adsabs/AstroCLIMB huggingface dataset:
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: Weight fractions of Si in the core for the results from the MCMC analysis. We used the measurements from Genova et al. (2019; G19), where we either set the weight fractions of the inner core and outer core to be the same (labeled “inner and outer core fraction”), or separate (indicated by “inner” and “outer”). We also used the measurements from Mazarico et al. (2014; M14), where the weight fractions were set to be the same. The solid lines indicate where we included k2 as a measurement (the G19 cases), and the dotted line indicates where we did not include k2 as a measurement (the M14 case).
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: Predicted parameters from our MCMC analysis using the measurements from Genova et al. (2019), including k2. We present results for the vertical tidal displacement Love number h2 (A), the horizontal displacement Love number l2 (B), the inner core temperature (C), and the pressure at the center of the core (D).
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: Viscosity at the CMB vs. the CMB radius (A), the CMB temperature (B), the grain size (C), and k2 (D), from the results of our MCMC analysis using the measurements of Genova et al. (2019). We also indicate the number of models in bins (with a width of 0.1 in log space for viscosity, 5 km for CMB radius, 5 K for CMB temperature, 1 cm for grain size, and 0.001 for k2) to highlight concentrations of models in the point cloud.
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: Ensemble and target ellipses for the results of our MCMC analysis using the measurements from Genova et al. (2019), where we now also include a convecting mantle, together with the results for a conducting mantle for comparison (A), and the resulting distributions for the CMB temperature (B), the inner core temperature (C), and the grain size (D).
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: Viscosity at the CMB vs. CMB radius (A), CMB temperature (B), the grain size (C), and k2 (D), from the results of our MCMC analysis using the measurements of Genova et al. (2019). For the results presented here, we modeled the mantle with one constant temperature when computing the tidal response, to mimic a convecting mantle. This temperature is equal to the CMB temperature, which is a parameter in the MCMC analysis. We extended the viscosity range, the CMB temperature range, and the grain size range, when compared to the results for the conducting mantle (Figure 7). We again indicate the number of models to highlight concentrations of models in the point cloud.
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: Pressure at the ICB vs. the temperature of the inner core, color-coded with the weight percentage of Si in the core for each MCMC model. Melt curves for pure Fe, FeSi at 9 wt% Si, and FeSi at 16 wt% Si are also shown. The results here exclude models where the core is assumed to be solid, but local conditions indicate that it is liquid.
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: Results from the MCMC analysis, where we plot the polar moment vs. the crust–mantle polar moment (A and B) or the polar moment vs. k2 (C and D). We use the measurements of C/(MR2), Cm/C, and average density from Hauck et al. (2013), indicated as H13, or Bertone et al. (2021), indicated as B21. We include ellipses for the measurements (“target”) as well as for the ensemble average. Because neither of these studies estimated k2, panels (C) and (D) show the predicted k2 results, and thus no target ellipse is included.
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: Results from the MCMC analysis, where we plot the polar moment vs. the crust–mantle polar moment (A−D) or the polar moment vs. k2 (E–H). Here, we use the measurements of Konopliv et al. (2020), where we make a distinction between the reported obliquity values, which result in a lower polar moment of inertia (labeled “low MoI”), and the obliquity derived from the reported pole coordinates, which results in a higher polar moment of inertia (labeled “high MoI”). We make the distinction to illustrate the influence on the mapping of the measurements. We show results for the analysis where we included k2 as a measurement and where we did not include it, but predicted its value.
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: Top (A): inner core weight fraction of Si vs. outer core weight fraction, with the count in bins of 0.5% shown to indicate clusters in the solutions. We used the measurements from Genova et al. (2019), where the weight fractions in the inner core and outer core are different. Bottom (B): weight fractions of Si in the core for the results from the MCMC analysis. We used the measurements from Genova et al. (2019; G19), where we either set the weight fractions of the inner core and outer core to be the same (labeled “inner and outer core fraction”) or separate (indicated by “inner” and “outer”). Here, we limit the difference in weight fraction between the inner and outer core to be at most 3%, as opposed to the results shown in Figure 8, where larger differences were allowed.
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: Top (A): viscosity vs. k2 (which we assume is equal to ﹩| {\bar{k}}_{2}| \sim {\mathfrak{R}}[{\bar{k}}_{2}]﹩) for different rheological laws, showing how different laws can affect k2 as viscosity varies. For this comparison, we assume a CMB radius of 2020 km, a rigidity of 54 GPa for both crust and mantle, a crustal thickness of 50 km, a core density of 7500 kg m−3, a mantle density of 3200 kg m−3, and a crustal density of 2800 kg m−3. Since we vary the viscosity as a parameter for this comparison, no temperature information is necessary. Bottom (B): results for k2 from our MCMC analysis when we use the measurements of Genova et al. (2019) with either an Andrade or Sundberg–Cooper rheology. The results are very close, despite possible differences in the viscosity–k2 relationship, as shown above. We include this merely to illustrate that with the current measurements we cannot distinguish rheological laws.
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: CMB and inner core temperatures for the results from the MCMC analysis using the measurements from Genova et al. (2019), where we expanded the bounds of the CMB temperatures from our original range of 1600–2000 K to 1200–2400 K. The solid lines indicate CMB temperatures and the dashed lines indicate inner core temperatures. While the temperature range increases with the expanded bounds, the results are very similar. We do not find preferences for higher CMB temperatures, for example.
Paper: Evaluation of Recent Measurements of Mercury’s Moments of Inertia and Tides Using a Comprehensive Markov Chain Monte Carlo Method
Authors: Sander Goossens, Joe P. Renaud, Wade G. Henning, Erwan Mazarico, Stefano Bertone, and Antonio Genova
Figure caption: Top (A): similar to Figure 10, this panel shows the pressure at the ICB vs. the temperature of the inner core, this time as a heat map of counts of models within bins. Bottom (B): the same as Figure 10, with models that have weight fractions of Si in the core less than 4% and CMB temperatures less than 1900 K excluded. Melt curves for pure Fe, FeSi at 9 wt% Si, and FeSi at 16 wt% Si are also shown.
Paper: Detecting Oceans on Exoplanets with Phase-dependent Spectral Principal Component Analysis
Authors: Dominick J. Ryan and Tyler D. Robinson
Figure caption: Apparent albedo spectra from the VPL Earth model across a range of phase angles and degraded to a resolving power of 140.
Paper: Detecting Oceans on Exoplanets with Phase-dependent Spectral Principal Component Analysis
Authors: Dominick J. Ryan and Tyler D. Robinson
Figure caption: Results of PCA applied to phase-dependent Earth spectra. Orbital inclination is edge-on (i = 90°) and 10 observations span gibbous to crescent phase. Realistic Earth results (left) can be compared to a glint-free Earth (right). The first three principal components are indicated, and a crescent-phase, cloud-free ocean-covered Earth spectrum is used to indicate the stand-alone glint signature (gray). Proportion of variance explained by components one, two, and three are 0.79, 0.20, and 0.006, respectively.
Paper: Detecting Oceans on Exoplanets with Phase-dependent Spectral Principal Component Analysis
Authors: Dominick J. Ryan and Tyler D. Robinson
Figure caption: Same as Figure 2, except for an orbital inclination of 75°. For the case that includes glint (left), the proportions of variance explained by components one, two, and three are 0.70, 0.29, and 0.007, respectively.
Paper: Detecting Oceans on Exoplanets with Phase-dependent Spectral Principal Component Analysis
Authors: Dominick J. Ryan and Tyler D. Robinson
Figure caption: Same as Figure 2, except for an orbital inclination of 60°. For the case that includes glint (left), the proportions of variance explained by components one, two, and three are 0.72, 0.28, and 0.008, respectively.
Paper: Detecting Oceans on Exoplanets with Phase-dependent Spectral Principal Component Analysis
Authors: Dominick J. Ryan and Tyler D. Robinson
Figure caption: Same as Figure 2, except for an inclination of 45° as applied to models that include glint (solid) as well as identical models where glint is removed (dashed). For the case that includes glint, the proportions of variance explained by components one, two, and three are 0.85, 0.15, and 0.015, respectively.
Paper: Detecting Oceans on Exoplanets with Phase-dependent Spectral Principal Component Analysis
Authors: Dominick J. Ryan and Tyler D. Robinson
Figure caption: Results of PCA applied to phase-dependent Earth spectra when only two phase-resolved observations are adopted—one at gibbous phase and one at crescent phase. Orbital inclination is edge-on (i = 90°). Component spectra (colors) can be compared to the stand-alone glint signature (gray). Proportions of variance explained by components one and two are 0.84 and 0.16, respectively.
Paper: Detecting Oceans on Exoplanets with Phase-dependent Spectral Principal Component Analysis
Authors: Dominick J. Ryan and Tyler D. Robinson
Figure caption: Same as Figure 6, except for inclinations of 75° (left) and 60° (right). For the 75° case, the proportions of variance explained by components one and two are 0.74 and 0.26, respectively. For the 60° case, the proportions of variance explained by components one and two are 0.64 and 0.36, respectively.
Paper: Detecting Oceans on Exoplanets with Phase-dependent Spectral Principal Component Analysis
Authors: Dominick J. Ryan and Tyler D. Robinson
Figure caption: Left: Apparent albedo spectra of Earth with (solid) and without (dashed) glint at select crescent phases (colors). Right: Wavelength-dependent fractional brightness increase due to glint over a range of crescent phase angles.
Paper: Detecting Oceans on Exoplanets with Phase-dependent Spectral Principal Component Analysis
Authors: Dominick J. Ryan and Tyler D. Robinson
Figure caption: Exposure time required to reach a spectrally resolved S/N of 10 for both the HabEx (brown) and LUVOIR-A (green) mission concepts for a crescent-phase (α = 135°) Earth-twin exoplanet orbiting a Sun-like host at 5 pc.
Paper: Detecting Oceans on Exoplanets with Phase-dependent Spectral Principal Component Analysis
Authors: Dominick J. Ryan and Tyler D. Robinson
Figure caption: Exposure time required to detect the Y-band crescent-phase glint signature at an S/N of 5 as a function of distance to the exo-Earth twin and assuming a Sun-like host. Results for both the HabEx (brown) and LUVOIR-A (green) concepts are shown, and curves for different orbital inclinations are indicated by line style.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Number of asteroids affected by a multiepoch clustering threshold value of N days as a function of N. Note that the curve flattens at a threshold value of ∼30 days.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Definition of coordinate frame for NEATM calculations. Both the Sun and telescope are in the plane of the page. The spin vector is not shown.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Ratio of the 2010 yearly averaged solar flux from satellite measurements to the flux of a blackbody at 5778 K. Deviations of up to 20% occur at WISE operating wavelengths.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Best-fit models to 38 observations of asteroid 7451 Verbitskaya with the standard NEATM (least-squares model) and our regularized approach (regularized model). Flux values shown in this figure are displayed as a function of asteroid–Sun distance and reduced to the values that would be observed at an asteroid–observer distance rao = 1 au. The least-squares model completely misses the data in W2, and the miss is not due to the small number of points in W2 because the least-squares model fits the data well in W1 with the same number of points. In addition, the small number of points in W2 does not prevent the regularized model from fitting the data. The χ2 values are 152 (least-squares model) and 25 (regularized model), whereas the sums of squares of (unweighted) residuals are 3.7 (least-squares model) and 0.075 (regularized model).
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Ratio of the largest and smallest T1 values among the seven solutions to our fitting procedure. For ratios below 0.95, the fits fall into one of two local minima. We report the best-fit solution from the high-T1 group.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Comparison of diameter estimates from stellar occultation observations to the results presented in this work. Herald et al. (2019) did not report uncertainties for the data points without vertical error bars. The agreement between the two data sets is quantified by a mean normalized orthogonal distance metric 〈d⊥〉 of 1.1645 (see text). Asteroid 874 has a stellar occultation diameter of 51.21 ± 30.9 km with a quality code of 3 and is not plotted for clarity but is included in the 〈d⊥〉 calculation.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Comparison of 2789 NEOWISE four-band diameter results to the results presented in this work. The best-fit T1 parameter is shown with a color scale. The apparent horizontal structure is related to the fact that NEOWISE diameter uncertainties are generally ∼3 times smaller than the more realistic bootstrap uncertainties used in this work.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Distribution of NEOWISE four-band diameters divided by the corresponding diameters obtained in this work. The red solid line shows the mean ratio obtained in consecutive diameter bins each containing 100 values. Approximately 98% of the 2651 asteroids among our carefully curated sample of 4420 asteroids have NEOWISE diameter values that agree with ours within ± 20%.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Comparison of 2971 NEOWISE visible albedo results with the results presented in this work. In this comparison, HORIZONS values of H were used in the calculation of pV. Asteroid 2010 MA113, which does not have a NEOWISE albedo estimate, is not shown.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Comparison of 2788 NEOWISE visible albedo results with the results presented in this work, as a function of D. The red solid line shows the mean ratio obtained in consecutive diameter bins each containing 100 values. In this comparison, HORIZONS values of H were used in the calculation of pV. Asteroid 2010 MA113, which does not have a NEOWISE albedo estimate, is not shown.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Visible-band geometric albedo pV as a function of the asteroid diameter D. The data are color-coded according to pseudo-temperature T1. We assumed an uncertainty of 0.25 mag (Vereš et al. 2015, Figure 5) on the H values to calculate the error bars on pV. Top: albedos calculated with H values obtained from HORIZONS. Bottom: albedos calculated with H values obtained from Vereš et al. (2015).
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Visible-band geometric albedo pV as a function of the asteroid diameter D for 791 asteroids with known taxonomic classifications. S/A/L/E-class asteroids are split according to their median infrared emissivity (Section 4.3). Albedos were calculated with H values obtained from HORIZONS.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Ratio of the two terms used to calculate the visible-band geometric albedo pV error. We assumed an uncertainty of 0.25 mag (Vereš et al. 2015, Figure 5) on the H values. Errors on the diameter estimates were obtained by calculating the standard deviations of 200 bootstrap resampling solutions. Note that the error on H is the dominant contribution for >91% of the asteroids.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Histograms of best-fit emissivity values for each of the WISE bands for 4420 asteroids.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Histogram of ϵ4 − ϵ3 values for 4420 asteroids.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Histograms of best-fit emissivity values for each of the WISE bands for 791 asteroids with known taxonomic type.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Relationship between visible-band geometric albedo pV and median infrared emissivity for 4420 asteroids. The colored curves represent Equation (8) with q = 0.384, η = 1, and various values of the pseudo-temperature T1.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Left: a subset of the W2 WISE observations of asteroid 85839 are well fit by a sinusoidal curve with a peak-to-peak light-curve amplitude App = 0.91 and a mean magnitude M = 12.7. Right: histograms of diameter estimates for 10,000 Monte Carlo realizations obtained with N = 3, 12, or 46 randomly selected flux observations with App = 0.91, expressed as a function of the “true” (mean) effective diameter. We used these simulations to quantify the approximate 1σ diameter errors caused by incomplete sampling of asteroid light curves.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Visible-band geometric albedo pV as a function of the asteroid diameter D, color-coded according to the median phase angle (top) and the quantity rao × ras (bottom). We assumed an uncertainty of 0.25 mag (Vereš et al. 2015, Figure 5) on the H values to calculate the error bars on pV. Albedos are calculated with H values obtained from HORIZONS (Vereš et al. 2015).
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Visible-band geometric albedo as a function of pseudo-temperature T1 for the 4685 asteroid fits presented in this work.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Distribution of the median phase angles α for the 4685 asteroid fits presented in this work.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Median emissivity value across all four WISE bands as a function of pseudo-temperature T1 for the 4685 asteroid fits presented in this work.
Paper: Analysis of Four-band WISE Observations of Asteroids
Authors: Nathan Myhrvold, Pavlo Pinchuk, and Jean-Luc Margot
Figure caption: Beaming parameter η as a function of pseudo-temperature T1 for the 4685 asteroid fits presented in this work.