adsabs/AstroCLIMB huggingface dataset:
Paper: An ALMA Molecular Inventory of Warm Herbig Ae Disks. II. Abundant Complex Organics and Volatile Sulphur in the IRS 48 Disk
Authors: Alice S. Booth, Milou Temmink, Ewine F. van Dishoeck, Lucy Evans, John D. Ilee, Mihkel Kama, Luke Keyte, Charles J. Law, Margot Leemker, Nienke van der Marel, Hideko Nomura, Shota Notsu, Karin Öberg, Catherine Walsh
Figure caption: Matched filter responses for the IRS 48 and HD 100546 (taken from Booth et al. 2024) disks showing the full frequency coverage of the observations and highlighting the main molecules detected in each disk. Note that the HD 100546 response has been inverted, and the lines reaching the top and bottom of the y-axis have responses >50σ. The molecule labels at the top and bottom of the plot indicate from which disk the line is more strongly detected, and the vertical gray lines show the location of particular molecular transitions in more crowded regions of the spectrum. Both matched filter responses were generated using Keplerian models with an outer radius of 150 au for IRS 48 and 300 au for HD 100546. A fully annotated version of the IRS 48 response is shown in Figure 7.
Paper: An ALMA Molecular Inventory of Warm Herbig Ae Disks. II. Abundant Complex Organics and Volatile Sulphur in the IRS 48 Disk
Authors: Alice S. Booth, Milou Temmink, Ewine F. van Dishoeck, Lucy Evans, John D. Ilee, Mihkel Kama, Luke Keyte, Charles J. Law, Margot Leemker, Nienke van der Marel, Hideko Nomura, Shota Notsu, Karin Öberg, Catherine Walsh
Figure caption: Azimuthal line emission profiles for the IRS 48 disk generated from the maps presented in Figure 2. The dashed lines show the millimeter dust emission normalized to the peak of the line emission in each panel.
Paper: An ALMA Molecular Inventory of Warm Herbig Ae Disks. II. Abundant Complex Organics and Volatile Sulphur in the IRS 48 Disk
Authors: Alice S. Booth, Milou Temmink, Ewine F. van Dishoeck, Lucy Evans, John D. Ilee, Mihkel Kama, Luke Keyte, Charles J. Law, Margot Leemker, Nienke van der Marel, Hideko Nomura, Shota Notsu, Karin Öberg, Catherine Walsh
Figure caption: Top: disk-integrated fluxes for the molecules detected in the IRS 48 (purple) and HD 100546 (orange) disks. Bottom: disk-integrated fluxes relative to the C17O J = 3 − 2 line flux for each disk. Vertical lines and numbers show the relative differences in the different line ratios between each disk where this value is >10×. Triangles pointing down are 3σ upper limits, and triangles pointing up are lower limits. For most of the lines, the ±1σ error bars are smaller than the plot markers.
Paper: An ALMA Molecular Inventory of Warm Herbig Ae Disks. II. Abundant Complex Organics and Volatile Sulphur in the IRS 48 Disk
Authors: Alice S. Booth, Milou Temmink, Ewine F. van Dishoeck, Lucy Evans, John D. Ilee, Mihkel Kama, Luke Keyte, Charles J. Law, Margot Leemker, Nienke van der Marel, Hideko Nomura, Shota Notsu, Karin Öberg, Catherine Walsh
Figure caption: Integrated intensity maps of the 0.9 mm dust continuum emission and molecular line emission from the IRS 48 disk. The continuum map is shown on a color log scale to highlight the weak millimeter emission in the north of the disk. The beam is shown in the left-hand corner of each panel.
Paper: An ALMA Molecular Inventory of Warm Herbig Ae Disks. II. Abundant Complex Organics and Volatile Sulphur in the IRS 48 Disk
Authors: Alice S. Booth, Milou Temmink, Ewine F. van Dishoeck, Lucy Evans, John D. Ilee, Mihkel Kama, Luke Keyte, Charles J. Law, Margot Leemker, Nienke van der Marel, Hideko Nomura, Shota Notsu, Karin Öberg, Catherine Walsh
Figure caption: Polar deprojection of the IRS 48 integrated intensity maps that highlight the different emission morphologies compared to the dust. The dashed contour traces the 500σ level of the dust continuum emission. The units of the color bar are mJy beam−1 km s−1 for the molecular lines and mJy beam−1 for the continuum. The arrow highlights the direction of the disk rotation.
Paper: An ALMA Molecular Inventory of Warm Herbig Ae Disks. II. Abundant Complex Organics and Volatile Sulphur in the IRS 48 Disk
Authors: Alice S. Booth, Milou Temmink, Ewine F. van Dishoeck, Lucy Evans, John D. Ilee, Mihkel Kama, Luke Keyte, Charles J. Law, Margot Leemker, Nienke van der Marel, Hideko Nomura, Shota Notsu, Karin Öberg, Catherine Walsh
Figure caption: IRS 48 matched filter response using a 150 au in radius Keplerian model. Detected molecules/transitions above the 4σ level are labeled. New disk molecules are noted in purple, and notable nondetections are shown in gray.
Paper: An ALMA Molecular Inventory of Warm Herbig Ae Disks. II. Abundant Complex Organics and Volatile Sulphur in the IRS 48 Disk
Authors: Alice S. Booth, Milou Temmink, Ewine F. van Dishoeck, Lucy Evans, John D. Ilee, Mihkel Kama, Luke Keyte, Charles J. Law, Margot Leemker, Nienke van der Marel, Hideko Nomura, Shota Notsu, Karin Öberg, Catherine Walsh
Figure caption: Azimuthal column density profiles for the IRS 48 disk determined at a range of assumed excitation temperatures.
Paper: A Formally Motivated Retrieval Framework Applied to the High-resolution Transmission Spectrum of HD 189733 b
Authors: Doriann Blain, Alejandro Sánchez-López, Paul Mollière
Figure caption: In-transit cross-correlation matrix of the prepared data with our base model in Earth’s rest frame and for the order selection of Alonso-Floriano et al. (2019). The horizontal axis shows the different Doppler shifts applied to the model, and the vertical axis shows the exposures at different planet orbital phases. The white line represents the expected exoplanet velocities with respect to Earth during the observations, assuming the maximum significance K  P  of the CCF analyses (166 km s−1) and the observed −5.2 km s−1 blueshift. The red line shows the expected planet velocities with respect to Earth considering the expected planet K  p  (∼153 km s−1) and no additional sources of dynamics in the atmosphere.
Paper: A Formally Motivated Retrieval Framework Applied to the High-resolution Transmission Spectrum of HD 189733 b
Authors: Doriann Blain, Alejandro Sánchez-López, Paul Mollière
Figure caption: Results of the cross-correlation analysis for the order selection of Alonso-Floriano et al. (2019) using our base model. (a) Slice through the maximum significance CCF (166 km s−1) showing the detected CCF peak. (b) Cross-correlation map (expressed as S/N) of potential signals for H2O with respect to the exoplanet rest-frame velocity (horizontal axis) and K  p  (vertical axis). The horizontal dashed line marks the expected K  p  of the planet (≈153 km s−1). The vertical dashed line marks the rest-frame velocity of HD 189733 b when no additional sources of dynamics are considered (i.e., 0 km s−1).
Paper: A Formally Motivated Retrieval Framework Applied to the High-resolution Transmission Spectrum of HD 189733 b
Authors: Doriann Blain, Alejandro Sánchez-López, Paul Mollière
Figure caption: Posterior probability distributions of our simulations. Blue: pRT 1D simulation using Polyfit. Orange: pRT-Orange 3D simulation using Polyfit. The solid red lines correspond to the model input values for the 1D model. The dashed vertical blue lines represent the 0.16, 0.50, and 0.84 quantiles (i.e., median and 1σ error bar) of the distributions for the 1D simulation. On top of each column is indicated the median and the 1σ error bar of the retrieved parameters for the 1D simulation. The contours in the 2D histograms correspond to the 1σ, 2σ, and 3σ contours.
Paper: A Formally Motivated Retrieval Framework Applied to the High-resolution Transmission Spectrum of HD 189733 b
Authors: Doriann Blain, Alejandro Sánchez-López, Paul Mollière
Figure caption: Comparison between our different pRT models. Black: 1D model described in Section 3.1. Purple: 3D pRT-Orange model without rotation and winds. The 3D spectrum is different from the 1D spectrum because the former has 3D geometry with varying temperature profiles and uses equilibrium chemistry. Orange: 3D pRT-Orange model including rotation and winds. While we observe some shifts in the lines when only including rotation, the GCM’s strongly superrotating equatorial jet separates these into two small lines left and right from the central line position, where the blueshifted one is slightly stronger, as it corresponds to the hotter morning terminator. A dominating central peak remains in the middle, corresponding to the higher latitudes, which are above the equatorial jet and therefore dominated by the planet’s rotation.
Paper: A Formally Motivated Retrieval Framework Applied to the High-resolution Transmission Spectrum of HD 189733 b
Authors: Doriann Blain, Alejandro Sánchez-López, Paul Mollière
Figure caption: Illustration of the preparing pipeline effect on the order 46 of the studied data. First row: prepared model. The model is the same as in step 8 of Figure 3. While deformed, the spectral lines are clearly visible. The transit effect is also still visible. Second row: prepared noiseless simulated data. The simulated data used are the same as in step 9 of Figure 4. Third row: same as the second row, but with added noise. The lines are no longer visible to the naked eye. Bottom row: prepared CARMENES data. The white vertical stripes are masked telluric or stellar lines.
Paper: A Formally Motivated Retrieval Framework Applied to the High-resolution Transmission Spectrum of HD 189733 b
Authors: Doriann Blain, Alejandro Sánchez-López, Paul Mollière
Figure caption: Probability density distribution of the decimal logarithm of the absolute value of the BPM of different setups with our order selection. Black: BPM without pipeline ( R    F   = 1). Orange: BPM when applying the pipeline only to the data. Blue: standard BPM (Equation (29)). The vertical lines represent the 0.16, 0.50, and 0.84 quantiles of the distributions.
Paper: A Formally Motivated Retrieval Framework Applied to the High-resolution Transmission Spectrum of HD 189733 b
Authors: Doriann Blain, Alejandro Sánchez-López, Paul Mollière
Figure caption: Temperatures of the 3D model used (Drummond et al. 2018) at a pressure of 104 Pa, corresponding roughly to the pressure of the maximum average contribution for this CARMENES data set. The dotted lines corresponds to the leading (or morning) terminator and to the trailing (or evening) terminator. In the pRT-Orange model used, the longitude-dependent temperatures are set, at all latitudes, to the corresponding equatorial (latitude = 0°) temperatures of this model.
Paper: A Formally Motivated Retrieval Framework Applied to the High-resolution Transmission Spectrum of HD 189733 b
Authors: Doriann Blain, Alejandro Sánchez-López, Paul Mollière
Figure caption: Posterior probability distributions for P-01, using 100 live points. The dashed vertical blue lines represent the 0.16, 0.50, and 0.84 quantiles (i.e., median and 1σ error bar) of the distributions obtained with Polyfit. Indicated on top of each column are the median and the 1σ error bar of the retrieved parameters using Polyfit. The contours in the 2D histograms correspond to 1σ, 2σ, and 3σ.
Paper: A Formally Motivated Retrieval Framework Applied to the High-resolution Transmission Spectrum of HD 189733 b
Authors: Doriann Blain, Alejandro Sánchez-López, Paul Mollière
Figure caption: Illustration of the preparing effect on noiseless simulated data corresponding to order 46. Only the spectrum corresponding to orbital phase −0.0073 is shown. The spectrum used is the same as in step 9 of Figure 4. The spectra are given in arbitrary units.
Paper: Identifying Exoplanet Candidates Using WaveCeptionNet
Authors: Huiping Liao, Guangyue Ren, Xinghao Chen, Yuxiang Li, Guangwei Li
Figure caption: Architecture of our CNN model. Network inputs are passed through two repeated blocks of Inception. Convolutional layers are denoted Conv-kernel size-number of feature maps, max pooling layers are denoted MAXPOOL-window length-stride length, spatial dropout layers are denoted spatial dropout probability, and the fully connected layers are denoted FC-number of units. The output of the final, softmax layer is the predicted probability of the class for each light curve.
Paper: A Formally Motivated Retrieval Framework Applied to the High-resolution Transmission Spectrum of HD 189733 b
Authors: Doriann Blain, Alejandro Sánchez-López, Paul Mollière
Figure caption: Posterior probability distributions for a selection of Polyfit setups. The dashed vertical lines represent the 0.16, 0.50, and 0.84 quantiles (i.e., median and 1σ error bar) of the distributions obtained. Indicated below each panel are the median and the 1σ error bar of the retrieved parameters using the setup. The units are the same as in Figure 12.
Paper: Identifying Exoplanet Candidates Using WaveCeptionNet
Authors: Huiping Liao, Guangyue Ren, Xinghao Chen, Yuxiang Li, Guangwei Li
Figure caption: Wavelet representation normalization and interpolation. The classes, in order from top to bottom, are KP, EB, V, and IS. The left column is normalized and interpolated CA6. The right column is normalized and interpolated CD6. The orange curves represent the interpolation of the original blue curve.
Paper: Identifying Exoplanet Candidates Using WaveCeptionNet
Authors: Huiping Liao, Guangyue Ren, Xinghao Chen, Yuxiang Li, Guangwei Li
Figure caption: General flowchart of the wavelet representation preprocessing. The orange scatterplots represent a resampling of the original orange series. Finally, each light curve is transformed into a representation of dimensions (500, 2).
Paper: Identifying Exoplanet Candidates Using WaveCeptionNet
Authors: Huiping Liao, Guangyue Ren, Xinghao Chen, Yuxiang Li, Guangwei Li
Figure caption: Wavelet packet decomposition tree with three levels. Each decomposition results in a set of coefficients. If this pattern is repeated until the sixth level, it yields AAAAAA6 and DAAAAA6, typically referred to as low-frequency approximation (CA6) and high-frequency detail (CD6).
Paper: Identifying Exoplanet Candidates Using WaveCeptionNet
Authors: Huiping Liao, Guangyue Ren, Xinghao Chen, Yuxiang Li, Guangwei Li
Figure caption: Wavelet transform preprocessing. The classes, in order from top to bottom, are KP, EB, V, and IS. The left column is normalized flux. The middle column is a CA6 representation of original light curve. The right column is a CD6 representation of original light curve.
Paper: Identifying Exoplanet Candidates Using WaveCeptionNet
Authors: Huiping Liao, Guangyue Ren, Xinghao Chen, Yuxiang Li, Guangwei Li
Figure caption: The PR curve has recall on the x-axis and precision on the y-axis for the test set, showing the recall and precision at varying thresholds. TCEs above the threshold are classified as the corresponding class. Average precision is the weighted mean of precision at each threshold.
Paper: Identifying Exoplanet Candidates Using WaveCeptionNet
Authors: Huiping Liao, Guangyue Ren, Xinghao Chen, Yuxiang Li, Guangwei Li
Figure caption: Confusion matrix from the models predictions on the test set, where the vertical axis represents the actual category and the horizontal axis represents the predicted category.
Paper: Identifying Exoplanet Candidates Using WaveCeptionNet
Authors: Huiping Liao, Guangyue Ren, Xinghao Chen, Yuxiang Li, Guangwei Li
Figure caption: In the left-to-right sequence, the columns show the influence of S/N, orbital period, and transit duration on TPR. Both training (yellow) and test (purple) sets contain only PC on the test set.
Paper: Identifying Exoplanet Candidates Using WaveCeptionNet
Authors: Huiping Liao, Guangyue Ren, Xinghao Chen, Yuxiang Li, Guangwei Li
Figure caption: In the left-to-right sequence, the columns show the influence of stellar radius, planet radius, and transit depth on TPR. Both training (yellow) and test (purple) sets contain only PC on the test set.
Paper: Identifying Exoplanet Candidates Using WaveCeptionNet
Authors: Huiping Liao, Guangyue Ren, Xinghao Chen, Yuxiang Li, Guangwei Li
Figure caption: After model classification, the t-SNE embedding results from the final layer activations on the test set show a significant improvement in distinguishing between light curves.
Paper: Identifying Exoplanet Candidates Using WaveCeptionNet
Authors: Huiping Liao, Guangyue Ren, Xinghao Chen, Yuxiang Li, Guangwei Li
Figure caption: The t-SNE embedding results from CA6 and CD6 of the input data on the test set. PC (yellow) is close to EB (red), and V (green) is close to IS (purple).
Paper: Methods for the Detection of Stellar Rotation Periods in Individual TESS Sectors and Results from the Prime Mission
Authors: Isabel L. Colman, Ruth Angus, Trevor David, Jason Curtis, Soichiro Hattori, Yuxi (Lucy) Lu
Figure caption: Periods measured in single-sector light curves plotted against their effective temperatures. Periods that passed neither classifier are shown on the left, and those that passed both (i.e., detections) are shown on the right. The color scale indicates the amplitude associated with each detection. Note that 11,907 points are not plotted, representing 11,107 targets which do not have a value of T eff listed in either the TIC or Gaia DR3. This amounts to 2.8% of the sample. Histograms at either side show the distribution of periods, and across the top we show the T eff distribution, which is reassuringly uniform for detections and nondetections.
Paper: Methods for the Detection of Stellar Rotation Periods in Individual TESS Sectors and Results from the Prime Mission
Authors: Isabel L. Colman, Ruth Angus, Trevor David, Jason Curtis, Soichiro Hattori, Yuxi (Lucy) Lu
Figure caption: Comparison between this work (LS periods in dark blue and adjusted periods in light blue), Oelkers et al. (2018, burgundy), Santos et al. (2021, teal), Claytor et al. (2023, purple), Kounkel et al. (2022, pink), and Holcomb et al. (2022, yellow). The consolidated catalog (C24), containing detected rotation periods, is available as data behind the figure in the online journal.(The data used to create this figure are available.)
Paper: Methods for the Detection of Stellar Rotation Periods in Individual TESS Sectors and Results from the Prime Mission
Authors: Isabel L. Colman, Ruth Angus, Trevor David, Jason Curtis, Soichiro Hattori, Yuxi (Lucy) Lu
Figure caption: TESS rotation periods from our consolidated catalog compared with Oelkers et al. (2018, left), Holcomb et al. (2022, center), and Kounkel et al. (2022, right), with residuals shown in the bottom plots. Axes are truncated to exclude a small number of outliers, and points are color-coded by the number of distinct sectors used to calculate each median period.
Paper: Methods for the Detection of Stellar Rotation Periods in Individual TESS Sectors and Results from the Prime Mission
Authors: Isabel L. Colman, Ruth Angus, Trevor David, Jason Curtis, Soichiro Hattori, Yuxi (Lucy) Lu
Figure caption: Low-amplitude sinusoids of 1 and 5 days injected into the TESS single-sector light curve for TIC 137555668 (sector 14). The bottom panels show the LS periodogram, two-term LS periodogram, and ACF of the light curve. Peaks A, B, and C are marked by vertical highlights of decreasing width. Note in particular that, in a marginal case such as this, the LS periodogram still accurately detects the predominant signal of 1 day.
Paper: Methods for the Detection of Stellar Rotation Periods in Individual TESS Sectors and Results from the Prime Mission
Authors: Isabel L. Colman, Ruth Angus, Trevor David, Jason Curtis, Soichiro Hattori, Yuxi (Lucy) Lu
Figure caption: TESS rotation periods from our consolidated catalog compared with Holcomb et al. (2022) before (left) and after (right) adjustment for potential half-periods in C24. Detections are flagged as potential half-periods (dark points) if for at least one sector per target the two-term LS and ACF periods are both twice the LS period, within 10% tolerance.
Paper: Methods for the Detection of Stellar Rotation Periods in Individual TESS Sectors and Results from the Prime Mission
Authors: Isabel L. Colman, Ruth Angus, Trevor David, Jason Curtis, Soichiro Hattori, Yuxi (Lucy) Lu
Figure caption: Top row: ground truths for the validation data set for Classifier #1 (left), #2 (center), and both combined (right). Bottom row: the results of applying Classifiers #1 (left) and #2 (center) to the validation data set, and targets that pass both classifiers (right). Periods that pass classification are shown in green, larger points.
Paper: Methods for the Detection of Stellar Rotation Periods in Individual TESS Sectors and Results from the Prime Mission
Authors: Isabel L. Colman, Ruth Angus, Trevor David, Jason Curtis, Soichiro Hattori, Yuxi (Lucy) Lu
Figure caption: Corner plot showing the interactions between the five most important features in Classifier #2, including density histograms for each feature. Measurements that pass the classifier, i.e., accurate periods, are shown in teal, and periods deemed inaccurate are shown in black.
Paper: Methods for the Detection of Stellar Rotation Periods in Individual TESS Sectors and Results from the Prime Mission
Authors: Isabel L. Colman, Ruth Angus, Trevor David, Jason Curtis, Soichiro Hattori, Yuxi (Lucy) Lu
Figure caption: Corner plot showing the interactions between the five most important features in Classifier #1, including density histograms for each feature. Measurements that passed the classifier, i.e., detections of rotation, are shown in teal, and nondetections are shown in black.
Paper: Methods for the Detection of Stellar Rotation Periods in Individual TESS Sectors and Results from the Prime Mission
Authors: Isabel L. Colman, Ruth Angus, Trevor David, Jason Curtis, Soichiro Hattori, Yuxi (Lucy) Lu
Figure caption: A selection of long (>12 days) periods which passed both classifiers, and were clear enough to visually confirm.
Paper: The Epoch of Giant Planet Migration Planet Search Program. II. A Young Hot Jupiter Candidate around the AB Dor Member HS Psc 
Authors: Quang H. Tran, Brendan P. Bowler, William D. Cochran, Samuel Halverson, Suvrath Mahadevan, Joe P. Ninan, Paul Robertson, Guđmundur Stefánsson, Ryan C. Terrien
Figure caption: Top: RV curve of HS Psc b phase folded to the best-fit orbital period from Model 3. The blue and orange points denote the two different observing seasons, HPF1 and HPF2, respectively, and the best-fit RV model is shown as the solid black line. The fit residuals are plotted in the lower panels. The colored error bars are nominal RV errors and the gray error bars include the systematic jitter terms. 1σ and 3σ confidence intervals are plotted as gray shaded regions. The right panel displays the same best-fit orbit with the phased RV points representing median values in bins of ≈0.1 and ≈0.2 of the phase for the HPF1 and HPF2 RVs, respectively. The bottom panels display the joint posterior distributions of T 0,b , P  b , K  b , and e  b  from the Model 3 fit of HS Psc b. The diagonal panels show the marginalized distribution for each parameter. The upper right panels show the marginalized distributions for the M5/2 kernel parameters.
Paper: The Epoch of Giant Planet Migration Planet Search Program. II. A Young Hot Jupiter Candidate around the AB Dor Member HS Psc 
Authors: Quang H. Tran, Brendan P. Bowler, William D. Cochran, Samuel Halverson, Suvrath Mahadevan, Joe P. Ninan, Paul Robertson, Guđmundur Stefánsson, Ryan C. Terrien
Figure caption: TESS Sector 17 (top) and 57 (bottom) light curves of HS Psc. The best-fit mean GP model and 1σ variance are displayed as solid blue lines and shaded regions, respectively. The posterior distributions and MAP values (dashed vertical line) for the QP GP P rot hyperparameter for TESS Sectors 17 and 57 are shown in the right panels. The GP model separately recovers rotation periods of P rot,17 = 1.086 ± 0.003 days and P rot,57 = 1.086 ± 0.004 days for Sectors 17 and 57, respectively.