adsabs/AstroCLIMB huggingface dataset:
Paper: Jupiter’s Interior with an Inverted Helium Gradient
Authors: N. Nettelmann, J. J. Fortney
Figure caption: He depletion at the 1 Mbar level. Lines show the Y–T relation at 1 Mbar of adiabatic H/He profiles according to the LHR0911 H/He phase diagram for different shifts thereof, while points are for H/He profiles with a subadiabatic OSL. The color indicates T1 bar of the underlying adiabats (lines) or model P–T profiles (points).
Paper: Jupiter’s Interior with an Inverted Helium Gradient
Authors: N. Nettelmann, J. J. Fortney
Figure caption: Evolution of the atmospheric Ne/He ratio and the atmospheric He mass abundance due to the ongoing He rain underneath the OSL (a) or in the absence of an OSL (b) at time t0 when He rain begins; all curves begin at Ne/He=1. Left panel: different colors represent different H/He phase diagrams via the exponent n = 0.5 (blue), 1 (yellow), 2 (red). Color intensity increases from fenh = 50 to 140. Solid lines are for DNe = DHe while colored dashed lines for DNe < DHe. Thin, medium, and thick lines are for −ΔG = −1.6, −2.8, and −3.4. Free black dashed lines assume fenh = 80 and −ΔG = 2.8, but a thinner OSL compared to the respective solutions is indicated by a black dashed line on top of the colored lines of the same line style. Right panel: without an OSL, and therefore curves for different exponents n fall on top of each other. Color intensity indicates the Ne-partitioning preference ΔG. The black symbol indicates the observed value in Jupiter’s atmosphere.
Paper: Jupiter’s Interior with an Inverted Helium Gradient
Authors: N. Nettelmann, J. J. Fortney
Figure caption: Ratio of thermal to radiative gradient in the OSL. This ratio directly yields the required reduction in Rosseland mean opacity for solar composition κR ∼ ∇rad for the OSL to be radiative. Curves are for different assumed ΔY-values (color code) and the two different Bond albedo measurements.
Paper: Wind Shear and the Role of Eddy Vapor Transport in Driving Water Convection on Jupiter
Authors: Ramanakumar Sankar, Michael H. Wong, Csaba Palotai, Shawn Brueshaber
Figure caption: A periodic spacing of convective plumes was visible in the South Equatorial Belt in 2017, most clearly seen in the infrared at 4 μm (top panel), where reflectivity is greatest from cloud/haze features present at high altitude or containing large particles (or both). The bottom panel is a methane-band composite, where deep clouds appear red and high, clearings appear dark, and thick clouds appear white. The combination of these three elements is a signature of active moist convection (M. Imai et al. 2020; M. H. Wong et al. 2023). Blue arrows are evenly spaced 8° longitude apart. IRTF data are described in G. S. Orton et al. (2017), and HST data are described in M. H. Wong et al. (2020) and available from M. Wong (2017).
Paper: Wind Shear and the Role of Eddy Vapor Transport in Driving Water Convection on Jupiter
Authors: Ramanakumar Sankar, Michael H. Wong, Csaba Palotai, Shawn Brueshaber
Figure caption: Spectrogram showing the distribution of wavenumbers for different shear cases, averaged over the last 100 days at a latitude of 20° north and 40° south. Note the difference in the spectral distribution at the two locations and, for 20° north, how the higher-shear cases show both an increased spectral power distribution across the wavenumber space and more eddies with higher wavenumbers (i.e., smaller longitudinal extent).
Paper: Wind Shear and the Role of Eddy Vapor Transport in Driving Water Convection on Jupiter
Authors: Ramanakumar Sankar, Michael H. Wong, Csaba Palotai, Shawn Brueshaber
Figure caption: The difference between the temperature at days 50, 100, and 125 from the average temperature from the first 30 days of the simulation. The differences are zonally averaged. There is some evolution in the temperature field in the first 100 days, but the model achieves a quasi-steady state at this point, after which there is a much smaller change in the temperature field.
Paper: Wind Shear and the Role of Eddy Vapor Transport in Driving Water Convection on Jupiter
Authors: Ramanakumar Sankar, Michael H. Wong, Csaba Palotai, Shawn Brueshaber
Figure caption: The zonal mean cloud densities at three different time steps from our model atmosphere. There is little change in the cloud densities between the three time steps, showing that the model has reached a quasi-steady state by day 50, but cloud densities do still continue to evolve slowly during the latter part of the simulations.
Paper: Wind Shear and the Role of Eddy Vapor Transport in Driving Water Convection on Jupiter
Authors: Ramanakumar Sankar, Michael H. Wong, Csaba Palotai, Shawn Brueshaber
Figure caption: Effect of the model hyperviscosity on the convected water vapor. We find that the most prominent effect is in the first 10–15 days, whereas beyond this adjustment phase there is negligible effect of the hyperviscosity on the model atmosphere.
Paper: A Catalytic Pathway for the Formation of Cyanobenzene in Nitrogen-rich Environments and the Spectroscopy of the Reactive Intermediates
Authors: Vincent J. Esposito, Silvia Alessandrini, David Dubois, Ryan C. Fortenberry
Figure caption: Reaction pathway connecting isocyanobenzene with cyanobenzene computed at the CCSD(T)-F12b/cc-pVTZ-F12 // B3LYP/aug-cc-pVTZ level of theory. The negative charge is carried through the reaction coordinate but is only shown for the terminal structures. The reactive intermediates that underwent further spectroscopic characterization are indicated with a star.
Paper: A Catalytic Pathway for the Formation of Cyanobenzene in Nitrogen-rich Environments and the Spectroscopy of the Reactive Intermediates
Authors: Vincent J. Esposito, Silvia Alessandrini, David Dubois, Ryan C. Fortenberry
Figure caption: Rotational spectrum of the five intermediates obtained at T = 300 K in the range 0–300 GHz.
Paper: A Catalytic Pathway for the Formation of Cyanobenzene in Nitrogen-rich Environments and the Spectroscopy of the Reactive Intermediates
Authors: Vincent J. Esposito, Silvia Alessandrini, David Dubois, Ryan C. Fortenberry
Figure caption: Anharmonic IR absorption spectra from 300 to 3200 cm−1 of the reactive intermediates identified by a star in Figure 2. The spectra are artificially broadened with an FWHM = 1 cm−1.
Paper: A Catalytic Pathway for the Formation of Cyanobenzene in Nitrogen-rich Environments and the Spectroscopy of the Reactive Intermediates
Authors: Vincent J. Esposito, Silvia Alessandrini, David Dubois, Ryan C. Fortenberry
Figure caption: Schematic representation of the TM+LR approach for the five different intermediates of the reaction between NCN− and cyanobenzene. The halos indicate which fragments have been employed for the TM model: purple for benzene, light blue for methanimine, and green for H2NCN. The linkage bonds between fragments have been corrected using the linear regression model. Principal inertia axes are also shown.
Paper: A Catalytic Pathway for the Formation of Cyanobenzene in Nitrogen-rich Environments and the Spectroscopy of the Reactive Intermediates
Authors: Vincent J. Esposito, Silvia Alessandrini, David Dubois, Ryan C. Fortenberry
Figure caption: Anharmonic IR absorption spectra from 2000 to 2400 cm−1 of the reactive intermediates identified by a star in Figure 2. The spectra are artificially broadened with an FWHM of 1 cm−1.
Paper: A Catalytic Pathway for the Formation of Cyanobenzene in Nitrogen-rich Environments and the Spectroscopy of the Reactive Intermediates
Authors: Vincent J. Esposito, Silvia Alessandrini, David Dubois, Ryan C. Fortenberry
Figure caption: Anharmonic IR absorption spectra from 2800 to 3200 cm−1 of the reactive intermediates identified by a star in Figure 2. The spectra are artificially broadened with an FWHM of 1 cm−1.
Paper: A Catalytic Pathway for the Formation of Cyanobenzene in Nitrogen-rich Environments and the Spectroscopy of the Reactive Intermediates
Authors: Vincent J. Esposito, Silvia Alessandrini, David Dubois, Ryan C. Fortenberry
Figure caption: Anharmonic IR absorption spectra from 1300 to 1700 cm−1 of the reactive intermediates identified by a star in Figure 2. The spectra are artificially broadened with an FWHM = 1 cm−1.
Paper: Origin of Phobos and Deimos: Orbital Evolution Shortly after Formation from a Potential Dislocation
Authors: Ryan Dahoumane, Kévin Baillié, Valéry Lainey
Figure caption: Cumulative fraction of collisions as a function of simulation time. We made different simulations considering different configurations. For each of these configurations, we made 600 simulations for each value of aPhobos. The “Original” curves are a pure reproduction of R. Hyodo et al. (2022) results, and “New OE” curves have the same physical effects as those considered by R. Hyodo et al., but with the new initial orbital elements repartition detailed in this paper. Then, in the “J3” curves, we also added the oblateness term J3, after which we also added the Sun gravitational perturbations in the “J3 + Sun” curves. As mentioned in its name, we then added the precession in the “J3+Sun+Precession” curves, and finally, we added the Martian sectoral terms C22 and S22 in the “Full” simulation.
Paper: Origin of Phobos and Deimos: Orbital Evolution Shortly after Formation from a Potential Dislocation
Authors: Ryan Dahoumane, Kévin Baillié, Valéry Lainey
Figure caption: Representation of the fixed and moving frames. The first frame, which is fixed, is defined by arbitrary axes (X, Y, Z). After three rotations with the angles (I, ψ, χ), this fixed frame can be turned into the rotating frame ﹩({{\boldsymbol{X}}}^{{\prime} },{{\boldsymbol{Y}}}^{{\prime} },{\boldsymbol{k}})﹩, where ﹩{{\boldsymbol{X}}}^{{\prime} }﹩ is toward the first meridian and k is the perpendicular to the equator. We also represented ﹩\bar{{\boldsymbol{X}}}﹩, which is directed toward the ascending equatorial node.
Paper: Origin of Phobos and Deimos: Orbital Evolution Shortly after Formation from a Potential Dislocation
Authors: Ryan Dahoumane, Kévin Baillié, Valéry Lainey
Figure caption: Distribution of the initial semimajor axes and eccentricities of the simulations. Each colored box represents the orbital elements distribution allowed by the constraints mentioned in Section 2.3.1. The “H22” refers to the one used by R. Hyodo et al. (2022) in their simulations, while the “This Paper” shows those used in the present paper. Note that the green color is the superposition of yellow and light blue, while the purple is the overlap of red and dark blue.
Paper: Origin of Phobos and Deimos: Orbital Evolution Shortly after Formation from a Potential Dislocation
Authors: Ryan Dahoumane, Kévin Baillié, Valéry Lainey
Figure caption: Cumulative fraction of collisions as a function of impact velocity. We did the same plot as in R. Hyodo et al. (2022) to compare their results with our new simulations. These results come from the same simulations as those presented in Figure 3. The plain, dashed, and dotted lines represent represent, respectively, the reproduction of R. Hyodo et al.'s (2022) results, the results from a physical model similar to R. Hyodo et al. (2022) but with new orbital elements (see Figure 1), and the simulations with our new physical modeling and orbital elements distribution. The colors light, middle, and dark gray represent, respectively, the simulations in which we considered the initial semimajor axis of Phobos as equal to 6, 5.5, and 5 Mars radii.
Paper: Laser-induced Breakdown Spectroscopy of Ice-regolith Mixtures: Implications for Measurements on Planetary Surfaces
Authors: Frédéric Diotte, Myriam Lemelin, François R. Doucet, Lütfü Ç. Özcan
Figure caption: Predicted vs. actual H2O content plots for models evaluated using two different training/test data splits. The solid line is the linear regression line linking the predicted H2O content to the measured H2O content. The dashed lines indicate a 1:1 relationship between predicted and measured H2O contents. (a) The data set was randomly split on an 80/20 basis, and the optimal model employed six components with preprocessed spectra normalized to the total area under the continuum. (b) The same splitting procedure and the same model were used, but we used the average of the full scan instead of the first line. (c) “Cemented” ice-regolith simulants served as the training set, while “discrete” ice-regolith simulants were used as the test set. The optimal model used two components with preprocessed, nonnormalized spectra.
Paper: Laser-induced Breakdown Spectroscopy of Ice-regolith Mixtures: Implications for Measurements on Planetary Surfaces
Authors: Frédéric Diotte, Myriam Lemelin, François R. Doucet, Lütfü Ç. Özcan
Figure caption: Emission intensity of different lines and line ratios vs. percent hydrogen for all samples.
Paper: Laser-induced Breakdown Spectroscopy of Ice-regolith Mixtures: Implications for Measurements on Planetary Surfaces
Authors: Frédéric Diotte, Myriam Lemelin, François R. Doucet, Lütfü Ç. Özcan
Figure caption: PLS regression coefficients for models trained over two H2O content ranges. The blue lines represent the PLS coefficients, while the gray line represents a scaled LIBS spectrum of an LHS simulant containing 20 wt% H2O for comparison. (a) Model trained on regolith simulants with 0–10 wt% H2O. (b) Model trained on regolith simulants with 0–40 wt% H2O.
Paper: The Viability of Glycine Fermentation in Titan’s Subsurface Ocean
Authors: Antonin Affholder, Peter M. Higgins, Charles S. Cockell, Catherine Neish, Krista M. Soderlund, Michael J. Malaska, Kendra K. Farnsworth, Rosaly M. C. Lopes, Conor A. Nixon, Mohit Melwani Daswani, Kelly E. Miller, Christophe Sotin
Figure caption: Growth window for various organisms. (a) Box plots of the empirically measured maximum, optimum, and minimum growth temperatures for organisms in the data set used to build the habitability model in this work (shown in purple boxes; R. Corkrey et al. 2016) and for organisms in the class Clostridia from those indexed in the TEMPURA database (shown in olive boxes; Y. Sato et al. 2020). The outer whiskers show the total extent of the data sets. (b) The pressure and (c) pH limits of polyextremophiles from J. P. Harrison et al. (2013) and Clostridia indexed in IMG/M (I.-M. A. Chen et al. 2023). The blue bar shows Titan’s bulk ocean temperature window (C. Sotin et al. 2021) and the gray bar shows the pressure range in Titan’s ocean. The gray line in panel (c) shows the Titan ocean pH as modeled in this work (11.3; see Section 3.1.1).
Paper: The Viability of Glycine Fermentation in Titan’s Subsurface Ocean
Authors: Antonin Affholder, Peter M. Higgins, Charles S. Cockell, Catherine Neish, Krista M. Soderlund, Michael J. Malaska, Kendra K. Farnsworth, Rosaly M. C. Lopes, Conor A. Nixon, Mohit Melwani Daswani, Kelly E. Miller, Christophe Sotin
Figure caption: Value of the Gibbs free energy of the glycine fermentation reaction (Equation (1)) as a function of glycine concentration for the different considered endmember scenarios.
Paper: The Viability of Glycine Fermentation in Titan’s Subsurface Ocean
Authors: Antonin Affholder, Peter M. Higgins, Charles S. Cockell, Catherine Neish, Krista M. Soderlund, Michael J. Malaska, Kendra K. Farnsworth, Rosaly M. C. Lopes, Conor A. Nixon, Mohit Melwani Daswani, Kelly E. Miller, Christophe Sotin
Figure caption: Sketch of Titan’s internal structure summarizing the hypotheses that are tested in this work: 1—initial habitable conditions for glycine fermentation enabled by dissolution of core organic matter; 2—sustained population and biomass production from organic delivery from Titan’s surface. Approximate length scales for each layer are noted to the left. Approximate length scales for the internal structure are from C. Sotin et al. (2021), and approximate length scales for the atmosphere are from C. A. Nixon (2024). A possible shallow and variable organic-rich layer is noted to the right, with maximal depth rounded to ~1 km (the deepest observed labyrinth is approximately 800 m; M. J. Malaska et al. 2020). Not to scale.
Paper: ORIGIN: Laser Desorption Ionization Mass Spectrometry of Nucleobases for In Situ Space Exploration
Authors: Nikita J. Boeren, Peter Keresztes Schmidt, Marek Tulej, Peter Wurz, Andreas Riedo
Figure caption: Distribution of positive detections of adenine at m/z 135 and 136 (SNR > 6) for 900 positions with 100 laser shots applied per position. Light blue: no detection; dark blue: positive detection. The histogram on top shows the adenine signal as a function of applied laser shots; the histogram on the right shows the adenine signal as a function of location in the sample cavity. The measurement was performed on a sample deposit of 5 pmol adenine spread out in a 7.1 mm2 cavity.
Paper: ORIGIN: Laser Desorption Ionization Mass Spectrometry of Nucleobases for In Situ Space Exploration
Authors: Nikita J. Boeren, Peter Keresztes Schmidt, Marek Tulej, Peter Wurz, Andreas Riedo
Figure caption: Mass spectra acquired by the ORIGIN setup of adenine (A), guanine (G), uracil (U), thymine (T), cytosine (C), and 5-methylcytosine (mC) with their molecular structure and peaks annotated by their corresponding m/z value. Concentrations were 5 pmol mm−2 for A; 14 pmol mm−2 for G, C, and mC; 707 pmol mm−2 for U; and 141 pmol mm−2 for T.
Paper: ORIGIN: Laser Desorption Ionization Mass Spectrometry of Nucleobases for In Situ Space Exploration
Authors: Nikita J. Boeren, Peter Keresztes Schmidt, Marek Tulej, Peter Wurz, Andreas Riedo
Figure caption: Peak areas of adenine m/z 135 and 136 peaks summed over the number of positions (total 900 positions) from the same 30-by-30 raster campaign (Figure 3).
Paper: ORIGIN: Laser Desorption Ionization Mass Spectrometry of Nucleobases for In Situ Space Exploration
Authors: Nikita J. Boeren, Peter Keresztes Schmidt, Marek Tulej, Peter Wurz, Andreas Riedo
Figure caption: Mass spectra of four different mixtures of nucleobases adenine (A), guanine (G), cytosine (C), thymine (T), uracil (U), and 5-methylcytosine (mC), at various ratios acquired with ORIGIN. The ratios of the compounds in the mixtures can be found in Table 1.
Paper: Application of Machine Learning Techniques to Distinguish between Mare, Cryptomare, and Light Plains in Central Lunar South Pole−Aitken Basin
Authors: Frank C. Chuang, Matthew D. Richardson, Jennifer L. Whitten, Daniel P. Moriarty, Deborah L. Domingue
Figure caption: Central SPA study region (yellow) between 40° and 60° south and between 180° and 210° east with flat plains, low-albedo smooth maria, and rougher higher-standing terrain. Notable features within the study region include Apollo basin, “Mickey mare,” and craters Maksutov and Baldet with floors that are infilled by dark smooth maria (arrows). The locations of maria mapped by D. A. Nelson et al. (2014) and cryptomaria mapped by J. L. Whitten & J. W. Head (2015a) are outlined in black and white, respectively. The background LROC WAC mosaic at 100 m pixel−1 resolution is in a Lambert azimuthal map projection with a 180° east central meridian and a standard latitude of 45° south.
Paper: Application of Machine Learning Techniques to Distinguish between Mare, Cryptomare, and Light Plains in Central Lunar South Pole−Aitken Basin
Authors: Frank C. Chuang, Matthew D. Richardson, Jennifer L. Whitten, Daniel P. Moriarty, Deborah L. Domingue
Figure caption: TRI map derived from LRO WAC stereo DTM data for the central SPA study region. Areas showing the background grayscale LRO WAC basemap have been masked to focus on the lower-elevation plains and crater/basin floors where maria and cryptomaria are present. Locations with low ruggedness are in blue, and locations with higher ruggedness are in red. See text for details on the masking and calculation of TRI. The color ramp uses the full range of values with no stretch.
Paper: Application of Machine Learning Techniques to Distinguish between Mare, Cryptomare, and Light Plains in Central Lunar South Pole−Aitken Basin
Authors: Frank C. Chuang, Matthew D. Richardson, Jennifer L. Whitten, Daniel P. Moriarty, Deborah L. Domingue
Figure caption: Hapke photometric parameter band ratios for (a) 321/415 nm and (b) 566/689 nm in the central SPA study region. Note the strong signatures for dark smooth maria in the southwest Apollo basin and craters Maksutov, Nishina, and Baldet in the NUV 321/415 nm ratio. In comparison, the signature for the 566/689 nm ratio in the VNIR is spectrally indistinct with no particular features highlighted. The color ramps in both panels have a stretch of 0.5 standard deviation about the mean. Histograms of the (c) 321/415 nm and (d) 566/689 nm ratios show a narrow peak at 0.7–0.8 for the former and a broader peak between 0.7 and 1 for the latter. Values within the narrow peak are strongly associated with mare materials in the study region.
Paper: Cross Validation of Albedo Determination for 1627 Ivar from Three Different Techniques
Authors: Elena Selmi, M. Devogèle, J. R. Masiero, N. Vega Santiago, E. L. Wright, M. Ferrais, E. Fernández-Valenzuela, G. Borisov, Ph. Bendjoya, J.-P. Rivet, L. Abe, D. Vernet, A. Cellino
Figure caption: Left: phase–polarization curve of Ivar. The orange lines correspond to the fits explored by the MCMC before finding the best one (blue line). The 0 point at 4∘ was ignored, which did not affect the final results. Right: resulting calibration at angle α = 34﹩\mathop{.}\limits^{\unicode{x000b0}}﹩29. The asteroids used for the calibrations are 1990 UQ, 1998 OR2 (M. Devogèle et al. 2024), 1998 WT24 (N. Kiselev et al. 2002), 1999 RM45, 2000 PQ9, 2000 SL, 2001 SN 263, 2003 QQ47, 2005 UD (M. Devogèle et al. 2020; M. Ishiguro et al. 2022), Apollo, Eros, Midas (all three from P. Bendjoya et al. 2022), Bennu (A. Cellino et al. 2018), Don Quixote (J. Geem et al. 2022), Didymos (Z. Gray et al. 2024), Hephaistos, Nereus, Phaethon (M. Devogèle et al. 2018; R. Okazaki et al. 2020; N. Kiselev et al. 2022), and Ra Shalom (N. Kiselev et al. 1999).
Paper: Cross Validation of Albedo Determination for 1627 Ivar from Three Different Techniques
Authors: Elena Selmi, M. Devogèle, J. R. Masiero, N. Vega Santiago, E. L. Wright, M. Ferrais, E. Fernández-Valenzuela, G. Borisov, Ph. Bendjoya, J.-P. Rivet, L. Abe, D. Vernet, A. Cellino
Figure caption: First row: spectral energy distribution fits for the spherical (left) and triaxial (right) models for the 16 epochs listed in Table 1. The normalization on the units of the y-axis allows for a more direct comparison between different wavelength regimes, as per E. L. Wright (2007). Second and third row: diameter and albedo fits for the spherical (left) and triaxial (right) models. The red dashed lines correspond to the single fits with the lowest χ2, while we show in solid blue and green, respectively, the weighted mean and median fits, with dotted lines delimiting their corresponding 1σ regions.
Paper: Application of Machine Learning Techniques to Distinguish between Mare, Cryptomare, and Light Plains in Central Lunar South Pole−Aitken Basin
Authors: Frank C. Chuang, Matthew D. Richardson, Jennifer L. Whitten, Daniel P. Moriarty, Deborah L. Domingue
Figure caption: Hapke photometrically standardized maps of the (a) 360 nm band and (b) 643 nm band in the central SPA study region. The differences between each of the nine map bands are subtle, with greater spectral contrast at shorter wavelengths (360 nm) than at longer wavelengths (643 nm). Note the association of dark smooth mare areas in Figure 2 with the lowest spectral values in both panels. The color ramps in both panels have a stretch of 2.5 standard deviations about the mean.
Paper: Cross Validation of Albedo Determination for 1627 Ivar from Three Different Techniques
Authors: Elena Selmi, M. Devogèle, J. R. Masiero, N. Vega Santiago, E. L. Wright, M. Ferrais, E. Fernández-Valenzuela, G. Borisov, Ph. Bendjoya, J.-P. Rivet, L. Abe, D. Vernet, A. Cellino
Figure caption: Fits for the inversion angle (left) and the albedo distribution (right), as explored by the MCMC routine introduced in M. Devogèle et al. (2024).