adsabs/AstroCLIMB huggingface dataset:
Paper: PG 1004+130: Hybrid Morphology Source or a Restarted FRII? A uGMRT Polarimetric Investigation
Authors: Salmoli Ghosh, P. Kharb, J. Baghel, S. Silpa
Figure caption: The uGMRT 694 MHz polarization image (RM-corrected) of PG 1004+130 with contour levels at (−2.83, 2.83, 8.00, 22.63, 64.00, 181.02, 512.00) × 109 μJy beam−1. The positive and negative contours are shown with solid and dashed lines, respectively. The red ticks represent the RM-corrected EVPAs, and 10″ of the extent of these red vectors corresponds to an I  P  value of 6.25 mJy beam−1. The bottom right inset displays the RM-corrected inferred B-field structure for the SL at 694 MHz with the same contours and vector sizes as in the main image. The top left inset shows the VLA 6 GHz B-field structure of the inner jets and the core (Baghel et al. 2023). The ellipse in the bottom left corner of the figure shows the synthesized beam for the image with a size of 4.″86 × 3.″23 and a position angle of 41.°4.
Paper: Solar Magnetic Polarity Effect on Neutron Monitor Count Rates: Comparing Latitude Surveys and Antarctic Stations
Authors: K. Poopakun, W. Nuntiyakul, S. Khamphakdee, A. Seripienlert, D. Ruffolo, P. Evenson, P. Jiang, P. Chuanraksasat, K. Munakata, M. L. Duldig, J. E. Humble, J. Madsen, B. Soonthornthum, S. Komonjinda
Figure caption: The count rate recorded by a polar NM indicates the Galactic cosmic-ray flux above ∼1 GeV nucleon−1 as it undergoes “solar modulation” related to solar activity. As the raw or 13 month smoothed monthly sunspot number, which is an indicator of solar activity, increases (shown in the top panel; source: WDC-SILSO Royal Observatory of Belgium, Brussels), the pressure-corrected monthly count rate recorded by the Thule NM decreases (bottom panel; source: Bartol Research Institute, University of Delaware, USA). The solar magnetic polarity reversal can be observed as the polarity shifts between positive (represented by A > 0) and negative (represented by A < 0) values. This work presents latitude survey observations for the periods 1994–2007 and 2019–2020, as indicated by horizontal bars between the two panels.
Paper: PG 1004+130: Hybrid Morphology Source or a Restarted FRII? A uGMRT Polarimetric Investigation
Authors: Salmoli Ghosh, P. Kharb, J. Baghel, S. Silpa
Figure caption: The uGMRT 694 MHz total intensity image of PG 1004+130, showing different radio features as listed in the image. The contour levels are at (20, 40, 80, 113.14, 160, 226.27, 320, 452.55) × 120 μJy beam−1. The inset shows a zoomed-in version of the jet–core–counterjet structure. The surface brightness in color ranges from 0 to 60 mJy beam−1.
Paper: PG 1004+130: Hybrid Morphology Source or a Restarted FRII? A uGMRT Polarimetric Investigation
Authors: Salmoli Ghosh, P. Kharb, J. Baghel, S. Silpa
Figure caption: The RM image of PG 1004+130 using uGMRT 694 MHz and VLA 6 GHz (split into two subbands) data. The RM values are shown in color, with the color scale extending from −300 to 200 rad m−2. The RM values are only obtained for the SJ and NH here. The contour levels are at (−4, −2, 4, 8, 16, 32, 64, 128, 256, 512) × 120 μJy beam−1.
Paper: PG 1004+130: Hybrid Morphology Source or a Restarted FRII? A uGMRT Polarimetric Investigation
Authors: Salmoli Ghosh, P. Kharb, J. Baghel, S. Silpa
Figure caption: Left: 0.694–1.5 GHz spectral index image of PG 1004+130 in color with 1.5 GHz contour levels at 120 × (−4, 4, 8, 16, 32, 64, 128, 256) μJy beam−1. The synthesized beam is 5″ × 5″ at a position angle of 0°. Right: 1.5 − 6 GHz spectral index image of PG 1004+130 in color with 6 GHz contour levels at 120 × (−1, 2, 4, 8, 16, 32, 64, 128) μJy beam−1. The synthesized beam is 1.″57 × 1.″43 at a position angle of −25.°84.
Paper: Solar Magnetic Polarity Effect on Neutron Monitor Count Rates: Comparing Latitude Surveys and Antarctic Stations
Authors: K. Poopakun, W. Nuntiyakul, S. Khamphakdee, A. Seripienlert, D. Ruffolo, P. Evenson, P. Jiang, P. Chuanraksasat, K. Munakata, M. L. Duldig, J. E. Humble, J. Madsen, B. Soonthornthum, S. Komonjinda
Figure caption: Hourly data for survey years 2018[(a)–(c)] and 2019 [(d)–(f)] as a function of time. Panels (a) and (d): Summed counting rates of the two leaded detector tubes. Gray points show the raw count rates, while blue points show pressure-corrected data. An attempt at normalizing the southbound data, shown in red, is discussed in the text. Panels (b) and (e): Barometric pressure. Panels (c) and (f): Geomagnetic cutoff rigidity—black for the apparent cutoff and blue for the vertical cutoff. Data shown in yellow were excluded from the analysis because they show evidence of environmental disturbance while the ship was in or near a port.
Paper: Solar Magnetic Polarity Effect on Neutron Monitor Count Rates: Comparing Latitude Surveys and Antarctic Stations
Authors: K. Poopakun, W. Nuntiyakul, S. Khamphakdee, A. Seripienlert, D. Ruffolo, P. Evenson, P. Jiang, P. Chuanraksasat, K. Munakata, M. L. Duldig, J. E. Humble, J. Madsen, B. Soonthornthum, S. Komonjinda
Figure caption: Response functions for survey years 2018 and 2019. Panels (a) and (c) show the data and the Dorman function fits, determining the integral response functions. Panels (b) and (d) are the differential response functions calculated analytically from the Dorman functions. A filled symbol indicates the availability of data for multiple voyage segments. The vertical error bar signifies the standard error across these segments; in all cases, the error bar is smaller than the plotted symbol. An open symbol with no error bar indicates that data were available for only one segment.
Paper: Solar Magnetic Polarity Effect on Neutron Monitor Count Rates: Comparing Latitude Surveys and Antarctic Stations
Authors: K. Poopakun, W. Nuntiyakul, S. Khamphakdee, A. Seripienlert, D. Ruffolo, P. Evenson, P. Jiang, P. Chuanraksasat, K. Munakata, M. L. Duldig, J. E. Humble, J. Madsen, B. Soonthornthum, S. Komonjinda
Figure caption: Regression of the mobile NM count rate in different apparent cutoff rigidity bins against the count rate of the Mawson NM. To improve clarity, we plotted every third bin. Filled circles indicate positive (A > 0) solar magnetic polarity, while open circles indicate negative polarity. Lines are fit separately for positive and negative polarity. Triangles indicate times of uncertain polarity not included in the fits.
Paper: Solar Magnetic Polarity Effect on Neutron Monitor Count Rates: Comparing Latitude Surveys and Antarctic Stations
Authors: K. Poopakun, W. Nuntiyakul, S. Khamphakdee, A. Seripienlert, D. Ruffolo, P. Evenson, P. Jiang, P. Chuanraksasat, K. Munakata, M. L. Duldig, J. E. Humble, J. Madsen, B. Soonthornthum, S. Komonjinda
Figure caption: Differential response functions for survey year 2019 compared to earlier surveys performed near solar minima. Panel (a): The 1997 (red) and 2006 (blue) surveys, which had opposite solar magnetic polarity, show a crossover near 5 GV. Panel(b): The 1997 (red) and 2019 (black) surveys for T1 and T3, which had the same polarity, do not show a crossover. Panel (c): Results of the 2006 (blue) and 2019 (black) surveys, again with opposite polarity, show a crossover near 5 GV, similar to (a). The solid line represents the best-fit line, and the shaded area represents the possible range of fits (±2σ).
Paper: Solar Magnetic Polarity Effect on Neutron Monitor Count Rates: Comparing Latitude Surveys and Antarctic Stations
Authors: K. Poopakun, W. Nuntiyakul, S. Khamphakdee, A. Seripienlert, D. Ruffolo, P. Evenson, P. Jiang, P. Chuanraksasat, K. Munakata, M. L. Duldig, J. E. Humble, J. Madsen, B. Soonthornthum, S. Komonjinda
Figure caption: Panel (a): Pressure-corrected hourly count rate of the Mawson NM for all survey years, after adjustment for the configuration change in 2002. Panel (b): McMurdo and Jang Bogo hourly count rates for the same period. Panel (c) Ratio of the data in (b) to data in (a).
Paper: Solar Magnetic Polarity Effect on Neutron Monitor Count Rates: Comparing Latitude Surveys and Antarctic Stations
Authors: K. Poopakun, W. Nuntiyakul, S. Khamphakdee, A. Seripienlert, D. Ruffolo, P. Evenson, P. Jiang, P. Chuanraksasat, K. Munakata, M. L. Duldig, J. E. Humble, J. Madsen, B. Soonthornthum, S. Komonjinda
Figure caption: Distribution of the Tasvan (at zero cutoffs) to Mawson count rate ratio for annual latitude surveys in positive solar magnetic polarity.
Paper: Solar Magnetic Polarity Effect on Neutron Monitor Count Rates: Comparing Latitude Surveys and Antarctic Stations
Authors: K. Poopakun, W. Nuntiyakul, S. Khamphakdee, A. Seripienlert, D. Ruffolo, P. Evenson, P. Jiang, P. Chuanraksasat, K. Munakata, M. L. Duldig, J. E. Humble, J. Madsen, B. Soonthornthum, S. Komonjinda
Figure caption: Tracks of ship-borne NM latitude surveys conducted during survey years 1994–2006 (Nuntiyakul et al. 2014) and 2018–2019 (Khamphakdee et al. 2021; Yakum et al. 2022) are shown with a contour map of the vertical cutoff rigidity (GV) calculated for 2019 February 11 at 12:00 UT.
Paper: Solar Magnetic Polarity Effect on Neutron Monitor Count Rates: Comparing Latitude Surveys and Antarctic Stations
Authors: K. Poopakun, W. Nuntiyakul, S. Khamphakdee, A. Seripienlert, D. Ruffolo, P. Evenson, P. Jiang, P. Chuanraksasat, K. Munakata, M. L. Duldig, J. E. Humble, J. Madsen, B. Soonthornthum, S. Komonjinda
Figure caption: Regression coefficients (slopes) of mobile monitor vs. Mawson NM count rate plotted as a function of the geomagnetic cutoff rigidity (GV).
Paper: Black Hole Polarimetry I. A Signature of Electromagnetic Energy Extraction
Authors: Andrew Chael, Alexandru Lupsasca, George N. Wong, Eliot Quataert
Figure caption: Left: histograms of ∠β 2 covering different velocity prescriptions in axisymmetric, equatorial models of emission around M87*. In these models, the emission radius is fixed to r = 2 r + and the lab-frame magnetic field B  i  given by the BZ monopole solution. For each value of black hole spin, the histograms cover uniform priors in the velocity parameters ξ, β  r , β  ϕ  in the range [0, 1] for both prograde (a * > 0) and retrograde (a * < 0) orbits. The observer inclination θ o is 163° relative to the spin axis for a * > 0 and 17° for a * < 0. The stars on the x -axis indicate the values of ∠β 2 for the same fields B  i  assuming the self-consistent BZ drift-frame velocity. The range of ∠β 2 values consistent with EHT observations of M87* in 2017 (EHTC VII) is indicated with the blue band. Right: representative images of the equatorial BZ monopole model for ∣a *∣ = 0.5 with a prograde Keplerian velocity model, a retrograde Keplerian velocity model, and the outflowing drift-frame velocity from the complete BZ monopole solution, from left to right, respectively.
Paper: Black Hole Polarimetry I. A Signature of Electromagnetic Energy Extraction
Authors: Andrew Chael, Alexandru Lupsasca, George N. Wong, Eliot Quataert
Figure caption: Schematic diagram illustrating the connection between different simple equatorial axisymmetric magnetic field configurations around a black hole and the polarimetric observable ∠β 2. No relativistic or propagation effects (e.g., parallel transport, aberration, or Faraday rotation) are included. The ﹩+\hat{z}﹩ axis is into the page, and the local polarization direction is given by ﹩\hat{z}\times {\boldsymbol{B}}﹩. The range of values obtained by the EHT for M87* (−163° < ∠β 2 < −129°;  EHTC VIII) is consistent with a ratio B  ϕ /B  r  < 0 in the emission region. Assuming that the black hole spin is aligned with ﹩\hat{z}﹩, that the magnetic field is axisymmetric and degenerate, and that the magnetic field lines corotate with the black hole, this field structure produces an outward Poynting flux by Equation (8).
Paper: Characterizing the Atmospheric Dynamics of HD 209458b-like Hot Jupiters Using AI-driven Image Recognition/Categorization
Authors: F. Sainsbury-Martinez, P. Tremblin, M. Mancip, S. Donfack, E. Honore, M. Bourenane
Figure caption: A selection of maps showing the temporally averaged zonal, meridional, or vertical enthalpy transport at selected pressure levels for our exemplary hot (top) and cool (bottom) HD 209458b-like atmospheric models. Here, positive (red) fluxes represent eastward/polar/outward flows for the zonal/meridional/vertical enthalpy flux maps, respectively. Note: We include two maps for the zonal-enthalpy transport, at different pressure levels, in order to emphasize how the zonal advection changes with both height and orbital radius.
Paper: Characterizing the Atmospheric Dynamics of HD 209458b-like Hot Jupiters Using AI-driven Image Recognition/Categorization
Authors: F. Sainsbury-Martinez, P. Tremblin, M. Mancip, S. Donfack, E. Honore, M. Bourenane
Figure caption: Helmholtz decomposition of the radially and temporally averaged horizontal wind for both our hot (top) and cool (bottom) HD 209458b-like atmospheric models. To the left, we plot the divergent component (﹩{{\boldsymbol{u}}}_{\mathrm{div}}﹩) of the Helmholtz decomposition, in the middle, the rotational component ( u  rot), and on the right the eddy component (﹩{{\boldsymbol{u}}}_{\mathrm{eddy}}={{\boldsymbol{u}}}_{\mathrm{rot}}-\left\langle {{\boldsymbol{u}}}_{\mathrm{rot}}\right\rangle ﹩) of the rotational component of the wind. A video version of this plot is available in Figures 12 and 13.
Paper: Characterizing the Atmospheric Dynamics of HD 209458b-like Hot Jupiters Using AI-driven Image Recognition/Categorization
Authors: F. Sainsbury-Martinez, P. Tremblin, M. Mancip, S. Donfack, E. Honore, M. Bourenane
Figure caption: Flowchart showing the layers and blocks of a half resolution (initial image resolution is 180 × 360, half that produced by Matplotlib for print quality figures) image-recognition network designed to detect the six features of interest in the thermal structures of our HD 209458b-like atmospheric models. Note that in each box we provide the name of the layer, the output resolution of the layer, as well as the number of trainable parameters, when nonzero.
Paper: Characterizing the Atmospheric Dynamics of HD 209458b-like Hot Jupiters Using AI-driven Image Recognition/Categorization
Authors: F. Sainsbury-Martinez, P. Tremblin, M. Mancip, S. Donfack, E. Honore, M. Bourenane
Figure caption: Distribution of (thermal) training/validation data before (top) and after (bottom) applying an oversampling technique to the inversion data set so as to generate artificial training data. The total count of items in each training data set is shown in gray. Note that we do not include the amount of training data used for the jet detection for two reasons: (a) unlike all the other features that were trained on the thermal structure, the jet tag was trained in the horizontal wind, and (b) the jet detection model did not make it into our final analysis due to problems with detecting highly symmetric structures (Section 3.4.1).
Paper: High-angular-resolution Imaging of the V892 Tau Binary System: A New Circumprimary Disk Detection and Updated Orbital Constraints
Authors: Christina L. Vides, Steph Sallum, Josh Eisner, Andy Skemer, Ruth Murray-Clay
Figure caption: contrast curves for V892 Tau at ﹩L^{\prime} ﹩ band (left) and ﹩K^{\prime} ﹩ band (right) using NRM and PyWFS. We find that the PyWFS contrast is 0.5–1 mag better than the observations with NIRC2 NRM behind SHWFS. We use these contrast curves to place limits on undetected companions and find that we are sensitive to ≳20 M  J  planets at ﹩L^{\prime} ﹩ band and ≳50 M  J  planets at ﹩K^{\prime} ﹩ band (assuming an age of ∼1 Myr).
Paper: High-angular-resolution Imaging of the V892 Tau Binary System: A New Circumprimary Disk Detection and Updated Orbital Constraints
Authors: Christina L. Vides, Steph Sallum, Josh Eisner, Andy Skemer, Ruth Murray-Clay
Figure caption: Left: 50 random orbits sampled from the distribution using Orbitize!. The orange stars represent all astrometric measurements of V892 Tau to date. The color bar represents one orbital period (∼7 yr). Top right: the multiepoch separation of the stellar companion and predictions of future locations. Bottom right: same as top right but for position angle. We find that the orbit is consistent with the astrometry estimated by the SQUEEZE images as well.
Paper: Anisotropic Star Clusters around Recoiling Supermassive Black Holes
Authors: Tatsuya Akiba, Ann-Marie Madigan
Figure caption: Parameter study with stellar distributions of varying initial inclinations. Top two rows: the postkick distribution of the z-component of the angular momentum (normalized by the circular angular momentum at a given radius) as a function of semimajor axis, with the color bar showing the y-component of the eccentricity vector for six different simulation runs. Rows correspond to inclination Rayleigh distributed with σ  i  = 30° (top) and isotropically distributed orbits (second from top). Columns correspond to circular (left), e = 0.99 (center), and eccentricity profile N(e) = 2e de (right) with a Bahcall–Wolf cusp density profile (ρ ∼ a −1.75; Bahcall & Wolf 1976). The first two columns use the same number density as before, which translates to a volume density ρ ∼ a −2. Second from bottom: the y-component of the mean eccentricity vector separated into prograde and retrograde orbits (about the z-axis) as a function of semimajor axis corresponding to the isotropic simulations in the panels above. Bottom: the mean first component of the tilt vector, 〈t 1〉, binned by semimajor axis where the plane of reference is the plane perpendicular to the kick (y–z) and the reference direction is +y. In this rotated coordinated system, t 1 still measures roll over the major axis but now with respect to the new plane of reference (y–z). For the bottom two rows, the shaded noise floor shows the maximum expected deviation from 0 (at the 3σ level) for an isotropic distribution. All of these simulations develop postkick anisotropies. The isotropic simulations form a torus-like structure of eccentric orbits that preferentially align in the plane perpendicular to the recoil kick.
Paper: Anisotropic Star Clusters around Recoiling Supermassive Black Holes
Authors: Tatsuya Akiba, Ann-Marie Madigan
Figure caption: Spherically isotropic distribution with an N(e) = 2e de eccentricity profile and a Bahcall–Wolf cusp density profile. The line-of-sight velocities in the frame comoving with the recoiling black hole in the x–y plane (top) and y–z plane (bottom) at t = 0 (left), t = 0.25 Myr (center), and t = 0.5 Myr (right). In each orientation, the color bar is adjusted such that approaching velocities are blue and receding velocities are red. The recoil kick direction is marked and labeled as v kick in each row. The length scale and time units assume a black hole mass of M • = 4 × 106 M ⊙ and a kick of v kick = 100 km s−1. In the x–y plane, there appears a cluster of stars with high line-of-sight velocities right behind the recoiling black hole. In the y–z plane, the edges become more blueshifted over time.
Paper: Anisotropic Star Clusters around Recoiling Supermassive Black Holes
Authors: Tatsuya Akiba, Ann-Marie Madigan
Figure caption: Spherically isotropic distribution with an N(e) = 2e de eccentricity profile and a Bahcall–Wolf cusp density profile. The postkick surface density distribution of bound stars in the x–y plane (top) and y–z plane (bottom) at t = 0 (left), t = 0.1 Myr (center), and t = 0.2 Myr (right). The “o” marker shows the recoiling black hole, and the density contours are computed in the frame comoving with the black hole. In each orientation, the recoil kick direction is marked and labeled as v kick. The length scale and time units assume a black hole mass of M • = 4 × 106 M ⊙ and a kick of v kick = 100 km s−1. The x–y plane density contours reveal the fan shape behind the recoiling black hole found in Merritt et al. (2009).
Paper: Anisotropic Star Clusters around Recoiling Supermassive Black Holes
Authors: Tatsuya Akiba, Ann-Marie Madigan
Figure caption: Spherically isotropic distribution with an N(e) = 2e de eccentricity profile and a Bahcall–Wolf cusp density profile. The postkick distribution of stars in the x–y plane at t = 0 (top left), t = 0.15 Myr (top right), and t = 0.75 Myr (bottom). Bound stars are separated into prograde (blue triangles) and retrograde (orange “+” markers) about the z-axis. The unbound stars are marked with green dots. The “x” marker shows the center of the galaxy and the “o” marker shows the recoiling black hole. The recoil kick direction is marked by the arrow labeled v kick. All positions are computed in the galactic center frame of reference. The length scale and time units assume a black hole mass of M • = 4 × 106 M ⊙ and a kick of v kick = 100 km s−1. Even for an isotropic distribution, the prograde and retrograde stars seem to have a clear division at large radii.
Paper: Anisotropic Star Clusters around Recoiling Supermassive Black Holes
Authors: Tatsuya Akiba, Ann-Marie Madigan
Figure caption: Initially circular orbits in a spherically isotropic distribution, with the recoil kick along the x-axis. A two-dimensional projection of the postkick eccentricity vectors in spherical coordinates where θ is the polar angle and ϕ is the azimuthal angle. With respect to the z-axis, prograde stars are marked with blue triangles, and retrograde stars are marked with orange “+” markers. Eccentricity vectors preferentially lie in the plane perpendicular to the recoil kick (y–z), and this torus-like structure has a clear division when separated into prograde and retrograde stars about a certain axis within that plane (z-axis). Prograde stars have preferentially positive e  y  and retrograde stars have preferentially negative e  y .
Paper: Anisotropic Star Clusters around Recoiling Supermassive Black Holes
Authors: Tatsuya Akiba, Ann-Marie Madigan
Figure caption: Spherically isotropic distribution with an N(e) = 2e de eccentricity profile and a Bahcall–Wolf cusp density profile. A histogram of the postkick mean anomaly (left), ﹩{ \mathcal M }﹩, and argument of periapsis (right), ω. The mean anomalies are clustered at 0 and the ω values are clustered at π, even for an initially isotropic distribution.
Paper: A Simple Method for Predicting N H Variability in Active Galactic Nuclei
Authors: Isaiah S. Cox, Núria Torres-Albà, Stefano Marchesi, Xiurui Zhao, Marco Ajello, Andrealuna Pizzetti, Ross Silver
Figure caption: The HR1 and HR2 values along with the associated 68% errors for simulated spectra with 1000 counts in the 2–10 keV energy range. The colors represent different N H values starting at N H = 1023 cm−2 and ending at N H = 1.1 × 1024 cm−2 in increments of N H = 5 × 1022 cm−2. The 10 colors shown cycle through in the same order. There are 100 spectra simulated for each N H value. The HRs change predictably with N H along the trend lines, so there is no confusion. The left panel shows the case for an inclination angle θ inc = 45°, which is the typical inclination angle expected for a random distribution of orientations. The right panel shows the edge-on case with θ inc = 87°.
Paper: A Simple Method for Predicting N H Variability in Active Galactic Nuclei
Authors: Isaiah S. Cox, Núria Torres-Albà, Stefano Marchesi, Xiurui Zhao, Marco Ajello, Andrealuna Pizzetti, Ross Silver
Figure caption: The FPR as a function of the N H for three different threshold ﹩{\chi }_{{\rm{c}}}^{2}﹩ values. The left panel shows inclination angle θ inc = 45°. The right panel shows inclination angle θ inc = 87°. The blue line uses a threshold ﹩{\chi }_{{\rm{c}}}^{2}﹩ of 2.706, corresponding to 90% confidence. The FPR is ≲20% for all levels of obscuration in both cases. For the higher threshold ﹩{\chi }_{{\rm{c}}}^{2}﹩ values, the FPR drops essentially to zero.