adsabs/AstroCLIMB huggingface dataset:
Paper: The Karl G. Jansky Very Large Array Local Group L-Band Survey (LGLBS)
Authors: Eric W. Koch, Adam K. Leroy, Erik W. Rosolowsky, Laura Chomiuk, Julianne J. Dalcanton, Nickolas M. Pingel, Sumit K. Sarbadhicary, Snežana Stanimirović, Fabian Walter, Haylee N. Archer, Alberto D. Bolatto, Michael P. Busch, Hongxing Chen, Ryan Chown, Harrisen Corbould, Serena A. Cronin, Jeremy Darling, Thomas Do, Jennifer Donovan Meyer, Cosima Eibensteiner, Deidre Hunter, Rémy Indebetouw, Preshanth Jagannathan, Amanda A. Kepley, Chang-Goo Kim, Shin-Jeong Kim, Timea O. Kovacs, Joshua Marvil, Eric J. Murphy, Claire E. Murray, Jürgen Ott, D.J. Pisano, Mary Putman, Daniel R. Rybarczyk, Julia Roman-Duval, Karin Sandstrom, Eva Schinnerer, Evan D. Skillman, Adam Smercina, Ioana Stelea, Jay Strader, Jiayi Sun, Devisree Tallapaneni, Elizabeth Tarantino, Vicente Villanueva, Daniel R. Weisz, Thomas G. Williams, Tony Wong
Figure caption: LGLBS H I column density sensitivity and physical resolution relative to comparable nearby galaxy and Local Group surveys. The LGLBS points show the range of sensitivity and resolution within the target velocity resolution, and the labels indicate the combination of VLA configurations combined to reach these targets. The dashed gray lines indicate constant 5σ H I mass sensitivity. LGLBS fills an important gap in the H I survey parameter space between the nearby galaxy population (e.g., EveryTHINGS, I. Chiang et al. 2025, in preparation; HALOGAS, G. Heald et al. 2011; LITTLE THINGS, D. A. Hunter et al. 2012; LVHIS, B. S. Koribalski et al. 2018; PHANGS-VLA, presented in J. Sun et al. 2022; THINGS, F. Walter et al. 2008; VIVA, A. Chung et al. 2009; VLA-ANGST, J. Ott et al. 2012; VLA-HERACLES, A. Schruba et al. 2011; MHONGOOSE, W. J. G. de Blok et al. 2024), and LMC and SMC (e.g., GASKAP-HI, N. M. Pingel et al. 2022), which are >10× nearer than any of the LGLBS targets. See also F. M. Maccagni & W. J. G. de Blok (2024).
Paper: The Karl G. Jansky Very Large Array Local Group L-Band Survey (LGLBS)
Authors: Eric W. Koch, Adam K. Leroy, Erik W. Rosolowsky, Laura Chomiuk, Julianne J. Dalcanton, Nickolas M. Pingel, Sumit K. Sarbadhicary, Snežana Stanimirović, Fabian Walter, Haylee N. Archer, Alberto D. Bolatto, Michael P. Busch, Hongxing Chen, Ryan Chown, Harrisen Corbould, Serena A. Cronin, Jeremy Darling, Thomas Do, Jennifer Donovan Meyer, Cosima Eibensteiner, Deidre Hunter, Rémy Indebetouw, Preshanth Jagannathan, Amanda A. Kepley, Chang-Goo Kim, Shin-Jeong Kim, Timea O. Kovacs, Joshua Marvil, Eric J. Murphy, Claire E. Murray, Jürgen Ott, D.J. Pisano, Mary Putman, Daniel R. Rybarczyk, Julia Roman-Duval, Karin Sandstrom, Eva Schinnerer, Evan D. Skillman, Adam Smercina, Ioana Stelea, Jay Strader, Jiayi Sun, Devisree Tallapaneni, Elizabeth Tarantino, Vicente Villanueva, Daniel R. Weisz, Thomas G. Williams, Tony Wong
Figure caption: VLA correlator setup used for LGLBS (VLA Project ID 20A-346). The black, gray, and blue regions represent individual spectral windows (SPWs) used in the LGLBS setup. The primary LGLBS data products are the H I and 4 OH lines (black regions), and the Stokes I L-band continuum. Four continuum SPWs are also observed in Baseband A (labeled SPW 0, 4, 8 11 here) to allow for calibration checks between the basebands. The tuning also includes full polarization for the continuum windows shown in blue (with requisite polarization calibration observations taken) and eight hydrogen radio recombination lines (RRLs, black regions). Commensal data for FRB detections was collected with REALFAST for all LGLBS observations (C. J. Law et al. 2018). The Stokes I continuum, H I, and OH line coverage are similar in all archival observations (Table 4) but may not exactly match the tuning used for the primary LGLBS observations. The RRL and polarization coverage vary somewhat across the archival data but are all part of all LGLBS observations.
Paper: The Karl G. Jansky Very Large Array Local Group L-Band Survey (LGLBS)
Authors: Eric W. Koch, Adam K. Leroy, Erik W. Rosolowsky, Laura Chomiuk, Julianne J. Dalcanton, Nickolas M. Pingel, Sumit K. Sarbadhicary, Snežana Stanimirović, Fabian Walter, Haylee N. Archer, Alberto D. Bolatto, Michael P. Busch, Hongxing Chen, Ryan Chown, Harrisen Corbould, Serena A. Cronin, Jeremy Darling, Thomas Do, Jennifer Donovan Meyer, Cosima Eibensteiner, Deidre Hunter, Rémy Indebetouw, Preshanth Jagannathan, Amanda A. Kepley, Chang-Goo Kim, Shin-Jeong Kim, Timea O. Kovacs, Joshua Marvil, Eric J. Murphy, Claire E. Murray, Jürgen Ott, D.J. Pisano, Mary Putman, Daniel R. Rybarczyk, Julia Roman-Duval, Karin Sandstrom, Eva Schinnerer, Evan D. Skillman, Adam Smercina, Ioana Stelea, Jay Strader, Jiayi Sun, Devisree Tallapaneni, Elizabeth Tarantino, Vicente Villanueva, Daniel R. Weisz, Thomas G. Williams, Tony Wong
Figure caption: Left panel: star formation rate vs. stellar mass of the LGLBS targets, the SMC, LMC, and Milky Way relative to the local galaxy population (d < 50 Mpc) from z0MGS (an archival project combining Wide-field Infrared Survey Explorer (WISE) and GALEX images of nearby galaxies that is complete to M⋆ > 109 M⊙; A. K. Leroy et al. 2019). Right panel: H I mass vs. distance for Local Group galaxies with H I detections from the sample compiled in M. E. Putman et al. (2021). The LGLBS H I masses are given in Table 1 from this work. Milky Way values adopted from T. C. Licquia & J. A. Newman (2015) and K. M. Ferrière (2001).
Paper: The Karl G. Jansky Very Large Array Local Group L-Band Survey (LGLBS)
Authors: Eric W. Koch, Adam K. Leroy, Erik W. Rosolowsky, Laura Chomiuk, Julianne J. Dalcanton, Nickolas M. Pingel, Sumit K. Sarbadhicary, Snežana Stanimirović, Fabian Walter, Haylee N. Archer, Alberto D. Bolatto, Michael P. Busch, Hongxing Chen, Ryan Chown, Harrisen Corbould, Serena A. Cronin, Jeremy Darling, Thomas Do, Jennifer Donovan Meyer, Cosima Eibensteiner, Deidre Hunter, Rémy Indebetouw, Preshanth Jagannathan, Amanda A. Kepley, Chang-Goo Kim, Shin-Jeong Kim, Timea O. Kovacs, Joshua Marvil, Eric J. Murphy, Claire E. Murray, Jürgen Ott, D.J. Pisano, Mary Putman, Daniel R. Rybarczyk, Julia Roman-Duval, Karin Sandstrom, Eva Schinnerer, Evan D. Skillman, Adam Smercina, Ioana Stelea, Jay Strader, Jiayi Sun, Devisree Tallapaneni, Elizabeth Tarantino, Vicente Villanueva, Daniel R. Weisz, Thomas G. Williams, Tony Wong
Figure caption: Median percent of flagged data per SPW, where the error bars reflect the 15th–85th percentile range of 337 LGLBS tracks. The continuous blue lines indicate flagging percentages for the continuum SPWs, and the orange diamonds are the line SPWs for H I  and the four OH lines (the OH1665/1667 are recorded together in the same SPW). The current LGLBS processing does not include the hydrogen RRLs included in the spectral setup.
Paper: The Karl G. Jansky Very Large Array Local Group L-Band Survey (LGLBS)
Authors: Eric W. Koch, Adam K. Leroy, Erik W. Rosolowsky, Laura Chomiuk, Julianne J. Dalcanton, Nickolas M. Pingel, Sumit K. Sarbadhicary, Snežana Stanimirović, Fabian Walter, Haylee N. Archer, Alberto D. Bolatto, Michael P. Busch, Hongxing Chen, Ryan Chown, Harrisen Corbould, Serena A. Cronin, Jeremy Darling, Thomas Do, Jennifer Donovan Meyer, Cosima Eibensteiner, Deidre Hunter, Rémy Indebetouw, Preshanth Jagannathan, Amanda A. Kepley, Chang-Goo Kim, Shin-Jeong Kim, Timea O. Kovacs, Joshua Marvil, Eric J. Murphy, Claire E. Murray, Jürgen Ott, D.J. Pisano, Mary Putman, Daniel R. Rybarczyk, Julia Roman-Duval, Karin Sandstrom, Eva Schinnerer, Evan D. Skillman, Adam Smercina, Ioana Stelea, Jay Strader, Jiayi Sun, Devisree Tallapaneni, Elizabeth Tarantino, Vicente Villanueva, Daniel R. Weisz, Thomas G. Williams, Tony Wong
Figure caption: Example of an interactive plot used to quality assure LGLBS visibility data. Calibrated visibilities for the gain calibrator J0102+5824 (used for NGC 6822 observations), with plots showing average amplitude and phase as a function of time, frequency, antenna, and uv distance. This plot shows the initial calibrated visibilities from the pipeline without additional manual flagging applied. We indicate several cases of additional RFI that were not automatically flagged, and an example of a set of poor amplitude/phase baselines arising from a single antenna in one scan. In bold text, we highlight features of the interactive plots that enable rapid identification of visibility errors, including the interactive key where data from individual SPWs can be toggled to select, hide, or zoom to a subset of the data.
Paper: The Karl G. Jansky Very Large Array Local Group L-Band Survey (LGLBS)
Authors: Eric W. Koch, Adam K. Leroy, Erik W. Rosolowsky, Laura Chomiuk, Julianne J. Dalcanton, Nickolas M. Pingel, Sumit K. Sarbadhicary, Snežana Stanimirović, Fabian Walter, Haylee N. Archer, Alberto D. Bolatto, Michael P. Busch, Hongxing Chen, Ryan Chown, Harrisen Corbould, Serena A. Cronin, Jeremy Darling, Thomas Do, Jennifer Donovan Meyer, Cosima Eibensteiner, Deidre Hunter, Rémy Indebetouw, Preshanth Jagannathan, Amanda A. Kepley, Chang-Goo Kim, Shin-Jeong Kim, Timea O. Kovacs, Joshua Marvil, Eric J. Murphy, Claire E. Murray, Jürgen Ott, D.J. Pisano, Mary Putman, Daniel R. Rybarczyk, Julia Roman-Duval, Karin Sandstrom, Eva Schinnerer, Evan D. Skillman, Adam Smercina, Ioana Stelea, Jay Strader, Jiayi Sun, Devisree Tallapaneni, Elizabeth Tarantino, Vicente Villanueva, Daniel R. Weisz, Thomas G. Williams, Tony Wong
Figure caption: A subset of quick-look imaging for a single M33 field shows examples used to quality assure LGLBS visibility data, which the LGLBS pipeline generates for every science field. We show four examples generated from single 64 MHz continuum SPWs with no deconvolution applied. The left column shows examples of poor data quality, due to either remaining RFI that requires flagging (top) or where strong RFI has been automatically flagged by the VLA pipeline (bottom). The right column are examples of SPWs with minimal strong RFI remaining, where the artifacts are consistent with the VLA’s point-spread function (PSF) shape.
Paper: The Karl G. Jansky Very Large Array Local Group L-Band Survey (LGLBS)
Authors: Eric W. Koch, Adam K. Leroy, Erik W. Rosolowsky, Laura Chomiuk, Julianne J. Dalcanton, Nickolas M. Pingel, Sumit K. Sarbadhicary, Snežana Stanimirović, Fabian Walter, Haylee N. Archer, Alberto D. Bolatto, Michael P. Busch, Hongxing Chen, Ryan Chown, Harrisen Corbould, Serena A. Cronin, Jeremy Darling, Thomas Do, Jennifer Donovan Meyer, Cosima Eibensteiner, Deidre Hunter, Rémy Indebetouw, Preshanth Jagannathan, Amanda A. Kepley, Chang-Goo Kim, Shin-Jeong Kim, Timea O. Kovacs, Joshua Marvil, Eric J. Murphy, Claire E. Murray, Jürgen Ott, D.J. Pisano, Mary Putman, Daniel R. Rybarczyk, Julia Roman-Duval, Karin Sandstrom, Eva Schinnerer, Evan D. Skillman, Adam Smercina, Ioana Stelea, Jay Strader, Jiayi Sun, Devisree Tallapaneni, Elizabeth Tarantino, Vicente Villanueva, Daniel R. Weisz, Thomas G. Williams, Tony Wong
Figure caption: Cumulative distribution functions (CDFs) of the percent of flagged data split by SPW over 337 LGLBS tracks. Left panel: flagging percentage CDFs for the sixteen 64 MHz continuum SPWs covering 1–2 GHz. Right panel: flagging percentage CDFs for the H I  and four OH line SPWs.
Paper: The Karl G. Jansky Very Large Array Local Group L-Band Survey (LGLBS)
Authors: Eric W. Koch, Adam K. Leroy, Erik W. Rosolowsky, Laura Chomiuk, Julianne J. Dalcanton, Nickolas M. Pingel, Sumit K. Sarbadhicary, Snežana Stanimirović, Fabian Walter, Haylee N. Archer, Alberto D. Bolatto, Michael P. Busch, Hongxing Chen, Ryan Chown, Harrisen Corbould, Serena A. Cronin, Jeremy Darling, Thomas Do, Jennifer Donovan Meyer, Cosima Eibensteiner, Deidre Hunter, Rémy Indebetouw, Preshanth Jagannathan, Amanda A. Kepley, Chang-Goo Kim, Shin-Jeong Kim, Timea O. Kovacs, Joshua Marvil, Eric J. Murphy, Claire E. Murray, Jürgen Ott, D.J. Pisano, Mary Putman, Daniel R. Rybarczyk, Julia Roman-Duval, Karin Sandstrom, Eva Schinnerer, Evan D. Skillman, Adam Smercina, Ioana Stelea, Jay Strader, Jiayi Sun, Devisree Tallapaneni, Elizabeth Tarantino, Vicente Villanueva, Daniel R. Weisz, Thomas G. Williams, Tony Wong
Figure caption: H I  peak brightness temperature maps for combined CD and GBT imaging over the full LGLBS field of view for each target. The images show the extent of emission and complex morphology visible in the bright H I at high ∼100 pc resolution.
Paper: Forecasting Major Flares Using Magnetograms and Knowledge-informed Features: A Comparative Study of Deep Learning Models with Generalization to Multiple Data Products
Authors: Xuebao Li, Shunhuang Zhang, Yanfang Zheng, Ting Li, Rui Wang, Yingbo Liu, Hongwei Ye, Noraisyah Mohamed Shah, Pengchao Yan, Xuefeng Li, Xiaotian Wang, Yongshang Lv, Jinfang Wei, Honglei Jin, Changtian Xiang
Figure caption: The magnetograms on SHARP, HMI, and FMG data, along with the corresponding heat maps and regions of interest highlighted by the CNN-BiLSTM model. AR 13315 erupted an M-class flare on 2023 May 26, at 22:48 UT. Panel (a) shows the magnetogram of AR 13315 on SHARP data, panel (b) presents the heat map of the corresponding magnetogram generated by the CNN-BiLSTM model, and panel (c) is the overlay of panels (a) and (b). Similarly, panels (d), (e), and (f) and panels (g), (h), and (i) correspond to the HMI and FMG data, respectively.
Paper: Forecasting Major Flares Using Magnetograms and Knowledge-informed Features: A Comparative Study of Deep Learning Models with Generalization to Multiple Data Products
Authors: Xuebao Li, Shunhuang Zhang, Yanfang Zheng, Ting Li, Rui Wang, Yingbo Liu, Hongwei Ye, Noraisyah Mohamed Shah, Pengchao Yan, Xuefeng Li, Xiaotian Wang, Yongshang Lv, Jinfang Wei, Honglei Jin, Changtian Xiang
Figure caption: The magnetograms on SHARP, HMI, and FMG data, along with the corresponding heat maps and regions of interest highlighted by the CNN model. AR 13315 erupted an M-class flare on 2023 May 26, at 22:48 UT. Panel (a) shows the magnetogram of AR 13315 on SHARP data, panel (b) presents the heat map of the corresponding magnetogram generated by the CNN model, and panel (c) is the overlay of panels (a) and (b). Similarly, panels (d), (e), and (f) and panels (g), (h), and (i) correspond to the HMI and FMG data, respectively.
Paper: Forecasting Major Flares Using Magnetograms and Knowledge-informed Features: A Comparative Study of Deep Learning Models with Generalization to Multiple Data Products
Authors: Xuebao Li, Shunhuang Zhang, Yanfang Zheng, Ting Li, Rui Wang, Yingbo Liu, Hongwei Ye, Noraisyah Mohamed Shah, Pengchao Yan, Xuefeng Li, Xiaotian Wang, Yongshang Lv, Jinfang Wei, Honglei Jin, Changtian Xiang
Figure caption: The magnetograms on SHARP, HMI, and FMG data, along with the corresponding heat maps and regions of interest highlighted by the ViT model. AR 13315 erupted an M-class flare on 2023 May 26, at 22:48 UT. Panel (a) shows the magnetogram of AR 13315 on SHARP data, panel (b) presents the heat map of the corresponding magnetogram generated by the ViT model, and panel (c) is the overlay of panels (a) and (b). Similarly, panels (d), (e), and (f) and panels (g), (h), and (i) correspond to the HMI and FMG data, respectively.
Paper: Forecasting Major Flares Using Magnetograms and Knowledge-informed Features: A Comparative Study of Deep Learning Models with Generalization to Multiple Data Products
Authors: Xuebao Li, Shunhuang Zhang, Yanfang Zheng, Ting Li, Rui Wang, Yingbo Liu, Hongwei Ye, Noraisyah Mohamed Shah, Pengchao Yan, Xuefeng Li, Xiaotian Wang, Yongshang Lv, Jinfang Wei, Honglei Jin, Changtian Xiang
Figure caption: The TSS variation curves for iTransformer and NASA/CCMC at different probability thresholds.
Paper: A Search of Periodic Variable Stars in the LMC by JWST Photometry
Authors: Jiyu Wang, Xiaodian Chen, Jianxing Zhang, Ziming Yan, Shu Wang, Licai Deng
Figure caption: The figure presents an example of the crossmatching results between the reference catalog and the catalog to be corrected, including a histogram of angular separations and scatterplots of R.A. and decl. residuals. The left panels show the distribution before astrometric calibration, where correctly matched sources form a high-density cluster in the residual plot. The right panels display the postcorrection distribution, with most matched sources exhibiting angular separations less than 0﹩\mathop{.}\limits^{\unicode{x02033}}﹩01.
Paper: A Search of Periodic Variable Stars in the LMC by JWST Photometry
Authors: Jiyu Wang, Xiaodian Chen, Jianxing Zhang, Ziming Yan, Shu Wang, Licai Deng
Figure caption: The figure illustrates the distribution of zero-point corrections across different filters, with short-wavelength bands exhibiting more pronounced corrections compared to long-wavelength bands. Notably, anomalous offsets deviating from the overall trend are observed in the F070W and F277W bands. Given that each detector module contains a calibration star sample exceeding 200 sources—satisfying statistical robustness criteria—these anomalies are unlikely to originate from photometric errors of individual sources.
Paper: A Search of Periodic Variable Stars in the LMC by JWST Photometry
Authors: Jiyu Wang, Xiaodian Chen, Jianxing Zhang, Ziming Yan, Shu Wang, Licai Deng
Figure caption: CMD of sources in the sample with more than five photometric epochs in both F150W and F200W bands. The density of sources is color-mapped, and confirmed variable stars are indicated by distinct symbols.
Paper: A Search of Periodic Variable Stars in the LMC by JWST Photometry
Authors: Jiyu Wang, Xiaodian Chen, Jianxing Zhang, Ziming Yan, Shu Wang, Licai Deng
Figure caption: Distribution of crowding parameters for spurious sources from diffraction spikes and the overall sample. The crowding distributions exhibit a pronounced disparity between spurious sources and normal stars, with spurious sources predominantly clustered above 0.3 while typical stars are primarily concentrated below 0.2.
Paper: A Search of Periodic Variable Stars in the LMC by JWST Photometry
Authors: Jiyu Wang, Xiaodian Chen, Jianxing Zhang, Ziming Yan, Shu Wang, Licai Deng
Figure caption: The figure shows a JWST/NIRCam composite image in six filters (F070W, F150W, F200W, F277W, F356W, and F444W) of a ﹩\sim 6.2^{\prime} \times 3.6^{\prime} ﹩ field in the LMC, representing the primary region analyzed in this study.
Paper: The Karl G. Jansky Very Large Array Local Group L-Band Survey (LGLBS)
Authors: Eric W. Koch, Adam K. Leroy, Erik W. Rosolowsky, Laura Chomiuk, Julianne J. Dalcanton, Nickolas M. Pingel, Sumit K. Sarbadhicary, Snežana Stanimirović, Fabian Walter, Haylee N. Archer, Alberto D. Bolatto, Michael P. Busch, Hongxing Chen, Ryan Chown, Harrisen Corbould, Serena A. Cronin, Jeremy Darling, Thomas Do, Jennifer Donovan Meyer, Cosima Eibensteiner, Deidre Hunter, Rémy Indebetouw, Preshanth Jagannathan, Amanda A. Kepley, Chang-Goo Kim, Shin-Jeong Kim, Timea O. Kovacs, Joshua Marvil, Eric J. Murphy, Claire E. Murray, Jürgen Ott, D.J. Pisano, Mary Putman, Daniel R. Rybarczyk, Julia Roman-Duval, Karin Sandstrom, Eva Schinnerer, Evan D. Skillman, Adam Smercina, Ioana Stelea, Jay Strader, Jiayi Sun, Devisree Tallapaneni, Elizabeth Tarantino, Vicente Villanueva, Daniel R. Weisz, Thomas G. Williams, Tony Wong
Figure caption: Three-color optical images showing the six Northern Hemisphere local galaxies ordered by decreasing stellar mass (image credits: DESI Legacy Survey; T. M. C. Abbott et al. 2018; E. Morganson et al. 2018; B. Flaugher et al. 2015) overlaid with the VLA pointings. The scale bars on the lower-right corners indicate about one radius (for M31 and M33) and a half of the radius (for IC 10, NGC 6822, IC 1613, and WLM) of one VLA pointing. The lower row shows the full extent of the LGLBS pointings.
Paper: Identifying Carbon Star Candidates from LAMOST DR11 and SDSS DR18 Based on a Parallel Feature Recognition Method
Authors: Lichan Zhou, 立婵 周, Jianghui Cai, 江辉 蔡, Haifeng Yang, 海峰 杨, Ali Luo, 阿理 罗, Yinbi Li, 荫碧 李, Chenhui Shi, 晨辉 史, Boyu Zhang, 博宇 张, Jianing Tian, 佳宁 田, Yinan Yuan, 艺楠 员, Yuqing Yang, 雨晴 杨
Figure caption: Two H-R diagrams of carbon stars from LAMOST on M_G vs. G_BP-G_RP and M_G vs. effective temperature. M_G, G_BP, G_RP, and effective temperature are from Gaia DR2. The interstellar dust extinction and redden on M_G, G_BP, and G_RP are also corrected by geometric distances from C. A. L. Bailer-Jones et al. (2021), E(B − V) values of G. M. Green et al. (2019) and the extinction coefficient of S. Wang & X. Chen (2019). Shapes are used to present subtypes of carbon stars. Different colors represent the density of subtypes of carbon stars. Red shows the highest density among other colors. The red dotted line at M_G = 5 mag is often used to separate white dwarfs from carbon stars.
Paper: Identifying Carbon Star Candidates from LAMOST DR11 and SDSS DR18 Based on a Parallel Feature Recognition Method
Authors: Lichan Zhou, 立婵 周, Jianghui Cai, 江辉 蔡, Haifeng Yang, 海峰 杨, Ali Luo, 阿理 罗, Yinbi Li, 荫碧 李, Chenhui Shi, 晨辉 史, Boyu Zhang, 博宇 张, Jianing Tian, 佳宁 田, Yinan Yuan, 艺楠 员, Yuqing Yang, 雨晴 杨
Figure caption: JHK diagram of subtypes of carbon stars from LAMOST. J, H, K magnitudes are obtained from the 2MASS database. The interstellar dust extinction and redden on J, H, K magnitudes are also corrected by geometric distances from C. A. L. Bailer-Jones et al. (2021), E(B − V) values of G. M. Green et al. (2019) and the extinction coefficient of S. Wang & X. Chen (2019). Subtypes of carbon stars are marked in different colors. The red dotted line is J − H = −0.6851 × H − K + 1.0974 (J.-M. Si et al. 2015), which is used to separate subtypes of carbon stars.
Paper: Identifying Carbon Star Candidates from LAMOST DR11 and SDSS DR18 Based on a Parallel Feature Recognition Method
Authors: Lichan Zhou, 立婵 周, Jianghui Cai, 江辉 蔡, Haifeng Yang, 海峰 杨, Ali Luo, 阿理 罗, Yinbi Li, 荫碧 李, Chenhui Shi, 晨辉 史, Boyu Zhang, 博宇 张, Jianing Tian, 佳宁 田, Yinan Yuan, 艺楠 员, Yuqing Yang, 雨晴 杨
Figure caption: Spectra of C-H, C-R, Ba, and G stars from LAMOST. Spectral characteristics are marked in blue, such as C2 molecular bands, CN molecular bands, Ba II line, and Ca I. Other features like the P-branch are highlighted in red.
Paper: Identifying Carbon Star Candidates from LAMOST DR11 and SDSS DR18 Based on a Parallel Feature Recognition Method
Authors: Lichan Zhou, 立婵 周, Jianghui Cai, 江辉 蔡, Haifeng Yang, 海峰 杨, Ali Luo, 阿理 罗, Yinbi Li, 荫碧 李, Chenhui Shi, 晨辉 史, Boyu Zhang, 博宇 张, Jianing Tian, 佳宁 田, Yinan Yuan, 艺楠 员, Yuqing Yang, 雨晴 杨
Figure caption: Spatial distribution of carbon stars from LAMOST. The first subfigure is the spatial distribution of old carbon stars from LAMOST DR7 (L. Li et al. 2024). And the second subfigure is the spatial distribution of new carbon stars found in our paper. Subtypes of Ba, C-H, C-N, C-R, and Unknown stars are marked in red, blue, green, black, and purple, respectively.
Paper: Identifying Carbon Star Candidates from LAMOST DR11 and SDSS DR18 Based on a Parallel Feature Recognition Method
Authors: Lichan Zhou, 立婵 周, Jianghui Cai, 江辉 蔡, Haifeng Yang, 海峰 杨, Ali Luo, 阿理 罗, Yinbi Li, 荫碧 李, Chenhui Shi, 晨辉 史, Boyu Zhang, 博宇 张, Jianing Tian, 佳宁 田, Yinan Yuan, 艺楠 员, Yuqing Yang, 雨晴 杨
Figure caption: Spectra of C-N, G, K, and gM stars from LAMOST. Spectral characteristics are marked in blue, such as C2 molecular bands, CN molecular bands. Other features like weak flux are highlighted in red.
Paper: Identifying Carbon Star Candidates from LAMOST DR11 and SDSS DR18 Based on a Parallel Feature Recognition Method
Authors: Lichan Zhou, 立婵 周, Jianghui Cai, 江辉 蔡, Haifeng Yang, 海峰 杨, Ali Luo, 阿理 罗, Yinbi Li, 荫碧 李, Chenhui Shi, 晨辉 史, Boyu Zhang, 博宇 张, Jianing Tian, 佳宁 田, Yinan Yuan, 艺楠 员, Yuqing Yang, 雨晴 杨
Figure caption: Light curve of LAMOST J054809.51+380835.3 from the ASAS-SN variable stars database.
Paper: Identifying Carbon Star Candidates from LAMOST DR11 and SDSS DR18 Based on a Parallel Feature Recognition Method
Authors: Lichan Zhou, 立婵 周, Jianghui Cai, 江辉 蔡, Haifeng Yang, 海峰 杨, Ali Luo, 阿理 罗, Yinbi Li, 荫碧 李, Chenhui Shi, 晨辉 史, Boyu Zhang, 博宇 张, Jianing Tian, 佳宁 田, Yinan Yuan, 艺楠 员, Yuqing Yang, 雨晴 杨
Figure caption: Photometric image time series of LAMOST J054809.51+380835.3 from ZTF.