adsabs/AstroCLIMB huggingface dataset:
Paper: Very Large Array Radio Study of a Sample of Nearby X-Ray and Optically Bright Early-type Galaxies
Authors: Romana Grossová, Norbert Werner, Francesco Massaro, Kiran Lakhchaura, Tomáš Plšek, Krisztina Gabányi, Kamlesh Rajpurohit, Rebecca E. A. Canning, Paul Nulsen, Ewan O'Sullivan, Steven W. Allen, Andrew Fabian
Figure caption: The X-ray Chandra-smoothed (with a 2″ Gaussian kernel) images overlaid by 1.5 GHz VLA A, AB/B, and C/D configuration contours in the red, cyan and white, respectively. In all cases, the contours are created at 5  ×  σ rms and increase by the power of 2 up to the peak intensity. The center of the galaxy is represented by a black “+” sign. The Rms noise and peak intensity values are given in Table 1.
Paper: Very Large Array Radio Study of a Sample of Nearby X-Ray and Optically Bright Early-type Galaxies
Authors: Romana Grossová, Norbert Werner, Francesco Massaro, Kiran Lakhchaura, Tomáš Plšek, Krisztina Gabányi, Kamlesh Rajpurohit, Rebecca E. A. Canning, Paul Nulsen, Ewan O'Sullivan, Steven W. Allen, Andrew Fabian
Figure caption: The X-ray Chandra-smoothed (with a 2″ Gaussian kernel) images overlaid by 1.5 GHz VLA A, AB/B, and C/D configuration contours in the red, cyan and white, respectively. In all cases, the contours are created at 5  ×  σ rms and increase by the power of 2 up to the peak intensity. The center of the galaxy is represented by a black “+” sign. The Rms noise and peak intensity values can be found in Table 1.
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: Example of a simulated LSST type Ibc supernova light curve from PLAsTiCC, showing how we preprocess light curves to remove season gaps. The original and processed light curves are shown in the top and bottom panels, respectively. The processed light curve corresponds to the shaded region on the original light curve with the first observation translated to time zero. The observations in different passbands are shown in different colors.
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: SN Ibc light curve, where the points show the observations, along with their error bars, and the lines and the shaded regions show the mean and standard deviation of the GP fit, respectively. The left panel shows the one-dimensional GP fit to each available passband, and the right panel shows the two-dimensional GP fit to all of the passbands (shown in different colors). The two-dimensional GP infers the light curve in passbands where there are no (or few) observations, unlike the one-dimensional GP.
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: Host-galaxy photometric redshift distribution per supernova class, where SNe Ia, SNe Ibc, and SNe II are shown, respectively, on the left, middle, and right panels. The distribution of the training, augmented training, and test sets are shown as fine solid, bold solid, and dashed lines, respectively. Although the training set distribution is not representative of the test set, the augmented training set (Section 4) is close to the desired test distribution.
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: The left panel shows an SN Ibc light curve where the points show the observations, along with their error bars, and the lines and the shaded regions show the mean and standard deviation of the GP fit, respectively. The right panel shows a synthetic event at a different redshift generated from the original event using the procedure described in Section 4. Note that, in this example, the original event was simulated in the higher-cadence DDF survey, and we generated the synthetic event in the WFD survey.
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: WFD test-set normalized confusion matrix for the classifier trained on the augmented training set and its log-loss performance. Each event is assigned to the class with the highest prediction.
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: DDF test-set normalized confusion matrix for the classifier trained with (left panel) the general WFD+DDF augmented training set and (right panel) with the DDF-only augmented training set. The results show the importance of using an augmented training set customized for the specific survey mode characteristics.
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: WFD test-set recall (left panel) and precision (middle panel) as a function of light-curve length per SNe class. The right panel shows the density of events as a function of light-curve length. Because of the low number of events in the tails of the distribution, we restrict our analysis to between 50 and 175 days (comprising 94% of the events). Recall and precision increase for longer light curves.
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: WFD test-set recall (left panel) and precision (middle panel) as a function of median inter-night gap per SNe class for events with light curves between 50 and 175 days long. In general, the recall and precision are higher for events whose median inter-night gap is <3.5 days (left side of the black line). The right panel shows the density of events as a function of median inter-night gap; ∼64% of SNe Ia, ∼63% of SNe Ibc, and ∼66% of SNe II from the test-set events have median inter-night gap <3.5 days and light-curve lengths between 50 and 175 days.
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: WFD test-set recall (left panels) and precision (middle panels) as a function of the number of gaps longer than 10 days (top row) and the length of the longest inter-night gap (bottom row), per SN class. We only included events with median inter-night gap <3.5 days and light curves between 50 and 175 days long. These results show that large gaps do not significantly impact the SNe classification for this subset. The right panel shows the density of events as a function of the number of large gaps (top row) and the length of the longest inter-night gap (bottom row). We note that the results in the tails of the distribution are dominated by small number effects.
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: WFD test-set recall (left panel) and precision (middle panel) as a function of the number of observation between 10 days before and 30 days after the peak per SNe class. We only included events with median inter-night gap <3.5 days and light curves between 50 and 175 days long. In general, the recall and precision increase with the number of observations near the peak, until they reach an approximately constant value for events with ≥9 observations. The right panel shows the density of events as a function of number of observations near peak. We note that, as with previous plots, the results in the tails of the distribution are dominated by small number effects.
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: Distribution of the GP errors resulting from extrapolating GP fits to u or y passbands. F true is the true flux of an observation, and F predicted and σ predicted are the flux and its uncertainty, respectively, predicted by a GP fit at the corresponding epoch and passband. An ideal error estimation results in a unit Gaussian (black line).
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: WFD test-set recall (top two rows) and precision (bottom two rows) as a function of light-curve length (left panels), median inter-night gap (middle panels), and number of gaps larger than 10 days (right panels), per SN class. In the first and third rows, we reproduce the results of this work previously shown in Figures 7, 8, and 9. In the second and fourth rows, we show the classification predictions obtained by Boone (2019).
Paper: Considerations for Optimizing the Photometric Classification of Supernovae from the Rubin Observatory
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Tarek Allam, Rahul Biswas
Figure caption: WFD test-set recall (top two rows) and precision (bottom two rows) as a function of the length of the longest inter-night gap (left panels) and the number of observations between 10 days before and 30 days after the peak length (right panels), per SN class. In the first and third rows, we reproduce the results of this work previously shown in Figures 9 and 10. In the second and fourth rows, we show the classification predictions obtained by Boone (2019).
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Redshift distribution for pixels in the Lyα forest from the quasar spectra available in DR16Q.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Mean flux and mean signal-to-noise ratio (S/N) for pixels in the Lyα forest. Top panel: the distribution for the complete sample (blue) and for the restricted sample with high DLA detection efficiency; quasar redshift z QSO > 2.2 and mean forest flux ﹩\overline{{f}_{\lambda }}\gt 2.0﹩ (in units of 10−19 W m−2 nm−1 = 10−17 erg s−1 cm−2 Å−1). Bottom panel: S/N as a function of ﹩\overline{{f}_{\lambda }}﹩ for three ranges of the mean forest redshift, as labeled. For clarity, the S/N is offset by (0,5,10) units.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Distributions of z DLA (left) and ﹩\mathrm{log}(N({H}_{I})/{\mathrm{cm}}^{-2})﹩ (right) for the 218,124 HCD systems placed in mocks (blue) and for the 132,226 DLAs reported by the CNN (red). The excess of detected DLAs at ﹩\mathrm{log}(N({H}_{I})/{\mathrm{cm}}^{-2})\approx 20﹩ is due to the poor purity at this ﹩\mathrm{log}N﹩, as seen in Figure 3.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Mean flux and mean S/N for mocks pixels in the Lyα forest for the complete sample (blue) and for the restricted sample with high DLA detection efficiency (red): quasar redshift z QSO > 2.2 and mean forest flux ﹩\overline{{f}_{\lambda }}\gt 2.0﹩.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Mean difference between detected and generated DLA redshifts versus the mean forest flux, ﹩\overline{{f}_{\lambda }}﹩.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Efficiency (left) and purity (right) versus redshift and column density using matching criterion Δz DLA < 0.02.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Same as Figure 6 for forests with ﹩\overline{{f}_{\lambda }}\gt 2\times {10}^{-19}\,{\rm{W}}\,{{\rm{m}}}^{-2}\,{\mathrm{nm}}^{-1}﹩.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Same as Figure 6 for forests with ﹩\overline{{f}_{\lambda }}\lt 2\times {10}^{-19}\,{\rm{W}}\,{{\rm{m}}}^{-2}\,{\mathrm{nm}}^{-1}﹩.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Same as Figure 6 for forests with confidence >0.9.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Confidence parameter distributions for the 132,226 absorbing systems found by the CNN: 69,380 false positives (red) and 62,846 true positives (blue). False positives are defined as HCD systems found by the CNN but that do not match the HCD system input. To match an input HCD system, it must be on the same sight line with Δz DLA < 0.02.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Difference in output and input values of N(H  I ) (in red for the CNN and blue for the fitter) vs. input for the 25,696 found DLAs in the Lyα forest, i.e., in the rest-frame range 1040 Å ≤ λ RF ≤1216 Å.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Distributions of the difference in ﹩\mathrm{log}(N({H}_{I})/{\mathrm{cm}}^{-2})﹩ between the CNN predictions and the mock inputs for DLA candidates with confidence >0.9 (red) and confidence ≤0.9 (blue). The distributions are shown for four ranges of ﹩\mathrm{log}(N({H}_{I})/{\mathrm{cm}}^{-2})﹩ (CNN value), as labeled.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Distribution of z DLA and ﹩\mathrm{log}(N({H}_{I})/{\mathrm{cm}}^{-2})﹩ of the 117,458 absorbers detected by the CNN in DR16Q for the 20,375 bright forests with ﹩\overline{{f}_{\lambda }}\gt 2\times {10}^{-19}\,{\rm{W}}\,{{\rm{m}}}^{-2}\,{\mathrm{nm}}^{-1}﹩ (red) and the remaining 97,083 faint forests with ﹩\overline{{f}_{\lambda }}\leqslant 2\times {10}^{-19}\,{\rm{W}}\,{{\rm{m}}}^{-2}\,{\mathrm{nm}}^{-1}﹩ (blue). The dashed lines show the same samples reduced to confident absorbers only with confidence ≥0.9.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Distribution of N(H  I ) for the 12,081 DLAs of N12 found and not found by the CNN in red and blue, respectively. The statistical sample consists of confident DLA candidates with high S/N (> 3 with DR9 measurements), which are used in N12 to measure the ﹩\mathrm{log}(N({H}_{I})/{\mathrm{cm}}^{-2})﹩ distribution and the cosmological mass density of neutral gas.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Distribution of N(H  I ) for the 25,160 confident DLAs (p DLA > 0.9) of H21 with BAL_PROB = 0 found and not found by the CNN in red and blue respectively.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Comparison of the 3070 N(H  I ) of the DR9 absorbers in the forest, i.e., in the rest-frame range 1040 Å ≤ λ RF ≤ 1216 Å, found in both N12 and this study, using either the CNN (red) or the fitter (blue) result.
Paper: The Completed Sloan Digital Sky Survey IV Extended Baryon Oscillation Spectroscopic Survey: The Damped Lyα Systems Catalog
Authors: Solène Chabanier, Thomas Etourneau, Jean-Marc Le Goff, James Rich, Julianna Stermer, Bela Abolfathi, Andreu Font-Ribera, Alma X. Gonzalez-Morales, Axel de la Macorra, Ignasi Pérez-Ràfols, Patrick Petitjean, Matthew M. Pieri, Corentin Ravoux, Graziano Rossi, Donald P. Schneider
Figure caption: Same as Figure 16 for H21. The sample contains 12,449 absorbers in the forest.
Paper: The Spectroscopic Binaries from the LAMOST Medium-resolution Survey. I. Searching for Double-lined Spectroscopic Binaries with a Convolutional Neural Network
Authors: Bo Zhang, Ying-Jie Jing, Fan Yang, Jun-Chen Wan, Xin Ji, Jian-Ning Fu, Chao Liu, Xiao-Bin Zhang, Feng Luo, Hao Tian, Yu-Tao Zhou, Jia-Xin Wang, Yan-Jun Guo, Weikai Zong, Jian-Ping Xiong, Jiao Li
Figure caption: The CMD of the LAMOST DR8 observed sources in solar neighborhood (ϖ > 3). G 0 is the absolute Gaia G magnitude, and ﹩{({G}_{\mathrm{BP}}-{G}_{\mathrm{RP}})}_{0}﹩ is the intrinsic color. Gray contours show the distribution of all observations in LAMOST DR8. while colored dots have high binary probabilities. The left/middle/right panel shows the 2246/1876/1069 spectra with ﹩{p}_{0}^{{\rm{\Lambda }}=16}\gt 0.5﹩ at blue/red/both arms. The superposed isochrones have ages ﹩\mathrm{log}\tau =8.1,8.9﹩, and 9.7. Approximate effective temperature is determined by interpolating the log τ = 8.1 isochrone.
Paper: The Spectroscopic Binaries from the LAMOST Medium-resolution Survey. I. Searching for Double-lined Spectroscopic Binaries with a Convolutional Neural Network
Authors: Bo Zhang, Ying-Jie Jing, Fan Yang, Jun-Chen Wan, Xin Ji, Jian-Ning Fu, Chao Liu, Xiao-Bin Zhang, Feng Luo, Hao Tian, Yu-Tao Zhou, Jia-Xin Wang, Yan-Jun Guo, Weikai Zong, Jian-Ping Xiong, Jiao Li
Figure caption: The CMD of the SB2 candidates selected via high binary probability (﹩{p}_{0}^{{\rm{\Lambda }}=16}\gt 0.5﹩) in both arms. The black dots represent the 116 eliminated objects, and cyan dots are the final SB2 candidates. Insets show the CCFs of 10 randomly picked stars from different regions in the CMD. Blue and red CCFs are for blue and red arms of the selected stars, respectively, in the −600 to 600 km s−1 interval. Note that the CCFs are corrected with their RVs to center the primary peaks. The contour shows the distribution of all LAMOST MRS DR8 observations.
Paper: The Spectroscopic Binaries from the LAMOST Medium-resolution Survey. I. Searching for Double-lined Spectroscopic Binaries with a Convolutional Neural Network
Authors: Bo Zhang, Ying-Jie Jing, Fan Yang, Jun-Chen Wan, Xin Ji, Jian-Ning Fu, Chao Liu, Xiao-Bin Zhang, Feng Luo, Hao Tian, Yu-Tao Zhou, Jia-Xin Wang, Yan-Jun Guo, Weikai Zong, Jian-Ping Xiong, Jiao Li
Figure caption:  The counts of observations for the 2198 SB2 candidates with at least one epoch detected high binary probability (﹩{p}_{0}^{{\rm{\Lambda }}=16}\gt 0.5﹩) at both arms. Blue shows the counts of observations with high binary probability, while black shows the counts of all observations for these objects. Bin width of N obs is 1.