adsabs/AstroCLIMB huggingface dataset:
Paper: A Detailed Study of Jupiter’s Great Red Spot over a 90-day Oscillation Cycle
Authors: Amy A. Simon, Michael H. Wong, Phillip S. Marcus, Patrick G. J. Irwin
Figure caption: GRS size variation over time. Top left: GRS size from visually identified elliptical red cloud boundaries. Top right: GRS core size from smoothed (elliptical) brightness contours. Bottom left: dynamical size based on the velocity field, with the red cloud size overlaid for comparison; dynamical semimajor axis data are offset by 0.5 day for clarity. Bottom right: aspect ratios (major/minor axes) from the measures in the other three panels; dynamical aspect ratio data are offset by 0.5 day for clarity.
Paper: A Detailed Study of Jupiter’s Great Red Spot over a 90-day Oscillation Cycle
Authors: Amy A. Simon, Michael H. Wong, Phillip S. Marcus, Patrick G. J. Irwin
Figure caption: GRS brightness over time. Top: latitude scans, averaged over the central longitude, in the F275W, F395N, F502N, and FQ889N filters for each date. Bottom: longitude scans, averaged over the central latitude, in the same filters for each date. The gray shaded areas correspond to the average red ellipse and core sizes.
Paper: A Detailed Study of Jupiter’s Great Red Spot over a 90-day Oscillation Cycle
Authors: Amy A. Simon, Michael H. Wong, Phillip S. Marcus, Patrick G. J. Irwin
Figure caption: GRS core ellipse fitting on unsharp masked F502N images. For each date, images were scaled to the same contrast, and contours of I/F = 0.5 were identified (white lines). The ellipse (red) that best overlaid the contours was then used to determine size and orientation.
Paper: A Detailed Study of Jupiter’s Great Red Spot over a 90-day Oscillation Cycle
Authors: Amy A. Simon, Michael H. Wong, Phillip S. Marcus, Patrick G. J. Irwin
Figure caption: GRS altitude and false-color composite maps. Left column: GRS in F395N shows the extent of redder material (blue absorption). Second column: F275W highlights the highest-altitude material. Third column: false-color composite of the FQ889N (R), FQ727N (G), and F631N (B) filters further highlights the GRS as high (pink shades), with entering high-altitude streamer material. Right column: reversed false-color composite with the F631N (R), FQ727N (G), and FQ889N (B) filters highlights the deep convective storms in the wake in red, with streamers visible in pale blue.
Paper: A Detailed Study of Jupiter’s Great Red Spot over a 90-day Oscillation Cycle
Authors: Amy A. Simon, Michael H. Wong, Phillip S. Marcus, Patrick G. J. Irwin
Figure caption: GRS dark lanes and corresponding IR hot spots. Top: near-simultaneous Hubble, Juno, and Gemini images from 2018 April 1. Left: Hubble data at ∼09:00 UT, with arrows marking dark lanes. Middle: JunoCam image (from NASA PIA21985) taken at ∼10:00 UT and the same features noted. Right: Gemini NIRI data taken at ∼10:50 UT, showing 5 µm IR hot spots at the same locations as the interior dark features (from M. H. Wong et al. 2020). Bottom: Hubble WFC3 images showing examples of the more frequent high-contrast dark lanes seen since 2018.
Paper: A Detailed Study of Jupiter’s Great Red Spot over a 90-day Oscillation Cycle
Authors: Amy A. Simon, Michael H. Wong, Phillip S. Marcus, Patrick G. J. Irwin
Figure caption: GRS cloud edge elliptical sizes on enhanced F502N image maps. For each date, the F502N GRS map was first lightly contrast enhanced and sharpened with an unsharp mask. The ellipse that best contained the red (dark) cloud area was visually identified. This was compared with the same images after further contrast enhancement and sharpening, as well as against brightness contours, to ensure a good match to the vortex edges.
Paper: A Detailed Study of Jupiter’s Great Red Spot over a 90-day Oscillation Cycle
Authors: Amy A. Simon, Michael H. Wong, Phillip S. Marcus, Patrick G. J. Irwin
Figure caption: Comparison of vorticity ratios to aspect ratio using the Kida relation. Left: the GRS red ellipse (blue points) or dynamical size (green points) only overlap with the vorticity ratio (red points) on the January dates, even with the large error bars; data were offset by 0.5 days for clarity. Right: the same comparison for the core ellipse and vorticity ratio shows they also disagree.
Paper: Visual-band Brightnesses of Near-Earth Objects that will be Discovered in the Infrared by NEO Surveyor
Authors: Joseph R. Masiero, Tyler Linder, Amy Mainzer, Dar W. Dahlen, Yuna G. Kwon
Figure caption:  V-band magnitude distribution of all simulated NEOs at the time they would be first detected by NEO Surveyor. The vertical dotted line indicates V = 22 mag, the approximate limiting magnitude of current NEO surveys and follow-up.
Paper: Visual-band Brightnesses of Near-Earth Objects that will be Discovered in the Infrared by NEO Surveyor
Authors: Joseph R. Masiero, Tyler Linder, Amy Mainzer, Dar W. Dahlen, Yuna G. Kwon
Figure caption:  V − NC2 color distribution of all simulated NEOs at the time they would be first detected by NEO Surveyor. The cross indicates the median value of the distribution, while the whiskers show the range spanned by the 2.5th and 97.5th percentiles.
Paper: Visual-band Brightnesses of Near-Earth Objects that will be Discovered in the Infrared by NEO Surveyor
Authors: Joseph R. Masiero, Tyler Linder, Amy Mainzer, Dar W. Dahlen, Yuna G. Kwon
Figure caption:  V − NC2 color vs. signal-to-noise (SNR) of the NC2 detection for simulated NEOs at the time of first detection. Spatial bins in this plot represent a logarithmic count of objects; the vast majority of detections are at SNR ∼ 5. Due to the expected photometric systematic uncertainties, sources have an effective upper limit to their SNR causing the apparent increase in source density at SNR ∼ 34 for all objects brighter than this limit.
Paper: Visual-band Brightnesses of Near-Earth Objects that will be Discovered in the Infrared by NEO Surveyor
Authors: Joseph R. Masiero, Tyler Linder, Amy Mainzer, Dar W. Dahlen, Yuna G. Kwon
Figure caption:  V-band magnitude as a function of elongation for all simulated NEOs at the time they would be first detected by NEO Surveyor. The horizontal dotted line indicates V = 22 mag, the approximate limiting magnitude of current NEO surveys and follow-up. Spatial bins in this plot represent a linear count of objects.
Paper: Visual-band Brightnesses of Near-Earth Objects that will be Discovered in the Infrared by NEO Surveyor
Authors: Joseph R. Masiero, Tyler Linder, Amy Mainzer, Dar W. Dahlen, Yuna G. Kwon
Figure caption:  V − NC2 color at the time of first detection vs the size of the simulated NEOs. Spatial bins in this plot represent a logarithmic count of objects. Larger objects are skewed bluer as they are more likely to be detected further from the Sun, but they still span a significant range of colors.
Paper: Constraining Ocean and Ice Shell Thickness on Miranda from Surface Geological Structures and Stress Modeling
Authors: Caleb Strom, Tom A. Nordheim, D. Alex Patthoff, Sherry K. Fieber-Beyer
Figure caption: (a) A cylindrical map made in JMARS of Miranda with Arden Corona and Elsinore Corona indicated. (b) A SatStressGUI plot using a cylindrical projection showing the asymmetric antipodal stress pattern of obliquity tidal stress. In the SatStressGUI plot, there is an antipodal (longitudinal) asymmetry where one hemisphere is in tension (red and positive) and the other hemisphere is in compression. (c) An overlay of the SatStressGUI obliquity tidal stress plot in (b) onto the map in (a). The plot shows the similarity in the antipodal asymmetry in the obliquity tidal stress field and the antipodal asymmetry implied by the surface geology of Miranda. Note that although the overlap is not exact, both (a) and (b) exhibit a 180° longitudinal separation between maximum tensile stress and maximum compressional stress across hemispheres. The mosaic of Miranda used as a base map was made by P. M. Schenk (2013).
Paper: Constraining Ocean and Ice Shell Thickness on Miranda from Surface Geological Structures and Stress Modeling
Authors: Caleb Strom, Tom A. Nordheim, D. Alex Patthoff, Sherry K. Fieber-Beyer
Figure caption: Under obliquity tidal stress and polar wander stress, stress from compression yields magnitudes sufficient to fracture ice under compression based on experiments (e.g., E. M. Schulson 2002), or ∼≥10 MPa. The 1 km brittle crust thickness plots on the left have logarithmic scales on their vertical axes.
Paper: Constraining Ocean and Ice Shell Thickness on Miranda from Surface Geological Structures and Stress Modeling
Authors: Caleb Strom, Tom A. Nordheim, D. Alex Patthoff, Sherry K. Fieber-Beyer
Figure caption: For ice shell thickening, the model results are shown for a lower ice shell viscosity of 1E12 Pa-s. The plot shows that ice shell thickening in all cases produces stress ≥1000 kPa. The markers are added for clarity, not to represent actual data points. Note that the thickness values represent the upper brittle ice shell thickness and ocean thickness only, not the whole hydrosphere.
Paper: Artificial Impacts on the Moon: Modeling 3D Seismic Propagation Effects with AxiSEM3D
Authors: Ceri Nunn, Benjamin A. Fernando, Mark P. Panning
Figure caption: (a) Rise time; (b) characteristic decay time. We estimated rise time and characteristic decay time for observations of the impacts of the lunar modules (purple), the Saturn IV boosters (pink), and simulation M-2 (blue). Rise time T max (in seconds) is the time from the event origin to the arrival of the maximum energy. Characteristic decay time τ  d  (in seconds) is the time taken for the coda to fall to 1/e of its initial value. Envelopes were filtered at 0.4–0.5 Hz and smoothed over 200 periods at the mid-frequency (giving a smoothing window of ∼445 s). The error bars on the rise time are the length of the smoothing window. Characteristic decay was estimated from a section of the waveform that started 300 s after T max and was 1500 s long.
Paper: Artificial Impacts on the Moon: Modeling 3D Seismic Propagation Effects with AxiSEM3D
Authors: Ceri Nunn, Benjamin A. Fernando, Mark P. Panning
Figure caption: Comparing the impact of Apollo 15's Saturn IV booster (at 11.72°) with simulations at low frequencies. All seismograms are filtered between 0.05 and 0.1 Hz (10–20 s periods), and the time axis is from –100 to 3000 s. Other details are the same as in Figure 9.
Paper: Artificial Impacts on the Moon: Modeling 3D Seismic Propagation Effects with AxiSEM3D
Authors: Ceri Nunn, Benjamin A. Fernando, Mark P. Panning
Figure caption: Coda decay (top) and signal onset (bottom) for observations vs. simulation M-2. The observations (gray) are from the Apollo 14 lunar module, Apollo 17 Saturn IV booster, and Apollo 17 lunar module and are at 2.17°, 28.05°, and 57.68° from the seismic station, respectively. Simulation M-2 is shown in blue. The time axis is in seconds. In panel (a), the time series begins at 300 s to exclude the initial pulse and better show the coda decay. We use seismic traces in velocity that are squared and then smoothed over a smoothing window of ∼22 s (top row) and ∼11 s (bottom row). The arrivals of the P (blue dashed line) and PS (pink dashed line) phases are calculated from Model M1 (R. F. Garcia et al. 2019). The PS phase does not form close to the source.
Paper: Artificial Impacts on the Moon: Modeling 3D Seismic Propagation Effects with AxiSEM3D
Authors: Ceri Nunn, Benjamin A. Fernando, Mark P. Panning
Figure caption: Simulations using Model M-2. M-2 includes ± 50% perturbation (tapering to zero perturbation at 50 km depth). The 1D background model is M1. Other details are the same as in Figure 6.
Paper: Artificial Impacts on the Moon: Modeling 3D Seismic Propagation Effects with AxiSEM3D
Authors: Ceri Nunn, Benjamin A. Fernando, Mark P. Panning
Figure caption: Comparing the impact of Apollo 17's lunar module (at 57.67°) with simulations. The time axis is from 0 to 3600 s. Other details are the same as in Figure 9.
Paper: Artificial Impacts on the Moon: Modeling 3D Seismic Propagation Effects with AxiSEM3D
Authors: Ceri Nunn, Benjamin A. Fernando, Mark P. Panning
Figure caption: Frequency dependence for observations (top) and simulation M-2 (bottom). Envelopes are shown at 0.1–0.2 Hz (green), 0.4–0.5 Hz (orange), and 0.8–0.9 Hz (purple). Envelopes are smoothed over 10 periods at the mid-frequency of each band. 0.1–0.2 Hz is noisy at the largest distance, and 0.8–0.9 Hz is not available for the simulations. Other details are the same as in Figure 14.
Paper: Zonal and Regional Jupiter Brightness Trends from the Hubble Outer Planet Atmospheres Legacy Program
Authors: Amy A. Simon, Michael H. Wong
Figure caption: Zonal average reflectivity at select latitudes (i.e., power spectrum peaks in Figures 5–8), with longitudinal brightness standard deviations as the uncertainty bars. (a) F275W curves display the largest variations above the longitudinal standard deviations at the equator and NTB (24° north). (b) F395N curves showing blue absorption changes at multiple latitudes. (c) F631N curves, showing that variation, largely due to cloud opacity, is largest in the NTB and NTrZ (19° north). (d) FQ889N curves showing upper troposphere/lower stratosphere clouds have the largest variations at the equator and NTB (24° north).
Paper: Zonal and Regional Jupiter Brightness Trends from the Hubble Outer Planet Atmospheres Legacy Program
Authors: Amy A. Simon, Michael H. Wong
Figure caption: FQ889N brightness scans (left) and Lomb–Scargle periodogram (right).
Paper: Zonal and Regional Jupiter Brightness Trends from the Hubble Outer Planet Atmospheres Legacy Program
Authors: Amy A. Simon, Michael H. Wong
Figure caption: F275W maps covering all longitudes and ±40° latitude for three dates, with contrast scaled the same. A large active plume was visible in 2020 near 20° north, 100° west, and a periodic train of diffuse brightness variations are visible in the 2017 April map (15° north, 240°–340° west).
Paper: Zonal and Regional Jupiter Brightness Trends from the Hubble Outer Planet Atmospheres Legacy Program
Authors: Amy A. Simon, Michael H. Wong
Figure caption: FQ889N maps covering all longitudes and ±40° latitude, with contrast scaled the same. Small-amplitude residual fringing is apparent, and transiting moons saturate (visible in 2020 and 2024). The diffuse bright spots in the F275W data (Figure 9, faint periodic spots in 2017 and a high-intensity, isolated spot in 2020) appear dark in the methane band maps.
Paper: Zonal and Regional Jupiter Brightness Trends from the Hubble Outer Planet Atmospheres Legacy Program
Authors: Amy A. Simon, Michael H. Wong
Figure caption: GRS maps centered at −23°, spanning ±7° of latitude and ±15° of longitude. These maps span the UV to near-IR, using the F275W (top row), F395N (middle; no data in 2009), and FQ889N (bottom) filters. In 2021, the F395N brightness temporarily increased, even though no effects were seen in the other filters.
Paper: Zonal and Regional Jupiter Brightness Trends from the Hubble Outer Planet Atmospheres Legacy Program
Authors: Amy A. Simon, Michael H. Wong
Figure caption: Brightness trends in the GRS. Meridional scans across the GRS center. Bottom: averaging over −22.°5 to −23.°5 to encompass the core region and over −19.°5 to −20.°5 for the collar.
Paper: Zonal and Regional Jupiter Brightness Trends from the Hubble Outer Planet Atmospheres Legacy Program
Authors: Amy A. Simon, Michael H. Wong
Figure caption: F631N maps covering all longitudes and ±40° latitude for three dates, with contrast scaled the same. Dark regions are cloud clearings; “hot spots” at the edge of the EZ are prominent.
Paper: Zonal and Regional Jupiter Brightness Trends from the Hubble Outer Planet Atmospheres Legacy Program
Authors: Amy A. Simon, Michael H. Wong
Figure caption: F395N maps covering all longitudes and ±40° latitude for three dates, with contrast scaled the same. Longitudinal structure varies widely with latitude and date.
Paper: Zonal and Regional Jupiter Brightness Trends from the Hubble Outer Planet Atmospheres Legacy Program
Authors: Amy A. Simon, Michael H. Wong
Figure caption: F631N brightness scans (left) and Lomb–Scargle periodogram (right).
Paper: Brightness Behavior of Distant Oort Cloud Comets
Authors: Carrie E. Holt, Matthew M. Knight, Michael S. P. Kelley, Tim Lister, Quanzhi Ye, 泉志 叶, Colin Snodgrass, Cyrielle Opitom, Rosita Kokotanekova, Megan E. Schwamb, Matthew M. Dobson, Michele T. Bannister, Marco Micheli, Stefanie N. Milam, Derek C. Richardson, Edward Gomez, Joseph P. Chatelain, Sarah Greenstreet
Figure caption: Median-combined g image of the ephemeris location of C/2021 O3 on 2022 May 27, when r h = 0.99 au and Δ = 0.79 au. A diffuse cloud is observed in the center of the image.
Paper: Predictions for Sparse Photometry of Jupiter-family Comet Nuclei in the LSST Era
Authors: A. Donaldson, C. Snodgrass, R. Kokotanekova, A. Rożek
Figure caption: Distribution of phase function fits to 100 MC lightcurves for three different cases. The dashed vertical line shows the input phase function value β  L . The orange line (β scat) demonstrates weighted linear regression on reduced magnitudes with lightcurve amplitude scatter. The mean of this distribution is 0.0567 ± 0.0005 mag deg–1. The red line (β corr,s ) shows the distribution of phase functions for lightcurves corrected for rotation by a convex model constructed from purely sparse lightcurves with mean 0.0591 ± 0.0015 mag deg–1. The purple line (labeled β corr,sd ) results from the phase function fit using a convex model constructed from a combination of sparse and dense lightcurves, with mean 0.0591 ± 0.0012 mag deg–1.
Paper: Predictions for Sparse Photometry of Jupiter-family Comet Nuclei in the LSST Era
Authors: A. Donaldson, C. Snodgrass, R. Kokotanekova, A. Rożek
Figure caption: Distribution of principal axis ratios a/b and b/c for the top two shape models from 100 MC randomized lightcurve trials. The color scale depicts pole longitude: darker colored points correspond to pole orientations closest to the simulation input pole, and lighter colors are shapes at the mirror pole. Also shown are axis ratios for the noiseless models developed in Section 3 and previously published models by Lowry et al. (2012, L12) and Mottola et al. (2014, M14).
Paper: Predictions for Sparse Photometry of Jupiter-family Comet Nuclei in the LSST Era
Authors: A. Donaldson, C. Snodgrass, R. Kokotanekova, A. Rożek
Figure caption: Pole orientations corresponding to the top two unique pole solutions from lightcurve inversion of 100 sparse-in-time lightcurves. Color corresponds to the density of points, where lighter regions have a larger number of points. Dashed lines mark the input pole coordinates (λ  i , β  i ).
Paper: Predictions for Sparse Photometry of Jupiter-family Comet Nuclei in the LSST Era
Authors: A. Donaldson, C. Snodgrass, R. Kokotanekova, A. Rożek
Figure caption: A comparison of (upper) the representative shape model used to create the synthetic lightcurves and (lower) the best-fit shape model resulting from the lightcurve inversion analysis for (a) 9P/Tempel 1, (b) Arrokoth, and (c) 103P/Hartley 2.
Paper: Predictions for Sparse Photometry of Jupiter-family Comet Nuclei in the LSST Era
Authors: A. Donaldson, C. Snodgrass, R. Kokotanekova, A. Rożek
Figure caption: Distribution of χ 2 values for tested pole orientations using a synthetic lightcurve generated with model input rotation period Pi  = 23.9344696 hr. The yellow lines enclose regions where the χ 2 values lie within 10% of the minimum χ 2 value, which is located at the position of the yellow circle.
Paper: Predictions for Sparse Photometry of Jupiter-family Comet Nuclei in the LSST Era
Authors: A. Donaldson, C. Snodgrass, R. Kokotanekova, A. Rożek
Figure caption: Same MC analysis as in Figure 9 but with the addition of a dense lightcurve to the sparse survey data points.
Paper: The Discovery and Evolution of a Possible New Epoch of Cometary Activity by the Centaur (2060) Chiron
Authors: Matthew M. Dobson, Megan E. Schwamb, Alan Fitzsimmons, Charles Schambeau, Aren Beck, Larry Denneau, Nicolas Erasmus, A. N. Heinze, Luke J. Shingles, Robert J. Siverd, Ken W. Smith, John L. Tonry, Henry Weiland, David. R. Young, Michael S. P. Kelley, Tim Lister, Pedro H. Bernardinelli, Marin Ferrais, Emmanuel Jehin, Grigori Fedorets, Susan D. Benecchi, Anne J. Verbiscer, Joseph Murtagh, René Duffard, Edward Gomez, Joey Chatelain, Sarah Greenstreet
Figure caption: Estimated V-band absolute magnitude (corrected for distance, phase angle, and filter color difference) vs. time of Chiron, with values obtained from our observations and literature measurements. Dates of aphelion and perihelion are indicated by the blue vertical solid and dotted lines, respectively. Chiron was known to exhibit a visible coma during its outburst commencing around 1989 (Meech & Belton 1989; Hartmann et al. 1990; Meech 1990), with later confirmed detections of a coma in 1998 (Silva & Cellone 2001). Chiron was observed to dim in brightness as it approached perihelion in 1996 February, reaching its dimmest recorded absolute magnitude shortly after perihelion around 1999. Other likely cometary outbursts are thought to have occurred in the 1970s (Bus et al. 2001) and around the year 2000 (Duffard et al. 2002) as evidenced by Chiron’s sudden increases in absolute magnitude around these times. The lightcurve as predicted from the ring model of Ortiz et al. (2015) is plotted in black. Chiron’s 2021 Brightening Event contrasts with the gradual dimming as predicted by Ortiz et al. (2015).
Paper: The Discovery and Evolution of a Possible New Epoch of Cometary Activity by the Centaur (2060) Chiron
Authors: Matthew M. Dobson, Megan E. Schwamb, Alan Fitzsimmons, Charles Schambeau, Aren Beck, Larry Denneau, Nicolas Erasmus, A. N. Heinze, Luke J. Shingles, Robert J. Siverd, Ken W. Smith, John L. Tonry, Henry Weiland, David. R. Young, Michael S. P. Kelley, Tim Lister, Pedro H. Bernardinelli, Marin Ferrais, Emmanuel Jehin, Grigori Fedorets, Susan D. Benecchi, Anne J. Verbiscer, Joseph Murtagh, René Duffard, Edward Gomez, Joey Chatelain, Sarah Greenstreet
Figure caption: Upper plot: estimated V-band absolute magnitude (corrected for distance, phase angle, and filter color difference) vs. time for Chiron across our baseline of observations, with the high-precision observations from Gemini, Gaia, DES, and ZTF highlighted for clarity. Centre plot: estimated V-band absolute magnitude (corrected for distance, phase angle, and filter color difference) vs. time for Chiron across observing seasons L–N (2020–2023) highlighting the brightening in Chiron’s magnitude due to the 2021 Brightening Event. Lower plot: estimated V-band absolute magnitude (corrected for distance, phase angle, and filter color difference) vs. time for Chiron across observing seasons L–N (2020–2023) highlighting the brightening in Chiron’s magnitude due to the 2021 Brightening Event. The observations from Gemini and ZTF are highlighted for clarity. All observing seasons are labeled as per Table 2. In all subplots, the date of aphelion is indicated by the solid blue line. Chiron’s absolute magnitude as predicted by Ortiz et al. (2015) is plotted in black.
Paper: The Discovery and Evolution of a Possible New Epoch of Cometary Activity by the Centaur (2060) Chiron
Authors: Matthew M. Dobson, Megan E. Schwamb, Alan Fitzsimmons, Charles Schambeau, Aren Beck, Larry Denneau, Nicolas Erasmus, A. N. Heinze, Luke J. Shingles, Robert J. Siverd, Ken W. Smith, John L. Tonry, Henry Weiland, David. R. Young, Michael S. P. Kelley, Tim Lister, Pedro H. Bernardinelli, Marin Ferrais, Emmanuel Jehin, Grigori Fedorets, Susan D. Benecchi, Anne J. Verbiscer, Joseph Murtagh, René Duffard, Edward Gomez, Joey Chatelain, Sarah Greenstreet
Figure caption: Dust grain velocity measurements of outbursts from the JFC 67P/Churuymov–Gerasimenko compared to the range of escape velocity values of Chiron (gray) estimated from known densities of Centaur binaries. The horizontal dashed black line indicates the value of Chiron’s escape velocity according to the density estimate of Braga-Ribas et al. (2023).