with depth, and the breathing skin depth is small. Parameters: ϕ = 0.4, λ = 71 μm, Δz = 1 mm, Δt = 24 steps per sol, and i = 25°. The initial adsorbate concentration was 0.06 monolayers. After 25 Ma, the concentration profile is close to equilibrated.
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Distribution of desorption energies in an idealized model (blue line). The highest desorption energies are filled first (blue filled area).
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Equilibrium distribution of adsorbate densities, Θ(E), for endmember 2 at three different temperatures. For this adsorbate distribution, the same number of water molecules is desorbed for each surface element, balancing the areally uniform distribution of incoming molecules. The total flux is S = 1012 molecules m−2 s−1 for all three temperatures.
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Adsorbate profile above an ice table at 10 cm depth. Over time the adsorbate profile relaxes toward a steady-state profile, where the desorption rate increases linearly with depth. The initial adsorbate concentration was assumed to be zero. The model calculations include space weathering and geothermal heat. Parameters: ϕ = 0.4, λ = 71 μm, Δz = 0.5 mm, and Δt = 10 yr.
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Adsorbate concentrations above an ice table. (a) Temperature profiles. (b) Adsorbate profile with and without a temperature amplitude after 100 ka and 0.5 Ma, respectively. (c) Surface temperature over the last lunar day. (d) Time variability on the surface over the last lunar day in response to a temperature amplitude. Parameters: ϕ = 0.4, λ = 71 μm, Δz = 0.5 mm, Δt = 24 steps per sol, and i = 85°.
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Desorption rate as a function of adsorbate coverage based on Equations (4)–(8). The new choice for the parameter γ, Equation (8), provides a smoother transition from the submonolayer parameterization to the sublimation rate of ice than the previous choice, Equation (7).
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Comparison of the amount desorbed between endmember models 1 and 2, when desorbing at constant temperature. For endmember 2, it is assumed that the initial distribution is uniform in area. Desorption occurs faster for endmember 2, and the relative difference becomes larger for smaller initial amounts.
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Adsorbate profile above an ice table at 0.1 m depth. This is the equilibrium adsorbate concentration for a static temperature profile with geothermal heat. The numerical grid spacing is Δz = 0.5 mm.
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Distribution of desorption energies starting with half a monolayer and no lateral diffusion as calculated with Equation (38). Molecules with lower desorption energies are lost much faster than those with higher energies.
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Example of an idealized rough surface used for the calculation of an obstruction factor, Y.
Paper: Diffusion-adsorption of Water Vapor in Chemically Activated Lunar Soil
Authors: Norbert Schörghofer
Figure caption: Obstruction factor and roughness factor for different height-to-width ratios according to Equations (A11) and (A12). Higher surface area corresponds to more obstructed flight paths.
Paper: Europa’s Sodium and Potassium Exosphere during Juno’s Flyby
Authors: Emma Lovett, Carl Schmidt, Patrick Lierle
Figure caption: Map of Europa’s sodium column density on 2022 September 29, as reconstructed from the HIRES guide camera. The 28″ slit is oriented EW and NS on-disk, as well as off-disk 10 and 20 RE in each direction. The additional 44° position angle aligns with the Juno spacecraft trajectory concurrent in time. Spatially overlapping measurements are averaged. Europa itself is shown to scale, and spectra with tangent altitudes <3 RE are masked due to contamination by bright reflected sunlight.
Paper: Europa’s Sodium and Potassium Exosphere during Juno’s Flyby
Authors: Emma Lovett, Carl Schmidt, Patrick Lierle
Figure caption: Radial profiles of the sodium brightness above Europa’s disk on 2022 September 29 with the HIRES 28″ long slit oriented EW (pink filled) and NS (teal filled). On-disk profiles taken by Brown on 1999 December 28 show the EW (magenta open) and NS (green open) Na profiles with the 40″ slit length that is no longer available on HIRES. The 2022 data represent five on-disk spectra with error bars from sunlight subtraction shown for one scan. Photon scattering efficiency between the 1999 and 2022 measurements differs by ∼4%.
Paper: Europa’s Sodium and Potassium Exosphere during Juno’s Flyby
Authors: Emma Lovett, Carl Schmidt, Patrick Lierle
Figure caption: Radial profile of Na (red filled circles) and K (light blue filled circles) column densities as a function of distance from Europa. The yellow line shows the exponential function best fit to the Na profile with the form 2.80 × 1011 × R−1.12, whereas the blue line shows the exponential function best fit to the K profile with the form 3.42 × 109 × R0.66.
Paper: Europa’s Sodium and Potassium Exosphere during Juno’s Flyby
Authors: Emma Lovett, Carl Schmidt, Patrick Lierle
Figure caption: Left: map of Na D2 line widths. A Gaussian profile is fit to each spatial row, and the instrumental line width is deconvolved to give the Doppler width, ΔλD. Close to Europa’s disk, ΔλD is too narrow to distinguish from the limiting instrumentation resolution. Right: radial profiles of derived effective temperature in Na D2 (orange circles) and D1 (red triangles) as a function of tangent altitude. The yellow and teal lines show the averaged D2 and D1 data in 2 RE bins, respectively.
Paper: Europa’s Sodium and Potassium Exosphere during Juno’s Flyby
Authors: Emma Lovett, Carl Schmidt, Patrick Lierle
Figure caption: Reconstructed map of Europa’s K column density obtained immediately following Juno’s closest approach and the sodium map in Figure 4. The 28″ slit is oriented EW and offset 10 and 20RE north and south of Europa's disk, but the effective slit length is a lesser 25″ due to order overlap.
Paper: Europa’s Sodium and Potassium Exosphere during Juno’s Flyby
Authors: Emma Lovett, Carl Schmidt, Patrick Lierle
Figure caption: Panels following the Figure 1 caption for a 240 s integration of Europa’s K emissions oriented EW and positioned 10 RE north of Europa. At Europa’s 13.8 km s−1 orbital velocity, the D lines are Doppler-shifted completely out of the solar Fraunhofer wells, and so recovered emissions show the expected 2:1 D2/D1 optically thin line ratio for photon scattering in the solar continuum.
Paper: Europa’s Sodium and Potassium Exosphere during Juno’s Flyby
Authors: Emma Lovett, Carl Schmidt, Patrick Lierle
Figure caption: Normalized sodium D2 line profiles at 5 RE (orange), 10 RE (pink), and 20 RE (red). A nearby thorium emission line (black dashed) shows the local instrumental line-spread function and has been shifted in wavelength for comparison.
Paper: Investigating Local- and Global-scale Dust Redistribution on Comet 67P/Churyumov–Gerasimenko
Authors: Jacob L. Kloos, Tony L. Farnham, Jessica M. Sunshine, Juan Luis Rizos
Figure caption: Data–model comparison of the H2O gas production. Gray circles show ROSINA measurements of water production as described in N. Fougere et al. (2016). The blue squares show the modeled gas production for a uniform mantle thickness of 3 mm. The red triangles show the modeled gas production for a 0.3 mm dust mantle in the south and a 5 mm dust mantle in the north. The asymmetric dust mantle provides a better fit to the ROSINA data, particularly during the inbound phase of the orbit.
Paper: Investigating Local- and Global-scale Dust Redistribution on Comet 67P/Churyumov–Gerasimenko
Authors: Jacob L. Kloos, Tony L. Farnham, Jessica M. Sunshine, Juan Luis Rizos
Figure caption: (a) Six pits located on the large lobe of C-G. The yellow circles outline the approximate locations of the pit walls. (b) Thermal erosion of the nucleus using a 50,000-facet shape model (average facet area of ∼900 m2), highlighting the nonuniform erosion of the pits.
Paper: Investigating Local- and Global-scale Dust Redistribution on Comet 67P/Churyumov–Gerasimenko
Authors: Jacob L. Kloos, Tony L. Farnham, Jessica M. Sunshine, Juan Luis Rizos
Figure caption: Modeled output of (b) dust loss, (c) deposition, and (d) net dust accumulation for the Imhotep region on C-G. Panel (a) shows an Osiris image (N46147323222) of the region acquired on 2014 August 16.
Paper: Lake Stars as an Earth Analog for Europa’s Manannán Crater Spider Feature
Authors: Lauren E. Mc Keown, Elodie Lesage, Jennifer E. Scully, Erin J. Leonard, Robert T. Pappalardo, Marjorie Potter, Victor Tsai, Mathieu Choukroun, Elodie Gloesener, Serina Diniega, Nicholas Hatcher, Duncan McBryde
Figure caption: Examples of lake stars on Earth. (a) Melt “pools” that surround lake stars in Alaska directly during and shortly after their formation, before they freeze again (Source: Ned Rozell, Tohru Saito). (b), (e) Lake stars in New Hampshire and Breckenridge, respectively, on a thick layer of snow indicating they form both through slush and dry snow. Skates are ∼0.5 m long. Source (b): Jamie Hess (http://lakeice.squarespace.com/ice-stars/). Source (e): author. (c), (f) Linear lake stars (yellow arrows) in Breckenridge, CO, with minimal or no visible second- or third-order branches. Source: author. (d) Dendritic lake star on lake ice covered in wet layer of slush in Alaska. Ice skater can be seen in the background for sale. Source: Joe Stock.
Paper: Lake Stars as an Earth Analog for Europa’s Manannán Crater Spider Feature
Authors: Lauren E. Mc Keown, Elodie Lesage, Jennifer E. Scully, Erin J. Leonard, Robert T. Pappalardo, Marjorie Potter, Victor Tsai, Mathieu Choukroun, Elodie Gloesener, Serina Diniega, Nicholas Hatcher, Duncan McBryde
Figure caption: Manannán’s Damhán Alla geomorphologic map. (a) Geomorphologic map of all of Manannán crater, showing the central pit, Damhán Alla, and the crater rim. The base data are 20 m pixel–1 Galileo images (grayscale) and digital elevation models (DEMs) made from the same SSI data. The vertical range of the DEMs is 400 m, where red is high and blue is low. (b) Central pit and Damhán Alla in 20 m pixel–1 Galileo images (grayscale). (c) Central pit and Damhán Alla with geomorphic mapping on top of 20 m pixel–1 Galileo images (grayscale). (d) Central pit and Damhán Alla with geomorphologic mapping on top of the DEM with a vertical range of 250 m (where red is high and blue is low) and 20 m pixel–1 Galileo images (grayscale). In (b)–(d) the (i) en echelon patterns, (ii) scarps with vertical offset, and (iii) horsetail splay-like features discussed in the text are labeled. A full geologic map of Manannán crater can be found in J. E. C. Scully et al. (2023).
Paper: Lake Stars as an Earth Analog for Europa’s Manannán Crater Spider Feature
Authors: Lauren E. Mc Keown, Elodie Lesage, Jennifer E. Scully, Erin J. Leonard, Robert T. Pappalardo, Marjorie Potter, Victor Tsai, Mathieu Choukroun, Elodie Gloesener, Serina Diniega, Nicholas Hatcher, Duncan McBryde
Figure caption: “Lab star” patterns developed under simulated post-impact temperature regimes in a cold LN2 glove box. (a), (b) Lab star patterns formed in pure non-salty deionized Europa granular ice simulant. (c), (d) Fainter lab star patterns formed in 2.3 wt% Europa granular ice simulant. These often appeared less dendritic than non-salty granular ice. (e), (f) Dendritic channels formed in fine (<20 μm) atomized Europa granular ice simulant. Images show refrozen ice and the pattern generated at its base. Note less channels formed at lower temperatures close to −80° C. (g) LN2-cooled glove box within which experiments were performed. (h) The system used to develop fine granular ice simulant. (i) The process through which lab star patterns were developed in the laboratory.