adsabs/AstroCLIMB huggingface dataset:
Paper: Subsurface Thermophysical Properties of Europa’s Leading and Trailing Hemispheres as Revealed by ALMA
Authors: Alexander E. Thelen, Katherine de Kleer, Maria Camarca, Alex Akins, Mark Gurwell, Bryan Butler, Imke de Pater
Figure caption: Comparison of residuals for Europa’s leading hemisphere in ALMA Band 3 using two different global porosity models: 20% (A) and 70% (B). Europa’s surface is denoted by a dashed circle. Contours, increasing in 3σ intervals, are shown (solid lines).
Paper: Signatures of X-Ray-dominated Chemistry in the Spectra of Exoplanetary Atmospheres
Authors: Daniele Locci, Giambattista Aresu, Antonino Petralia, Giuseppina Micela, Antonio Maggio, Cesare Cecchi-Pestellini
Figure caption: Transmission spectra computed by varying the value of the X-ray luminosity: L X = 1026 (green line), 1028 (red line), and 1030 erg s−1 (blue line) with T X = 0.3, 0.5, and 1 keV, respectively.
Paper: Signatures of X-Ray-dominated Chemistry in the Spectra of Exoplanetary Atmospheres
Authors: Daniele Locci, Giambattista Aresu, Antonino Petralia, Giuseppina Micela, Antonio Maggio, Cesare Cecchi-Pestellini
Figure caption: Transmission spectra for L X = 1028 erg s−1 (left panel) and L X = 1030 erg s−1 (right panel), in which the contributions arising from individual species are highlighted.
Paper: Signatures of X-Ray-dominated Chemistry in the Spectra of Exoplanetary Atmospheres
Authors: Daniele Locci, Giambattista Aresu, Antonino Petralia, Giuseppina Micela, Antonio Maggio, Cesare Cecchi-Pestellini
Figure caption: Chemical vertical profiles for the species CH4, C2H2, and ﹩\mathrm{HCN}﹩ positively reacting to the presence of XUV radiation (left panels) and their individual transmission spectra (right panels). Dashed lines in the left panels indicate the pressure at which the integrated contribution function, Equation (6), of the individual species is q = 0.1 and 0.9 for the three values of L X. Green lines: L X = 1026 erg s−1; red lines: L X = 1028 erg s−1; blue lines: L X = 1030 erg s−1.
Paper: Signatures of X-Ray-dominated Chemistry in the Spectra of Exoplanetary Atmospheres
Authors: Daniele Locci, Giambattista Aresu, Antonino Petralia, Giuseppina Micela, Antonio Maggio, Cesare Cecchi-Pestellini
Figure caption: Wavelength-dependent contribution functions using low- (red lines) and high- (blue lines) resolution powers for increasing values of the boundary pressure P = 1 × 10−5, 1 × 10−4, 1 × 10−3, and 1 × 10−2 bars (top to bottom) for L X = 1026 erg s−1 (left panel) and L X = 1030 erg s−1 (right panel). We recall that contribution functions vary from 0 (no signal) to 1 (full contribution).
Paper: Signatures of X-Ray-dominated Chemistry in the Spectra of Exoplanetary Atmospheres
Authors: Daniele Locci, Giambattista Aresu, Antonino Petralia, Giuseppina Micela, Antonio Maggio, Cesare Cecchi-Pestellini
Figure caption: Difference spectra in percent between the model with L X = 1028 and 1026 erg s−1 (left panel) and the model with L X = 1030 and 1026 erg s−1 (right panel), constructed using three values of the resolving power, R = 300 (red line), 3000 (green line), and 50,000 (blue line).
Paper: Signatures of X-Ray-dominated Chemistry in the Spectra of Exoplanetary Atmospheres
Authors: Daniele Locci, Giambattista Aresu, Antonino Petralia, Giuseppina Micela, Antonio Maggio, Cesare Cecchi-Pestellini
Figure caption: Histogram of the number of lines arising from single pressure layers. Top panel: L X = 1026 erg s−1; bottom panel: L X = 1030 erg s−1. Green line: low resolution; red lines: high resolution.
Paper: Signatures of X-Ray-dominated Chemistry in the Spectra of Exoplanetary Atmospheres
Authors: Daniele Locci, Giambattista Aresu, Antonino Petralia, Giuseppina Micela, Antonio Maggio, Cesare Cecchi-Pestellini
Figure caption: Wavelength-dependent contribution functions using low, R = 300 (left panel), and high, R = 50,000 (right panel), resolution powers, displayed for the whole range of pressures (i.e., from p = 10−10 to 1 bar). The X-ray intensity is L X = 1030 erg s−1.
Paper: Signatures of X-Ray-dominated Chemistry in the Spectra of Exoplanetary Atmospheres
Authors: Daniele Locci, Giambattista Aresu, Antonino Petralia, Giuseppina Micela, Antonio Maggio, Cesare Cecchi-Pestellini
Figure caption: Same as Figure 3 for the negatively reacting species, H2O, CO, and CO2.
Paper: Three Years of ACB Phase Function Observations from the Mars Science Laboratory: Interannual and Diurnal Variability and Constraints on Ice Crystal Habit
Authors: Alex C. Innanen, Brittney A. Cooper, Conor W. Hayes, Charissa L. Campbell, Jacob L. Kloos, Scott D. Guzewich, John E. Moores
Figure caption: The three frames of the Sol 2633 pointing 5 movie before (top) and after (bottom) MFS. Cloud features that are not present in the raw frames are clear in the MFS frames.
Paper: Juno’s JunoCam Images of Europa
Authors: C. J. Hansen, M. A. Ravine, P. M. Schenk, G. C. Collins, E. J. Leonard, C. B. Phillips, M. A. Caplinger, F. Tosi, S. J. Bolton, Björn Jónsson
Figure caption: (a) Map showing the four JunoCam color images coregistered and map-projected onto a monochrome Voyager-Galileo global mosaic in simple cylindrical projection (cropped to highlight the JunoCam coverage area). The view is centered on the sub-Jovian hemisphere with some additional terrains to the east. The bright rayed crater Pwyll is just beyond the eastern edge of the JunoCam coverage area at −30, 90E but its rays of ejecta are visible in the fourth image. The abundant dark lineaments are double ridges flanked by dark reddish deposits. (b) Cylindrical maps showing phase, incidence, and emission angles and pixel scales for the four JunoCam mosaics of Europa, with range of angles and pixel scales represented in the 0–256 brightness scale. Map coverage is 60S to 90N, −12E to 105E.
Paper: Juno’s JunoCam Images of Europa
Authors: C. J. Hansen, M. A. Ravine, P. M. Schenk, G. C. Collins, E. J. Leonard, C. B. Phillips, M. A. Caplinger, F. Tosi, S. J. Bolton, Björn Jónsson
Figure caption: The image on the left is a composite of the four images JunoCam received, from the perspective of the fourth image. On the right side the four individual images show the rapid change in altitude and coverage. The upper left on the right side is the first image, the upper right is the second image, the lower left is the third image, and the lower right is the fourth image. The diagram on the bottom right shows the small area covered by JunoCam images relative to the Galileo map.
Paper: Juno’s JunoCam Images of Europa
Authors: C. J. Hansen, M. A. Ravine, P. M. Schenk, G. C. Collins, E. J. Leonard, C. B. Phillips, M. A. Caplinger, F. Tosi, S. J. Bolton, Björn Jónsson
Figure caption: Portion of JunoCam Europa mosaic 1. (a) Green filter mosaic map-projected at native 1000 m pixel−1 resolution; (b) global integrated super-resolution mosaic map-projected at 330 m pixel−1 scales, illustrating the improvement in feature recognition using the technique described in the text.
Paper: Juno’s JunoCam Images of Europa
Authors: C. J. Hansen, M. A. Ravine, P. M. Schenk, G. C. Collins, E. J. Leonard, C. B. Phillips, M. A. Caplinger, F. Tosi, S. J. Bolton, Björn Jónsson
Figure caption: Full-resolution RGB cylindrical map projection of Europa using the mosaic 1 imaging data from JunoCam. This projection was processed using the “super-resolution” technique as described in the text. While the JunoCam colors are reasonable approximations to the human color range, each color band here has been given an optimum contrast stretch to maximize color and brightness contrast.
Paper: Juno’s JunoCam Images of Europa
Authors: C. J. Hansen, M. A. Ravine, P. M. Schenk, G. C. Collins, E. J. Leonard, C. B. Phillips, M. A. Caplinger, F. Tosi, S. J. Bolton, Björn Jónsson
Figure caption: Juno viewing geometry at closest approach (left) and a few minutes later (right, not to scale) when JunoCam took the four images of the illuminated surface. The color bar shows the altitude of the spacecraft along the groundtrack, changing rapidly. Black dots along the groundtrack are spaced by 1 minute. The time in the center of the disk on the left globe is the time of closest approach to Io.
Paper: Juno’s JunoCam Images of Europa
Authors: C. J. Hansen, M. A. Ravine, P. M. Schenk, G. C. Collins, E. J. Leonard, C. B. Phillips, M. A. Caplinger, F. Tosi, S. J. Bolton, Björn Jónsson
Figure caption: Location of four limb tracks of the JunoCam mosaics (1–4). The white and black dots across the map of Europa show the approximate locations of putative large plumes identified elsewhere and tabulated in Table 2. White dots might have been visible to JunoCam while black dots were not.
Paper: Juno’s JunoCam Images of Europa
Authors: C. J. Hansen, M. A. Ravine, P. M. Schenk, G. C. Collins, E. J. Leonard, C. B. Phillips, M. A. Caplinger, F. Tosi, S. J. Bolton, Björn Jónsson
Figure caption: These figures show RGB framelets 7 and 8 from the fourth JunoCam image, stretched to look for bright eruptions along the limb. None are apparent. Similar processing was carried on all framelets in all four images.
Paper: Juno’s JunoCam Images of Europa
Authors: C. J. Hansen, M. A. Ravine, P. M. Schenk, G. C. Collins, E. J. Leonard, C. B. Phillips, M. A. Caplinger, F. Tosi, S. J. Bolton, Björn Jónsson
Figure caption: JunoCam had a north polar view of Europa on PJ40. The figure shows (left to right) the best PJ40 JunoCam image, a polar grid on the JunoCam image, and the current existing Galileo map with the same orientation. Some albedo units close to the pole can be filled in.
Paper: Juno’s JunoCam Images of Europa
Authors: C. J. Hansen, M. A. Ravine, P. M. Schenk, G. C. Collins, E. J. Leonard, C. B. Phillips, M. A. Caplinger, F. Tosi, S. J. Bolton, Björn Jónsson
Figure caption: This highly stretched version of the first JunoCam image was processed by citizen scientist Brian Swift. We can see the portion of the planet illuminated by Jupiter shine adjacent to normally illuminated dayside topography.
Paper: Rotational Study of 5:3 and 7:4 Resonant Objects within the Main Classical Trans-Neptunian Belt
Authors: Audrey Thirouin, Scott S. Sheppard
Figure caption: TNOs trapped in the 5:3 (circles) and 7:4 (squares) resonances with Neptune based on the DES classification are plotted with the following legend: black symbols for TNOs never observed for lightcurve studies, blue symbols for TNOs with some photometric information in the literature (Table 3), and red symbols for TNOs observed during our survey (Table 1). The red triangle corresponds to the object 2003 SP317, whose dynamical classification is 17:9 resonant or classical TNO. Note that our survey targeted 2008 CS190 and 2001 XP254 (plotted with red symbols), which have been studied as well by Kecskeméthy et al. (2023).
Paper: Rotational Study of 5:3 and 7:4 Resonant Objects within the Main Classical Trans-Neptunian Belt
Authors: Audrey Thirouin, Scott S. Sheppard
Figure caption: The main peak of the Lomb periodogram (plot (a)) is located at 3.44 cycles day−1. The double-peaked lightcurve of 2013 FR28 with ﹩{P}_{\mathrm{rotational}}^{\mathrm{double}}﹩ = 13.97 ± 0.04 hr has an amplitude larger than the cutoff at 0.9 mag and the V/U morphology of a most likely contact binary (plot (b)). The Fourier series fit (black solid line) cannot match the observations with χ 2 = 4.90.
Paper: Rotational Study of 5:3 and 7:4 Resonant Objects within the Main Classical Trans-Neptunian Belt
Authors: Audrey Thirouin, Scott S. Sheppard
Figure caption: The lightcurve of 2003 SP317 is asymmetric and double-peaked with a period ﹩{P}_{\mathrm{rotational}}^{\mathrm{double}}﹩ = 12.39 ± 0.03 hr and Δm = 0.85 ± 0.03 mag. We classify this body as a likely contact binary due to its high variability and V shape at the minima and because the Fourier series fit is unable to reproduce the lightcurve (χ 2 = 1.02).
Paper: Rotational Study of 5:3 and 7:4 Resonant Objects within the Main Classical Trans-Neptunian Belt
Authors: Audrey Thirouin, Scott S. Sheppard
Figure caption: The periodogram’s main peak is at 3.12 cycles day−1 (plot (a)). Because of the large photometric variability of 2003 YW179, the double-peaked rotational period of 15.41 hr is best suited. A second-order Fourier fit (black curve) is a good match to our data sets inferring that this object is elongated (plot (b)).
Paper: Expanding Mars’s Climate Modeling: Interpretable Machine Learning for Modeling Mars Science Laboratory Relative Humidity
Authors: Nour Abdelmoneim, Dattaraj B. Dhuri, Dimitra Atri, Germán Martínez
Figure caption: VSN results. Panel (a) shows the average weights assigned by the VSN (model weights) for each input feature grouped by predicted humidity ranges. Panels (b), (c), (d), and (e) display the model weights of the top four input features. They also show how model weights vary with each respective feature value and predicted humidity. Circle sizes represent the number of samples present.
Paper: Expanding Mars’s Climate Modeling: Interpretable Machine Learning for Modeling Mars Science Laboratory Relative Humidity
Authors: Nour Abdelmoneim, Dattaraj B. Dhuri, Dimitra Atri, Germán Martínez
Figure caption: DNN architecture. The VSN consists of the layers past the encoding layers and prior to the output dense layer. The model receives 11 MCD features as inputs. Each feature is then linearly encoded and fed individually into its own GRN. The 11 encoded MCD features are also concatenated and fed into one additional GRN that outputs the variable selection weight for each feature. The GRN architecture contains a GLU that determines whether the network will include an additional nonlinear (sigmoid) layer. The output of each individual feature GRN is then weighted with its variable selection weight and combined to form the RH prediction. Dense layers, or fully connected layers, form the building blocks of this architecture. For each dense layer, the activation function used is indicated in the corresponding parentheses.
Paper: Expanding Mars’s Climate Modeling: Interpretable Machine Learning for Modeling Mars Science Laboratory Relative Humidity
Authors: Nour Abdelmoneim, Dattaraj B. Dhuri, Dimitra Atri, Germán Martínez
Figure caption: Normalized mutual information scores of MCD features with REMS RH. Features with normalized mutual information scores of ≥ 0.5 are highlighted.
Paper: Expanding Mars’s Climate Modeling: Interpretable Machine Learning for Modeling Mars Science Laboratory Relative Humidity
Authors: Nour Abdelmoneim, Dattaraj B. Dhuri, Dimitra Atri, Germán Martínez
Figure caption: MSE of persistence models for filling gaps in observations. The MSE of a naive persistence model is shown with the pink solid line. The prediction errors of all intervals N sols apart are averaged to obtain the MSE for each look-forward time. The MSE of the DNN is indicated with the dashed line and remains consistent for all look-forward times since it does not directly depend on any RH measurements as input to make inferences. Past RH data are only used to train the DNN, and no RH measurements are used as inputs or referenced during inference.
Paper: Expanding Mars’s Climate Modeling: Interpretable Machine Learning for Modeling Mars Science Laboratory Relative Humidity
Authors: Nour Abdelmoneim, Dattaraj B. Dhuri, Dimitra Atri, Germán Martínez
Figure caption: Comparisons between REMS and MCD. Panel (a) shows REMS RH measurements compared with RH calculated from MCD water vapor VMR, temperature, and pressure. Panel (b) shows MCD water vapor VMR and water vapor VMR calculated from REMS RH, pressure, and temperature measurements. Both panels show REMS measurements taken between 4:00 and 7:00 LMST when the uncertainty of the RHS is at its lowest.
Paper: Expanding Mars’s Climate Modeling: Interpretable Machine Learning for Modeling Mars Science Laboratory Relative Humidity
Authors: Nour Abdelmoneim, Dattaraj B. Dhuri, Dimitra Atri, Germán Martínez
Figure caption: Behavior of quantile loss. At a true RH value of 50%, quantile loss is larger for model predictions that are <50% for higher quantiles, effectively penalizing underpredictions more than overpredictions. The opposite is true for lower quantiles, which penalize overpredictions more. Quantile 0.5 is highlighted with a dashed line, where the loss is the same for over- and underpredictions, making it equivalent to MAE in terms of optimization.
Paper: Expanding Mars’s Climate Modeling: Interpretable Machine Learning for Modeling Mars Science Laboratory Relative Humidity
Authors: Nour Abdelmoneim, Dattaraj B. Dhuri, Dimitra Atri, Germán Martínez
Figure caption: Model predictions compared with ground-truth data for the 15,158 samples in the test set. The blue solid line shows the DNN predictions vs. the true RH binned by 1% RH; one standard error is indicated with the blue shaded region. A perfect outcome is shown (red dashed diagonal), with the calibration uncertainty range of the REMS RH data highlighted in the red shaded region.
Paper: Expanding Mars’s Climate Modeling: Interpretable Machine Learning for Modeling Mars Science Laboratory Relative Humidity
Authors: Nour Abdelmoneim, Dattaraj B. Dhuri, Dimitra Atri, Germán Martínez
Figure caption: Predicted and observed (true) RH for sols with high and low RH values. Solid blue lines show the predicted RH, and blue shaded regions show the predicted quantile range (P10 and P90). The true RH values are shown in red.
Paper: Measurements of Titan’s Stratospheric Winds during the 2009 Equinox with the eSMA
Authors: Siobhan Light, Mark Gurwell, Alexander Thelen, Nicholas A Lombardo, Conor Nixon
Figure caption: (a) Photograph of the observatories involved with the eSMA, left to right: SMA, JCMT, CSO. (Photo credit: Jonathan Weintroub) (b) Map view; small green circles indicate the location of SMA antennas, yellow triangle represents JCMT location, and the pink diamond represents CSO location. (Photo credit: Google Earth)
Paper: Measurements of Titan’s Stratospheric Winds during the 2009 Equinox with the eSMA
Authors: Siobhan Light, Mark Gurwell, Alexander Thelen, Nicholas A Lombardo, Conor Nixon
Figure caption: Integrated across all channels and continuum-subtracted CH3CN (J = 19–18, ν = 0)-centered emission maps for 2009 (top panel) and 2010 (bottom panel). Plotting adapted from Cordiner et al. (2018). Wireframe spheres indicate Titan’s surface and orientation in the field of view, with latitudes denoted. The images were convolved to natural beams. The plots show the rectangular areas integrated to calculate zonal wind speed. Each panel shows the beam FWHM (i.e., spatial resolution) in its bottom right corner. Contour intervals are based on percentiles of the maximum flux.
Paper: Measurements of Titan’s Stratospheric Winds during the 2009 Equinox with the eSMA
Authors: Siobhan Light, Mark Gurwell, Alexander Thelen, Nicholas A Lombardo, Conor Nixon
Figure caption: (a) Simulations from Newman et al. (2011) TitanWRF for the 2009 zonal wind velocities. (b) Simulations from Newman et al. (2011) TitanWRF for the 2010 zonal wind velocities. (c) Simulations from Lombardo & Lora (2023a) TAM for the 2009 zonal wind velocities. (d) Simulations from Lombardo & Lora (2023a) TAM for the 2010 zonal wind velocities. Dashed horizontal lines represent the average peak contribution pressures for the eSMA wind measurements, and dotted horizontal lines represent the lower and upper bounds based on the associated error bars, indicating the range of uncertainty around the average peak contribution pressures.
Paper: Measurements of Titan’s Stratospheric Winds during the 2009 Equinox with the eSMA
Authors: Siobhan Light, Mark Gurwell, Alexander Thelen, Nicholas A Lombardo, Conor Nixon
Figure caption: Comparison of the measured Doppler-shifted velocities from seven rectangular regions spanning all latitudes on Titan, along with their associated errors. Blue squares represent 2009 data, while red circles depict 2010 data. Dashed lines, optimized to align with solid body rotation acting as a proxy for zonal wind, are fit for each respective year. Shaded regions indicate the 95% confidence interval ( ±1.96σ) on the velocity fits. The SMA beam size corresponds to the east–west projection of the major axis of the 2009 “natural” beam shape.
Paper: Measurements of Titan’s Stratospheric Winds during the 2009 Equinox with the eSMA
Authors: Siobhan Light, Mark Gurwell, Alexander Thelen, Nicholas A Lombardo, Conor Nixon
Figure caption: (a) Moving average of integrated flux over a radius 0.60 arcsec centered on Titan, smoothing together three channels at a time. Each channel has a resolution of 0.203125 MHz. The spectrum from 2009 is in purple and 2010 is in black. Individual transition lines are noted with dashed lines since measurements were made relative to CH3CN J = 19k–18k (with k = 3, 2, 1, 0) transitions. (b) 2009 spectra from the east limb of Titan, with fits overlapped in dashed lines. (c) Fit of the 193–183 component of the 2009 eastern limb spectra, with a red line showing the center of the fit; the blue dotted line shows the rest frequency of the transition, and the turquoise dashed line shows the model fit (d). Similar to (c) but for the western limb.
Paper: Measurements of Titan’s Stratospheric Winds during the 2009 Equinox with the eSMA
Authors: Siobhan Light, Mark Gurwell, Alexander Thelen, Nicholas A Lombardo, Conor Nixon
Figure caption: Normalized functional derivatives calculated using NEMESIS of the spectral radiance with respect to 2009 CH3CN (J = 19–18, ν = 0) abundance, pressure/altitude, and frequency. Absolute contour values are shown in side bar (e.g., the white contour shade corresponds to the highest contribution, ∼1.000).
Paper: Possible Anthropogenic Contributions to the LAMP-observed Surficial Icy Regolith within Lunar Polar Craters: A Comparison of Apollo and Starship Landings
Authors: William M. Farrell, P. Prem, D. M. Hurley, O. J. Tucker, R. M. Killen
Figure caption: The distribution of transiently adsorbed water molecules (outside PSRs) in the vicinity of the south pole at approximately one (left) and two (right) lunar days after a landing at 89° S, 180° E, assuming a desorption activation energy E  a  = 0.7 eV (top) and 0.5 eV (bottom). White circles indicate the modeled locations and sizes of the 13 largest south polar PSRs. In this simulation of a midsized lunar lander, ∼40 kg of water vapor was assumed to be released during descent. For a smooth surface, one monolayer corresponds to ∼1019 molecules m−2.
Paper: Possible Anthropogenic Contributions to the LAMP-observed Surficial Icy Regolith within Lunar Polar Craters: A Comparison of Apollo and Starship Landings
Authors: William M. Farrell, P. Prem, D. M. Hurley, O. J. Tucker, R. M. Killen
Figure caption: The amount of water (as a percentage of the total amount released during spacecraft descent) that is temporarily adsorbed to the surface or in the exosphere at any given time, and the cumulative amount that has been photodestroyed, captured at north and south polar cold traps, and has escaped lunar gravity, over the course of two lunar days. Solid lines indicate values for E  a  = 0.7 eV, and dashed–dotted lines indicate values for E  a  = 0.5 eV.
Paper: Possible Anthropogenic Contributions to the LAMP-observed Surficial Icy Regolith within Lunar Polar Craters: A Comparison of Apollo and Starship Landings
Authors: William M. Farrell, P. Prem, D. M. Hurley, O. J. Tucker, R. M. Killen
Figure caption: Figure 5-5 from the Apollo 11 mission report showing the evolution of the LM pitch angle as a function of time. The pitch angle is the angle between the LM vertical x-axis and the surface normal. The blue lines and labels are our additions used to estimate the propulsion exhaust mass directed toward the surface.
Paper: Possible Anthropogenic Contributions to the LAMP-observed Surficial Icy Regolith within Lunar Polar Craters: A Comparison of Apollo and Starship Landings
Authors: William M. Farrell, P. Prem, D. M. Hurley, O. J. Tucker, R. M. Killen
Figure caption: The three primary factors that define the water delivery from a lunar lander exhaust plume to PSRs. Plume water incident with the surface creates a topside plume surface deposit that desorbs over time, with the released molecules migrating about the Moon (some molecules eventually migrating into the PSRs).