adsabs/AstroCLIMB huggingface dataset:
Paper: Phase Mixing and the 1/f Spectrum in the Solar Wind
Authors: Norbert Magyar, Tom Van Doorsselaere
Figure caption: Perpendicular energy spectra at different heights, for the three noise maps used, Brownian (−2), Kolmogorov (−1.66), and pink (−1), respectively (from left to right). The line corresponding to the spectra at 15 R ⊙ is thicker for easier identification. The dashed lines represent spectral slopes corresponding to the noise color.
Paper: Phase Mixing and the 1/f Spectrum in the Solar Wind
Authors: Norbert Magyar, Tom Van Doorsselaere
Figure caption: Plots of the perpendicular velocity perturbation magnitude in a slice across the background magnetic field, at three different radial distances, 1, 7.5, and 15 r/R ⊙, respectively (from left to right). The Kolmogorov noise density profile was used for this example.
Paper: Phase Mixing and the 1/f Spectrum in the Solar Wind
Authors: Norbert Magyar, Tom Van Doorsselaere
Figure caption: Plot of the perpendicular velocity perturbation magnitude in a slice along the background magnetic field at x = 0, at the end of the simulation time. The Kolmogorov noise density profile is used in this example.
Paper: Phase Mixing and the 1/f Spectrum in the Solar Wind
Authors: Norbert Magyar, Tom Van Doorsselaere
Figure caption: Vector plot of a single realization of the driven velocity perturbations at the bottom radial boundary, for the surface Alfvén wave setup. The color and size of the individual vectors represent velocity magnitude, in units of kilometers per second.
Paper: Transient Radio Emission from Low-redshift Galaxies at z < 0.3 Revealed by the VLASS and FIRST Surveys
Authors: Fabao Zhang, Xinwen Shu, Luming Sun, Lei Yang, Ning Jiang, Liming Dou, Jianguo Wang, Tinggui Wang
Figure caption: The percentage change in radio flux over the period of the two-epoch VLASS observations, which is defined as (F epoch II − F epoch I)/F epochI. The flux errors include the 5% uncertainties in the flux densities measured from CASA, to account for the flux calibration uncertainties of the VLASS data (Lacy et al. 2020).
Paper: Transient Radio Emission from Low-redshift Galaxies at z < 0.3 Revealed by the VLASS and FIRST Surveys
Authors: Fabao Zhang, Xinwen Shu, Luming Sun, Lei Yang, Ning Jiang, Liming Dou, Jianguo Wang, Tinggui Wang
Figure caption: The BPT diagram, based on the emission-line ratios of O [III]/H β vs. N [II]/H α. The SDSS galaxies are shown with the gray dots, while the radio transients in our sample are shown with the red circles. The different lines represent the boundaries that are commonly used to classify sources between star-forming galaxies, LINERs, composites, and AGNs, taken from Kewley et al. (2001), Kauffmann et al. (2003), and Schawinski et al. (2007). The upper panel shows the classification of the radio transients according to the emission-line diagnosis of the nuclear activity.
Paper: Transient Radio Emission from Low-redshift Galaxies at z < 0.3 Revealed by the VLASS and FIRST Surveys
Authors: Fabao Zhang, Xinwen Shu, Luming Sun, Lei Yang, Ning Jiang, Liming Dou, Jianguo Wang, Tinggui Wang
Figure caption: Radio SEDs between 888 MHz and 3 GHz. For sources that are not detected in FIRST or RACS, the 3σ upper limits on the flux are shown. The error bars for the radio spectral index (α 0.89–3 GHz) are estimated using Monte Carlo simulations (the green shaded regions), assuming that the error on each flux follows a Gaussian distribution. The filled red circle in each panel represents the extrapolated 1.4 GHz flux density, based on the best-fit radio slope.
Paper: Signatures of Mass Ratio Reversal in Gravitational Waves from Merging Binary Black Holes
Authors: Floor S. Broekgaarden, Simon Stevenson, Eric Thrane
Figure caption: Effective spin and delay time for MRR (left) and non-MRR (right) binary black holes in our 20 stellar evolution simulations. Convolving the delay times with a metallicity-specific star formation history (﹩{ \mathcal S }(Z,z)﹩) provides the binary black holes as a function of redshift. There is an anticorrelation present where binary black holes with larger effective spins have shorter delay times, which is particularly visible in the MRR panel. We provide the same figure for each model separately at GitHub. https://github.com/FloorBroekgaarden/MRR_Project/blob/main/Figure_7_and_8_and_9_and_10_Discussion_2D_slices/ChiEff_vs_tdelay_2Dplot_priorWeighted_not_drawing.png https://github.com/FloorBroekgaarden/MRR_Project/blob/main/Figure_7_and_8_and_9_and_10_Discussion_2D_slices/Make_2D_scatter_Distributions.ipynb.
Paper: Signatures of Mass Ratio Reversal in Gravitational Waves from Merging Binary Black Holes
Authors: Floor S. Broekgaarden, Simon Stevenson, Eric Thrane
Figure caption: Cumulative distribution function of the zero-age main sequence more massive mass (left panel), mass ratio (center panel), and separation (right panel) for our 560 model realizations. For each panel we show the distribution for MRR (orange) and non-MRR (blue). MRR binaries have more equal mass ratios and shorter separations at zero-age main sequence compared to the overall binary black hole population. In each panel for comparison in gray the birth distribution of all binaries in COMPAS are shown. Three realizations, “K123”, “O312” and “T231” (see Github) are highlighted with a dotted, dashed–dotted and dotted curve, respectively. https://github.com/FloorBroekgaarden/MRR_Project/blob/main/Figure_Appendix_MRR_Properties_vs_nonMRR_ZAMS_CDFs_Panels/CDF_models_multiPanel_ZAMS.png https://github.com/FloorBroekgaarden/MRR_Project/blob/main/Figure_Appendix_MRR_Properties_vs_nonMRR_ZAMS_CDFs_Panels/FractionOfDetectable_BBHs.ipynb.
Paper: Signatures of Mass Ratio Reversal in Gravitational Waves from Merging Binary Black Holes
Authors: Floor S. Broekgaarden, Simon Stevenson, Eric Thrane
Figure caption: Same as Figure 4 but assuming spin thresholds of 0.01 (top left), 0.1 (top right), 0.25 (bottom left), and 0.5 (bottom right). https://github.com/FloorBroekgaarden/MRR_Project/blob/main/Figure4_spinning_BBH_Rates/Rate_MRR_spins_panels_spin_threshold_0.05.pdf https://github.com/FloorBroekgaarden/MRR_Project/blob/main/Figure4_spinning_BBH_Rates/Plot_fraction_spinning_BBHs.ipynb
Paper: Fast Neutrino Cooling in the Accreting Neutron Star MXB 1659-29
Authors: Melissa Mendes, Farrukh J. Fattoyev, Andrew Cumming, Charles Gale
Figure caption: As Figure 4, but including proton (top panel) and neutron (bottom panel) superfluidity. In the upper panel, the proton gap models BS and CCYps give the same results as the case with no pairing shown in Figure 4; we show only CCYps (in purple) in the Figure. In the lower panel, neutron gap model EEHOr (in gray) corresponds to the no-pairing curve shown in Figure 4.
Paper: Fast Neutrino Cooling in the Accreting Neutron Star MXB 1659-29
Authors: Melissa Mendes, Farrukh J. Fattoyev, Andrew Cumming, Charles Gale
Figure caption: As Figure 4, but for three examples of NT and PS combinations. In each case, we show the results with proton pairing only, neutron pairing only, and with both neutron and proton pairing included. Top panel: gap models PS EEHO and NT AO. NT AO's curve is under the curve of the combination. Middle panel: gap models PS CCDK and NT T. Bottom panel: gap models PS CCDK and NT SYHHP.
Paper: Fast Neutrino Cooling in the Accreting Neutron Star MXB 1659-29
Authors: Melissa Mendes, Farrukh J. Fattoyev, Andrew Cumming, Charles Gale
Figure caption: Heat capacity as a function of dUrca neutrino luminosity for neutron stars with different choices for NT and PS gaps. Models calculated for L = 47, 72, and 112.7 MeV, respectively, on the top, middle, and bottom panels. We show results for no pairing (dashed curve) and for three combinations of NT and PS gaps as indicated (black, red, and blue curves). The vertical gray area highlights the inferred neutrino luminosity range for MXB 1659-29 from Brown et al. (2018). The horizontal gray area shows the contribution to the heat capacity from leptons. Diagonal dashed lines show the predicted surface temperature variation over a decade given the values of L  ν  and C.
Paper: Fast Neutrino Cooling in the Accreting Neutron Star MXB 1659-29
Authors: Melissa Mendes, Farrukh J. Fattoyev, Andrew Cumming, Charles Gale
Figure caption: Top panel: neutron star mass that reproduces the neutrino luminosity of MXB 1659-29 as a function of the dUrca reduction factor f red for neutron star models with neutron pairing only. The error bars correspond to the 1σ uncertainty in neutrino luminosity from Brown et al. (2018). We show results for the strongest NT gap model NT AO (stars) and the weakest NT gap model NT EEHOr (circles), for L = 47 MeV (black) and L = 112.7 MeV (blue), intermediate values of L lie between these curves. Bottom panel: percentage of the core volume involved in dUrca reactions for NT EEHOr. The shaded region corresponds to the 1σ uncertainty in the top panel.
Paper: Fast Neutrino Cooling in the Accreting Neutron Star MXB 1659-29
Authors: Melissa Mendes, Farrukh J. Fattoyev, Andrew Cumming, Charles Gale
Figure caption: Cumulative dUrca neutrino luminosity as a function of radial distance, for a star with total mass M = 1.60 M ⊙ and L = 90 MeV. We display the no gap case (black curve) along with the PS CCDK only case (orange curve), the NT SYHHP only case (green curve), and the PS CCDK  + NT SYHHP combination (red curve). The region to the left of the vertical yellow line (dUrca threshold) represents the radii emitting dUrca neutrinos. The NT SYHHP opening curve is the dotted dashed green vertical line. The shaded areas are regions under superfluidity (a detailed explanation is given in the text).
Paper: Fast Neutrino Cooling in the Accreting Neutron Star MXB 1659-29
Authors: Melissa Mendes, Farrukh J. Fattoyev, Andrew Cumming, Charles Gale
Figure caption: Masses of neutron stars that can cool by dUrca for the gap model NT SYHHP (shaded regions). dUrca is unsuppressed at low masses for L ≳ 70 MeV or at high masses close to the maximum mass. At intermediate masses, dUrca is quenched by superfluidity. We show the dUrca threshold (orange curve), maximum mass (blue curve), and the opening (dotted green) and closing (dashed green) curves of NT SYHHP as a function of L.
Paper: Fast Neutrino Cooling in the Accreting Neutron Star MXB 1659-29
Authors: Melissa Mendes, Farrukh J. Fattoyev, Andrew Cumming, Charles Gale
Figure caption: Reduction factor R  L  of gap models PS CCDK and NT SYHHP as a function of core number density over saturation density, for a neutron star with L = 85 MeV and M = 1.74 M ⊙. The vertical dotted line represents the dUrca threshold and the region to the right of it, indicated with the arrow, where dUrca reactions take place.
Paper: Fast Neutrino Cooling in the Accreting Neutron Star MXB 1659-29
Authors: Melissa Mendes, Farrukh J. Fattoyev, Andrew Cumming, Charles Gale
Figure caption: Neutron star heat capacity as a function of L for models that reproduce the inferred neutrino luminosity of MXB 1659-29. The shaded regions around each curve correspond to the 1σ uncertainty in neutrino luminosity from Brown et al. (2018). We show results for no pairing and for different NT gap models.
Paper: LensingETC: A Tool to Optimize Multifilter Imaging Campaigns of Galaxy-scale Strong Lensing Systems
Authors: Anowar J. Shajib, Karl Glazebrook, Tania Barone, Geraint F. Lewis, Tucker Jones, Kim-Vy H. Tran, Elizabeth Buckley-Geer, Thomas E. Collett, Joshua Frieman, Colin Jacobs
Figure caption: Comparison of parameter uncertainties between the six observing strategies or cases for HST SNAP program: for Einstein radius θ E in the left-hand panel, and for the logarithmic slope parameter γ in the right-hand panel. For each observing strategy or case, the illustrated parameter uncertainty is the mean of the individual uncertainties from 20 lens systems. The six strategies distribute ∼2000 s of total observing time of one HST truncated orbit between two filters: from allocating all the time for the F140W filter in Case 1 to allocating all the time for the F200LP filter in Case 6. As the F200LP band allows for higher resolution than the F140W band, a higher image resolution is more constraining for lens models than a higher S/N for typical strong lensing systems.
Paper: LensingETC: A Tool to Optimize Multifilter Imaging Campaigns of Galaxy-scale Strong Lensing Systems
Authors: Anowar J. Shajib, Karl Glazebrook, Tania Barone, Geraint F. Lewis, Tucker Jones, Kim-Vy H. Tran, Elizabeth Buckley-Geer, Thomas E. Collett, Joshua Frieman, Colin Jacobs
Figure caption: Example of a simulated lens system in the six observing scenarios and two filters for a HST SNAP program. The first and third columns illustrate the simulated imaging data, and the second and fourth columns illustrate the exposure time map after accounting for the impact of cosmic-ray hits. A montage of the full sample of 20 lenses is given in Figure 7.
Paper: LensingETC: A Tool to Optimize Multifilter Imaging Campaigns of Galaxy-scale Strong Lensing Systems
Authors: Anowar J. Shajib, Karl Glazebrook, Tania Barone, Geraint F. Lewis, Tucker Jones, Kim-Vy H. Tran, Elizabeth Buckley-Geer, Thomas E. Collett, Joshua Frieman, Colin Jacobs
Figure caption: Deviations in power-law slope parameter γ for galaxy–galaxy and point-source lenses modeled with and without supersampled PSF. The illustrated distributions correspond to kernel density estimates from 20 lens systems for each case. For galaxy–galaxy lens systems (dashed lines), the PSF supersampling does not noticeably impact the distribution of deviations. However, for point-source lenses, modeling with the nonsupersampled PSF creates a larger scatter than that with the supersampled PSF. In all cases, the mean deviation at the sample level is within 0.25% from zero.
Paper: LensingETC: A Tool to Optimize Multifilter Imaging Campaigns of Galaxy-scale Strong Lensing Systems
Authors: Anowar J. Shajib, Karl Glazebrook, Tania Barone, Geraint F. Lewis, Tucker Jones, Kim-Vy H. Tran, Elizabeth Buckley-Geer, Thomas E. Collett, Joshua Frieman, Colin Jacobs
Figure caption: False-color composite images of the simulated galaxy–galaxy (tow 2 rows) and point-source (bottom 2 rows) lens systems from Sections 3 and 4. The RGB images are created from a weighted combination of monochrome images from the F140W and F200LP filters.
Paper: MEGASIM: Lifetimes and Resonances of Earth Trojan Asteroids—The Death of Primordial ETAs?
Authors: Travis Yeager, Nathan Golovich
Figure caption: The black line is the ETA ejection FFT spectrum. The x-axis is the period of a signal in years, and the y-axis is the relative strength of a given signal. Panel (a) spans 65 kyr to 1 Myr, with the color lines representing the periods of the Milankovitch cycles. The orange lines are the periods of known modes in the Milankovitch cycles due to changes in Earth’s eccentricity at 95, 125, and 413 kyr, which loosely combine to a period of 100 kyr. In green we plot periods of inclination changes at 70 and 100 kyr. Finally, in purple we show the period of apsidal precession at 112 kyr. Panel (b) shows the positions of the planetary s (solid) and g (dashed) resonances overlaid on the ETA ejection FFT, spanning 10 kyr to 10 Myr. Color indicates the corresponding planet, listed in the legend on the right.
Paper: Accelerated Bayesian SED Modeling Using Amortized Neural Posterior Estimation
Authors: ChangHoon Hahn, Peter Melchior
Figure caption: The distribution of the SED model parameters, redshift, photometric magnitudes, and uncertainties of the data used to train SEDFLOW. We plot a subset of the parameters (﹩\mathrm{log}{M}_{* }﹩, β 1) and photometric bands for clarity. The training data was constructed by sampling SED model parameters from the prior and forward modeling optical photometry using the PROVABGS and noise models (Section 3). For comparison, we present the distribution of the redshift, magnitudes, and uncertainties for galaxies in the NSA catalog (blue). The training set encompasses the observations; thus, SEDFLOW can be used to infer the posteriors for the NSA galaxies.
Paper: MEGASIM: Lifetimes and Resonances of Earth Trojan Asteroids—The Death of Primordial ETAs?
Authors: Travis Yeager, Nathan Golovich
Figure caption: FFT of planetary orbital elements using 1 Myr to 1 Gyr of simulation data. Panels only span 10 kyr to 1 Myr to focus on the many lower frequencies that exist in both the planetary orbital elements and ETA ejections. In each panel is a different planet with line colors from the bottom up: black shows ETA ejections, blue shows the semimajor axis, orange shows the eccentricity, green shows the inclination, red shows the true longitude, purple shows the argument of periapsis, and brown shows the longitude of the ascending node.
Paper: MEGASIM: Lifetimes and Resonances of Earth Trojan Asteroids—The Death of Primordial ETAs?
Authors: Travis Yeager, Nathan Golovich
Figure caption: The standard deviation of the true anomalies in Earth in all 22,400 simulations as a function of simulation time. In the first 100 Myr, the simulations are largely in agreement, but between 100 and 200 Myr, the numerical drift of the simulations spreads out the individual solar systems. By 200 Myr, the standard deviation approaches the value for the standard deviation of a uniform distribution spanning 360° (﹩\sqrt{{(360-0)}^{2}/12}\approx 103.92﹩). This value is shown with a horizontal dotted line. This behavior of the member simulations matches the decoherence of the oscillatory ejection behavior present in panel (a) of Figure 4 very well.
Paper: MEGASIM: Lifetimes and Resonances of Earth Trojan Asteroids—The Death of Primordial ETAs?
Authors: Travis Yeager, Nathan Golovich
Figure caption: Panel (a) shows the binned ETA ejections over time spanning 0 to 200 Myr of the WHfast data set. Bin widths are 100 kyr, the same as Figure 2. Panel (b) shows the binned ETA ejections over time, spanning 0 to 10 Myr of the WHfast data set. Bin widths are 1000 yr.
Paper: MEGASIM: Lifetimes and Resonances of Earth Trojan Asteroids—The Death of Primordial ETAs?
Authors: Travis Yeager, Nathan Golovich
Figure caption: The range of data predicted by the stretched exponential fits to bootstrap resampled data as the domain over which the fit is performed is increased. The fits all begin at 15 kyr and extend to 100 to 1 Gyr, incremented by 100 Myr. The width of the orange lines extends from the 10th to 90th percentile obtained from bootstrap samples of the remaining ETA distribution.
Paper: MEGASIM: Lifetimes and Resonances of Earth Trojan Asteroids—The Death of Primordial ETAs?
Authors: Travis Yeager, Nathan Golovich
Figure caption: The remaining ETA fraction as a function of simulation time in black with a best-fit stretched exponential (dashed red line) overlaid. y(t) and t refer to variables found in Equation (3). The area where the black line is thicker is used for the stretched exponential fit to avoid the initial stages of the simulation where very unstable ETAs filter out. The fit spans 15 kyr to 1 Gyr.
Paper: MEGASIM: Lifetimes and Resonances of Earth Trojan Asteroids—The Death of Primordial ETAs?
Authors: Travis Yeager, Nathan Golovich
Figure caption: Same as Figure 7, but the periods in the range of 1 to 4 Myr are highlighted.
Paper: Differential Behaviors of Suprathermal 4He and Fe Populations in the Interplanetary Medium during Solar Cycle 24
Authors: Bijoy Dalal, D. Chakrabarty, N. Srivastava
Figure caption: Panel (a) shows typical variations of the 370 day averaged 4He flux (black) corresponding to 0.55 MeV n−1 (mentioned at the right corner) and SSN (red). Variations of the normalized cross-correlation coefficients between the 4He flux and SSN with respect to the lags (in multiples of 370 days) for SC23 and SC24 are shown in subplots (b) and (c), respectively. The scatter plots in subplots (d) and (e) represent variations of the averaged and adjusted 4He fluxes with respect to the SSN in SC23 and SC24, respectively (see the text for details). Pearson’s correlation coefficient (R) between flux and SSN and corresponding p values are mentioned at the bottom of panels (d) and (e).
Paper: Differential Behaviors of Suprathermal 4He and Fe Populations in the Interplanetary Medium during Solar Cycle 24
Authors: Bijoy Dalal, D. Chakrabarty, N. Srivastava
Figure caption: Original vis-à-vis modified (after removal of the transient events) variations of the fluxes of different elements for the entire period (1998–2020) along with the SSN data used in this paper (panel (a)). Subplots (b), (d), (f), (h), (j), and (l) show the original flux variations of H, 4He, 3He, Fe, C, and O, respectively. The modified (“quiet”) fluxes of the elements in the similar order are plotted in subplots (c), (e), (g), (i), (k), and (m). Legends for the different energy channels of an element are marked by colored dots and are appropriately placed at the left and right of the plots.
Paper: Differential Behaviors of Suprathermal 4He and Fe Populations in the Interplanetary Medium during Solar Cycle 24
Authors: Bijoy Dalal, D. Chakrabarty, N. Srivastava
Figure caption: The left column shows the proton flux data (a) before and (b) after the removal of the transient events. The dashed vertical lines indicate the start (red) and end (blue) times of the CIR event during this period as observed by ULEIS/ACE. The non-CIR transient events are indicated by arrows in (a). Different energy channels are represented by the mean of the lower and upper energy limits and are shown by colored dots. The right column shows the 4He flux variation before (c) and after (d) the removal of transient events similar to what has been done for the proton channels.
Paper: Differential Behaviors of Suprathermal 4He and Fe Populations in the Interplanetary Medium during Solar Cycle 24
Authors: Bijoy Dalal, D. Chakrabarty, N. Srivastava
Figure caption: Variations of Pearson’s CC between the lagged fluxes and SSN with respect to the averaging window. Panels (a), (c), (e), (g), (i), and (k) show the variations of CC for H, 4He, 3He, Fe, C, and O, respectively during SC23. Panels (b), (d), (f), (h), (j), and (l) represent the same for SC24. Energy channels corresponding to H, 4He, and 3He are written on the left side of the left column of the figure. The same corresponding to Fe, C, and O are mentioned on the right of the right column of the figure.
Paper: Using 1991T/1999aa-like Type Ia Supernovae as Standardizable Candles
Authors: Jiawen Yang, Lifan Wang, Nicholas Suntzeff, Lei Hu, Lauren Aldoroty, Peter J. Brown, Kevin Krisciunas, Iair Arcavi, Jamison Burke, Lluís Galbany, Daichi Hiramatsu, Griffin Hosseinzadeh, D. Andrew Howell, Curtis McCully, Craig Pellegrino, Stefano Valenti
Figure caption: Hubble residual vs. ﹩{{pEW}}_{{\rm{\max }}}﹩(SiII λλ6355). Open circles indicate objects with z cmb < 0.01. Blue vertical line in the right panel is where pEW = 55.62 Å. Black line in the right panel shows the best linear fit for objects with pEW < 55.62 Å (Hubble residual (mag) = ﹩0.009\,\times {{pEW}}_{{\rm{\max }}}\mathrm{Si}\ \mathrm{II}\lambda 6355(\mathring{\rm A} )-0.482﹩), and the weighted mean (= 0.036 mag) for objects with pEW > 55.62 Å.