adsabs/AstroCLIMB huggingface dataset:
Paper: The Volatile Composition and Activity Evolution of Main-belt Comet 358P/PANSTARRS
Authors: Henry H. Hsieh, John W. Noonan, Michael S. P. Kelley, Dennis Bodewits, Jana Pittichová, Audrey Thirouin, Marco Micheli, Matthew M. Knight, Michele T. Bannister, Colin O. Chandler, Carrie E. Holt, Matthew J. Hopkins, Yaeji Kim, Nicholas A. Moskovitz, William J. Oldroyd, Jack Patterson, Scott S. Sheppard, Nicole Tan, Chadwick A. Trujillo, Quanzhi Ye, 泉志 叶
Figure caption: Active ranges, extending between the earliest and latest observations for which activity has been reported during individual apparitions (Table B1), in terms of (a) true anomaly and (b) heliocentric distance for confirmed recurrently active MBCs. Filled blue line segments indicate the inbound (preperihelion) portion of each object’s orbit, while open blue line segments indicate the outbound (postperihelion) portion of each object’s orbit. In (a), individual active apparitions are plotted separately with apparitions for the same objects grouped together, with the earliest apparitions at the top and latest apparitions at the bottom of each grouping. Perihelion is marked with a solid vertical line, while the earliest and latest orbit positions in terms of true anomaly at which activity has been observed for any MBC (in this case, for 483P-B and 456P, respectively) are marked with a dashed and dotted vertical line, respectively. Numbers in parentheses on the right side indicate the number of active apparitions for which observations have been reported for each object as of 2024 October 28. In (b), filled and open blue line segments represent the combined ranges of reported observations from all active apparitions of each object, with horizontal black line segments indicating the heliocentric distance range covered by the orbit of each object. The most distant positions at which activity has been observed for any MBC inbound to and outbound from perihelion (in this case, for 324P and 238P, respectively) are marked with a dashed and dotted vertical line, respectively. After H. H. Hsieh et al. (2018c).
Paper: The Volatile Composition and Activity Evolution of Main-belt Comet 358P/PANSTARRS
Authors: Henry H. Hsieh, John W. Noonan, Michael S. P. Kelley, Dennis Bodewits, Jana Pittichová, Audrey Thirouin, Marco Micheli, Matthew M. Knight, Michele T. Bannister, Colin O. Chandler, Carrie E. Holt, Matthew J. Hopkins, Yaeji Kim, Nicholas A. Moskovitz, William J. Oldroyd, Jack Patterson, Scott S. Sheppard, Nicole Tan, Chadwick A. Trujillo, Quanzhi Ye, 泉志 叶
Figure caption: Plot of Af ρ values reported for 358P during its 2012–2013 (green diamonds), 2017 (blue circles), and 2023–2024 (orange squares) active apparitions vs. true anomaly, where 2012–2013 and 2017 data are from H. H. Hsieh et al. (2018a) and utilized ρ = 5″ photometry apertures and 2023–2024 data are from this work and utilized ρ = 5000 km photometry apertures. True anomaly positions at the time of NIRCam and NIRSpec observations by JWST are marked with red arrows as labeled.
Paper: The Volatile Composition and Activity Evolution of Main-belt Comet 358P/PANSTARRS
Authors: Henry H. Hsieh, John W. Noonan, Michael S. P. Kelley, Dennis Bodewits, Jana Pittichová, Audrey Thirouin, Marco Micheli, Matthew M. Knight, Michele T. Bannister, Colin O. Chandler, Carrie E. Holt, Matthew J. Hopkins, Yaeji Kim, Nicholas A. Moskovitz, William J. Oldroyd, Jack Patterson, Scott S. Sheppard, Nicole Tan, Chadwick A. Trujillo, Quanzhi Ye, 泉志 叶
Figure caption: (a) Modeled image from a Monte Carlo dust model for micron-sized grains accelerated by outgassing water from 358P using an active south pole, ε = 80°, and Φ = 245°, covering the inner 1500 × 1500 km of the coma as seen from JWST. Intensities in the model image indicate column density, where representative contours are shown as cyan lines. NIRCam F200W contours from Figure 6 are shown in white for comparison. (b) The same as (a) but for Φ = 260° as found by F. Moreno et al. (2013).
Paper: The Volatile Composition and Activity Evolution of Main-belt Comet 358P/PANSTARRS
Authors: Henry H. Hsieh, John W. Noonan, Michael S. P. Kelley, Dennis Bodewits, Jana Pittichová, Audrey Thirouin, Marco Micheli, Matthew M. Knight, Michele T. Bannister, Colin O. Chandler, Carrie E. Holt, Matthew J. Hopkins, Yaeji Kim, Nicholas A. Moskovitz, William J. Oldroyd, Jack Patterson, Scott S. Sheppard, Nicole Tan, Chadwick A. Trujillo, Quanzhi Ye, 泉志 叶
Figure caption: Composite images constructed from ground-based optical observations of 358P listed in Table 3.
Paper: The Volatile Composition and Activity Evolution of Main-belt Comet 358P/PANSTARRS
Authors: Henry H. Hsieh, John W. Noonan, Michael S. P. Kelley, Dennis Bodewits, Jana Pittichová, Audrey Thirouin, Marco Micheli, Matthew M. Knight, Michele T. Bannister, Colin O. Chandler, Carrie E. Holt, Matthew J. Hopkins, Yaeji Kim, Nicholas A. Moskovitz, William J. Oldroyd, Jack Patterson, Scott S. Sheppard, Nicole Tan, Chadwick A. Trujillo, Quanzhi Ye, 泉志 叶
Figure caption: Composite images constructed from ground-based optical observations of 238P listed in Table 4.
Paper: JWST Near-infrared Spectroscopy of High-albedo Jupiter Trojans: A New Surface Type in the Trojan Belt
Authors: Michael E. Brown, Ian Wong, Matthew Belyakov
Figure caption: Relative reflectivity, scaled to unity between 2.5 and 2.7 μm of the four high-albedo asteroids with different choices for the beaming parameter. In each case, we show our adopted beaming parameter as a black line and the derived reflectance for a beaming parameter 0.1 higher (red curve below adopted reflectance) and one 0.05 lower (red curve above adopted reflectance). The green dashed line shows the extension from 2.7 μm to the region beyond 3.7 μm, which we use as our estimate of the longer wavelength continuum.
Paper: JWST Near-infrared Spectroscopy of High-albedo Jupiter Trojans: A New Surface Type in the Trojan Belt
Authors: Michael E. Brown, Ian Wong, Matthew Belyakov
Figure caption: The average of the four high-albedo Jupiter Trojans, scaled to unity at the median of the value between 2.5 and 2.7 μm (black), compared to a smoothed and detrended spectrum of Patroclus (red) and to a model consisting of 85% coverage of Patroclus-like material and 15% water ice (blue), giving an albedo similar to the high-albedo Jupiter Trojans.
Paper: JWST Near-infrared Spectroscopy of High-albedo Jupiter Trojans: A New Surface Type in the Trojan Belt
Authors: Michael E. Brown, Ian Wong, Matthew Belyakov
Figure caption: Spectra of four high-albedo Jupiter Trojans (in black) along with the spectrum of SNAP-2, a solar analog star (in red). The object name associated with each spectrum is shown in the figure in order from brightest to faintest at 1 μm. The Trojan spectra are dominated by reflected sunlight except for the regions beyond  ~4.5 μm. The relative signal-to-noise across the spectra is determined by the total irradiance and the NIRSpec/PRISM throughput, both of which decrease to longer wavelength. The total uncertainty can be estimated from the scatter in these largely featureless spectra.
Paper: JWST Near-infrared Spectroscopy of High-albedo Jupiter Trojans: A New Surface Type in the Trojan Belt
Authors: Michael E. Brown, Ian Wong, Matthew Belyakov
Figure caption: Absolute reflectance of four high-albedo Jupiter Trojans. The absolute reflectance is determined by assuming that the linear spectrum from 0.8 to 1.3 μm extends downward to 0.55 μm, where the visible albedo is defined.
Paper: The Interplay of Surface Composition, Mineralogy, and Physical Conditions That Affect the Surface Release Processes and Particle Environment of Mercury
Authors: Peter Wurz, Noah Jäggi, André Galli, Audrey Vorburger, Deborah Domingue, Paul S. Szabo, Johannes Benkhoff, Océane Barraud, Daniel Wolf Savin
Figure caption: Overview of the depth of information for the various techniques used to infer the chemical and mineralogical composition of Mercury’s surface together with the approximate structure of the regolith. Sputtering refers to the release of particles from the surface via ion sputtering, XPS is X-ray photo-electron spectroscopy (not used in the MESSENGER mission, but potentially on a future mission), VIS & IRS is the visible and infrared spectroscopy of reflected light, XRS is X-ray spectroscopy, GRS is gamma-ray spectroscopy, and NS is neutron spectrometry. The dark-gray bars give the typical information scale of the technique and the light-gray bars the possible maximum range. The last column gives the approximate vertical structure of the lunar surface (G. H. Heiken et al. 1991), which is expected to be similar on Mercury (A. Y. Zharkova et al. 2020). The regolith sits on top of large-scale ejecta (R2), a structurally disturbed crust (R3), and a fractured crust (R4). The orange background indicates the typical range of space weathering of 30 nm and its maximal extent to about 100 nm depth.
Paper: Methods for Experimental Planetary Geology in Reduced-gravity Parabolic Flight: A Case Study of Researching Impact Crater Ejecta
Authors: Kirby D. Runyon, Daniel D. Durda, Viliam Klein, Constantine C. C. Tsang, Chloe B. Beddingfield, Carolyn M. Ernst, Olivier S. Barnouin, H. Todd Smith
Figure caption: Top: perspective view of the experiment operated by the team. Though our experiment did not require it, note the aircraft electrical panel that is available for experiments. This view is from the rear of the airplane looking forward. Other teams, unrelated to the present research, are visible (blurred for privacy). Note the large gray Pelican case in the middle of the plane (top of image); this is a general storage area for small items for any of the flying research teams. Image credit: Zero-G. Bottom: overview of the science glovebox and ejecta catapult (mostly obscured) installed in Zero-G Corp.’s aircraft. Note the ejecta curtain, composed of white-colored crushed chalk, flying from left to right. Crushed chalk pieces of various colors from previous experiments are visible along the bottom of the clear-sided target tray. The glovebox (dimensions 72 × 33 × 30 inches; six gloved arm holes) is bolted to the steel baseplate, which in turn is bolted to preexisting holes in the aircraft floor under the beige-colored padding. The science glovebox is made of 80/20 aluminum rods overlain with acrylic. After takeoff, we attached LED lights to better illuminate the scene for the GoPro video cameras (four visible on the side; two GoPros are out-of-scene at the top). The catapult is partially obscured at left. Image credit: the authors.
Paper: Methods for Experimental Planetary Geology in Reduced-gravity Parabolic Flight: A Case Study of Researching Impact Crater Ejecta
Authors: Kirby D. Runyon, Daniel D. Durda, Viliam Klein, Constantine C. C. Tsang, Chloe B. Beddingfield, Carolyn M. Ernst, Olivier S. Barnouin, H. Todd Smith
Figure caption: Top: Concepción Crater (10 m diameter) on Meridiani Planum imaged by the Mars Exploration Rover Opportunity. Note the blocky ejecta rays extending away from the crater. Bottom left: Kepler Crater (30 km diameter) on the Moon with its widespread ejecta rays. Bottom right: at least two craters on the surface of asteroid Bennu. The largest crater on the right is Bralgah Crater (70 m diameter; M. E. Perry et al. 2022). Ejecta retained on the surface would likely blend in with the background. Understanding how Martian, lunar, and asteroidal gravity affect ejecta emplacement and interaction with preexisting regolith is an aim of our reduced-gravity geology experiments. Image credit: Top: NASA/JPL-Caltech/Cornell/color mosaic by James Canvin/The Planetary Society. Bottom left: NASA/Goddard/QuickMap. Bottom right: NASA/Goddard/University of Arizona.
Paper: Methods for Experimental Planetary Geology in Reduced-gravity Parabolic Flight: A Case Study of Researching Impact Crater Ejecta
Authors: Kirby D. Runyon, Daniel D. Durda, Viliam Klein, Constantine C. C. Tsang, Chloe B. Beddingfield, Carolyn M. Ernst, Olivier S. Barnouin, H. Todd Smith
Figure caption: The Boeing 727 aircraft “G-Force One” used by Zero-G Corp., on which we conducted our planetary geology experiments. Note the forklift used for lifting experiments into the open cargo door in the side of the aircraft. The deployed airstairs at the aircraft’s aft end allow experimenters onboard access. Image credit: the authors.
Paper: Methods for Experimental Planetary Geology in Reduced-gravity Parabolic Flight: A Case Study of Researching Impact Crater Ejecta
Authors: Kirby D. Runyon, Daniel D. Durda, Viliam Klein, Constantine C. C. Tsang, Chloe B. Beddingfield, Carolyn M. Ernst, Olivier S. Barnouin, H. Todd Smith
Figure caption: Numerical simulations in SolidWorks of an off-nominal 9 g in the forward direction, showing the structural integrity of the glovebox.
Paper: Radiance Contrasts at Possible Lunar Water Ice Exposures Seen by ShadowCam
Authors: Jordan Ando, Shuai Li, Mark Robinson, Robert Wagner
Figure caption: Normalized histograms of PSR area in the (a) northern and (b) southern lunar polar regions. The PID-PSR distribution (blue) includes PSRs with at least one M3 water ice detection; the NID-PSR histogram (gray) contains only PSRs lacking water ice detections. PSRs with area >100 km2 are excluded for clarity owing to low counts.
Paper: Radiance Contrasts at Possible Lunar Water Ice Exposures Seen by ShadowCam
Authors: Jordan Ando, Shuai Li, Mark Robinson, Robert Wagner
Figure caption: North pole maximum radiance mosaic map, clipped to PSRs. Grid lines extend to 80° north, in increments of 1°.
Paper: Radiance Contrasts at Possible Lunar Water Ice Exposures Seen by ShadowCam
Authors: Jordan Ando, Shuai Li, Mark Robinson, Robert Wagner
Figure caption: South pole maximum radiance mosaic, clipped to PSRs. 80° south, in increments of 1°.
Paper: Radiance Contrasts at Possible Lunar Water Ice Exposures Seen by ShadowCam
Authors: Jordan Ando, Shuai Li, Mark Robinson, Robert Wagner
Figure caption: Normalized histogram of ShadowCam radiance at southern polar PSR pixels with slopes <10° underlying M3 PIDs, compared to the histogram of NID southern polar PSR ShadowCam pixels. This is performed for M3 pixels of the original resolution (280 m pixel−1).
Paper: Radiance Contrasts at Possible Lunar Water Ice Exposures Seen by ShadowCam
Authors: Jordan Ando, Shuai Li, Mark Robinson, Robert Wagner
Figure caption: Histograms of all pixels in southern polar PID-PSRs that have at least one M3 water ice detection (cyan) and NID-PSRs with no water ice detections (gray). Panel (a) includes only PSRs with areas of 25 km2 or less, while panel (b) includes PSRs with areas of 100 km2 or less.
Paper: Radiance Contrasts at Possible Lunar Water Ice Exposures Seen by ShadowCam
Authors: Jordan Ando, Shuai Li, Mark Robinson, Robert Wagner
Figure caption: ShadowCam maximum radiance mosaics of PSRs (a) Cabeus and (b) Hermite. Yellow contours represent LOLA-derived elevation. Cyan squares are to-scale 280 m M3 ice detections.
Paper: Radiance Contrasts at Possible Lunar Water Ice Exposures Seen by ShadowCam
Authors: Jordan Ando, Shuai Li, Mark Robinson, Robert Wagner
Figure caption: Deviations of radiance at M3 ice detections from their neighboring pixels for southern polar PSRs, computed from comparisons between the (a) median and (b) maximum radiance values of ShadowCam pixels with slopes <10° underlying the M3 ice detections (280 m pixel−1) and their neighboring M3 pixel-sized regions. See Figure 6 for more details.
Paper: Radiance Contrasts at Possible Lunar Water Ice Exposures Seen by ShadowCam
Authors: Jordan Ando, Shuai Li, Mark Robinson, Robert Wagner
Figure caption: Normalized histograms of radiance of ShadowCam PID pixels with slopes <10° (purple) that underlie the M3 ice detections (280 m pixel−1) compared to NID pixels (black) for 14 southern polar PSRs.
Paper: Supercooling, Glass Formation, and Mineral Assemblages upon Freezing of Salty Ice Grains from Enceladus’s Ocean
Authors: Fabian Klenner, Lucas M. Fifer, Baptiste Journaux, Ardith D. Bravenec, Allan M. M. Leal, Steven D. Vance, David C. Catling
Figure caption: Example thermogram of solution II (Enceladus ocean simulant with 10× solute concentrations), with the lower panel showing expanded detail. The cooling rate was 10 K minute−1. Indicated events (red) are also observed in solution I (our standard Enceladus ocean simulant), but are less pronounced. The melting temperature is the temperature at which a horizontal line (drawn from a local maximum before the second melting valley) intersects with a tangential line drawn from an inflection point within the second melting valley where the derivative equals zero (black lines). Melting of the H2O phase of the sample is included in the second melting valley.
Paper: Supercooling, Glass Formation, and Mineral Assemblages upon Freezing of Salty Ice Grains from Enceladus’s Ocean
Authors: Fabian Klenner, Lucas M. Fifer, Baptiste Journaux, Ardith D. Bravenec, Allan M. M. Leal, Steven D. Vance, David C. Catling
Figure caption: Precipitating mineral assemblages (top), pH evolution (center), and residual liquid water (bottom) upon freezing of solution I at 3.1 bar. Left panels show PHREEQC simulations; right panels show Reaktoro simulations.
Paper: Supercooling, Glass Formation, and Mineral Assemblages upon Freezing of Salty Ice Grains from Enceladus’s Ocean
Authors: Fabian Klenner, Lucas M. Fifer, Baptiste Journaux, Ardith D. Bravenec, Allan M. M. Leal, Steven D. Vance, David C. Catling
Figure caption: Degree of vitrification as a function of cooling rate and salinity. The salinity of solution I is ∼14.7 g kg−1. The salinity of solution II is ∼147 g kg−1. Data points are fitted and extrapolated to faster cooling rates using exponential functions (orange and light blue curves). For reference, the estimated salinity range of Enceladus’s ocean lies between ∼8 and 26 g kg−1.
Paper: Supercooling, Glass Formation, and Mineral Assemblages upon Freezing of Salty Ice Grains from Enceladus’s Ocean
Authors: Fabian Klenner, Lucas M. Fifer, Baptiste Journaux, Ardith D. Bravenec, Allan M. M. Leal, Steven D. Vance, David C. Catling
Figure caption: Degree of supercooling of solution I and solution II as a function of droplet diameter derived from DSC experiments with a cooling rate of 150 K minute−1. The uncertainty of the degrees of supercooling is ±0.15 K. The droplet diameter was calculated with an accuracy of ±0.03 mm.
Paper: Probing Lateral Density Variations in the Crust from Gravity and Topography: Applications to the Moon and Mars
Authors: Sander Goossens, Terence J. Sabaka
Figure caption: Theoretical admittance for Mercury (top), Venus (middle), and Mars (bottom), using the model of D. Turcotte et al. (1981), for various values of elastic thickness TE (for a fixed value of crustal thickness of 35 km). Darker colors indicate larger elastic thicknesses. The degree where the curves become mostly independent of elastic thickness is the degree from which gravity and topography should correlate highly.
Paper: In situ, Surface-deployed Distributed Instruments for Planetary Science: Scientific Opportunities and Technology Feasibility
Authors: Federico Rossi, Robert C. Anderson, Saptarshi Bandyopadhyay, Erik Brandon, Ashish Goel, Joshua Vander Hook, Michael Mischna, Michaela Villarreal, Mark Wronkiewicz
Figure caption: Artist’s representation of a notional distributed instrument to study the Martian global climate, inspired by the recommendations in the Mars Concurrent Exploration Science Analysis Group report (MEPAG MCE-SAG 2023). A network of 16 sensing units is distributed across the Martian surface to provide coverage of the entire planet. Each sensing unit contains a weather station, a dust instrument, a camera to observe atmospheric opacity and cloud formation, and a spectrometer. Sensor readings are relayed to Earth by an existing orbiter. The distributed instrument allows scientists to study the spatial and temporal correlation of weather and climate patterns (in particular the water, dust, and CO2 cycles) on the planet. The scientific promise of such an instrument is discussed in Section 3.2.
Paper: In situ, Surface-deployed Distributed Instruments for Planetary Science: Scientific Opportunities and Technology Feasibility
Authors: Federico Rossi, Robert C. Anderson, Saptarshi Bandyopadhyay, Erik Brandon, Ashish Goel, Joshua Vander Hook, Michael Mischna, Michaela Villarreal, Mark Wronkiewicz
Figure caption: Illustration of the MESUR project’s geophysical observation stations (G. S. Hubbard et al. (1991), © NASA).
Paper: In situ, Surface-deployed Distributed Instruments for Planetary Science: Scientific Opportunities and Technology Feasibility
Authors: Federico Rossi, Robert C. Anderson, Saptarshi Bandyopadhyay, Erik Brandon, Ashish Goel, Joshua Vander Hook, Michael Mischna, Michaela Villarreal, Mark Wronkiewicz
Figure caption: Identification of the source of methane emission sites relies on accurate knowledge and modeling of atmospheric circulation. Here, the MarsWRF general circulation model (M. I. Richardson et al. 2007) is used to resolve the local atmospheric circulation at the scale of the Gale crater with 4 km resolution (left), a regional scale with 13 km resolution (center), and global scale with 2° (≈120 km) resolution (right). The Stochastic Time-Inverted Lagrangian Transport model, adapted to Mars, is used to trace, backwards in time, upstream locations from where surface emissions can exert influence on the detected methane concentration. Warmer colors show greater influence from that region to a methane signal measured at the Curiosity landing site (white star). From Y. Luo et al. (2021).
Paper: In situ, Surface-deployed Distributed Instruments for Planetary Science: Scientific Opportunities and Technology Feasibility
Authors: Federico Rossi, Robert C. Anderson, Saptarshi Bandyopadhyay, Erik Brandon, Ashish Goel, Joshua Vander Hook, Michael Mischna, Michaela Villarreal, Mark Wronkiewicz
Figure caption: Autonomy will allow distributed instruments to increase science return by detecting and reacting to rare events while preserving system resources. Top left: three spatially separated weather stations regularly communicate with each other. Top right: a dust storm approaches and is detected by one station. The event triggers a network response to initiate high-frequency data collection across all stations. Bottom: example data collection from all three weather stations before and during a dust storm. By default, the network records wind speed at low rates to conserve energy and data volume. However, once a rare weather event is detected at Station A, the distributed instrument increases its sampling frequency at all locations to capture the approaching storm in detail.
Paper: In situ, Surface-deployed Distributed Instruments for Planetary Science: Scientific Opportunities and Technology Feasibility
Authors: Federico Rossi, Robert C. Anderson, Saptarshi Bandyopadhyay, Erik Brandon, Ashish Goel, Joshua Vander Hook, Michael Mischna, Michaela Villarreal, Mark Wronkiewicz
Figure caption: Autonomy will facilitate selection and downlink prioritization of scientifically valuable data. Left: three spatially separated seismographs record ground motion from quakes, impacts, or other events that produce ground motion. Right: the raw seismograph data will contain rare, scientifically interesting events (e.g., quakes) against a background of less interesting data. Autonomy allows each instrument to detect seismic onsets and then select a window of raw data (red) for return to ground. Data from other times (light gray) can be summarized with simple statistics (e.g., mean and variance). Furthermore, the quake magnitude (red numbers) can be used to determine downlink priority (far right).