adsabs/AstroCLIMB huggingface dataset:
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: AI multi-categorization map for the HD 209458b atmospheric model of Sainsbury-Martinez et al. (2019). Here we show the categories detected (with the opacity of each detection point representing the strength of the detection) at each pressure level (where an increase in pressure level corresponds to a decrease in actual pressure as we move to higher altitudes) against time (where t = 0 corresponds to solid-body, adiabatic, initialization, and each latter point corresponds to the center of the temporal mean). The categories in question correspond to the detection of a north–south asymmetric thermal structure in blue, a banded (i.e., horizontally homogenized) thermal structure in orange, a radiative-dominated thermal structure (driven by tidal locking) in green, a butterfly thermal structure (i.e., eastward equatorial advection flanked by slight, off-equator, westward advection) in red, and an equatorial (wind) jet in purple. Note that this model was run at a lower resolution than the other models considered here, which has slightly impacted the ability of the CNN to discriminate between different atmospheric features.
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: Longitudinally and temporally averaged zonal wind (left) and meridional circulation stream function (right) for both our hot (top) and cool (bottom) HD 209458b-like atmospheric models. In the zonal wind maps, positive quantities correspond to eastward flows, while in the meridional circulation profiles clockwise circulations are shown in red and anticlockwise in blue. Additionally, the meridional circulation stream function is plotted on a log scale.
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: Equilibrium temperature–pressure (left) and radiative timescale (right) profiles for the Newtonian cooling schemes used in our exemplary hot (top) and cool (bottom) HD 209458b-like atmospheric models. Note that in the above plots, the background solid lines correspond to the 1D ATMO models upon which the equilibrium profiles (dashed lines) are based/extrapolated.
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: Convergence tests for our multi-categorization CNN, i.e., thermal features CNN, showing the convergence of the loss function during both training (green) and validation (orange). The training is considered complete/optimized after 30 iterations since this is the point at which overfitting starts to occur, as represented by a regression in validation accuracy (i.e., an increase in loss).
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: An example CNN layer structure used for modern optical character recognition. Note the use of stacked, and hence nonlinear, convolution layers that are separated by dimensionality-reducing pooling layers, and that eventually feed into fully connected neural network layers that perform the final image classification. Reproduced from O’Shea & Nash (2015).
Paper: Global Deceleration and Inward Movements of X-Ray Knots and Rims of RCW 103
Authors: Hiromasa Suzuki, Takaaki Tanaka, Tsuyoshi Inoue, Hiroyuki Uchida, Takuto Narita
Figure caption: Radial profiles and derived χ 2–Δx (shift) plots extracted from Reg. 5 (a) and from Reg. 6 (b). In the radial profiles, negative directions correspond to outer regions. In the χ 2–Δx plots, positive values indicate outward movements.
Paper: Global Deceleration and Inward Movements of X-Ray Knots and Rims of RCW 103
Authors: Hiromasa Suzuki, Takaaki Tanaka, Tsuyoshi Inoue, Hiroyuki Uchida, Takuto Narita
Figure caption: Locations of the magnetar 1E 161348−5055 in 1999, 2010, and 2016. The central positions and radii of the ellipses indicate the estimated positions of the magnetar at different times and their statistical errors.
Paper: Global Deceleration and Inward Movements of X-Ray Knots and Rims of RCW 103
Authors: Hiromasa Suzuki, Takaaki Tanaka, Tsuyoshi Inoue, Hiroyuki Uchida, Takuto Narita
Figure caption: Exposure-corrected Chandra image of RCW 103 in the energy band 0.5–5.0 keV. The radial-profile extraction regions are indicated with the green boxes.
Paper: Global Deceleration and Inward Movements of X-Ray Knots and Rims of RCW 103
Authors: Hiromasa Suzuki, Takaaki Tanaka, Tsuyoshi Inoue, Hiroyuki Uchida, Takuto Narita
Figure caption: Proper motion velocities of our analysis regions. Positive velocities indicate outward movements. A distance of 3.1 kpc is assumed in calculation of the velocities.
Paper: Calibrating VLBI Polarization Data Using GPCAL. II. Time-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Derived off-axis D-terms for the BM462M data as a function of time. The filled circles and open squares represent the D-terms for RCP and LCP, respectively. The upper and lower plots in each panel display the real and imaginary parts of the results for each antenna. Different rows of results are presented for different pairs of adjacent sources in the sky (3C 273 and 3C 279 in the top row, 3C 454.3 and CTA 102 in the middle row, and 3C 345 and 1633+382 in the bottom row). In each figure, the averaged norm L 1 ≡ ∣D  i  − D  j ∣ between the neighboring scans (separated by less than 10 minutes) for the adjacent sources i and j is shown for each polarization. The Δd denotes the distance between adjacent sources in the celestial sphere. While we provide results for only three antennas as an illustration, the findings for other antennas were also qualitatively comparable.
Paper: Calibrating VLBI Polarization Data Using GPCAL. II. Time-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: The PDF of D Truth − D Recon for each source. The red solid lines represent Gaussian distributions fitted to the PDFs. In each panel, the standard deviation (σ) of the best-fit Gaussian distribution is indicated in percentage units. The average S/Ns of the parallel-hand (〈S/N〉par) and cross-hand (〈S/N〉cro) visibilities for each source are denoted in each panel.
Paper: Calibrating VLBI Polarization Data Using GPCAL. II. Time-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Linear polarization images of 3C 279 (top) and 3C 345 (bottom) from the BM462M data set. The hot color indicates the total intensity distribution, and the colored ticks indicate the electric vector position angles, with the color scales indicating Ricean debiased linearly polarized intensity. Presented in the left and right panels are images obtained before and after time-dependent leakage correction. There is a note in each panel indicating the linear polarization dynamic range, which is defined as the ratio of the peak linear polarization intensity to the linear polarization off-source rms noise. In the bottom right corner, the shape of the synthesized beam is shown.
Paper: Calibrating VLBI Polarization Data Using GPCAL. II. Time-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Comparison of the time-dependent, ground-truth D-term components (real and imaginary parts) assumed in the synthetic data sets, shown on the x-axis, with the reconstructed D-term components derived by GPCAL, shown on the y-axis, for each scan. Each station’s result is presented using distinct colors. For each source, a correlation is shown between the true and estimated D-terms in percentage units. Over all antennas, the L 1 ≡ ∣D Truth − D Recon∣ norm is averaged over the real and imaginary components of the D-terms for RCP and LCP.
Paper: Calibrating VLBI Polarization Data Using GPCAL. II. Time-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Amplitudes of the gain correction factors (top) and off-axis D-terms (bottom) for the VLBA Pie Town station for different pairs of adjacent sources in the BM462M data set as a function of time. The filled circles and open squares represent the results for RCP and LCP, respectively.
Paper: Calibrating VLBI Polarization Data Using GPCAL. II. Time-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Off-axis D-term amplitudes as a function of gain correction factors for the BM462M data set. The RCP and LCP are represented by filled circles and open squares, respectively. Different stations are represented by different colors.
Paper: Calibrating VLBI Polarization Data Using GPCAL. II. Time-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Same as Figure 3 but for the BP249H data. After UT 3, rain was reported at the VLBA LA station (middle panels), following which the off-axis D-term amplitudes increased substantially.
Paper: Calibrating VLBI Polarization Data Using GPCAL. II. Time-dependent Calibration
Authors: Jongho Park, Keiichi Asada, Do-Young Byun
Figure caption: Same as Figure 7 but for the BP249H data for 3C 273 (top) and M87 (bottom).
Paper: Are Quasi-periodic Pulsations Independent of Loop Oscillations in Solar Flare?
Authors: Fanpeng Shi, 帆鹏 史, Dong Li, 东 李, Zongjun Ning, 宗军 宁, Yangfan Guo, 杨帆 郭, Song Feng, 松 冯, Jun Xu, 俊 徐
Figure caption: Top panel: full-disk normalized light curves detected by NoRP 3.75 GHz (magenta), 9.40 GHz (cyan), Fermi 30–70 keV (black), and GOES 0.5–4 Å (red). Local normalized light curves in AIA 94 (green), 171 (brown), 211 (pink), 304 (sky blue), 335 (blue), 1600 (purple), and 1700 Å (gold), which were integrated over the whole region in Figure 1. The gray and yellow background represent the time interval of QPPs and loop oscillations, respectively. Middle panel: the corresponding rapidly varying components between 01:37 UT and 01:52 UT. Bottom panel: the Morlet wavelet spectrum of the rapid-varying component of Fermi 50–101 keV and its global power spectrum. The 99.7% significance level is also marked.
Paper: Are Quasi-periodic Pulsations Independent of Loop Oscillations in Solar Flare?
Authors: Fanpeng Shi, 帆鹏 史, Dong Li, 东 李, Zongjun Ning, 宗军 宁, Yangfan Guo, 杨帆 郭, Song Feng, 松 冯, Jun Xu, 俊 徐
Figure caption: (a) The NoRP 9.40 GHz PSD and its best fit for model M 0. The red dashed line represents the 95% confidence level (or 5% significance level). (b) The PSD and its best fit for model M 1. The positive ﹩{\rm{\Delta }}{\mathrm{BIC}}_{{M}_{0}-{M}_{1}}﹩ means that model M 1 is more suitable than model M 0. The central frequency of the Gaussian component is also given. (c) Test statistic T  R  distribution for preferred model M 1. The p = 0.65 indicates that the PSD can be well interpreted by model M 1. (d)–(f) Similar to above, the Fermi 50–101 keV PSD, best-fit, and test statistic results. (g)–(i) The GOES 0.5–4 Å PSD, best-fit, and test statistic results, but the ﹩{\rm{\Delta }}{\mathrm{BIC}}_{{M}_{0}-{M}_{1}}﹩ = –2.62 means that model M 0 is marginally preferred.
Paper: Are Quasi-periodic Pulsations Independent of Loop Oscillations in Solar Flare?
Authors: Fanpeng Shi, 帆鹏 史, Dong Li, 东 李, Zongjun Ning, 宗军 宁, Yangfan Guo, 杨帆 郭, Song Feng, 松 冯, Jun Xu, 俊 徐
Figure caption: (a1)–(b1)–(c1) Fe XXI 1354.08 Å line parameters from 01:36 UT to 02:30 UT. Low signal-to-noise ratio points are shown in white in the Dopplergram and black in other panels, and the vertical line at 02:15 UT is caused by the lack of observed data. (a2)–(b2)–(c2) The line parameters in the area bounded by two magenta lines.
Paper: Are Quasi-periodic Pulsations Independent of Loop Oscillations in Solar Flare?
Authors: Fanpeng Shi, 帆鹏 史, Dong Li, 东 李, Zongjun Ning, 宗军 宁, Yangfan Guo, 杨帆 郭, Song Feng, 松 冯, Jun Xu, 俊 徐
Figure caption: (a)–(f) Six samples of observed spectra and their Gaussian fitting results. The orange profile is the original spectrum at the Y-axis marked by two green lines. The magenta and cyan profiles represent the fitting of Fe XXI 1354.08 Å and C I 1354.29 Å in a linear background (black horizontal dashed line), respectively. Two vertical red lines show their reference rest wavelengths. The black profile is the sum of fitting components. The line parameters and uncertainties are also given.
Paper: Are Quasi-periodic Pulsations Independent of Loop Oscillations in Solar Flare?
Authors: Fanpeng Shi, 帆鹏 史, Dong Li, 东 李, Zongjun Ning, 宗军 宁, Yangfan Guo, 杨帆 郭, Song Feng, 松 冯, Jun Xu, 俊 徐
Figure caption: The intensity fluctuations at Fermi 50–101 keV vs. at NoRP 9.40 GHz (a), NoRP 3.75 GHz (b), and GOES 0.5–4 Å (c). Black and red represent the data in the corresponding time interval. The maximum correlation coefficient (CC) is also given. (d) The microwave spectra at 01:40 and 01:47 UT corresponding to the form of the gyrosynchrotron spectra.
Paper: Varstrometry for Off-nucleus and Dual Sub-kiloparsec Active Galactic Nuclei (VODKA): Very Long Baseline Array Searches for Dual or Off-nucleus Quasars and Small-scale Jets
Authors: Yu-Ching Chen, Xin Liu, Joseph Lazio, Peter Breiding, Sarah Burke-Spolaor, Hsiang-Chih Hwang, Yue Shen, Nadia L. Zakamska
Figure caption: Illustration of different physical origins that can cause VLBA-Gaia offsets. The scales of offsets shown here are usually < 0.″2, which is Gaia’s point-spread function (blue ellipse). The optical position from Gaia is an unresolved weighted center (blue diamond), while the radio emission (yellow hexagon) is resolved with VLBA’s mas angular resolution. (a) Dual quasar: the optical emission of two quasars is blended in Gaia resulting in a weighted optical center, while the radio emission is centered at individual quasar because of VLBA’s high angular resolution. (b) Dual quasar: if only one quasar is radio-bright, the binary quasar shows an optical-radio offset. (c) Off-nucleus quasar: the optical center is a weighted position of an off-nucleus quasar and a host galaxy, while the radio position is centered at the quasar’s position. (d) Radio jet from a single quasar: the optical center is centered at the quasar’s position, while the radio position is shifted toward the jet direction.
Paper: Varstrometry for Off-nucleus and Dual Sub-kiloparsec Active Galactic Nuclei (VODKA): Very Long Baseline Array Searches for Dual or Off-nucleus Quasars and Small-scale Jets
Authors: Yu-Ching Chen, Xin Liu, Joseph Lazio, Peter Breiding, Sarah Burke-Spolaor, Hsiang-Chih Hwang, Yue Shen, Nadia L. Zakamska
Figure caption: VLBA (C-band, X-band, and/or Ku-band) images of the eight (four in this figure and four in Figure 4) targets that exhibit significant offsets between VLBA and Gaia positions or/and have multiple radio components. The images are oriented with north up and east to the left. The Gaia DR2 positions are indicated by red crosses, with their lengths representing 1σ rms errors, and the red ellipses show the 3σ rms position error. The VLBA positions are marked by blue crosses, and the blue ellipses indicate the 3σ rms position error. The synthesized beam sizes are shown in the bottom-right corners of the images. The solid contours correspond to 5, 10, 20, 40, 80, 160, and 320 times the 1σ rms level. The typical 1σ rms noise level is approximately 0.1 mJy beam−1, but for bright sources, it can reach up to 1 mJy beam−1.
Paper: Varstrometry for Off-nucleus and Dual Sub-kiloparsec Active Galactic Nuclei (VODKA): Very Long Baseline Array Searches for Dual or Off-nucleus Quasars and Small-scale Jets
Authors: Yu-Ching Chen, Xin Liu, Joseph Lazio, Peter Breiding, Sarah Burke-Spolaor, Hsiang-Chih Hwang, Yue Shen, Nadia L. Zakamska
Figure caption: Sample selection and the target properties. We selected the targets based on their peak flux densities (>15 mJy) in FIRST and astrometric excess noise >3σ at a given Gaia magnitude. Left: FIRST flux density vs. redshift for the final analysis sample of 23 targets (marked in red) compared to all FIRST-detected sources in the parent quasar sample (marked in black), with a blue horizontal line indicating the 15 mJy threshold. Right: astrometric excess noise vs. Gaia magnitude for the final analysis sample of 23 targets (marked in red) compared to all radio-bright (>15 mJy) SDSS quasars (marked in black), with a blue curve indicating the >3σ threshold of astrometric excess noise at a given Gaia magnitude, based on all SDSS quasars.
Paper: Varstrometry for Off-nucleus and Dual Sub-kiloparsec Active Galactic Nuclei (VODKA): Very Long Baseline Array Searches for Dual or Off-nucleus Quasars and Small-scale Jets
Authors: Yu-Ching Chen, Xin Liu, Joseph Lazio, Peter Breiding, Sarah Burke-Spolaor, Hsiang-Chih Hwang, Yue Shen, Nadia L. Zakamska
Figure caption: Distribution of positional offsets between the Gaia DR3 optical position and the VLBA radio source positions for the 21 VLBA-detected targets. Targets with offsets greater than 3σ  are highlighted in blue. The error bars represent 1σ errors considering the fitting error, the phase calibrator’s position uncertainty, and the error associated with the phase-referencing technique, as described in Section 4.4. The axes of the insets are in units of milliarcseconds identical to those in the main plot.
Paper: Varstrometry for Off-nucleus and Dual Sub-kiloparsec Active Galactic Nuclei (VODKA): Very Long Baseline Array Searches for Dual or Off-nucleus Quasars and Small-scale Jets
Authors: Yu-Ching Chen, Xin Liu, Joseph Lazio, Peter Breiding, Sarah Burke-Spolaor, Hsiang-Chih Hwang, Yue Shen, Nadia L. Zakamska
Figure caption: VLBA (C-band, X-band, and/or Ku-band) images of the eight (four in Figure 3 and four in this figure) targets that exhibit significant offsets between VLBA and Gaia positions or/and have multiple radio components. Notations are the same as those in Figure 3.
Paper: Varstrometry for Off-nucleus and Dual Sub-kiloparsec Active Galactic Nuclei (VODKA): Very Long Baseline Array Searches for Dual or Off-nucleus Quasars and Small-scale Jets
Authors: Yu-Ching Chen, Xin Liu, Joseph Lazio, Peter Breiding, Sarah Burke-Spolaor, Hsiang-Chih Hwang, Yue Shen, Nadia L. Zakamska
Figure caption: Distribution of VLBA-Gaia offsets for the 21 targets that have a detection in our sample (in red) compared to those for single normal quasars (in gray) in Makarov et al. (2019). We apply the criteria of G > 18.5 and 0.5 < redshift < 3 to the quasars from the literature to ensure comparability with our sample. We also show the subset of the 21 targets that still pass varstrometry selection using Gaia DR3 (in dark red). Our sample shows a notable excess in large VLBA-Gaia offsets.
Paper: Varstrometry for Off-nucleus and Dual Sub-kiloparsec Active Galactic Nuclei (VODKA): Very Long Baseline Array Searches for Dual or Off-nucleus Quasars and Small-scale Jets
Authors: Yu-Ching Chen, Xin Liu, Joseph Lazio, Peter Breiding, Sarah Burke-Spolaor, Hsiang-Chih Hwang, Yue Shen, Nadia L. Zakamska
Figure caption: VLBA (C-band and/or X-band) continuum images of the 15 targets that either show consistent positions between VLBA and Gaia or are undetected. Other information is the same as that in Figure 3.
Paper: Varstrometry for Off-nucleus and Dual Sub-kiloparsec Active Galactic Nuclei (VODKA): Very Long Baseline Array Searches for Dual or Off-nucleus Quasars and Small-scale Jets
Authors: Yu-Ching Chen, Xin Liu, Joseph Lazio, Peter Breiding, Sarah Burke-Spolaor, Hsiang-Chih Hwang, Yue Shen, Nadia L. Zakamska
Figure caption: Radio spectra of the six targets for which we have detections at at least two frequencies.
Paper: Improving Coronal Hole Detections and Open Flux Estimates
Authors: Ronald M. Caplan, Emily I. Mason, Cooper Downs, Jon A. Linker
Figure caption: Model results. Left: CH area vs. open flux measurements for the equatorial CH indicated by the black arrow in Figure 4. Right: CH area vs. extrapolated interplanetary magnetic field at 1 au, for the full Sun. In each plot, the blue squares and black circles are the results of overlaying the CH detections on the surface ﹩{B}_{r}﹩ magnetogram for the full ensemble of reasonable CH detections using the MIDM and synoptic EUV maps, respectively. The yellow-filled circle and the cyan-filled square are the selected best visual CH detections within each ensemble. The triangles represent the open flux computed with the true open field contour at various effective heights (see Section 3.1). The green triangles use B  r  at the same height as the known open field contour, while the red triangles use (incorrectly) the surface B  r  at the non-surface open field contour height.
Paper: Improving Coronal Hole Detections and Open Flux Estimates
Authors: Ronald M. Caplan, Emily I. Mason, Cooper Downs, Jon A. Linker
Figure caption: Results of CH detection on the model’s synthetic EUV images. The left column shows the subjectively determined best visual CH boundaries made with ezseg for the synoptic method EUV full Sun map overlaid as the black boundary in each row, while the boundary on the right column uses the MIDM EUV map. The first row shows a composite 193 Å map for each of the respective methods; the second row shows a map of ﹩{B}_{r}^{\odot }﹩ in the model, masked with the respective CH detection contours; the third row shows the percentages of the total open flux in each discrete CH that was detected. The blue rectangles highlight differences in the obscuration of the polar CH between the two methods for all three sets of plots, while the red rectangles show differences in the vicinity of an active region. The black arrow in the middle row indicates the CH whose open flux is computed in Figure 6. The quantitative measurements of total open flux are shown in Figure 6.
Paper: Improving Coronal Hole Detections and Open Flux Estimates
Authors: Ronald M. Caplan, Emily I. Mason, Cooper Downs, Jon A. Linker
Figure caption: Figure analogous to Figure 4 but for AIA data, with a cyan box highlighting differences along the polar CH boundary and the red box indicating differences in the vicinity of an active region.
Paper: Improving Coronal Hole Detections and Open Flux Estimates
Authors: Ronald M. Caplan, Emily I. Mason, Cooper Downs, Jon A. Linker
Figure caption: Top to bottom: open field maps from the MHD model at ﹩r=1.00\,{R}_{\odot },1.01\,{R}_{\odot },﹩                    and ﹩1.02\,{R}_{\odot }﹩                   , respectively. These can be compared with the middle panels of Figure 4. The left column shows the ﹩{B}_{r}﹩ magnetogram; the right column shows the relative percentages of open flux.
Paper: Improving Coronal Hole Detections and Open Flux Estimates
Authors: Ronald M. Caplan, Emily I. Mason, Cooper Downs, Jon A. Linker
Figure caption: Observational open flux results. Left: CH area vs. open flux measurements for the equatorial CH which crosses the ϕ = π line. Right: CH area vs. extrapolated interplanetary magnetic field at 1 au, for the full Sun. The interplanetary flux inferred from observations for this time period was ≈1.71 nT (Linker et al. 2021).
Paper: Improving Coronal Hole Detections and Open Flux Estimates
Authors: Ronald M. Caplan, Emily I. Mason, Cooper Downs, Jon A. Linker
Figure caption: Processed CR 2101 photospheric radial magnetic field map used for the MAS MHD model.
Paper: Improving Coronal Hole Detections and Open Flux Estimates
Authors: Ronald M. Caplan, Emily I. Mason, Cooper Downs, Jon A. Linker
Figure caption: Pole-filled HMI ﹩{B}_{r}﹩ map used with AIA observational data for open flux calculations.