adsabs/AstroCLIMB huggingface dataset:
Paper: Chemical Fractionation Modeling of Plumes Indicates a Gas-rich, Moderately Alkaline Enceladus Ocean
Authors: Lucas M. Fifer, David C. Catling, Jonathan D. Toner
Figure caption: The three models of ocean outgassing considered in this study. (a) In a thin-film gas exsolution model, outgassing fluxes from the ocean are determined by diffusive mass transfer across a hypothetical stagnant (i.e., not convecting) thin film at the ocean–gas interface. (b) In a boiling-dominated model, gases exsolve into vapor bubbles that rise and grow from a boiling depth ∼0.71 m below the surface (Ingersoll & Nakajima 2016). The relative gas abundances in the plume are then set by the gas abundances acquired during the bubbles’ short (<5 s) journey to the surface. (c) In a droplet-dominated degassing model (Glein & Waite 2020), gas in the plume is the result of complete vaporization of the outer layer of aerosol-like water droplets, while the inner volume of the droplets freeze and form ice grains of the plume.
Paper: Chemical Fractionation Modeling of Plumes Indicates a Gas-rich, Moderately Alkaline Enceladus Ocean
Authors: Lucas M. Fifer, David C. Catling, Jonathan D. Toner
Figure caption: Apparent affinity for methanogenesis in the ocean, i.e., the available energy for methanogenesis per mole of reaction in the ocean shown as color shading and black contour lines. The x-axis represents the denominator of the reaction quotient (Equation (36)) for the methanogenesis reaction, while the y-axis represents the numerator of the reaction quotient (assuming the activity of water ≈1). Increasing concentrations of CO2 or H2 (x-axis) increase the energy per mole of reaction (i.e., methanogenesis is more favored), while increasing concentrations of CH4 (y-axis) lower the energy per mole of reaction (i.e., methanogenesis is less favored). The region outlined by a blue dashed line encompasses the full range of our predictions for CO2, H2, and CH4 concentrations, with upper limits applied from compatibility with CDA measurements. The region outlined by an orange dashed line encompasses the range of predictions for gas concentrations and affinity from Waite et al. (2017). The yellow circles are points of reference, indicating the affinity for hypothetical oceans with equal concentrations of CO2, H2, and CH4 at 10−7, 10−5, and 10−3 molal. Due to higher gas concentrations overall, we predict a slightly greater maximum affinity, ∼130 kJ mol−1 CH4, for methanogenesis in Enceladus’ ocean compared to Waite et al. (2017).
Paper: Chemical Fractionation Modeling of Plumes Indicates a Gas-rich, Moderately Alkaline Enceladus Ocean
Authors: Lucas M. Fifer, David C. Catling, Jonathan D. Toner
Figure caption: Our predicted pH for the ocean (plotted in color, with white contour lines of constant pH), as a function of predicted oceanic [NH3] and [CO2]. The dashed shape indicates the uncertainty space of our predictions for [NH3] and [CO2], and is the region of overlap between our physical chemistry models and allowable ion concentrations from the CDA analysis that was shown in Figure 4. Consequently, the full range of pH is that within the dashed shape. Higher concentrations of CO2 lead to lower pH, because dissolved CO2 acts as a weak acid, and higher concentrations of NH3 tend to lead to higher pH, because dissolved NH3 acts as a weak base. The pH range plotted here (8.00–9.00) is specific to the salt concentrations [NaHCO3 or Na2CO3] = 0.05 molal and [NaCl] = 0.1 molal, but this pH range is very similar to our full predicted pH (∼7.95–9.05) that includes the full uncertainty in ocean salt concentrations (Postberg et al. 2009).
Paper: Insight into the Distribution of High-pressure Shock Metamorphism in Rubble-pile Asteroids
Authors: Nicole Güldemeister, Juulia-Gabrielle Moreau, Tomas Kohout, Robert Luther, Kai Wünnemann
Figure caption: Quantification of ejected shock-darkened material as a function of impact velocity for different collision scenarios. Square symbols represent rubble-pile asteroids with boulder porosity of 10% and triangular symbols with boulder porosity of 30%. The fine material has a porosity of 75%. We also indicate different mass ratios of asteroid to impactor through color coding of symbols. (a) Total ejected mass of the asteroid normalized to the projectile mass. (b) Ejected shock-darkened mass as a percentage of the total ejected mass. (c) Ejected shock-darkened mass as a percentage of the total shock-darkened mass of the asteroid.
Paper: Insight into the Distribution of High-pressure Shock Metamorphism in Rubble-pile Asteroids
Authors: Nicole Güldemeister, Juulia-Gabrielle Moreau, Tomas Kohout, Robert Luther, Kai Wünnemann
Figure caption: Shock-darkening at a given pressure regime happens in specific conditions, which are illustrated in the graphic by dark gray polygons depicting a correlation between the timescale of impact events driving shock pulse duration and the pre-shock porosity of the silicates driving post-shock temperatures. The two dark gray areas are two hypothetical darkening-enabling conditions with metal and iron sulfide melt migration or whole rock melting. A transitional zone of partial melting of silicates inhibits the migration of a metal and iron sulfide melt, and separates the two dark gray polygons. An impact on a large but nonporous body as indicated on the horizontal axis is likely to produce less shock-darkened material, because of FeS and FeNi metal rapidly cooling into surrounding silicates, due to heat conduction, while an impact on a smaller and more porous body may result in more prominent shock-darkening.
Paper: Insight into the Distribution of High-pressure Shock Metamorphism in Rubble-pile Asteroids
Authors: Nicole Güldemeister, Juulia-Gabrielle Moreau, Tomas Kohout, Robert Luther, Kai Wünnemann
Figure caption: (a) Peak shock pressure distribution for a monolithic (left panel) and rubble-pile asteroid (right panel). Tracers are set back to their initial position for better visibility. (b) Apparent fraction of material experiencing certain shock stages (Stöffler et al. 2018) for a monolithic asteroid (left) and a rubble-pile asteroid (right). The numbers in the right part of the images indicate shock stages of individual gray polygons for better identification.
Paper: Tilting Uranus via Spin–Orbit Resonance with Planet Nine
Authors: Tiger Lu, Gregory Laughlin
Figure caption: Level curves of the spin axis Hamiltonian (in black) with α/g = 1.25 > (α/g)crit, with the Cassini state equilibrium points labeled (Cassini state 3 corresponds to a retrograde spin state and is not shown). Spin axis trajectories are confined to these level curves. The colored lines track the evolution of one such trajectory as the ratio ∣α/g∣ changes; note how the curve begins as a circulating trajectory and evolves into a librating one.
Paper: A New Archive of Apollo’s Lunar Seismic Data
Authors: Ceri Nunn, Yosio Nakamura, Sharon Kedar, Mark P. Panning
Figure caption: Variation in the sampling interval. (a) The variability of the sampling interval for each of the stations during 1973. (b) The variability of the sampling interval from 1973 January 1 to 7 for station S12, recorded at different ground stations (02: Ascension Island; 05: Guam; 11: Corpus Christi, Texas). The rotation of the Earth has a small effect on the apparent sampling rate (it does not affect the real sampling rate). The increase in the apparent sampling rate while a ground station is recording on (b) is due to the rotation of the Earth. The apparent sampling rate is lower when a new ground station starts recording. In both plots, we averaged the sampling over approximately 15 minutes. The plots show alternating periods of lunar night (purple) and lunar day (white). The red lines show the nominal sampling interval (0.1509434 s).
Paper: A New Archive of Apollo’s Lunar Seismic Data
Authors: Ceri Nunn, Yosio Nakamura, Sharon Kedar, Mark P. Panning
Figure caption: Data cleaning. The top panel shows the original data imported from the tape. The bottom panel shows the same data reimported, but excluding data with incorrect Barker codes (incorrect Barker codes indicate data frames that were not transmitted correctly). We have also removed single digital spikes from the trace (Figure 5 shows examples of these spikes).
Paper: A New Archive of Apollo’s Lunar Seismic Data
Authors: Ceri Nunn, Yosio Nakamura, Sharon Kedar, Mark P. Panning
Figure caption: Divergence between sample time and timestamp. Each of the data samplers controlling the sampling on the seismometers had a slightly different sampling rate that varied over time. As far as possible, the data are provided as continuous traces. Therefore, there is some divergence between the time estimates from the continuous sampling and the recorded timestamps. Data users should be aware of these differences and may need to correct for them. The divergence lines are curved. Additionally, the traces show some gaps where data were not recovered due to timing issues.
Paper: A New Archive of Apollo’s Lunar Seismic Data
Authors: Ceri Nunn, Yosio Nakamura, Sharon Kedar, Mark P. Panning
Figure caption: Data tracks provided in the miniSEED files. The top four traces show the components MHZ, MH1, MH2, and SHZ. The x-axis is the time in seconds after the P-arrival (1971-02-07 00:45:45) and the y-axis is in DU. The fifth trace, ATT, shows the timestamp. The y-axis is the number of seconds since 1970 January 1 (it is displayed with an offset of 34735545.6 s between 1970 January 1 and the arrival time).
Paper: A New Archive of Apollo’s Lunar Seismic Data
Authors: Ceri Nunn, Yosio Nakamura, Sharon Kedar, Mark P. Panning
Figure caption: Digital spike removal. The top panel shows test data with added digital spikes, while the bottom panel shows the data after the spike removal process. The algorithm removes single spikes, spikes before a gap, and spikes after a gap. Up and down spikes and double spikes (which have two data points within the spikes) are not removed by the algorithm.
Paper: Tilting Uranus via Spin–Orbit Resonance with Planet Nine
Authors: Tiger Lu, Gregory Laughlin
Figure caption: Torques associated with perturbing planets cause the inclined orbit of a planet (with normal ﹩\hat{n}﹩) to recess about the invariant plane normal ﹩\hat{k}﹩ at a rate of ﹩g\,=\dot{{\rm{\Omega }}}﹩. The planet’s spin axis ﹩\hat{s}﹩ is also shown. Not shown on this figure is the longitude of periapsis ϖ, defined as ϖ = Ω + ω.
Paper: Tilting Uranus via Spin–Orbit Resonance with Planet Nine
Authors: Tiger Lu, Gregory Laughlin
Figure caption: Torques associated with the host star and satellite system cause the spin axis to precess about the orbit normal with frequency ﹩\alpha \cos \theta ﹩.
Paper: Let It Go: Geophysically Driven Ejection of the Haumea Family Members
Authors: Jessica L. Noviello, Steven J. Desch, Marc Neveu, Benjamin C. N. Proudfoot, Sarah Sonnett
Figure caption: Visual representation of all of the pre-fling scenarios included in Table 5. The three cases with the lowest values of b/a and c are cases 16, 18, and 41.
Paper: Let It Go: Geophysically Driven Ejection of the Haumea Family Members
Authors: Jessica L. Noviello, Steven J. Desch, Marc Neveu, Benjamin C. N. Proudfoot, Sarah Sonnett
Figure caption: Average density ρ avg as a function of axes a and b.
Paper: Let It Go: Geophysically Driven Ejection of the Haumea Family Members
Authors: Jessica L. Noviello, Steven J. Desch, Marc Neveu, Benjamin C. N. Proudfoot, Sarah Sonnett
Figure caption: Core density ρ c as a function of axes a and b.
Paper: Topographically Influenced Evolution of Large-scale Changes in Comet 67P/Churyumov–Gerasimenko's Imhotep Region
Authors: Abhinav S. Jindal, Samuel P. D. Birch, Alexander G. Hayes, Orkan M. Umurhan, Raphael Marschall, Jason M. Soderblom, Jean-Baptiste Vincent, Dennis Bodewits
Figure caption: Correlations between regions with high mass-loss rates and observed activity. (a)–(e) Georeferenced images (the date the image was acquired can be found on the top left of each panel) of the Imhotep region with labeled scarps as seen in Figure 2. (f)–(j) Same images as in panels (a)–(e). The regions shaded in yellow are regions of the highest integrated mass loss (80th percentile or higher) within the selected period of time ((f) 2015 May 24–June 5, (g) 2015 June 1–June 27, (h) 2015 June 23–July 11, (i) 2015 July 7–August 6, and (j) 2015 August 2–August 23). Stars indicate the points of origin for scarps originating within the given time period, with the colors of the stars the same as the colors of the scarp labels in panels (a)–(e).
Paper: Topographically Influenced Evolution of Large-scale Changes in Comet 67P/Churyumov–Gerasimenko's Imhotep Region
Authors: Abhinav S. Jindal, Samuel P. D. Birch, Alexander G. Hayes, Orkan M. Umurhan, Raphael Marschall, Jason M. Soderblom, Jean-Baptiste Vincent, Dennis Bodewits
Figure caption: Hypothesized stratigraphy of ices within the smooth terrains. The particles closest to the surface are the most ice-depleted, and the ice content increases with depth. The figure shows three discrete subsurface ice concentrations, while the actual distribution will smoothly vary. The dashed orange, red, and green lines represent the progression of scarps “a,” “d,” and “h,” respectively.
Paper: Topographically Influenced Evolution of Large-scale Changes in Comet 67P/Churyumov–Gerasimenko's Imhotep Region
Authors: Abhinav S. Jindal, Samuel P. D. Birch, Alexander G. Hayes, Orkan M. Umurhan, Raphael Marschall, Jason M. Soderblom, Jean-Baptiste Vincent, Dennis Bodewits
Figure caption: Duration of migration and average migration rates for scarps within the Imhotep basin. Colors are the same as in Figure 3. (a) The solid bars represent the duration for which scarps migrate, with the dashed line indicating the uncertainty in this duration (due to the cadence of the images). The two stars connected by a dotted line indicate the period within which a given scarp is buried under sediment. The red vertical dashed line indicates perihelion passage for 67P. Scarps are arranged from top to bottom in decreasing order of latitude. (b) The range of average migration rates for each scarp is shown, with outliers denoted by single points. Scarps are arranged from left to right in order of when they start migrating.
Paper: Topographically Influenced Evolution of Large-scale Changes in Comet 67P/Churyumov–Gerasimenko's Imhotep Region
Authors: Abhinav S. Jindal, Samuel P. D. Birch, Alexander G. Hayes, Orkan M. Umurhan, Raphael Marschall, Jason M. Soderblom, Jean-Baptiste Vincent, Dennis Bodewits
Figure caption: Topography of the triple-scarp system in Imhotep. (a) DTM for the region encompassing the triple scarp on 2015 June 27. (b) Vertically exaggerated line profile (taken along the dashed line in panel (a)) showing the topography of the triple-scarp system. The slope along the scarp face is ∼10°. The stars along the profile indicate corresponding points in panel (a). The average velocity over the duration of migration (v) and the height of each scarp (H) are also indicated. Note that the ice-depleted layer is far thinner than the scarp depth (see Figure 10).
Paper: Topographically Influenced Evolution of Large-scale Changes in Comet 67P/Churyumov–Gerasimenko's Imhotep Region
Authors: Abhinav S. Jindal, Samuel P. D. Birch, Alexander G. Hayes, Orkan M. Umurhan, Raphael Marschall, Jason M. Soderblom, Jean-Baptiste Vincent, Dennis Bodewits
Figure caption: Thermal model setup. (a) The surface is divided into cliffs and plains, and a shape analysis is performed to calculate the total thermal input for every facet. A receiver facet (indicated in red) within a small portion of Imhotep on the SHAP4S model is highlighted in this example; this calculation is repeated for all facets on the shape. (b) We assume a two-layered structure under each facet where a volatile-rich layer (dark blue) is blanketed by a more ice-depleted (though not ice-free) top layer (light blue).
Paper: Topographically Influenced Evolution of Large-scale Changes in Comet 67P/Churyumov–Gerasimenko's Imhotep Region
Authors: Abhinav S. Jindal, Samuel P. D. Birch, Alexander G. Hayes, Orkan M. Umurhan, Raphael Marschall, Jason M. Soderblom, Jean-Baptiste Vincent, Dennis Bodewits
Figure caption: The propagation of a thermal heat wave into the smooth terrains. The dotted line indicates the thermal heat wave, while the yellow line indicates the depth the thermal wave needs to propagate to in order to initiate the positive feedback cycle of scarp migration. Once the thermal wave reaches this depth, the yellow line resets, and the cycle needs to repeat in order to reinitiate scarp migration.
Paper: Topographically Influenced Evolution of Large-scale Changes in Comet 67P/Churyumov–Gerasimenko's Imhotep Region
Authors: Abhinav S. Jindal, Samuel P. D. Birch, Alexander G. Hayes, Orkan M. Umurhan, Raphael Marschall, Jason M. Soderblom, Jean-Baptiste Vincent, Dennis Bodewits
Figure caption: Average direction of migration for scarps within the Imhotep basin. (a) Scarps initiating between 2015 May 24 and June 13. (b) Scarps initiating between 2015 June 13 and July 1. (c) Scarps initiating between 2015 July 1 and August 13.
Paper: Topographically Influenced Evolution of Large-scale Changes in Comet 67P/Churyumov–Gerasimenko's Imhotep Region
Authors: Abhinav S. Jindal, Samuel P. D. Birch, Alexander G. Hayes, Orkan M. Umurhan, Raphael Marschall, Jason M. Soderblom, Jean-Baptiste Vincent, Dennis Bodewits
Figure caption: Variability of direct solar input within the triple-scarp region. (a) Cropped image of the triple-scarp region taken on 2014 September 5. The region remains unaltered until 2015 June 3, when scarp “a” starts migrating. (b) Modeled direct solar input within the triple-scarp region on 2015 June 1. The cyan box covers the region through which scarp “a” migrates; the pink box covers the area through which scarps “d” and “h” migrate.
Paper: Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra
Authors: Konstantin T. Matchev, Katia Matcheva, Alexander Roman
Figure caption: Scatter plots of 25,000 data points: the average μ(M) (plotted on the x-axis) vs. the standard deviation σ(M) (plotted on the y-axis). In each panel, the points are color-coded by the value of one of the five target variables, indicated at the top. The black ⋆ symbol marks the location of the hot gas giant exoplanet WASP-12b.
Paper: Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra
Authors: Konstantin T. Matchev, Katia Matcheva, Alexander Roman
Figure caption: The same as Figure 4, but plotted in the plane of the first and second PCA components (top row) or the plane of the second and third PCA components (bottom row).
Paper: Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra
Authors: Konstantin T. Matchev, Katia Matcheva, Alexander Roman
Figure caption: Scatter plots of 15,000 data points from the benchmark data set: M(λ 1) vs. T (left panel) and M(λ 1) vs. the variable in (12), which can be equivalently expressed as ﹩{\mathrm{log}}_{10}({X}_{{{\rm{H}}}_{2}{\rm{O}}}{X}_{\mathrm{HCN}}{X}_{{\mathrm{NH}}_{3}}{\kappa }_{\mathrm{cl}})﹩ (right panel). The points are color-coded by the value of ﹩{\mathrm{log}}_{10}({\tau }_{0})﹩, as indicated on the colorbar. The horizontal black dotted lines denote the constant threshold ﹩M{({\lambda }_{1})=({R}_{0}/{R}_{S})}^{2}\,\times \,100 \% ﹩.
Paper: Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra
Authors: Konstantin T. Matchev, Katia Matcheva, Alexander Roman
Figure caption: The dependence of the equivalent thickness h (measured in units of H) on the optical thickness τ 0. The blue solid line gives the exact result (5), the red dotted–dashed line is approximation (9), and the black dotted line shows the effect of the E 1 term (8).
Paper: Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra
Authors: Konstantin T. Matchev, Katia Matcheva, Alexander Roman
Figure caption: Correlation matrix of the 13 features {M(λ  i )}, i = 1,…,13.
Paper: Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra
Authors: Konstantin T. Matchev, Katia Matcheva, Alexander Roman
Figure caption: Correlation scatter plots (25,000 points) of the first two PCA components against the summary statistics parameters μ(M) and σ(M), respectively.
Paper: Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra
Authors: Konstantin T. Matchev, Katia Matcheva, Alexander Roman
Figure caption: The cumulative explained variance ratio as a function of the number of included PCA components.
Paper: Unsupervised Machine Learning for Exploratory Data Analysis of Exoplanet Transmission Spectra
Authors: Konstantin T. Matchev, Katia Matcheva, Alexander Roman
Figure caption: The same as Figure 7, but plotted in the plane of the first two ISOMAP components.
Paper: A New Archive of Apollo’s Lunar Seismic Data
Authors: Ceri Nunn, Yosio Nakamura, Sharon Kedar, Mark P. Panning
Figure caption: Seismic data availability. The experiments included three-component mid-period instruments (MHZ, MH1, and MH2), which operated in either peaked mode (green lines) or flat mode (light blue lines), and short-period instruments (SHZ; dark blue lines). We exclude S12's SHZ component (which was inoperative throughout the mission) and we partially exclude S14's MHZ component (which was inoperative for much of the mission).
Paper: A New Archive of Apollo’s Lunar Seismic Data
Authors: Ceri Nunn, Yosio Nakamura, Sharon Kedar, Mark P. Panning
Figure caption: Transfer functions. Displacement amplitude (top) and phase (bottom) transfer functions for the flat and peaked modes of the mid-period seismometer and the short-period seismometer. The plots show the nominal responses up to the Nyquist frequency (dashed lines). The units of amplitude are the DUs per meter. The phases show the counterclockwise angle from the positive real axis on the complex plane in radians. The transfer functions in velocity and acceleration are available in Nunn et al. (2020).
Paper: A New Archive of Apollo’s Lunar Seismic Data
Authors: Ceri Nunn, Yosio Nakamura, Sharon Kedar, Mark P. Panning
Figure caption: Examples of a deep moonquake, a meteoroid impact, a shallow moonquake, and an artificial impact. The events were recorded on seismic station S12 on the vertical component (MHZ). The timing for each event is in minutes and relative to the arrival time. The traces are displayed in displacement (in meters), with different scales for each event. The amplitude of the artificial impact signal exceeded the range of the instrument.
Paper: A New Archive of Apollo’s Lunar Seismic Data
Authors: Ceri Nunn, Yosio Nakamura, Sharon Kedar, Mark P. Panning
Figure caption: The locations of the seismic stations. The plot shows the locations of the stations included in the archive. The background shows lunar topography from Araki et al. (2009).
Paper: Chemical Equilibrium between Cores, Mantles, and Atmospheres of Super-Earths and Sub-Neptunes and Implications for Their Compositions, Interiors, and Evolution
Authors: Hilke E. Schlichting, Edward D. Young
Figure caption: Same as Figure 10, but for the unreactive metal scenario. Mole fractions of species in the atmosphere as a function of hydrogen fraction varying from 1% to 14% by weight at a fixed magma ocean surface temperature of 4500 K.
Paper: Free Core Nutation and Its Relation to the Spin-over Mode
Authors: Jérémy Rekier
Figure caption: Magnitude (top) and phase (bottom) of the transfer function for the two-layer elastic planet for the parameters of Table 1, with the exception that ﹩{e}_{{\rm{f}}}+\mathrm{Re}({K}_{\mathrm{cmb}})﹩ is treated as a constant (see main text). The blue curve corresponds to K cmb = 0, the yellow one to K cmb ≠ 0, and the green one is similar to the yellow one but for ﹩{\bar{\omega }}_{\mathrm{som}}^{\epsilon }\to -1﹩. The black dashed and dotted lines indicate the positions of the frequencies ﹩\mathrm{Re}({\bar{\omega }}_{\mathrm{fcn}})﹩ and ﹩\mathrm{Re}({\bar{\omega }}_{\mathrm{som}}^{\epsilon })﹩, respectively. Their red equivalents respectively correspond to the maximum and minimum of the yellow curve.