adsabs/AstroCLIMB huggingface dataset:
Paper: Telescope-to-Fireball Characterization of Earth Impactor 2022 WJ1
Authors: Theodore Kareta, Denis Vida, Marco Micheli, Nicholas Moskovitz, Paul Wiegert, Peter G. Brown, Phil J. A. McCausland, Hadrien A. R. Devillepoix, Barbara Malečić, Maja Telišman Prtenjak, Damir Šegon, Benjamin Shafransky, Davide Farnocchia
Figure caption: A comparison between the photometrically derived reflectance of WJ1 (white circles) with reflectance spectra of different asteroid types that share some spectral properties in common (left panel) and with reflectance spectra of meteorites that are potential analogs for those asteroid types (right panel). In the left panel, the O-, B-, and Q-type asteroid classes are plotted as filled areas in gray, blue, and red colors. The vertical spread of these areas indicates the variation of objects within these classes. The S-complex asteroid types (particularly the O- and Q-types) are significantly better matches than the B- or other types, indicating that a rocky composition—and thus moderate albedo and density—is most likely for WJ1. Given that asteroid taxonomies are based on the reflectivities of larger asteroids, some differences might be expected for a meter-class object like WJ1. The visible spectrum of a ∼kilometer-scale O-type asteroid, 2007 MK6 (M. Devogèle et al. 2019), is also plotted for comparison as black filled circles. While the reflectance of WJ1 does fall within the range of spectral behaviors seen on the O-type asteroids, these size-dependent spectral trends prevent a completely unambiguous association with one rocky type of asteroid over another. In the right panel, the three meteorites plotted, two ordinary chondrites and one howardite, are spectra of chips of those meteorites (R. Milliken 2020). They are thus analogous to a surface with some larger pieces and little reoligth, as we might expect for an object as small as WJ1. The composition and reflectivity of WJ1 are discussed at more length in the text.
Paper: Telescope-to-Fireball Characterization of Earth Impactor 2022 WJ1
Authors: Theodore Kareta, Denis Vida, Marco Micheli, Nicholas Moskovitz, Paul Wiegert, Peter G. Brown, Phil J. A. McCausland, Hadrien A. R. Devillepoix, Barbara Malečić, Maja Telišman Prtenjak, Damir Šegon, Benjamin Shafransky, Davide Farnocchia
Figure caption: The brightness of WJ1 in the Sloan g, r, i, and z filters. The along-streak photometry is shown as a solid line in each filter’s color and the median magnitude extracted from that frame as an open dot. The decreasing number of streaks per cluster as a function of time is related to the object’s increasing speed on-sky and thus the decreasing time it took for WJ1 to cross the detector. The extent of Figure 3 is shown as a box in the top left. The last observation, a single streak in Sloan r, immediately precedes the object passing into the shadow of the Earth and may be artificially dimmer as a result. The effect of the object’s placement with respect to the penumbra is discussed in the text.
Paper: Telescope-to-Fireball Characterization of Earth Impactor 2022 WJ1
Authors: Theodore Kareta, Denis Vida, Marco Micheli, Nicholas Moskovitz, Paul Wiegert, Peter G. Brown, Phil J. A. McCausland, Hadrien A. R. Devillepoix, Barbara Malečić, Maja Telišman Prtenjak, Damir Šegon, Benjamin Shafransky, Davide Farnocchia
Figure caption: The brightness of WJ1 in the Sloan r filter as measured at the first pointing in which we observed the target. (The full multicolor data set is presented in the next figure.) The along-streak photometry is shown as a solid black line and the median magnitude extracted from that frame as an open black dot. The absolute magnitude available on JPL Horizons for this object, consisting of dozens of measurements from many observers, is shown as a dashed red line. The short-term variations along each of the streaks are a combination of subsecond atmospheric variations and the actual changing brightness of the target, while the median magnitudes for each frame vary much more smoothly. That said, and as discussed at greater length in the text, no rotation period was found that could fit the brightness variations seen in our full data set, and thus we assume WJ1 to either be tumbling (i.e., non-principal-axis rotation) or have a rotation period too short or too long to resolve with our data set.
Paper: Telescope-to-Fireball Characterization of Earth Impactor 2022 WJ1
Authors: Theodore Kareta, Denis Vida, Marco Micheli, Nicholas Moskovitz, Paul Wiegert, Peter G. Brown, Phil J. A. McCausland, Hadrien A. R. Devillepoix, Barbara Malečić, Maja Telišman Prtenjak, Damir Šegon, Benjamin Shafransky, Davide Farnocchia
Figure caption: Mosaic showing observations of the fireball used in the trajectory solution. The parallel streak in the CA001T image above the bright fireball is due to an internal reflection in the optics. Note that the constellation of Orion is visible in the CAO RASC image for scale. The moving direction of the fireball for each camera is toward: Caistor—upper right, Tavistock—bottom right, CAO RASC—bottom left, CA001T—left, Cronyn—bottom right.
Paper: Telescope-to-Fireball Characterization of Earth Impactor 2022 WJ1
Authors: Theodore Kareta, Denis Vida, Marco Micheli, Nicholas Moskovitz, Paul Wiegert, Peter G. Brown, Phil J. A. McCausland, Hadrien A. R. Devillepoix, Barbara Malečić, Maja Telišman Prtenjak, Damir Šegon, Benjamin Shafransky, Davide Farnocchia
Figure caption: The apparent magnitude (upper panel) and distance from the Earth (lower panel) for WJ1 at 1 day intervals during the 50 yr prior to impact. Presented are 100 clones generated from the JPL covariance matrix area; their dispersion is less than the thickness of the plotted lines. WJ1 would have remained too faint to be observed during this time interval.
Paper: Telescope-to-Fireball Characterization of Earth Impactor 2022 WJ1
Authors: Theodore Kareta, Denis Vida, Marco Micheli, Nicholas Moskovitz, Paul Wiegert, Peter G. Brown, Phil J. A. McCausland, Hadrien A. R. Devillepoix, Barbara Malečić, Maja Telišman Prtenjak, Damir Šegon, Benjamin Shafransky, Davide Farnocchia
Figure caption: The ground track of the fireball (red) together with the locations of cameras used in the trajectory solution. The Great Lakes and other bodies of water are marked in gray.
Paper: The Global Distribution of Water and Hydroxyl on the Moon as Seen by the Moon Mineralogy Mapper (M3)
Authors: Roger N. Clark, Neil C. Pearson, Thomas B. McCord, Deborah L. Domingue, Keith Eric Livo, Joseph W. Boardman, Daniel P. Moriarty, Amanda R. Hendrix, Georgiana Kramer, Maria E. Banks
Figure caption: (a) Tetracorder mineral map for electronic absorptions. The scattered light in the instrument has spectral shapes very similar to iron oxides (hematite, goethite, and other Fe3+-bearing minerals). The Fe2+ signatures are commonly due to pyroxenes and olivines. We cannot find any evidence of published lunar spectra with iron oxide signatures, and we attribute the “identifications” in this image to scattered light and not actual detections of hematite, goethite, or other Fe3+-bearing minerals. This is a Tetracorder standard product. (b) Tetracorder mineral map for electronic absorptions for the region around and south of Copernicus (large crater above left of center). The scattered light in the instrument has spectral shapes very similar to iron oxides (hematite, goethite, and other Fe3+-bearing minerals). The Fe2+ signatures are commonly due to pyroxenes and olivines. Here different orbits show mapping of different compositions, e.g., yellow (goethite) vs. blue (Fe2+ commonly pyroxenes) due to changing scattered light and instrument temperature on different orbits. The hematite, goethite, and other Fe3+ detections are not real and due to these instrumental effects. The three circles show the positions for the three spectra in Figure 28(c). (c) Lunar spectra of Copernicus crater and just north and south of the crater. Red: spectra from M3. Black: spectra from an Earth-based telescope. The red arrows point to apparent absorptions in the M3 spectra that are located near iron oxide absorptions. There is no hint of the iron oxide absorptions in the Earth-based telescopic spectra. The M3 spectra are showing false-positive absorptions due to incomplete correction for gain corrections in the M3 instrument as a function of instrument temperature and scattered light within the instrument.
Paper: The Global Distribution of Water and Hydroxyl on the Moon as Seen by the Moon Mineralogy Mapper (M3)
Authors: Roger N. Clark, Neil C. Pearson, Thomas B. McCord, Deborah L. Domingue, Keith Eric Livo, Joseph W. Boardman, Daniel P. Moriarty, Amanda R. Hendrix, Georgiana Kramer, Maria E. Banks
Figure caption:                         (a) Pyroxene band depth derived from ±15° latitude, all longitudes. There is a clear dependence of band depth with incidence (zenith) angle. With a mean band depth near 0° zenith angle of about 0.02 to a mean of about 0.12 between 50° and 60° zenith angle, the band depth varies by over a factor of 5 with solar zenith angle. This dependence indicates that pyroxene is concentrated in higher abundance in the surface layer, the pyroxene has a larger grain size in the surface layer, or both. Either way, this trend is showing evidence for layered media. (b) Pyroxene band depth vs. solar zenith angle for latitude 15°S–45°S, all longitudes. (c) Pyroxene band depth vs. solar zenith angle for latitude 15°N–45°N, all longitudes. (d) Pyroxene band depth vs. solar zenith angle for latitude 45°S–75°S, all longitudes. (e) Pyroxene band depth vs. solar zenith angle for latitude 45°N–75°N, all longitudes. (f) Pyroxene 2 μm band depth vs. solar zenith angle. The pyroxene 2 μm band depth is very weak and commonly only seen in mare. Because the feature is weak and in limited locations, the data here are the sum of three traverses at 0°, 5°, and 10° latitude. Only a weak small increase with viewing geometry is observed, but the absorptions are so weak that there may be systematic impacts due to the calibration applied (see Figure 4(d)).
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: 1:3M mapping (originally mapped at 1:200,000) of a portion of the Orientale basin. The full resolution is available online (K. Runyon & D. Moriarty 2024). The small craters near “Pa” (red and yellow stars) excavate Orientale melt from beneath the mare and serve as a useful type example for similar small craters in similar basins. Maunder, the large crater in the NW part of the map, is Eratosthenian in age. The area in the white box is shown in greater detail in Figure 3.
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: Subset of Figure 2, shown at 1:1M (original mapping at 1:200,000). The full resolution is available online (K. Runyon & D. Moriarty 2024). “Plagioclase crater” (at arrow, toward the lower right corner in the mare with the hatched mapping around it) and the other starred (red and yellow stars) sites are examples of strong candidates for sampling datable Orientale impact melt, either from below the mare or as uplifted rims. Kopff crater is associated with features interpreted to be a volcanic vent, low-reflectance pyroclastic deposits, a mafic compositional anomaly, and fractures similar to type 3 floor-fractured craters (L. M. Jozwiak et al. 2012).
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: Top: context image for the Orientale basin location on the Moon, straddling the near-side/far-side boundary. Basemap: LROC WAC mosaic from Quickmap.lroc.asu.edu. Bottom: simplified schematic cross-sectional diagram across the Orientale basin with units labeled; impact melt (pink) and impact melt mixed with other lithologies (pink with brown stripes and/or mottling) (adapted and modified from LPI/D. Kring).
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: (a) Legend for maps in Figures 2, 3. (b) Type areas of each geomorphic unit (10 × 10 km crops of the WAC mosaic). Similar-appearing units were differentiated based on geographic context.
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: LROC NAC images, Kaguya mineralogy, and Diviner (bottom panel) products for Maunder’s central peak illustrating compositional heterogeneity. The white arrows highlight low-FeO areas that exhibit low OPX and variable CPX and olivine. Maximum and minimum color values are reported in each frame. For scale, each frame is 20 km wide. Composite image from Quickmap.lroc.asu.edu. Kaguya composition data products derived from M. Lemelin et al. (2019).
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: Mineralogical maps for the Maunder region from Kaguya (M. Lemelin et al. 2019) and Diviner (bottom panel). Olivine, TiO2, and the CPX/OPX ratio are distinctly higher in the ejecta butterfly (indicating a basaltic/gabbroic composition), whereas OPX is more elevated in the crater interior and central peak (where olivine, TiO2, and CPX/OPX are much lower). Maximum and minimum color values are reported in each frame. For scale, Maunder crater is 55 km in diameter.
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: M3 thermal images (1489 nm) showing the variable thickness in Mare Orientale and Lacus Veris. (a) Map of Mare Orientale with thickness labeled, as inferred from crater excavation depths (D. Stöffler et al. 1975). Craters highlighted in yellow represent those excavating mare material, and those in white represent craters ejecting feldspathic basin material. (b) Il’in crater (∼13 km in diameter) excavates only mafic material. (c) Hohmann crater (∼17 km in diameter) flooded with mare, with a feldspathic rim. (d) Southwest polygon. (e) Kipukas protruding from mare surface in the center of the basin. (f) Close-up of the north central region in Lacus Veris with a distinct example of thickness variation. This panel shares the same color scheme as panel (a). Reproduced from Figure 3 of J. Whitten et al. (2011).
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: Mineralogical and albedo maps for the Maunder region from Kaguya (M. Lemelin et al. 2019) and LROC (H. Sato et al. 2017) data. Plagioclase abundance and LROC WAC reflectance are inversely correlated with CPX and FeO abundance. Maximum and minimum color values are reported in each frame. For scale, Maunder crater is 55 km in diameter.
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: Olivine, clinopyroxene, OPX, plagioclase, and FeO abundances for a sampling of points capturing mineralogical diversity across Maunder’s central peak. FeO abundance increases from left to right. Point locations are given in Figure 10.
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: An oblique view of Maunder’s central peak showing the location of high-Fe and low-Fe units and correlations with boulders and outcrops. Specifically, higher-FeO compositions (warmer tones) are associated with boulders and rocky outcrops, whereas lower-FeO compositions (cooler tones) are associated with smooth areas.
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: Progression of mapping. Starting with panel (a), we used an LROC WAC basemap, referencing a global DTM when necessary (not shown). (b) At times we also used a Kaguya plagioclase abundance parameter map (M. Lemelin et al. 2019) georeferenced from QuickMap. These two layers allowed us to begin (panels (c) and (d)) drawing contacts on both geologic units and overlays (for the composition information). (e) Finally, we assigned unit colors.
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: Kaguya FeO data plotted across Maunder’s central peak. The locations of mineralogy data reported in Figure 11 are shown by labeled points. The white arrow shows the look direction for Figure 9.
Paper: Orientale Basin as a Guide for Identifying Lunar Basin Datable Impact Melt and Assessing Impact Melt Differentiation
Authors: Kirby Runyon, James Head, Debra Buczkowski, Carolyn van der Bogert, Daniel Moriarty, Harry Hiesinger, Ben Greenhagen, Tyler Powell
Figure caption: Correlation of map units. The relatively simple stratigraphy is dominated by the formation of Orientale, the eruption of mare basalts, and the later formation of Maunder impact crater in the Eratosthenian (D. E. Wilhelms et al. 1987; P. D. Spudis et al. 2014).
Paper: Crater Equilibrium State Characterization given Crater Production from a Single Power Law
Authors: Masatoshi Hirabayashi, Caleb I. Fassett, Emily S. Costello, David A. Minton
Figure caption: Degradation parameter concept for k  i,j  = 1 in the discrete form. Panel (a): ideal circular disk arrangement at the highest packing condition. The white circles with solid black edges are existing craters with an equivalent diameter of D  i , while those with dashed blue edges are a set of hypothetical circles eliminated from consideration. Panel (b): crater emplacement of size D  j  (red circle) on the geometric configuration.
Paper: Crater Equilibrium State Characterization given Crater Production from a Single Power Law
Authors: Masatoshi Hirabayashi, Caleb I. Fassett, Emily S. Costello, David A. Minton
Figure caption: Degradation parameter concept. The definition of the white disks is the same as in Figure 1. The transparent disks with red dashed lines show the rim of crater j. The green disks describe the area of degradation. The green disk’s transparency means how effective degradation is. A transparency gives ongoing, partial degradation, so the erasure is incomplete. Each column has equivalent degradation parameters.
Paper: Crater Equilibrium State Characterization given Crater Production from a Single Power Law
Authors: Masatoshi Hirabayashi, Caleb I. Fassett, Emily S. Costello, David A. Minton
Figure caption: Modeled class I crater equilibrium CSFDs. The full solution is in blue, while the analytical model is in orange. In this simulation, ﹩{D}_{{\rm{\min }}}=0.1﹩ km and ﹩{D}_{{\rm{\max }}}=1630﹩ km. Each panel gives different parameter settings. (a) α = 1.0, γ 1 = 2.0, γ 2 = 0.0, η = 3.0, β = 0.0; (b) α = 1.0, γ 1 = 2.0, γ 2 = 0.2, η = 3.0, β = 0.0; (c) α = 0.1, γ 1 = 2.0, γ 2 = 0.0, η = 3.0, β = 0.5; and (d) α = 1.0, γ 1 = 2.0, γ 2 = 0.0, η = 2.1, β = 0.0.
Paper: Crater Equilibrium State Characterization given Crater Production from a Single Power Law
Authors: Masatoshi Hirabayashi, Caleb I. Fassett, Emily S. Costello, David A. Minton
Figure caption: Modeled class II crater equilibrium CSFDs. The full solution is in blue, while the analytical model is in orange. Again, in this simulation, ﹩{D}_{{\rm{\min }}}=0.1﹩ km and ﹩{D}_{\max }=1630﹩ km. Each panel gives different parameter settings. (a) α = 1.0, γ 1 = 0.5, γ 2 = 0.0, η = 3.5, β = 0.0; (b) α = 1.0, γ 1 = 0.5, γ 2 = 0.2, η = 3.5, β = 0.0; (c) α = 1.0, γ 1 = 0.95, γ 2 = 0.0, η = 3.5, β = 0.0; and (d) α = 1.0, γ 1 = 0.95, γ 2 = 0.0, η = 3.0, β = 0.5.
Paper: Crater Equilibrium State Characterization given Crater Production from a Single Power Law
Authors: Masatoshi Hirabayashi, Caleb I. Fassett, Emily S. Costello, David A. Minton
Figure caption: Modeled class III crater equilibrium CSFDs. The full solution is in blue, while the analytical model is in orange. Again, in this simulation, ﹩{D}_{{\rm{\min }}}=0.1﹩ km and ﹩{D}_{{\rm{\max }}}=1630﹩ km. Each panel gives different parameter settings. (a) α = 1.0, γ 1 = 0.0, γ 2 = 0.0, η = 1.5, β = 0.0; (b) α = 1.0, γ 1 = 0.0, γ 2 = 0.5, η = 1.5, β = 0.0; (c) α = 1.0, γ 1 = 0.5, γ 2 = 0.0, η = 1.5, β = 0.0; and (d) α = 1.0, γ 1 = 0.0, γ 2 = 0.0, η = 1.95, β = 0.0.
Paper: Size Distribution of Small Grains in the Inner Zodiacal Cloud
Authors: J. R. Szalay, P. Pokorný, D. M. Malaspina
Figure caption: (a) Cumulative impact rate distribution as a function of impact amplitude for orbits 10–16, with color indicating the power-law fit index above 50 mV for each 8 hr impact rate interval considered. (b) Ratio of cumulative impact rates with their corresponding power-law fits. (c) Cumulative charge indices α  Q  as a function of heliocentric distance, with average values and standard deviation each 5 R ⊙; the histogram on the right shows the distribution of α  Q  values. (d) Impact rates as a function of heliocentric distance. Colors for panels (c) and (d) show orbit number.
Paper: Size Distribution of Small Grains in the Inner Zodiacal Cloud
Authors: J. R. Szalay, P. Pokorný, D. M. Malaspina
Figure caption: (a) Correction factor δ a for the mass-dependent portion of the impact speed. (b, c) Corrected cumulative mass indices α = α  Q (1 + δ a) corresponding to the minimum and maximum δ a values from panel (a). (d) Comprehensive estimate of α accounting for mass-dependent biases, with the uncorrected α  Q  ranges shown with gray circles.
Paper: Size Distribution of Small Grains in the Inner Zodiacal Cloud
Authors: J. R. Szalay, P. Pokorný, D. M. Malaspina
Figure caption: Comparison with size distribution at 1 au (E. Grün et al. 1985) derived from a large number of observations, as well as the modeled distribution at 0.1 au (H. Ishimoto & I. Mann 1998). The gray boxes show the values of α found here for grains with radii in the approximate range of ∼0.6-1.4  μm detectable by PSP.
Paper: Size Distribution of Small Grains in the Inner Zodiacal Cloud
Authors: J. R. Szalay, P. Pokorný, D. M. Malaspina
Figure caption: (a) Example impact rate from orbit 13, representative of orbits 10–16, along with the modeled abundances of α-meteoroids and β-meteoroids from our two-component fit (J. R. Szalay et al. 2021). (b) Fractional contribution of α-meteoroids and β-meteoroids to total modeled impact rate. (c) Same information as panel (b) shown in the ecliptic J2000 x - y plane with example α-meteoroid and β-meteoroid trajectories.