adsabs/AstroCLIMB huggingface dataset:
Paper: M31N 2017-01e: Discovery of a Previous Eruption in this Enigmatic Recurrent Nova
Authors: Allen W. Shafter, Kenta Taguchi, Jingyuan Zhao, 经远 赵, Kamil Hornoch
Figure caption: Top Left Panel: The Pan-STARRS (PS1) lightcurve for the 2012 January 11 eruption of PS1_DR2_11.04464+41.9061 (which we now designate as M31N 2012-01c). Top Right Panel: The ZTF lightcurve for the 2019 September 22 eruption of M31N 2017-01e. The lightcurve shows that t 2—the time to fade 2 mag—is just ∼6 days. Bottom Left Panel: The positions of M31N 2012-01c and 2017-01e are compared on the left showing that they are indeed spatially coincident (white: M31N 2012-01c; Black: M31N 2017-01e), while M31N 2017-01e is compared on the right with a deep field image from Massey et al. (2006) showing that it is also spatially coincident with the blue, V ∼ 20.4 source, which we identify with the quiescent nova (white: M31V J00441070+4154220; black: M31N 2017-01e). Bottom right panel: The phased B and V lightcurve of M31V J00441070+4154220 from the data from Vilardell et al. (2006). Both lightcurves exhibit an asymmetrical modulation throughout the putative 14.3 days orbital cycle of the quiescent nova. The data behind panels (a), (b), and (d) are available in the dbf1.tar.gz package.(The data used to create this figure are available.)
Paper: Fitting Rotational Frequency of Polytropes as a Function of their Oblateness
Authors: Shin'ichirou Yoshida
Figure caption: Left: Fitting curves of normalized ω 2 vs. normalized oblateness ﹩\tilde{{f}_{o}}﹩. The dashed line is the curve for the incompressible Maclaurin spheroid (Chandrasekhar 1987) in our normalization (for which f obl,MS = 1) . The bottom panel shows the relative residuals (in percent) of the fitting. The residuals in percent are defined as ﹩100\tfrac{{\omega }^{2}(\mathrm{numerical})-{\omega }^{2}(\mathrm{fitting})}{| {\omega }^{2}(\mathrm{numerical})-{\omega }^{2}(\mathrm{fitting})| /2}﹩, where ω 2(numerical) and ω 2(fitting) are the rotational frequency squared of the numerical models and the fitting formulae. Right: The oblateness at the mass-shedding limit versus the adiabatic index Γ. The light blue points are numerical data, while the solid black line is the fitted formula by Equation (3). The bottom panel shows the residuals.
Paper: Applying Random Forest Classification to Ultracool Dwarf Discovery in Deep Surveys. I. Color Classification with SDSS, UKIDSS, and WISE Photometry
Authors: Zijie Gong, Adriana Nava Vega, Eduardo Gauna Gutierrez, Arantxa Mendiola Maytorena, Carlos Verdaguer, Christian Aganze, Christopher Danner, Adam J. Burgasser
Figure caption: Random forest classification of ultracool dwarfs. (a) Confusion matrix for our UCD/non-UCD classifier. The number of sources classified in the test samples are indicated. Diagonal elements indicate correct classifications, off-diagonal elements mis-classifications. (b) Confusion matrix for UCD spectral group classification. (c) Feature importance plot indicating the relative importance (vertical axis) of various colors in determining UCD spectral group classifications. (d) Comparison of actual and predicted spectral types for UCDs based on the RF regressor model; the orange line indicates perfect agreement.
Paper: The Behavior of HgMn Stars in the Far UV −2: μ Leporis
Authors: Richard Monier
Figure caption: Left: Comparison of the mean spectral energy distribution of μ Leporis (in black) to that of SWP 40111 (FUV minimum in blue), Right: The mean spectral energy distribution of μ Leporis in the mid-UV.
Paper: X-Ray Chronicles of Alpha Centauri: The Swooning of α Cen B
Authors: Tom Ayres
Figure caption: Chandra HRC-I 0.1–2.4 keV X-ray light curves, normalized to bolometric luminosities (for a fairer comparison), of α Cen A (blue), B (red), and Procyon (green; monitor for HRC-I soft sensitivity). Red asterisks are XMM-Newton fluxes of B (scaled to HRC-I). Solar X-ray irradiances are gray/dark dots.
Paper: Pair-instability Mass Loss for Top-down Compact Object Mass Calculations
Authors: M. Renzo, D. D. Hendriks, L. A. C. van Son, R. Farmer
Figure caption: Each panel shows our fitting formula Equation (2) for the PPI induced mass-loss as a function of carbon-oxygen core mass at each metallicity Z. The crosses show the values from Table 1 Farmer et al. (2019).
Paper: Stars on the Verge: Analyses of the Complex Light Variations of the Hyper-luminous Red Supergiant VY Canis Majoris: On the Nature of the Star’s “Great Dimming” Episodes
Authors: Thinh H. Nguyen, Edward F. Guinan
Figure caption: The top panel (a) shows the photometry of VY CMa (1801–2021) plotted against the calendar date. The photographic (blue) observations have been normalized to the visual observations from overlapping data. The photographic (1889–1970) and AAVSO visual magnitudes (1960–2021) are plotted against Julian Dates in panels (b) and (c). Two intervals of large quasi-periodic light variations during 1920–1950 and 1985–1995 are apparent. Period studies of these data are given in Figures 1(d)–(g). The results of the WWZ analyses are presented in Figures 1(d) and (e). The dominant periods of ∼1415–1565 days are shown during the times of enhanced activity. The CLEANest program (Figures 1(f) and (g)) returns similar periodicities. Outside of the active times, the star typically has only small irregular brightness variations.
Paper: The Ultraviolet Variability of 78 Vir (A2p SrCrEu) throughout the IUE Mission
Authors: Richard Monier
Figure caption: Left: The far UV flux variations of 78 Vir—FUV maximum flux SWP 36485 (in black), FUV minimum flux SWP 30949 (in blue), Right: Absence of large variations at corresponding rotational phases in the range 2000–3000 Å.
Paper: The Behavior of HgMn Stars in the Far UV -1: χ Lupi
Authors: Richard Monier
Figure caption: Comparison of the mean spectral energy distribution of χ Lupi (in black) to that of SWP 48509 (FUV minimum in blue) and SWP 48510 (FUV maximum in red)
Paper: New Constraints on the Composition and Initial Speed of CNEOS 2014-01-08
Authors: Amir Siraj, Abraham Loeb
Figure caption: Total power released in the CNEOS 2014-01-08 fireball as a function of ram pressure, ρ v 2. Typical stony and iron meteorite yield strengths, 1–5 MPa and 50 MPa respectively, are indicated for convenience of comparison, and the three major flare events are labeled according to the order in which they occurred. We conservatively adopt a constant velocity between the flares. Note that 1 TW = 1019 erg s−1 and 1 MPa = 107 dyne cm−2.
Paper: Revisiting the Mass-excitation (MEx) Diagram using the MaNGA Data Set
Authors: J. K. Barrera-Ballesteros, S. F. Sánchez
Figure caption: The distribution of the entire MaNGA sample in the mass-excitation diagram (MEx) using central (left panel) and integrated (right panel) measurements. In both panels the distribution is binned and color-coded according to the average EW(Hα) within each bin. Yellow and color-coded stars represent the AGN Seyfert 1 and 2 samples selected by Sánchez et al. (2022), respectively. In both panels the dashed lines represent the demarcation lines derived by Juneau et al. (2014).
Paper: WASP Lightcurves: Red Noise and a Cautionary Tale
Authors: Coel Hellier
Figure caption: Night-by-night portions of WASP data (the y-axis is relative magnitude, the x-axis is JD omitting a leading 245). The top two panels are for the star TYC 2623-1439-1, first for a sequence of nights where the data normalization is correct, and then for some nights during the claimed 1% dip. The bottom two panels are for the nearby star 1SWASP J182419.61+302542.6, 281 arcsecs away, showing the same low normalization on the same nights. Note that the data for the nearby star have a larger scatter since it is fainter.
Paper: The Behavior of HgMn Stars in the Far UV −4: ι CrB A
Authors: Richard Monier
Figure caption: Left: the mean spectral energy distribution of ι CrB A in the FUV (the Ga II 1414.40 Å resonance line is marked by a dashed vertical line), Right: the coadded SOPHIE spectrum of ι CrB A in the range 4500–4520 Å(The Pt II line at 4514.14 Å is also marked).
Paper: The NASA GSFC TESS Full Frame Image Light Curve Data Set
Authors: Brian P. Powell, Ethan Kruse, Benjamin T. Montet, Adina D. Feinstein, Hannah M. Lewis, Daniel Foreman-Mackey, Thomas Barclay, Elisa V. Quintana, Knicole D. Colón, Veselin B. Kostov, Patricia Boyd, Alan P. Smale, Susan E. Mullally, Joshua E. Schlieder, Jeremy D. Schnittman, Mark L. Carroll, Laura E. Carriere, Ellen M. Salmon, Savannah L. Strong, Nicko D. Acks, Bruce E. Pfaff, Lyn E. Gerner, Timothy M. Burch
Figure caption: (Top panel) Histogram of the TESS magnitudes of the stars in the data set. (Bottom panel) Number of light curves in the data set (or number of stars brighter than 16th magnitude) by TESS sector.
Paper: UV Slopes at All Redshifts Are Consistent with H = 1 Stochastic Star Formation Histories
Authors: Daniel D. Kelson, Louis E. Abramson
Figure caption: Green lines show the distribution of unattenuated UV-slopes as a function of redshift assuming galaxy star formation is a stochastic process that starts at z = 20 with H = 1. These models also assume [Fe/H] = −1.2 dex for the metallicity of the stars. The solid line shows the median β value with redshift; dashed lines follow the 10th and 90th percentiles; dotted lines show the 2nd and 98th. The black X marks β 0 = −2.23 from Meurer et al. (1999)—the unattenuated value derived from local starbursts. Data from Jiang et al. (2020, red), Bhatawdekar & Conselice (2021, black), Nanayakkara et al. (2022, purple), and Atek et al. (2022, blue) fall within the predicted range at all epochs. Any reddening would skew β to the positive direction. For comparison, the orange line traces the median β(z) for solar metallicity.
Paper: An Implementation of Stochastic Forces for the N-body Code REBOUND
Authors: Hanno Rein, Nick Choksi
Figure caption: The relative semimajor axis change of a planet undergoing stochastic migration with different diffusion parameters. The dashed lines are analytic predictions from Rein & Papaloizou (2009).
Paper: Massive Black Hole Binaries from the TNG50-3 Simulation. II. Using Dual AGNs to Predict the Rate of Black Hole Mergers
Authors: Kunyang Li, Tamara Bogdanović, David R. Ballantyne, Matteo Bonetti
Figure caption: The fraction of dAGNs observed at a given redshift whose MBHs coalesce before z = 0. The red circles show the fraction using all 7988 dAGNs in the model suite, while the green triangles, blue squares, and cyan stars show how the fraction varies with dAGN separation. The black “+” symbols indicate the fraction of all dAGNs that lead to a LISA S/N > 8.
Paper: Massive Black Hole Binaries from the TNG50-3 Simulation. II. Using Dual AGNs to Predict the Rate of Black Hole Mergers
Authors: Kunyang Li, Tamara Bogdanović, David R. Ballantyne, Matteo Bonetti
Figure caption: The fraction of dAGNs at a given redshift that coalesce by z = 0. Left: the coalescence fraction of dAGNs grouped by the bulge mass. Green triangles represent systems with ﹩\mathrm{log}({M}_{\mathrm{sb}}/{M}_{\odot })=9﹩, blue squares represent systems with ﹩\mathrm{log}({M}_{\mathrm{sb}}/{M}_{\odot })=10﹩, and cyan stars represent systems with ﹩\mathrm{log}({M}_{\mathrm{sb}}/\,{M}_{\odot })=11﹩. Right: the coalescence fraction of dAGNs grouped by ﹩\mathrm{log}\,q﹩. Green triangles represent systems with ﹩\mathrm{log}\,q=-2﹩, blue squares represent systems with ﹩\mathrm{log}\,q=-1﹩, and cyan stars represent systems with ﹩\mathrm{log}\,q=-0.3﹩. In both panels, red circles illustrate the coalescence fraction of all dAGNs, and the black plus signs represent the fraction of all dAGNs that coalesce by z = 0 and can be detected by LISA.
Paper: Massive Black Hole Binaries from the TNG50-3 Simulation. II. Using Dual AGNs to Predict the Rate of Black Hole Mergers
Authors: Kunyang Li, Tamara Bogdanović, David R. Ballantyne, Matteo Bonetti
Figure caption: The separation and luminosity distributions at z dAGN = 0.1, 1, and 2 of dAGNs whose MBHs coalesce by z = 0. The blue solid histograms show all dAGNs that eventually lead to coalescence by z = 0, and the red hatched histograms show the systems in which the MBH merger has a LISA S/N > 8.
Paper: Massive Black Hole Binaries from the TNG50-3 Simulation. II. Using Dual AGNs to Predict the Rate of Black Hole Mergers
Authors: Kunyang Li, Tamara Bogdanović, David R. Ballantyne, Matteo Bonetti
Figure caption: Same as Figure 3 but for the scenario when the effects of radiation feedback are taken into account. The red circles show the fraction using all dAGNs in the model suite, while the green triangles, blue squares, and cyan stars show how the fraction varies with dAGN separations of 0.1, 0.4, and 0.7 kpc. The black “+” symbols indicate the fraction of all dAGNs that lead to a LISA S/N > 8 in the presence of RF.
Paper: Massive Black Hole Binaries from the TNG50-3 Simulation. II. Using Dual AGNs to Predict the Rate of Black Hole Mergers
Authors: Kunyang Li, Tamara Bogdanović, David R. Ballantyne, Matteo Bonetti
Figure caption: The cumulative coalescence fractions of dAGNs with L bol > 1043 erg s−1 at z dAGN = 1, 2, and 3. The dotted–dashed green lines show the CCFs of dAGNs with separations of a = 0.7 kpc, while the dotted orange lines and solid red lines represent dAGNs with separations of 0.4 and 0.1 kpc, respectively.
Paper: Massive Black Hole Binaries from the TNG50-3 Simulation. II. Using Dual AGNs to Predict the Rate of Black Hole Mergers
Authors: Kunyang Li, Tamara Bogdanović, David R. Ballantyne, Matteo Bonetti
Figure caption: As Figure 2, but now showing the separation and luminosity distributions when RF effects are included.
Paper: Massive Black Hole Binaries from the TNG50-3 Simulation. II. Using Dual AGNs to Predict the Rate of Black Hole Mergers
Authors: Kunyang Li, Tamara Bogdanović, David R. Ballantyne, Matteo Bonetti
Figure caption: The cumulative coalescence fractions of dAGNs at z dAGN = 0.1, 1, and 2 with L bol > 1043 erg s−1 grouped by the stellar bulge mass (top row) and the MBH mass ratio (bottom row). The dashed lines show the CCFs of mergers that result in LISA events with S/N > 8.
Paper: Massive Black Hole Binaries from the TNG50-3 Simulation. II. Using Dual AGNs to Predict the Rate of Black Hole Mergers
Authors: Kunyang Li, Tamara Bogdanović, David R. Ballantyne, Matteo Bonetti
Figure caption: As Figure 1, but now showing the redshift distributions when including the effects of radiation feedback.
Paper: Magnetohydrodynamical Torsional Oscillations from Thermoresistive Instability in Hot Jupiters
Authors: Raphaël Hardy, Paul Charbonneau, Andrew Cumming
Figure caption: An example of bursting behavior driven by TRI. We show the time series of (a) velocity and magnetic field and (b) temperature and magnetic Reynolds number in the center of the domain. The model shown has parameters B 0 = 30 G, ﹩\dot{v}=0.004﹩ m s−2, Pr = 0.01, κ th = 0.001 m2 kg−1, and T eq = 1000 K. The right panels zoom in on the gray shaded area indicated in the left panels.
Paper: Magnetohydrodynamical Torsional Oscillations from Thermoresistive Instability in Hot Jupiters
Authors: Raphaël Hardy, Paul Charbonneau, Andrew Cumming
Figure caption: (a) Schematic representation of the assumed flow and magnetic field geometry. The aspect ratio between inner and outer cylinders has been greatly exaggerated for visual clarity. The magnetic field lines are represented in green and the acceleration term in red. (b) Schematic representation of the system during its evolution. The magnetic field lines are stretched by the azimuthal flow. The Lorentz force acting to straighten the field lines is shown in light blue. The local ohmic heating is represented by the value of ﹩{J}_{y}^{2}﹩, where J  y  is the induced current, as color-coded. Note that since the atmosphere is geometrically thin, we use Cartesian rather than spherical coordinates in our calculations, as described in Section 2.
Paper: Magnetohydrodynamical Torsional Oscillations from Thermoresistive Instability in Hot Jupiters
Authors: Raphaël Hardy, Paul Charbonneau, Andrew Cumming
Figure caption: Phase-space trajectory at the center of the domain showing one recurrent cycle of the solution shown in Figure 3. The thinner the line, the faster the system travels in phase space. The color sequence cycles ten times through the 134 day recurrence time, so that one run through a color cycle is 13.4 days (about the time required for the system to restabilize after burst onset).
Paper: Magnetohydrodynamical Torsional Oscillations from Thermoresistive Instability in Hot Jupiters
Authors: Raphaël Hardy, Paul Charbonneau, Andrew Cumming
Figure caption: Schematic depiction of our four-substep time-stepping scheme n → n + 1 (see text). Filled (open) black circles indicate variable values known (unknown) at the beginning of step n, and filled colored circles denote variable values being computed during the substeps, as color-coded. Red (substeps 1 and 3) indicates Crank–Nicolson and/or Euler explicit stepping using known midstep values of MD and source terms; green (substep 2) indicates a posteriori midpoint evaluation. Blue (substep 4) represents Taylor linear extrapolation from n + 1 to n + 3/2, followed by calculation of the MD at n + 3/2, needed for substep 1 of the subsequent time step.
Paper: Magnetohydrodynamical Torsional Oscillations from Thermoresistive Instability in Hot Jupiters
Authors: Raphaël Hardy, Paul Charbonneau, Andrew Cumming
Figure caption: Evolution of the T–P profile for the same solution as shown in Figures 3 and 4. The colors represent the phase of the 134 day recurrent cycle. The dotted line shows the initial temperature profile.
Paper: Magnetohydrodynamical Torsional Oscillations from Thermoresistive Instability in Hot Jupiters
Authors: Raphaël Hardy, Paul Charbonneau, Andrew Cumming
Figure caption: Time series of the midpoint of three simulations with different treatments of the MD. We show (a) the velocity and (b) the temperature. The parameters of the simulation are the same as in Figure 3.
Paper: Magnetohydrodynamical Torsional Oscillations from Thermoresistive Instability in Hot Jupiters
Authors: Raphaël Hardy, Paul Charbonneau, Andrew Cumming
Figure caption: Spatiotemporal evolution of (a) the velocity, (b) the magnetic field, (c) temperature, and (d) MD profiles in P–t diagrams for the same solution as shown in Figures 3 and 4. The system evolution in this figure is focused on the Alfvénic oscillations and the following cooling.
Paper: Wide-bandwidth Observations of PSR J0941–39 and PSR J1107–5907
Authors: S. N. Sun, N. Wang, W. M. Yan, S. Q. Wang, J. T. Xie
Figure caption: Polarization profiles for the pulsar state and RRAT state for (a) PSR J0941–39 and (b) PSR J1107–5907. The black, red, and blue lines are for the total, linear, and circular polarizations, respectively. The red and gray dots in the upper panels are for the PAs of the average profile and single pulses, respectively. The green lines are for the RVM fitting results.
Paper: Wide-bandwidth Observations of PSR J0941–39 and PSR J1107–5907
Authors: S. N. Sun, N. Wang, W. M. Yan, S. Q. Wang, J. T. Xie
Figure caption: Normalized cumulative distributions of fluence for pulsar state pulses (green solid histogram) and RRAT state (red solid histogram) for (a) PSR J0941–39 and (b) PSR J1107–5907. The fluences are normalized by the mean on-pulse fluence 〈F〉. The dotted and dashed lines are for the fitting results; the vertical black dashed line represents 4〈F〉.
Paper: Wide-bandwidth Observations of PSR J0941–39 and PSR J1107–5907
Authors: S. N. Sun, N. Wang, W. M. Yan, S. Q. Wang, J. T. Xie
Figure caption: Flux density as a function of the frequency of the pulsar (black points with solid line) and RRAT (red points with solid line) states for (a) PSR J0941–39 and (b) PSR J1107–5907. The solid lines are for the power-law fitting results of different states of each pulsar.
Paper: Wide-bandwidth Observations of PSR J0941–39 and PSR J1107–5907
Authors: S. N. Sun, N. Wang, W. M. Yan, S. Q. Wang, J. T. Xie
Figure caption: Polarization profiles for the brightest 20 single pulses in RRAT states for (a) PSR J0941–39 and (b) PSR J1107–5907. The labels are the same as in Figure 2.
Paper: Wide-bandwidth Observations of PSR J0941–39 and PSR J1107–5907
Authors: S. N. Sun, N. Wang, W. M. Yan, S. Q. Wang, J. T. Xie
Figure caption: Summary of fractional linear (left), circular (middle), and absolute circular (right) polarizations versus frequency for PSR J0941–39 (black lines) and PSR J1107–5907 (red lines). The solid and dashed lines are for the pulsar and RRAT states, respectively.
Paper: Wide-bandwidth Observations of PSR J0941–39 and PSR J1107–5907
Authors: S. N. Sun, N. Wang, W. M. Yan, S. Q. Wang, J. T. Xie
Figure caption: Posterior distributions of the five parameters in RVM fitting that result from the MCMC process for PSR J0941–39. The dashed vertical lines indicate the median and the 16th and 84th percentiles of the distribution.
Paper: Wide-bandwidth Observations of PSR J0941–39 and PSR J1107–5907
Authors: S. N. Sun, N. Wang, W. M. Yan, S. Q. Wang, J. T. Xie
Figure caption: The polarization profiles of eight subbands with a bandwidth of 416 MHz for the pulsar and RRAT states for (a) PSR J0941–39 and (b) PSR J1107–5907. The labels are the same as in Figure 2.
Paper: Partial Eruption of Solar Filaments. I. Configuration and Formation of Double-decker Filaments
Authors: Yijun Hou, Chuan Li, Ting Li, Jiangtao Su, Ye Qiu, Shuhong Yang, Liheng Yang, Leping Li, Yilin Guo, Zhengyong Hou, Qiao Song, Xianyong Bai, Guiping Zhou, Mingde Ding, Weiqun Gan, Yuanyong Deng
Figure caption: Schematic diagram depicting the formation of the double-decker configuration consisting of two MFRs with opposite magnetic twist. The green and pink twisted curves in (a) represent the initial magnetic topologies of the two MFRs: the lower MFR with a direction of northeast to southwest and positive magnetic twist and the upper MFR with a direction of northwest to southeast and negative magnetic twist. The red curves in (b) delineate emerging dipolar magnetic fields with a direction of west–east between the northern footpoints of the two MFRs. The star symbol marks the site of magnetic reconnection between the emerging dipolar magnetic fields and the northwestern leg of the upper MFR, eventually producing the double-decker configurations consisting of MFR1 and MFR2 with similar footpoints but opposite magnetic twist (see the twisted curves in (c)).
Paper: Partial Eruption of Solar Filaments. I. Configuration and Formation of Double-decker Filaments
Authors: Yijun Hou, Chuan Li, Ting Li, Jiangtao Su, Ye Qiu, Shuhong Yang, Liheng Yang, Leping Li, Yilin Guo, Zhengyong Hou, Qiao Song, Xianyong Bai, Guiping Zhou, Mingde Ding, Weiqun Gan, Yuanyong Deng
Figure caption: Temporal evolution of magnetic and emission structures during the formation of the double-decker filament. (a1)–(a4) AIA 304 Å image and NLFFF extrapolation results at 09:36 UT exhibiting the filament system and its 3D magnetic topology at the early stage of formation. The green and pink field lines represent the initial magnetic topology of the lower MFR1 and upper MFR2, respectively. (b1)–(b4) Similar to (a1)–(a4), but for the time point of 13:24 UT at the late stage of formation.
Paper: An Optically Thin View of the Solar Chromosphere from Observations of the O I 1355 Å Spectral Line
Authors: Mats Carlsson, Bart De Pontieu
Figure caption: PDF of the O I 1355 Å line width as a function of the cosine of the viewing angle (μ) for the AR 12290 data sets (top panel) and the QS data sets (bottom panel). To facilitate comparison, a quadratic least-squares fit to the QS width as a function of μ is shown in both panels as a dashed line. The color scale is linear and profiles with a central intensity below 10 DN/pixel are not included.