adsabs/AstroCLIMB huggingface dataset:
Paper: Sample and Statistical Analysis on NEOWISE Variability of ATLASGAL Sources
Authors: Ying Lu, Xi Chen, Shi-Min Song, Jun-Ting Liu, Tian Yang, You-Xin Wang, Yan-Kun Zhang, Shi-Jie Zhang
Figure caption: The top panel shows a comparison of the 2D density distribution of ΔW2 vs. SD/σ between the sample of low-mass YSOs from Park et al. (2021) and our sample. The bottom two panels compare the statistical distribution of ΔW2 vs. SD/σ for our sample across four evolutionary stages (left) and different types of variability (right).
Paper: Sample and Statistical Analysis on NEOWISE Variability of ATLASGAL Sources
Authors: Ying Lu, Xi Chen, Shi-Min Song, Jun-Ting Liu, Tian Yang, You-Xin Wang, Yan-Kun Zhang, Shi-Jie Zhang
Figure caption: Examples of magnitude–color diagrams of three different types. The top left panel gives an example of the redder when brighter/bluer when dimming type (RB/BD), the top right diagram illustrates the bluer when brighter/redder when dimming type (BB/RD), and the bottom panel presents an example with different periods of magnitude and color variations (PD).
Paper: Sample and Statistical Analysis on NEOWISE Variability of ATLASGAL Sources
Authors: Ying Lu, Xi Chen, Shi-Min Song, Jun-Ting Liu, Tian Yang, You-Xin Wang, Yan-Kun Zhang, Shi-Jie Zhang
Figure caption: Examples of different variability types. Each panel provides the source name, corresponding evolutionary stage, and fitting results at the top. From top to bottom, the left panels display linear, sin, and sin+linear variations while the right panels show burst, drop, and irregular variations. The dashed line marks the median W2 magnitude, while the dotted line indicates the criterion for burst and drop variables.
Paper: Sample and Statistical Analysis on NEOWISE Variability of ATLASGAL Sources
Authors: Ying Lu, Xi Chen, Shi-Min Song, Jun-Ting Liu, Tian Yang, You-Xin Wang, Yan-Kun Zhang, Shi-Jie Zhang
Figure caption: Cumulative distribution of infrared spectral indices, W2 luminosities, and W1 − W2 colors between variables and nonvariables. The blue and orange solid curves represent the variables and nonvariables. The W2 luminosity is expressed in units of Jy kpc2. The p-value from the K-S test is shown in the plot.
Paper: Sample and Statistical Analysis on NEOWISE Variability of ATLASGAL Sources
Authors: Ying Lu, Xi Chen, Shi-Min Song, Jun-Ting Liu, Tian Yang, You-Xin Wang, Yan-Kun Zhang, Shi-Jie Zhang
Figure caption: Histogram distributions of the Stetson indices of all sources that satisfy the selection criteria, with the dotted line marking the criterion threshold (larger than 8.64) for identifying variables.
Paper: Sample and Statistical Analysis on NEOWISE Variability of ATLASGAL Sources
Authors: Ying Lu, Xi Chen, Shi-Min Song, Jun-Ting Liu, Tian Yang, You-Xin Wang, Yan-Kun Zhang, Shi-Jie Zhang
Figure caption: Comparative statistical analysis of the Stetson indices across four evolutionary stages (left) and different types of variability (right).
Paper: Application of Deep-learning Methods for Distinguishing Gamma-Ray Bursts from Fermi/GBM Time-tagged Event Data
Authors: Peng Zhang, 鹏 张, Bing Li, 兵 李, Renzhou Gui, 任舟 桂, Shaolin Xiong, 少林 熊, Ze-Cheng Zou, 泽城 邹, Xianggao Wang, 祥高 王, Xiaobo Li, 小波 李, Ce Cai, 策 蔡, Yi Zhao, 一 赵, Yanqiu Zhang, 艳秋 张, Wangchen Xue, 王陈 薛, Chao Zheng, 超 郑, Hongyu Zhao, 宏宇 赵
Figure caption: Right: the heat map of features and the mapping curves of features. Left: Curves obtained by summing the heat map of features along the channel dimension and the IoU (Fermi-T 90 and T 90,F ) are >0.3 with various feature thresholds from the identified GRBs in Section 4.2. The red dashed lines are the set of feature thresholds. The green area represents the period of T 90,F . The black vertical line indicates the Fermi-T 90.
Paper: Application of Deep-learning Methods for Distinguishing Gamma-Ray Bursts from Fermi/GBM Time-tagged Event Data
Authors: Peng Zhang, 鹏 张, Bing Li, 兵 李, Renzhou Gui, 任舟 桂, Shaolin Xiong, 少林 熊, Ze-Cheng Zou, 泽城 邹, Xianggao Wang, 祥高 王, Xiaobo Li, 小波 李, Ce Cai, 策 蔡, Yi Zhao, 一 赵, Yanqiu Zhang, 艳秋 张, Wangchen Xue, 王陈 薛, Chao Zheng, 超 郑, Hongyu Zhao, 宏宇 赵
Figure caption: Location of the Fermi spacecraft in orbit at the T 90,F  start time of the candidates. The color gradient shows the geomagnetic latitude according to the McIlwain L. If the spacecraft is in the region where the McIlwain L is greater than 1.5, the candidate is likely to be associated with local particles.
Paper: Application of Deep-learning Methods for Distinguishing Gamma-Ray Bursts from Fermi/GBM Time-tagged Event Data
Authors: Peng Zhang, 鹏 张, Bing Li, 兵 李, Renzhou Gui, 任舟 桂, Shaolin Xiong, 少林 熊, Ze-Cheng Zou, 泽城 邹, Xianggao Wang, 祥高 王, Xiaobo Li, 小波 李, Ce Cai, 策 蔡, Yi Zhao, 一 赵, Yanqiu Zhang, 艳秋 张, Wangchen Xue, 王陈 薛, Chao Zheng, 超 郑, Hongyu Zhao, 宏宇 赵
Figure caption: The localization of the unknown events. The color bar illustrates the localization error of events within 1σ equaled to the radius of spatial position error. The thick black circle encloses the events from SGR J1935+2154.
Paper:  β Cephei Pulsators in Eclipsing Binaries Observed with TESS
Authors: Christian I. Eze, Gerald Handler
Figure caption: A cutout session of the pixel-to-pixel plot of the aperture mask for V1216 Sco.
Paper:  β Cephei Pulsators in Eclipsing Binaries Observed with TESS
Authors: Christian I. Eze, Gerald Handler
Figure caption: H-R diagram of the stars listed in Tables 1–4. The dashed magenta line denotes the SPB instability strip, whereas the dashed–dotted cyan line denotes the β Cep instability strip. Stars with missing parameters (e.g., A 0, T eff) are not captured in the H-R diagram.
Paper:  β Cephei Pulsators in Eclipsing Binaries Observed with TESS
Authors: Christian I. Eze, Gerald Handler
Figure caption: An example figure of the light curve and DFT of a massive pulsator in eclipsing binaries (HD 329379) in our sample. The upper panel shows the TESS light curve. The middle panel shows the DFT of the light curve shown in the upper panel, whereas the lower panel shows the DFT of the residual light curve after removing the orbital light variations. The region showing the dominant β Cep pulsations is also zoomed in on and shown in the inset in the lower panel.
Paper:  β Cephei Pulsators in Eclipsing Binaries Observed with TESS
Authors: Christian I. Eze, Gerald Handler
Figure caption: Binned phase diagrams of light curves of the β Cep pulsators in eclipsing binaries after prewhitening the strongest pulsations.
Paper:  β Cephei Pulsators in Eclipsing Binaries Observed with TESS
Authors: Christian I. Eze, Gerald Handler
Figure caption: Binned phase diagrams of light curves of the candidates for β Cep pulsators in eclipsing binaries after prewhitening the strongest pulsations.
Paper: The Sloan Digital Sky Survey Reverberation Mapping Project: Key Results
Authors: Yue Shen, Catherine J. Grier, Keith Horne, Zachary Stone, Jennifer I. Li, Qian Yang, Yasaman Homayouni, Jonathan R. Trump, Scott F. Anderson, W. N. Brandt, Patrick B. Hall, Luis C. Ho, Linhua Jiang, Patrick Petitjean, Donald P. Schneider, Charling Tao, Fergus. R. Donnan, Yusra AlSayyad, Matthew A. Bershady, Michael R. Blanton, Dmitry Bizyaev, Kevin Bundy, Yuguang Chen, Megan C. Davis, Kyle Dawson, Xiaohui Fan, Jenny E. Greene, Hannes Gröller, Yucheng Guo, Héctor Ibarra-Medel, Yuanzhe Jiang, Ryan P. Keenan, Juna A. Kollmeier, Cassandra Lejoly, Zefeng Li, Axel de la Macorra, Maxwell Moe, Jundan Nie, Graziano Rossi, Paul S. Smith, Wei Leong Tee, Anne-Marie Weijmans, Jiachuan Xu, Minghao Yue, Xu Zhou, Zhimin Zhou, Hu Zou
Figure caption: An illustration of lag measurements using ICCF, Javelin, and PyROA, as well as our alias mitigation scheme using lag posterior weights. The left two panels show the light-curve data in points, and the PyROA model light curves in solid lines and shaded area (best model and 1σ uncertainty). The right panels show the lag measurements. The “ICCF” panel shows the original ICCF, with the red vertical line (and number) indicating the expected (observed-frame) lag for Hβ. The “Weights” panel shows the ACF (orange), periodic overlapping light-curve data points ﹩{(N(\tau )/{N}_{\max })}^{2}﹩ (gray), and the final weights (blue). The next three panels show the lag results for ICCF, Javelin, and PyROA, with the lag posterior displayed in the normalized histogram. The gray shaded band shows the boundaries of the identified primary peak, from which we measure the lag (median) and 1σ uncertainties (16th and 84th percentiles). The final lag and uncertainties are reported in each panel. For this particular object, the ICCF is relatively broad, resulting in a different lag using the cross-correlation centroid distribution (CCCD). However, the lag inferred from the cross-correlation peak distribution (CCPD; also see the top-right panel of this figure) is in excellent agreement with the Javelin and PyROA lags.
Paper: The Sloan Digital Sky Survey Reverberation Mapping Project: Key Results
Authors: Yue Shen, Catherine J. Grier, Keith Horne, Zachary Stone, Jennifer I. Li, Qian Yang, Yasaman Homayouni, Jonathan R. Trump, Scott F. Anderson, W. N. Brandt, Patrick B. Hall, Luis C. Ho, Linhua Jiang, Patrick Petitjean, Donald P. Schneider, Charling Tao, Fergus. R. Donnan, Yusra AlSayyad, Matthew A. Bershady, Michael R. Blanton, Dmitry Bizyaev, Kevin Bundy, Yuguang Chen, Megan C. Davis, Kyle Dawson, Xiaohui Fan, Jenny E. Greene, Hannes Gröller, Yucheng Guo, Héctor Ibarra-Medel, Yuanzhe Jiang, Ryan P. Keenan, Juna A. Kollmeier, Cassandra Lejoly, Zefeng Li, Axel de la Macorra, Maxwell Moe, Jundan Nie, Graziano Rossi, Paul S. Smith, Wei Leong Tee, Anne-Marie Weijmans, Jiachuan Xu, Minghao Yue, Xu Zhou, Zhimin Zhou, Hu Zou
Figure caption: Comparisons between the FWHM from the mean spectrum (for SE estimators) and the σ line,rms from the rms spectrum (for RM masses) for Hα, Hβ, Mg II, and C IV, color coded by the deviation from the sample median luminosity for the corresponding line (e.g., L5100, L3000, etc.). The Mg II σ line,rms here has been corrected for the velocity split of the doublet, but not for the SDSS spectral resolution (negligible). In each panel, the black dashed line is the unity relation, and the red dashed line represents the FWHM–σ line relation for a Gaussian profile. The best-fit linear regressions of (Y∣X) and (X∣Y) are also shown. There is no clear luminosity trend (measured with the deviations from the sample median luminosity, ﹩{\rm{\Delta }}\mathrm{log}L﹩) in the line-width correlation for all lines.
Paper: The Sloan Digital Sky Survey Reverberation Mapping Project: Key Results
Authors: Yue Shen, Catherine J. Grier, Keith Horne, Zachary Stone, Jennifer I. Li, Qian Yang, Yasaman Homayouni, Jonathan R. Trump, Scott F. Anderson, W. N. Brandt, Patrick B. Hall, Luis C. Ho, Linhua Jiang, Patrick Petitjean, Donald P. Schneider, Charling Tao, Fergus. R. Donnan, Yusra AlSayyad, Matthew A. Bershady, Michael R. Blanton, Dmitry Bizyaev, Kevin Bundy, Yuguang Chen, Megan C. Davis, Kyle Dawson, Xiaohui Fan, Jenny E. Greene, Hannes Gröller, Yucheng Guo, Héctor Ibarra-Medel, Yuanzhe Jiang, Ryan P. Keenan, Juna A. Kollmeier, Cassandra Lejoly, Zefeng Li, Axel de la Macorra, Maxwell Moe, Jundan Nie, Graziano Rossi, Paul S. Smith, Wei Leong Tee, Anne-Marie Weijmans, Jiachuan Xu, Minghao Yue, Xu Zhou, Zhimin Zhou, Hu Zou
Figure caption: Statistical detection of lags for the SDSS-RM sample using ICCF. As the ﹩{r}_{\max }﹩ value decreases, there are increased incidents of negative lags. While overall the asymmetry toward positive lags is clear, below ﹩{r}_{\max }=0.4﹩, the negative to positive lag ratio is substantially higher than that at ﹩{r}_{\max }\gt 0.4﹩, indicating a high false-positive rate for the positive lags measured with low ﹩{r}_{\max }﹩ values. The points are color coded by the line variability SNR2 (see Section 3.3). Objects with higher SNR2 values tend to cluster in the upper right quadrant, where a positive lag detection is more likely to happen, along with a high ﹩{r}_{\max }﹩ value.
Paper: The Sloan Digital Sky Survey Reverberation Mapping Project: Key Results
Authors: Yue Shen, Catherine J. Grier, Keith Horne, Zachary Stone, Jennifer I. Li, Qian Yang, Yasaman Homayouni, Jonathan R. Trump, Scott F. Anderson, W. N. Brandt, Patrick B. Hall, Luis C. Ho, Linhua Jiang, Patrick Petitjean, Donald P. Schneider, Charling Tao, Fergus. R. Donnan, Yusra AlSayyad, Matthew A. Bershady, Michael R. Blanton, Dmitry Bizyaev, Kevin Bundy, Yuguang Chen, Megan C. Davis, Kyle Dawson, Xiaohui Fan, Jenny E. Greene, Hannes Gröller, Yucheng Guo, Héctor Ibarra-Medel, Yuanzhe Jiang, Ryan P. Keenan, Juna A. Kollmeier, Cassandra Lejoly, Zefeng Li, Axel de la Macorra, Maxwell Moe, Jundan Nie, Graziano Rossi, Paul S. Smith, Wei Leong Tee, Anne-Marie Weijmans, Jiachuan Xu, Minghao Yue, Xu Zhou, Zhimin Zhou, Hu Zou
Figure caption: Expected Hβ lag in the observed frame for the SDSS-RM sample, estimated using the mean Hβ R–L relation from Bentz et al. (2013). The points are color coded by the fractional rms variability σ cont from the 11 yr photometric light curve, corrected for flux measurement uncertainties. The black and red dashed lines are the 7 yr spectroscopic baseline and the 11 yr photometric baseline, respectively. There is a general tendency of increasing variability toward lower luminosities (shorter lags) at fixed redshift.
Paper: The Sloan Digital Sky Survey Reverberation Mapping Project: Key Results
Authors: Yue Shen, Catherine J. Grier, Keith Horne, Zachary Stone, Jennifer I. Li, Qian Yang, Yasaman Homayouni, Jonathan R. Trump, Scott F. Anderson, W. N. Brandt, Patrick B. Hall, Luis C. Ho, Linhua Jiang, Patrick Petitjean, Donald P. Schneider, Charling Tao, Fergus. R. Donnan, Yusra AlSayyad, Matthew A. Bershady, Michael R. Blanton, Dmitry Bizyaev, Kevin Bundy, Yuguang Chen, Megan C. Davis, Kyle Dawson, Xiaohui Fan, Jenny E. Greene, Hannes Gröller, Yucheng Guo, Héctor Ibarra-Medel, Yuanzhe Jiang, Ryan P. Keenan, Juna A. Kollmeier, Cassandra Lejoly, Zefeng Li, Axel de la Macorra, Maxwell Moe, Jundan Nie, Graziano Rossi, Paul S. Smith, Wei Leong Tee, Anne-Marie Weijmans, Jiachuan Xu, Minghao Yue, Xu Zhou, Zhimin Zhou, Hu Zou
Figure caption: Fractional (intrinsic) rms variability for the four broad lines considered in this work vs. that of the continuum light curve. The dashed diagonal lines show the unity relation, and the horizontal red lines (with numbers) indicate the median fractional line variability. There are reasonably good correlations between the line and continuum rms variability, as expected from reverberation.
Paper: The Sloan Digital Sky Survey Reverberation Mapping Project: Key Results
Authors: Yue Shen, Catherine J. Grier, Keith Horne, Zachary Stone, Jennifer I. Li, Qian Yang, Yasaman Homayouni, Jonathan R. Trump, Scott F. Anderson, W. N. Brandt, Patrick B. Hall, Luis C. Ho, Linhua Jiang, Patrick Petitjean, Donald P. Schneider, Charling Tao, Fergus. R. Donnan, Yusra AlSayyad, Matthew A. Bershady, Michael R. Blanton, Dmitry Bizyaev, Kevin Bundy, Yuguang Chen, Megan C. Davis, Kyle Dawson, Xiaohui Fan, Jenny E. Greene, Hannes Gröller, Yucheng Guo, Héctor Ibarra-Medel, Yuanzhe Jiang, Ryan P. Keenan, Juna A. Kollmeier, Cassandra Lejoly, Zefeng Li, Axel de la Macorra, Maxwell Moe, Jundan Nie, Graziano Rossi, Paul S. Smith, Wei Leong Tee, Anne-Marie Weijmans, Jiachuan Xu, Minghao Yue, Xu Zhou, Zhimin Zhou, Hu Zou
Figure caption: An example of merged 11 yr photometric light curves for the SDSS-RM sample (see Section 3.2 for details). Light curves from different surveys are calibrated to the SDSS r band. For each SDSS-RM quasar, there are typically hundreds of nightly averaged photometric epochs, to go with 90 spectroscopic epochs (black open circles) from SDSS.
Paper: The Sloan Digital Sky Survey Reverberation Mapping Project: Key Results
Authors: Yue Shen, Catherine J. Grier, Keith Horne, Zachary Stone, Jennifer I. Li, Qian Yang, Yasaman Homayouni, Jonathan R. Trump, Scott F. Anderson, W. N. Brandt, Patrick B. Hall, Luis C. Ho, Linhua Jiang, Patrick Petitjean, Donald P. Schneider, Charling Tao, Fergus. R. Donnan, Yusra AlSayyad, Matthew A. Bershady, Michael R. Blanton, Dmitry Bizyaev, Kevin Bundy, Yuguang Chen, Megan C. Davis, Kyle Dawson, Xiaohui Fan, Jenny E. Greene, Hannes Gröller, Yucheng Guo, Héctor Ibarra-Medel, Yuanzhe Jiang, Ryan P. Keenan, Juna A. Kollmeier, Cassandra Lejoly, Zefeng Li, Axel de la Macorra, Maxwell Moe, Jundan Nie, Graziano Rossi, Paul S. Smith, Wei Leong Tee, Anne-Marie Weijmans, Jiachuan Xu, Minghao Yue, Xu Zhou, Zhimin Zhou, Hu Zou
Figure caption: Fractional (intrinsic) rms variability for additional broad lines vs. that of the continuum light curve. We do not report lag measurements for these lines, but their variability properties are compiled in Table 2.
Paper: Quantifying the Escape of Lyα at z ≈ 5–6: A Census of Lyα Escape Fraction with Hα-emitting Galaxies Spectroscopically Confirmed by JWST and VLT/MUSE
Authors: Xiaojing Lin, Zheng Cai, Yunjing Wu, Zihao Li, Fengwu Sun, Xiaohui Fan, Zuyi Chen, Mingyu Li, Fuyan Bian, Yuanhang Ning, Linhua Jiang, Gustavo Bruzual, Stephane Charlot, Jacopo Chevallard
Figure caption:  f esc,Lyα  varying with the observed UV slope β obs and E(B − V), under the assumption of Calz dust attenuation law. The light blue circles denote LAE individuals, and the light purple triangles are non-LAEs with forced f esc,Lyα  measured from the integrated Lyα flux within ±1000 km −1. For illustration purposes, we do not show the uncertainties of f esc,Lyα  of non-LAEs. The orange stars are the overall f esc,Lyα  of all HAEs derived from the Lyα stack results. The dashed lines represent the best-fit relations between f esc,Lyα  and E(B − V) or β obs based on the stack results as described in Equation (9). We show their 1σ uncertainties as shaded regions.
Paper: Quantifying the Escape of Lyα at z ≈ 5–6: A Census of Lyα Escape Fraction with Hα-emitting Galaxies Spectroscopically Confirmed by JWST and VLT/MUSE
Authors: Xiaojing Lin, Zheng Cai, Yunjing Wu, Zihao Li, Fengwu Sun, Xiaohui Fan, Zuyi Chen, Mingyu Li, Fuyan Bian, Yuanhang Ning, Linhua Jiang, Gustavo Bruzual, Stephane Charlot, Jacopo Chevallard
Figure caption:  f esc,Lyα  varying with different physical parameters of HAEs assuming the Calz dust attenuation law. The light blue dots denote the f esc,Lyα  measured for individual LAE; the light purple triangles are the forced measured f esc,Lyα  for non-LAEs. The uncertainties of f esc,Lyα  of non-LAEs are not shown for illustration purposes. The orange stars represent the stack f esc,Lyα . We label the correlation coefficients of the Spearman’s correlation analysis (ρ) and Kendall's correlation analysis (τ) for each property, as well as the corresponding p-values. The Spearman’s correlation analysis is based on the measured values and uncertainties of all individual LAEs and non-LAEs, while in the Kendall's tests we adopt the 3σ upper limits of f esc,Lyα  for non-LAEs.
Paper: Quantifying the Escape of Lyα at z ≈ 5–6: A Census of Lyα Escape Fraction with Hα-emitting Galaxies Spectroscopically Confirmed by JWST and VLT/MUSE
Authors: Xiaojing Lin, Zheng Cai, Yunjing Wu, Zihao Li, Fengwu Sun, Xiaohui Fan, Zuyi Chen, Mingyu Li, Fuyan Bian, Yuanhang Ning, Linhua Jiang, Gustavo Bruzual, Stephane Charlot, Jacopo Chevallard
Figure caption: The spatial and redshift distribution of Hα emitters. Left: the distribution of Hα sample in the footprints of multiband legacy data in GOODS-S. The blue-shaded region is covered by MUSE observations, including the MUSE-Wide (Urrutia et al. 2019) and MUSE Hubble UDF survey (Bacon et al. 2023), color-coded by the number of overlapping data cubes (darker color indicates more data cubes). The cyan, blue, and magenta frames represent the footprints of three fields in MUSE Hubble UDF survey: the 10 hr UDF, 31 hr UDF-10, and the >100 hr MXDF; the red rectangle shows the FoV of FRESCO JWST/NIRCam F444W imaging. Color-coded markers indicate the position of our Hα emitters. The color indicates their redshift in exactly the same scale as that on the right panel. An overdensity at z ≈ 5.3–5.4 is obvious, which has been reported in Helton et al. (2023). The crosses denote Hα emitters not covered by MUSE (41 in total); dots are within MUSE coverage (197 in total), and dots with black edges are selected sources we use for analysis (157 in total). Right: the redshift distribution of our Hα emitters. The distribution of selected Hα sources is wrapped with black edges.
Paper: Quantifying the Escape of Lyα at z ≈ 5–6: A Census of Lyα Escape Fraction with Hα-emitting Galaxies Spectroscopically Confirmed by JWST and VLT/MUSE
Authors: Xiaojing Lin, Zheng Cai, Yunjing Wu, Zihao Li, Fengwu Sun, Xiaohui Fan, Zuyi Chen, Mingyu Li, Fuyan Bian, Yuanhang Ning, Linhua Jiang, Gustavo Bruzual, Stephane Charlot, Jacopo Chevallard
Figure caption: The distribution of f esc,Lyα  for LAEs and non-LAEs, assuming the Calz dust attenuation law. For non-LAEs, we show the forced measured f esc,Lyα  based on the integrated flux over ±1000 km s−1 around the wavelength of Lyα. The mean errorbar of f esc,Lyα  of LAEs and non-LAEs are marked as the blue and green horizontal lines. The thick red curve is the best-fit exponential model for the f esc,Lyα  distribution; the thin red curves represent 100 exponential models with f * (Equation (7)) randomly drawn from the MCMC samples. f esc,Lyα  = 0 is labeled as the gray dotted line. The red dashed line denotes the median f esc,Lyα  predicted by the best-fit exponential model, and the orange dashed line is the f esc,Lyα  measured from the stack of all HAEs.
Paper: Quantifying the Escape of Lyα at z ≈ 5–6: A Census of Lyα Escape Fraction with Hα-emitting Galaxies Spectroscopically Confirmed by JWST and VLT/MUSE
Authors: Xiaojing Lin, Zheng Cai, Yunjing Wu, Zihao Li, Fengwu Sun, Xiaohui Fan, Zuyi Chen, Mingyu Li, Fuyan Bian, Yuanhang Ning, Linhua Jiang, Gustavo Bruzual, Stephane Charlot, Jacopo Chevallard
Figure caption: The distribution of EWHα  and EWLyα  of the 165 selected HAEs in the overlapping region of FRESCO and MUSE footprints. The EWs are calculated following Equation (5) with f cont from the SED-modeled stellar continuum assuming the Calz dust attenuation law. We label the mean uncertainty of EWHα  (pink in the left panel) and EWLyα  (blue for LAEs, and green for non-LAEs in the right panel) as horizontal lines, respectively. For non-LAEs, we note that the uncertainty of forced measured EWLyα  reaches an average of 163 Å when EWLyα  > 100 Å, although the mean uncertainty for non-LAEs is about 47 Å. We mark the EWLyα  = 0 as the gray dashed line.
Paper: Quantifying the Escape of Lyα at z ≈ 5–6: A Census of Lyα Escape Fraction with Hα-emitting Galaxies Spectroscopically Confirmed by JWST and VLT/MUSE
Authors: Xiaojing Lin, Zheng Cai, Yunjing Wu, Zihao Li, Fengwu Sun, Xiaohui Fan, Zuyi Chen, Mingyu Li, Fuyan Bian, Yuanhang Ning, Linhua Jiang, Gustavo Bruzual, Stephane Charlot, Jacopo Chevallard
Figure caption: HAE examples with their JWST/NIRcam F444W images (top first), pseudo-Lyα narrowband images (top second), and their Lyα (top third), Hα spectra (bottom). The solid box on the NB image is the 4 × 4 pixel boxy aperture used to identify Lyα and fit its profile; the dashed circle is the r = 1.″5 aperture for the total flux. The top third is the boxy-aperture extracted spectrum (black) and its uncertainty (gray shaded). We show the best-fit skewed Gaussian profile in red. The red-shaded region refers to the spectral window (3 pixel width) for Lyα NB. The bottom panels of each example demonstrate the 2D and 1D grism spectrum for Hα. The yellow cross marks the position of Hα emission in the 2D grism spectrum, and the best-fit Gaussian profile is presented in red.