adsabs/AstroCLIMB huggingface dataset:
Paper: Exoplanet Aeronomy: A Case Study of WASP-69 b’s Variable Thermosphere
Authors: W. Garrett Levine, Shreyas Vissapragada, Adina D. Feinstein, George W. King, Aleck Hernandez, Lía Corrales, Michael Greklek-McKeon, Heather A. Knutson
Figure caption: Two-dimensional histogram of the posterior distributions for ﹩{({R}_{p}/{R}_{\star })}_{{\rm{W}},2}﹩ vs. ﹩{({R}_{p}/{R}_{\star })}_{{\rm{W}},1}﹩. The dotted line represents equal planet-to-star ratios for the two metastable HeI transits obtained with WIRC.
Paper: Exoplanet Aeronomy: A Case Study of WASP-69 b’s Variable Thermosphere
Authors: W. Garrett Levine, Shreyas Vissapragada, Adina D. Feinstein, George W. King, Aleck Hernandez, Lía Corrales, Michael Greklek-McKeon, Heather A. Knutson
Figure caption: WIRC planet-to-star radius ratio vs. WASP-69's X-ray output, normalized by the Swift 95% upper confidence bound. The top x-axis shows the X-ray fluxes from WASP-69 in terms of what would be measured at Earth. The black point represents the constraint from contemporaneous multiwavelength data, where the WIRC night 2 transit depth is taken from Section 3.3. The gray horizontal shaded bar and the blue vertical shaded bar show the WIRC-like metastable HeI transit depth from GIANO night 1 in 2019 (best-fit value from Section 3.3) and the XMM-Newton X-ray flux from 2016, respectively. Lines represent theoretical p-winds model results for various T 0 values, where the mass-loss rates are calculated with the same efficiency ϵ that is required to match the contemporaneous data from 2023. WASP-69's X-ray flux from 2016, although not contemporaneous with any metastable HeI transmission, changes in a direction and magnitude consistent with the interpretation that the drop in planetary absorption data over time stems from long-term changes in the stellar XUV across the magnetic activity cycle.
Paper: Exoplanet Aeronomy: A Case Study of WASP-69 b’s Variable Thermosphere
Authors: W. Garrett Levine, Shreyas Vissapragada, Adina D. Feinstein, George W. King, Aleck Hernandez, Lía Corrales, Michael Greklek-McKeon, Heather A. Knutson
Figure caption: The top panels show the best-fit light curves for night 1 Palomar/WIRC photometry with different sets of detrending covariates. The fit with the best BIC from Section 3.1 is marked at the top of its light curve. Each light curve is annotated with the derived (R  p /R ⋆) from the given model. The middle panels show the residuals as the best-fit model subtracted from the detrended photometry. Background (gray) points on both panels derive from the individual images, and blue points are binned to 10 minute intervals. The bottom panels show the Allan deviation plots for each light-curve model. Colored lines with error bars denote the rms error of the binned residuals for each light curve. Solid black lines denote the expected noise from purely Poisson statistics, and dotted lines shows the photon noise scaled up to the rms error of the binned residuals.
Paper: Exoplanet Aeronomy: A Case Study of WASP-69 b’s Variable Thermosphere
Authors: W. Garrett Levine, Shreyas Vissapragada, Adina D. Feinstein, George W. King, Aleck Hernandez, Lía Corrales, Michael Greklek-McKeon, Heather A. Knutson
Figure caption: Derived planet-to-star radius ratios (R  p /R ⋆) vs. aperture size from fitting WIRC photometry with various sets of detrending covariates. Error bars indicate 1σ uncertainties. Vertical shading highlights the aperture size that minimized the rms scatter as described in Section 3.1. In addition to the covariates listed in the legend, all light curves are detrended by time.
Paper: Exoplanet Aeronomy: A Case Study of WASP-69 b’s Variable Thermosphere
Authors: W. Garrett Levine, Shreyas Vissapragada, Adina D. Feinstein, George W. King, Aleck Hernandez, Lía Corrales, Michael Greklek-McKeon, Heather A. Knutson
Figure caption: The main plot shows the estimated WASP-69 spectrum (black line), which was established from Swift observations and scaling HD 85512's spectrum (gray line) to solar X-ray/UV flux ratios. Each bandpass of interest is shown with background shading. The inset shows the TIMED/SEE data from Solar Cycle 24 from the F x and F euv,2 bands along with the best-fit power law.
Paper: Exoplanet Aeronomy: A Case Study of WASP-69 b’s Variable Thermosphere
Authors: W. Garrett Levine, Shreyas Vissapragada, Adina D. Feinstein, George W. King, Aleck Hernandez, Lía Corrales, Michael Greklek-McKeon, Heather A. Knutson
Figure caption: Normalized ΔBIC vs. aperture size for candidate sets of covariates. For each aperture size, the ΔBIC values are computed relative to the BIC of the best-fit model without any covariates other than a linear trend with time. The most negative values of ΔBIC for each aperture size indicate the most preferred set of detrending covariates by that model selection criterion, but can only be compared to the other ΔBIC values at the same aperture size. Vertical shading highlights the aperture size that minimized the rms scatter, as described in Section 3.1.
Paper: Exoplanet Aeronomy: A Case Study of WASP-69 b’s Variable Thermosphere
Authors: W. Garrett Levine, Shreyas Vissapragada, Adina D. Feinstein, George W. King, Aleck Hernandez, Lía Corrales, Michael Greklek-McKeon, Heather A. Knutson
Figure caption: Panel (a) shows the best-fit, phase-folded light-curve models from the procedure in Section 3.3. Panels (b), (c), (d), (e), (f), (g), (h), (i), and (j) show the residuals of the metastable HeI light-curve models vs. the best-fit light curve from panel (a). These residual plots correspond to WIRC night 1, WIRC night 2, CARMENES night 1, CARMENES night 2, SPIRou, Keck, GIANO night 1, GIANO night 2, and GIANO night 3, respectively; the legend in panel (a) also corresponds to the color-coding in panels (b)–(j). This figure is the analog of Figure 3 from Section 3.2 for the joint fit from Section 3.3.
Paper: Exoplanet Aeronomy: A Case Study of WASP-69 b’s Variable Thermosphere
Authors: W. Garrett Levine, Shreyas Vissapragada, Adina D. Feinstein, George W. King, Aleck Hernandez, Lía Corrales, Michael Greklek-McKeon, Heather A. Knutson
Figure caption: Corner plot of the planet-to-star radii ratios for all light curves from the joint fit in Section 3.3 that included broadband TESS observations with metastable HeI data from both ultranarrowband photometry and spectroscopy. Each of the two-dimensional histograms is annotated with the difference (in σ) between the two parameters as derived from the posterior samples themselves. The dotted black line on each two-dimensional histogram indicates where the two radii are equal.
Paper: Exoplanet Aeronomy: A Case Study of WASP-69 b’s Variable Thermosphere
Authors: W. Garrett Levine, Shreyas Vissapragada, Adina D. Feinstein, George W. King, Aleck Hernandez, Lía Corrales, Michael Greklek-McKeon, Heather A. Knutson
Figure caption: Analogous plot to Figure 8 that includes all the WIRC-like metastable HeI transits instead of only the extreme values. For each WIRC-like metastable HeI light curve without contemporaneous XUV data, we display a horizontal line at the best-fit planet-to-star radii ratio from the joint fit in Section 3.3. Uncertainty bounds on the WIRC-like metastable HeI transit depths are not displayed on the plot but are presented in Table 3.
Paper: Exoplanet Aeronomy: A Case Study of WASP-69 b’s Variable Thermosphere
Authors: W. Garrett Levine, Shreyas Vissapragada, Adina D. Feinstein, George W. King, Aleck Hernandez, Lía Corrales, Michael Greklek-McKeon, Heather A. Knutson
Figure caption: Analogous plots to Figure 9 for the night 2 WIRC photometry.
Paper: Extensive Pollution of Uranus and Neptune’s Atmospheres by Upsweep of Icy Material during the Nice Model Migration
Authors: Eva Zlimen, Elizabeth Bailey, Ruth Murray-Clay
Figure caption: The left column shows initial locations of accreted test particles in the disk and the planets they collided with. The right column gives the total collisions for Uranus (blue) and Neptune (purple), with the planets identified by their locations in their final configuration. The first two rows show simulations in which Uranus initially is exterior to Neptune (Swaps 1&2), whereas the bottom two rows show scenarios in which Neptune starts and ends exterior to Uranus (No Swaps 1&2). Collisions are normalized to the total number undergone by both ice giants in each simulation. The majority of particles were accreted by the initially outermost ice giant from the inner edge of the disk. The remainder of the accreted particles originated from all regions of the disk with little variation.
Paper: Extensive Pollution of Uranus and Neptune’s Atmospheres by Upsweep of Icy Material during the Nice Model Migration
Authors: Eva Zlimen, Elizabeth Bailey, Ruth Murray-Clay
Figure caption: Jupiter and Saturn were initialized in 3:2 mean-motion resonance, with libration angles φ  J  = 3λ  S  − 2λ  J  − ϖ  J  and φ  S  = 3λ  S  − 2λ  J  − ϖ  S , where λ refers to the mean longitude and ϖ is the longitude of pericenter. The angle φ  J  librates around 0 while φ  S  librates around π. Only the first 1 × 105 yr are shown for clarity. The ability of the resonance to survive 108 yr was used to determine the set of initial conditions used in this simulation (Table 1), which we employ for all subsequent simulations in this work. The relatively weak and noisy resonant behavior evident here results from inclusion of all four giant planets as well as the low initial eccentricities of Jupiter and Saturn.
Paper: Extensive Pollution of Uranus and Neptune’s Atmospheres by Upsweep of Icy Material during the Nice Model Migration
Authors: Eva Zlimen, Elizabeth Bailey, Ruth Murray-Clay
Figure caption: Semimajor axis (a), apocenter distance a(1 + e), and pericenter distance a(1 − e) vs. time of Jupiter (pink), Saturn (dark purple), Uranus (blue), and Neptune (light purple) along with the time and location of collisions with test particles for Uranus (blue triangles) and Neptune (purple stars) during the chaotic period. In this scenario (No Swap 1), the ice giants did not end with swapped positions: Neptune began and ended exterior to Uranus. Neptune was responsible for ∼80% of the total test particle collisions.
Paper: Extensive Pollution of Uranus and Neptune’s Atmospheres by Upsweep of Icy Material during the Nice Model Migration
Authors: Eva Zlimen, Elizabeth Bailey, Ruth Murray-Clay
Figure caption: Semimajor axis–eccentricity density plots for Neptune representing the evolution of a chaotic system as simulated with different integrators. For each integrator, 500 simulations were run with orbital elements recorded every 1000 yr. The orbital elements across all 500 simulations were compiled for each planet into one large pool of data. From this, 2000 points were randomly selected (black dots), so that we were sampling from a range of all simulations. The end result is the distribution at any given time, with increasing density as darker purple. This compares REBOUND’s IAS15 with the Mercurius default (Hillfactor = 3), and adjusted to a larger switchover radius (Hillfactor = 7).
Paper: Extensive Pollution of Uranus and Neptune’s Atmospheres by Upsweep of Icy Material during the Nice Model Migration
Authors: Eva Zlimen, Elizabeth Bailey, Ruth Murray-Clay
Figure caption: Fraction of particles initially located in each 2 au radial bin that ultimately collide with Neptune (purple) and Uranus (blue). This provides the probability of collision for a given initial test particle semimajor axis, for any initial surface density. The left plot shows the combined statistics for No Swaps 1&2 while the right plot shows the same for Swaps 1&2. Uranus and Neptune are identified by their locations in their final configuration.
Paper: Extensive Pollution of Uranus and Neptune’s Atmospheres by Upsweep of Icy Material during the Nice Model Migration
Authors: Eva Zlimen, Elizabeth Bailey, Ruth Murray-Clay
Figure caption: Test particles were integrated with initial conditions (Section 2.2) to determine the placement of the planetesimal disk. Final vs. initial semimajor axes of all test particles are shown after integration for three million years. Planet initial positions are shown for this nonchaotic simulation. Test particles (black dots) were almost entirely removed inward of 20 au, and thus this was chosen for the inner edge of the disk. Higher density is shown as darker purple.
Paper: Extensive Pollution of Uranus and Neptune’s Atmospheres by Upsweep of Icy Material during the Nice Model Migration
Authors: Eva Zlimen, Elizabeth Bailey, Ruth Murray-Clay
Figure caption: Simulated mean semimajor axes and eccentricities for each planet (colored rectangles) compared with the corresponding present-day values retrieved from JPL Horizons (black dots). Widths and heights of the rectangles correspond to the maximum and minimum values of the last five million years of the four chosen runs. In two of the runs, Uranus started and ended interior to Neptune (No Swap 1 and 2), while in the other two Uranus started exterior to Neptune (Swap 1 and 2).
Paper: Extensive Pollution of Uranus and Neptune’s Atmospheres by Upsweep of Icy Material during the Nice Model Migration
Authors: Eva Zlimen, Elizabeth Bailey, Ruth Murray-Clay
Figure caption: Semimajor axis (a), apocenter distance a(1 + e), and pericenter distance a(1 − e) vs. time of Jupiter (pink), Saturn (dark purple), Uranus (blue), and Neptune (light purple) along with the time and location of collisions with test particles for Uranus (blue triangles) and Neptune (purple stars) during the initial chaotic period. The first row shows simulations in which Neptune starts and ends exterior to Uranus (No Swaps 1&2), while the second row shows simulations in which Neptune starts interior to Uranus (Swaps 1&2).
Paper: Extensive Pollution of Uranus and Neptune’s Atmospheres by Upsweep of Icy Material during the Nice Model Migration
Authors: Eva Zlimen, Elizabeth Bailey, Ruth Murray-Clay
Figure caption: Semimajor axis (a), apocenter distance a(1 + e), and pericenter distance a(1 − e) vs. time of Jupiter (pink), Saturn (dark purple), Uranus (blue), and Neptune (light purple) for the full orbital evolution of the four chosen simulations. The first row shows simulations in which Neptune starts and ends exterior to Uranus (No Swaps 1&2) while the second row shows simulations in which Neptune starts interior to Uranus (Swaps 1&2). Note the differing timescales between plots.
Paper: Singular Spectrum Analysis of Exoplanetary Transits
Authors: Hossein Fatheddin, Sedighe Sajadian
Figure caption: Left panels: simulated light curves of low S/N planetary transits with different depths (δ) and noise levels (σ cdpp). In each simulation, the period is set to one day. The red curve in each figure corresponds to the best transit model derived from the BLS algorithm. The blue curves correspond to the actual transits without the noise factors. Right panels: the resulting light curves after the SSA denoising. Before SSA, differences can be noted between the BLS models and the actual transits. These differences are resolved after SSA. On top of each figure, Depth, σ cdpp and S/N of the transits are reported.
Paper: Singular Spectrum Analysis of Exoplanetary Transits
Authors: Hossein Fatheddin, Sedighe Sajadian
Figure caption: Left panels: visualizations of W-correlation matrices for SSA components of the simulations. It can be noted that some component time series show weak correlations with most of the other components, which represents their noise-like behavior. Right panels: W-correlation matrices of the denoised light curves. The number of noise components have decreased after SSA. The colorbar at the right of each figure shows the mapping from scalar weighted correlations in the W-correlation matrix to colors.
Paper: Singular Spectrum Analysis of Exoplanetary Transits
Authors: Hossein Fatheddin, Sedighe Sajadian
Figure caption: Figures (a) and (c) show the initial light curve and the river plot for TOI-4622, respectively. The light curve is folded over seven transits and the river plot shows the evolution of the noisy periodic transit signals over the course of the entire light curve. Figures (b) and (d) show the denoised versions of these plots after the implementation of SSA. The S/N of the transit has increased from 13.4 to 15.6.
Paper: Singular Spectrum Analysis of Exoplanetary Transits
Authors: Hossein Fatheddin, Sedighe Sajadian
Figure caption: Folded light curves of six encouraging TESS candidates. The left side light curve in each panel corresponds to the initial time series, whereas the right side ones belong to the resulting reconstructed data from SSA. The red curve in each figure corresponds to the best transit model derived from the BLS algorithm. On top of each figure, period, depth, σ cdpp, and S/N of the transits are reported. A decrease in fluctuations, improvements in the S/Ns and changes in the best fit BLS models can be noted in the folded light curves after the SSA.
Paper: Singular Spectrum Analysis of Exoplanetary Transits
Authors: Hossein Fatheddin, Sedighe Sajadian
Figure caption: Visualization of w-correlation matrix for TIC-65416038 with L = 100.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: Data were recorded three times for every scan during the BP175 campaign when antennas were on source: first at SX, then at at CX, and then again at SX.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: Location of the 10 VLBA radio telescopes.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The differences in R.A. scaled by the ﹩\cos \delta ﹩ factor derived from the analysis of 2.2/8.4 GHz observations at the VLBA and R1R4 networks.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The differences in R.A. scaled by the ﹩\cos \delta ﹩ factor derived from the analysis of 3.0/5.2/6.4/10.2 and 2.2/8.4 GHz geodetic VLBI observations.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The differences in R.A. scaled by the ﹩\cos \delta ﹩ factor derived from the analysis of 2.2/8.4 and 4.1/7.4 GHz VLBA observations.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The differences in decl. derived from the analysis of 2.2/8.4 GHz observations at the VLBA and R1R4 networks.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The differences in decl. derived from the analysis of 3.0/5.2/6.4/10.2 and 2.2/8.4 GHz geodetic VLBI observations.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The differences in decl. derived from the analysis of 2.2/8.4 and 4.1/7.4 GHz VLBA observations.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The differences in normalized arc lengths between the source positions derived from the analysis of 2.2/8.4 and 4.1/7.4 GHz VLBA observations. The pale pink points show the histogram computed with original uncertainties and the green points show the histogram computed with inflated uncertainties.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The differences in normalized arc lengths between the position estimates derived from analysis of 3.0/5.2/6.4/10.2 and 2.2/8.4 GHz geodetic VLBI observations. The pale pink points show the histogram computed with original uncertainties and the green points show the histogram computed with inflated uncertainties.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: Location of 13 radio telescopes that participated in the IVS quad-band campaign.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: Location of the 33 radio telescopes that participated in the IVS SX R1R4 campaigns.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The distribution of normalized arc lengths between the K-band and SX position estimates. The green bright circles show the distribution using original data. The pale pink circles show the distribution with the contribution of the residual ionospheric noise applied. The thick blue line shows the Rayleigh distribution with σ = 1 as a reference.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The normalized distribution of the position angles of the differences in source coordinates derived from SX and K-band data counted from the north celestial pole (green circles). The solid blue line shows its fit with two Gaussians and a constant. The yellow vertical lines show the maxima. The thin dashed red line shows the uniform distribution.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The green solid circles show the position differences in decl. from the analysis of VLBA data at 2.2/8.4 GHz vs. 23 GHz at seven decl. segments. The blue hollow circles show the median K-band position uncertainty. The pink solid line shows the predicted additional variance in decl. due to residual errors in the ionospheric contribution to the path delay (Petrov 2023).
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The normalized distribution of the position angles of the differences in source coordinates derived from SX and K-band data counted from jet directions relative to the source coordinates derived from the K-band data solution (green circles). The solid blue line shows its fit with two Gaussians and a constant. The yellow vertical lines show the maxima. The thin dashed red line shows the uniform distribution.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The differences in normalized arc lengths between the source positions derived from the analysis of 2.2/8.4 GHz data from the VLBA and R1R4 networks. The pale pink points show the histogram computed with original uncertainties and the green points show the the histogram computed with inflated uncertainties.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The distribution of normalized arc lengths between the K-band and SX source position estimates, with the contribution from the residual ionosphere and an extra noise along the jet directions applied with the admittance factors equal to 1. The thick blue line shows the Rayleigh distribution with σ = 1 as a reference.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The differences in R.A. scaled by ﹩\cos \delta ﹩ from the analysis of VLBA data at 2.2/8.4 GHz vs. 23 GHz.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The differences in decl. from the analysis of VLBA data at 2.2/8.4 GHz vs. 23 GHz.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: Images of the sources with large position differences between coordinates derived from 8.4/2.3 GHz data with respect to coordinates derived from 23.6 GHz data. Left: J0318 + 1628, also known as CTA21 (position difference –5.10 mas in R.A.). Center: J1217 + 5835—the position estimate at 2.2/8.4 GHz is shown with a green cross and the position estimate at 23.6 GHz is shown with a red star. Right: J1927 + 7358—the offset of the position from 2.2/8.4 GHz data relative to the position estimate at 23.6 GHz is shown with a blue arrow. The images are taken from the Astrogeo VLBI FITS image database, available at http://astrogeo.smce.nasa.gov/vlbi_images.
Paper: Radio Astrometry at Different Frequencies
Authors: Leonid Petrov
Figure caption: The normalized distribution of the position angles of the differences in source coordinates derived from IVS R1R4 SX and VLBA K-band data counted from the jet directions (green circles). The solid blue line shows its fit with two Gaussians and a constant. The yellow vertical lines show the maxima. The thin dashed red line shows the uniform distribution.