adsabs/AstroCLIMB huggingface dataset:
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption: Reference grids similar to those in Figure 18 with σ  v  = 10  km s−1 (b = 14 km s−1).
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption: Reference grids similar to those in Figure 18 with σ  v  = 20  km s−1 (b = 28 km s−1).
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption: Modeled water rovibrational spectra similar to Figure 5 with N tot = 1 × 1018, 5 × 1018 cm−2.
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption: Locations of spectral lines that consist of two unresolved components, which have different velocities but the velocity components blend into one absorption feature at the low-spectral resolution, on the space of curve of growth. Specifically, panels (a) and (e) present the curves of growth of absorbing gas under two physical conditions and the positions of individual isolated spectral lines on the curve. The physical parameters in the legend correspond to (N beam, T ex, σ  v , f  c ) in units of (per square centimeter, kelvin, kilometers per second, 1). “Model b” (and “c”) correspond to models b and c in Figures 3 and 7. The rest panels present data from the weighted sum of the two models. Four sets of combinations of the two models are presented. While W  λ /λ is directly observable, values of τ  p  depend on the physical conditions of the model. The magenta (blue) models in (a) and (e) were applied to panels (b) and (f) ((c) and (g)). We note that, in panels (e)–(h), the curves of growth of the two models overlap because N beam, b (= ﹩\sqrt{2}{\sigma }_{v}﹩), and f  c  are the same (see Section 3.2).
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption: Optically thin and thick spectral lines on the curve of growth. In all panels, the bullets represent specific spectral absorption lines. The red line represents the curve with the same physical parameters adopted from the spectrum in Figure 3(a) (f  c  = 0.4). The black lines represent curves of growth for a range of fractional coverage (f  c ), increasing from 0.1, 0.2, ... to 1 in step of 0.1. Panels (a) and (b) illustrate how the locations of spectral lines on curves of growth change under different fractional coverage but with the same N beam: panel (a) shows that, for optically thin lines, their measured equivalent widths do not change, so the column density N beam is well determined. This is consistent with the conclusion from Figure 2. In contrast, panel (b) indicates that the measured equivalent widths of optically thick lines change a lot, so N beam is not well determined unless f  c  is known (decoupled from (b)). Of course, changing the values of N beam can produce comparable equivalent widths, as is illustrated in panel (c). Then, for optically thick lines, the resulting N tot (=N beam/f  c ) can differ by 2 orders of magnitude, ranging from 2.5 × 1020 (f  c  = 0.2) to 1.2 × 1018 cm−2 (f  c  = 0.7), consistent with the conclusions from Figure 3. But when only optically thin lines are fitted, the derived N tot differs by a factor of a few, depending on the range of f  c .
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption: Two pairs of lines sharing the same lower energy state, 74,3–83,6, 72,5–83,6 and 132,1–133,10, 124,9–133,10 at an R = 3500 resolving power and their positions on the curve of growth. Both line pairs are sufficiently isolated from nearby spectral lines. The blue (model 1), red (model 2), and magenta (model 3) colors correspond to models (b), (a), and (c) adopted by Figure 3, with N tot = 5 × 1018, 2.5 × 1019, 2.5 × 1020 cm−2, N beam = 5 × 1018, 1019, 5 × 1019 cm−2, and σ  v  = 1, 2, 3 km s−1 (or b = 1.4, 2.8, 4.2 km s−1). On the curves of growth, the line pairs of models 1, 2, and 3 shift from the lower left to the upper right regions. Specifically, while other relatively deeper lines have similar depths in the three models, the color-filled lines with 83,6 or 133,10 as the lower level differ in the line depth as well as the opacity.
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption: Ratios of six pairs of isolated lines under σ  v  of 2, 10, 20, 50, 85, and 100 km s−1 (or b = 2.8, 14, 28, 70, 120, 140 km s−1), T ex of 50, 100, 200, 500 K, and N beam from 1017 to 5 × 1019 cm−2. The ratios are only available for specific temperatures and column densities. The shadowed regions correspond to the uncertainties of absorption depth or the depth ratios, adopting a continuum S/N of ∼100, or a noise level of 0.01 on a normalized continuum. The decrement in the ratios indicates that the line pairs are shifting from the linear part to the logarithmic part of the curve of growth and that the opacities are increasing from small to intermediate values. We note that some panels are empty because the targeted lines are either too weak or overlap with other lines under the designated physical conditions.
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption:                       ﹩{\chi }_{\nu }^{2}﹩ analysis of the parameters space based only on the optically thin (upper panels) and thick lines (lower panels). For better comparison, the contours of the upper (lower) panels are copied onto the lower (upper) panels. Specifically, optically thick lines (τ  p  > 5, or log10 τ  p  > 0.7) and optically thin (τ  p  < 1, or log10 τ  p  < 0) lines are chosen from the 5 to 8 μm range, and each panel presents the calculated χ 2 when adopting a noise level of 0.1, 0.05, 0.03 (or S/N = 100, 200, 300) on a normalized spectrum. The cyan–yellow and orange–red contours indicate contours of ﹩{\chi }_{\nu }^{2}﹩ corresponding to Q values of 0.1 and 0.001 (see text for the details). We note the scale of the x-axis, f  c , is scaled by the velocity width, as b of 2.8 km s−1 is used in the presented models.
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption: Similar to Figure 9, with two components differing in both the temperature and the column density.
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption: The lower and upper extremes of the wavelength range covered by the ν 2 band above a 1% absorption level under different T ex and N tot. While higher T ex or N tot both increase the coverage range, a rough estimation of the upper and lower limits on the temperature can be made. The uncertainty of the estimation increases with higher T ex, though.
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption: Modeled water rovibrational spectra similar to Figure 5 with N tot = 1 × 1017, 5 × 1017 cm−2.
Paper: On the Interpretation of Mid-infrared Absorption Lines of Gas-phase H2O as Observed by JWST/MIRI
Authors: Jialu Li, 佳璐 李, Adwin Boogert, Alexander G. G. M. Tielens
Figure caption: Optically thin (red) and thick (black) lines separated from part of the spectrum (a) in Figure 3.
Paper: Determining Stellar Elemental Abundances from DESI Spectra with the Data-driven Payne
Authors: Meng Zhang, Maosheng Xiang, Yuan-Sen Ting, Jiahui Wang, Haining Li, Hu Zou, Jundan Nie, Lanya Mou, Tianmin Wu, Yaqian Wu, Jifeng Liu
Figure caption: Comparison of distance (top left), height (top right), and metallicity (bottom) distributions for the DESI EDR, LAMOST DR9, and APOGEE DR17 stellar samples. The y-axis shows the normalized number density in logarithmic scale for both panels. For the DESI EDR sample, stars with S/N > 10 are shown, while for LAMOST DR9 and APOGEE DR17, stars with S/N > 15 are shown. The [Fe/H] values of LAMOST DR9 are determined with the DD-PAYNE method (M. Zhang et al. 2024, in preparation), similar to this work. The DESI EDR sample contains a larger proportion of distant (>20 kpc) and metal-poor ([Fe/H] < −1.0) stars than the LAMOST and APOGEE samples, while the latter have better sampling for the nearby Galactic disk.
Paper: Determining Stellar Elemental Abundances from DESI Spectra with the Data-driven Payne
Authors: Meng Zhang, Maosheng Xiang, Yuan-Sen Ting, Jiahui Wang, Haining Li, Hu Zou, Jundan Nie, Lanya Mou, Tianmin Wu, Yaqian Wu, Jifeng Liu
Figure caption: Stellar number density distributions in the J  ϕ −J  R  action plane (top left) and the apocenter radius (R apo)–orbital eccentricity (e) plane (top right). The colors represent the number density in individual bins of the plot. The vertical lines in both plots delineate the criteria we adopt for selecting the GES stars via kinematic criteria (see the text for details). The resultant low-angular-momentum and high-eccentricity GES stars are shown with the red dots. The black lines in the top right panel show two equal-density contours of the red dots. The bottom panels show the stellar number density distribution in the [Mg/Fe]–[Fe/H] (bottom left) and [Al/Fe]–[Fe/H] (bottom right) planes, with (kinematic) GES stars marked with the red dots (see the text for details).
Paper: Determining Stellar Elemental Abundances from DESI Spectra with the Data-driven Payne
Authors: Meng Zhang, Maosheng Xiang, Yuan-Sen Ting, Jiahui Wang, Haining Li, Hu Zou, Jundan Nie, Lanya Mou, Tianmin Wu, Yaqian Wu, Jifeng Liu
Figure caption: Left: distance distribution of the DESI EDR stars with spectral S/N > 10. Right: stellar distribution in the X−Z plane of the Galactic Cartesian coordinates, color coded by the median value of [Fe/H] in each X−Z bin. The zoomed-in plot shows the distribution in the window of 0 < X < 16 kpc and −10 < Z < 10 kpc.
Paper: Determining Stellar Elemental Abundances from DESI Spectra with the Data-driven Payne
Authors: Meng Zhang, Maosheng Xiang, Yuan-Sen Ting, Jiahui Wang, Haining Li, Hu Zou, Jundan Nie, Lanya Mou, Tianmin Wu, Yaqian Wu, Jifeng Liu
Figure caption: The measurement errors of the DD-PAYNE stellar label estimates for stars with T eff = 5900 K, ﹩\mathrm{log}\,g=4.0﹩, and [Fe/H] = −0.5. Results for different spectral S/Ns—namely 10, 20, 30, and 40—are shown.
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: For 5000 randomly selected synthetic light curves (adding 0.01 mag Gaussian noise) from the test set, their parameters were derived by Ding et al. (2022) and the proposed method respectively, and the parameters obtained by the two methods were input into the PHOEBE program to calculate the goodness of fit (R 2) between the newly generated light curve and the actual light curve, respectively, where the blue solid bar shows the R 2 distribution curve obtained by the proposed method, and the orange dashed bar indicates the R 2 distribution curve obtained by Ding et al. (2022).
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: The structure of the neural network: five input parameters, four hidden layers, the output is a light curve with 100 phase points, and the number in the box represents the number of nodes in each layer.
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: The posterior distribution of the four parameters (i, q, f, and T 2/T 1) of CSS_J021930.8−014451 derived by the NNHMC method. The contours from the inside out enclose the 68th, 95th, and 99th percentiles of the total probability in the six off-diagonal panels. The three vertical dashed lines in the four diagonal panels represent the lower error at the 16th percentile, the median at the 50th percentile, and the upper error at the 84th percentile of the distribution, respectively.
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: The parameters of 5172 CBs in the CSS were derived using the NNHMC method, and these obtained parameters were subsequently utilized as input for the PHOEBE program to calculate the R 2 and RMSE values between the newly generated light curve and the observed light curve. The distribution of R 2 and RMSE is shown. Colors represent the number of objects in each bin.
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: The fitting results for CSS_J021930.8−014451 and CSS_J045015.2−035058, where the blue dots and gray lines show the observed light curve with photometric error, and the red lines indicate the synthetic light curve generated by the input of parameters derived from the proposed method into the PHOEBE program.
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: The fitting results for CSS_J004435.8+320546 and CSS_J035119.7−033120, where the blue dots and gray lines show the observed light curve with photometric error, and the red lines indicate the synthetic light curve generated by the input of parameters derived from the proposed method into the PHOEBE program.
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: The fitting results for CSS_J032840.8+251929 and CSS_J050855.3+132320, where the blue dots and gray lines show the observed light curve with photometric error, and the red lines indicate the synthetic light curve generated by the input of parameters derived from the proposed method into the PHOEBE program.
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: The proximity of the two light curves generated by the two methods in the test set. The upper part of the figure displays the blue light curve generated by the PHOEBE program, while the orange light curve represents that generated by the NN model. In the lower half of the figure, blue dots represent residuals between these two light curves (orange minus blue), with a dashed red line indicating zero value.
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: The distribution of the standard deviation of residuals between 10,000 synthetic light curves and the light curves predicted by a neural network in the test set. The three orange vertical dashed lines in the figure represent the lower error at the 16th percentile, the median at the 50th percentile, and the upper error at the 84th percentile of the distribution, respectively.
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: The distribution of the parameters of the sample set.
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: Comparison of the R 2 values between the parameters of 2335 CBs in CSS derived by Sun et al. (2020) and the parameters rederived using the method proposed in this paper, where the blue solid bar shows the R 2 distribution curve obtained by the proposed method, and the orange dashed bar indicates the R 2 distribution curve obtained by Sun et al. (2020).
Paper: A Method of Rapidly Deriving Late-type Contact Binary Parameters and Its Application in the Catalina Sky Survey
Authors: JinLiang Wang, Xu Ding, JiaJia Li, JianPing Xiong, QiYuan Cheng, KaiFan Ji
Figure caption: Comparison of the R 2 values between the parameters of 30 CBs in CSS derived by Christopoulou et al. (2022) and the parameters rederived using the method proposed in this paper, where the blue solid bar shows the R 2 distribution curve obtained by the proposed method, and the orange dashed bar indicates the R 2 distribution curve obtained by Christopoulou et al. (2022).
Paper: Complex Network View of the Sun’s Magnetic Patches. I. Identification
Authors: Zahra Tajik, Nastaran Farhang, Hossein Safari, Michael S. Wheatland
Figure caption: (a) The HMI cutout image of an AR recorded by the SDO at 23:58 on 2022 January 17 (NOAA AR 2929). Panels (b)–(f) show the node-degree image for the magnetic network constructed from the HMI magnetogram with thresholds of 8, 12, 16, 20, and 24 G, respectively. The bright and dark regions/pixels indicate the inward and outward links, respectively. The node-degree images are the same size as the original cutout HMI magnetogram.
Paper: Complex Network View of the Sun’s Magnetic Patches. I. Identification
Authors: Zahra Tajik, Nastaran Farhang, Hossein Safari, Michael S. Wheatland
Figure caption: An HMI cutout image of the Sun taken by the SDO at 23:58 on 2022 January 17. As manifested in this graphical illustration, an arbitrary pixel can connect an opposite polarity (red asterisks) only if their magnetic intensities exceed the absolute values of all the pixels placed in between them (marked with blue flags in panel (b)). The absolute intensities of negative and positive fluxes are shown with black and white bars in panel (c), respectively. A partial 3D visualization of the magnetic connections that hold in the constructed network is displayed in panel (d). The heights of connections represent their weights.
Paper: Searching for Short-period Variables in M31: Method and Catalogs
Authors: Hongrui Gu, 弘睿 顾, Haibo Yuan, 海波 苑, Subo Dong, 苏勃 东, Chenfa Zheng, 晨发 郑, Shenzhe Cui, 深哲 崔, Yi Ren, 逸 任, Haozhu Fu, 皓竹 付, Yang Huang, 样 黄, Zhou Fan, 舟 范
Figure caption: An example plot prepared for each variable candidate for visual inspection. The 231 subimages at the top represent the portions of subtracted images obtained from a total of 231 observations in the CFHT g and r bands. The numerical colors on the subimages indicate the observed bands, with green representing the CFHT g band and red representing the CFHT r band. The numbers are sequentially assigned, with smaller numbers indicating earlier observations. The 231 subimages are divided into three segments, separated by two blank images, representing the three nights of observations. The two large images in the center right depict the reference image portions. The four panels in the center left represent the period analysis. The left two panels show the relationship between period and intensity obtained using the PDM algorithm, with smaller values indicating more significant periods. The right two panels display folded light curves. The top (bottom) two panels correspond to a search and best-matched folding result for a period range of 0–15 (0–1) days at a resolution of 0.1 (0.001) day. The bottom seven panels depict the time series, with the horizontal axes representing the observation time and the vertical axes representing the intensity, with colors indicating the observed bands. The six individual daily images on the left have the vertical axes represented in ADU values obtained from aperture photometry on the subtracted images, while the large panel on the right has the vertical axis represented in magnitudes.
Paper: Searching for Short-period Variables in M31: Method and Catalogs
Authors: Hongrui Gu, 弘睿 顾, Haibo Yuan, 海波 苑, Subo Dong, 苏勃 东, Chenfa Zheng, 晨发 郑, Shenzhe Cui, 深哲 崔, Yi Ren, 逸 任, Haozhu Fu, 皓竹 付, Yang Huang, 样 黄, Zhou Fan, 舟 范
Figure caption: Typical light curves of five different types of variable sources. The upper-right legend shows the respective type. The green and red dots represent data in the CFHT g and r bands, respectively. Note that the CFHT r magnitudes have been shifted to a position close to the CFHT g magnitudes by adding the average g − r color. The two vertical dashed lines are used to divide the data into three days.
Paper: Searching for Short-period Variables in M31: Method and Catalogs
Authors: Hongrui Gu, 弘睿 顾, Haibo Yuan, 海波 苑, Subo Dong, 苏勃 东, Chenfa Zheng, 晨发 郑, Shenzhe Cui, 深哲 崔, Yi Ren, 逸 任, Haozhu Fu, 皓竹 付, Yang Huang, 样 黄, Zhou Fan, 舟 范
Figure caption: Comparison between a single image (left panel) and its reference image (middle panel) in CFHT g band. Their subtraction image is shown in the right panel. The variable sources in this region are highlighted in the red circles.
Paper: Searching for Short-period Variables in M31: Method and Catalogs
Authors: Hongrui Gu, 弘睿 顾, Haibo Yuan, 海波 苑, Subo Dong, 苏勃 东, Chenfa Zheng, 晨发 郑, Shenzhe Cui, 深哲 崔, Yi Ren, 逸 任, Haozhu Fu, 皓竹 付, Yang Huang, 样 黄, Zhou Fan, 舟 范
Figure caption: Seeing (red and green crosses for r and g bands, respectively) as a function of time during the three nights of observations. The dots mark those for the reference images.
Paper: Searching for Short-period Variables in M31: Method and Catalogs
Authors: Hongrui Gu, 弘睿 顾, Haibo Yuan, 海波 苑, Subo Dong, 苏勃 东, Chenfa Zheng, 晨发 郑, Shenzhe Cui, 深哲 崔, Yi Ren, 逸 任, Haozhu Fu, 皓竹 付, Yang Huang, 样 黄, Zhou Fan, 舟 范
Figure caption: Flowchart of variable source selection. Min (f) here means the minimum period value provided by the PDM algorithm.
Paper: Searching for Short-period Variables in M31: Method and Catalogs
Authors: Hongrui Gu, 弘睿 顾, Haibo Yuan, 海波 苑, Subo Dong, 苏勃 东, Chenfa Zheng, 晨发 郑, Shenzhe Cui, 深哲 崔, Yi Ren, 逸 任, Haozhu Fu, 皓竹 付, Yang Huang, 样 黄, Zhou Fan, 舟 范
Figure caption: Spatial distribution of different types of variable sources. The black crosses represent the sky areas without targets due to problems in the image subtraction process. The red dots represent the interday variable stars, which are evenly distributed in the field of view of M31. The yellow triangles represent the intraday variable stars, which are concentrated in M31's spiral arms. The blue stars indicate the flares. The green square shows the candidate microlensing event. The two cyan ellipses indicate M32 and M110, whose positions and shape parameters are from de Vaucouleurs et al. (1991). A flag has been added to the variable sources within the two ellipses.