adsabs/AstroCLIMB huggingface dataset:
Paper: Time-variable Jet Ejections from RW Aur A, RY Tau, and DG Tau 
Authors: Michihiro Takami, Hans Moritz Günther, P. Christian Schneider, Tracy L. Beck, Jennifer L. Karr, Youichi Ohyama, Roberto Galván-Madrid, Taichi Uyama, Marc White, Konstantin Grankin, Deirdre Coffey, Chun-Fan Liu, Misato Fukagawa, Nadine Manset, Wen-Ping Chen, Tae-Soo Pyo, Hsien Shang, Thomas P. Ray, Masaaki Otsuka, Mei-Yin Chou
Figure caption: The velocity-integrated maps (left) and PV diagrams (right) of the [Fe II] 1.644 μm emission associated with the redshifted jet from RW Aur A. The top to bottom panels show the maps and diagrams for the eight epochs (see Table 3 for details). The data for the underlined dates were obtained with a photometric accuracy within 10%. The velocities for the PV diagrams are in terms of the systemic velocity of the star. The region within 0.″2 of the star is masked, as the imperfect subtraction of the bright continuum makes the data unreliable. The contour levels are arbitrarily chosen, to show the approximate locations of the jet knots. The positions of the maps and the diagrams are offset from those at the bottom (i.e., those for the most recent epoch) by 0.″2 yr−1, so as to easily identify the moving jet knots that are observed at different epochs. The dashed arrows in the vertical direction indicate the identified moving knots. We use either black or yellow for the arrows to aid visibility. The horizontal white dotted lines in each PV diagram show the range used in making the velocity-integrated maps. Their actual numbers are shown to the right of the lines. The black circles and ellipses to the right of the individual panels show the angular and velocity resolutions.
Paper: Time-variable Jet Ejections from RW Aur A, RY Tau, and DG Tau 
Authors: Michihiro Takami, Hans Moritz Günther, P. Christian Schneider, Tracy L. Beck, Jennifer L. Karr, Youichi Ohyama, Roberto Galván-Madrid, Taichi Uyama, Marc White, Konstantin Grankin, Deirdre Coffey, Chun-Fan Liu, Misato Fukagawa, Nadine Manset, Wen-Ping Chen, Tae-Soo Pyo, Hsien Shang, Thomas P. Ray, Masaaki Otsuka, Mei-Yin Chou
Figure caption: The [Fe II] 1.644 μm peak intensities (top), the I 1.533μm/I 1.644μm intensity ratios (middle), and the I 1.600μm/I 1.644μm intensity ratios as a function of the distance to the star. See the text for the selection criteria for the plotted data. For the intensity ratios, we show the corresponding electron densities for T e = 104 K to the right of the individual panels. Some dots are associated with the horizontal error bars, based on the uncertainties tabulated in Tables 4–6. The vertical error bars are only shown when they are larger than the dots. See the text for other details.
Paper: Time-variable Jet Ejections from RW Aur A, RY Tau, and DG Tau 
Authors: Michihiro Takami, Hans Moritz Günther, P. Christian Schneider, Tracy L. Beck, Jennifer L. Karr, Youichi Ohyama, Roberto Galván-Madrid, Taichi Uyama, Marc White, Konstantin Grankin, Deirdre Coffey, Chun-Fan Liu, Misato Fukagawa, Nadine Manset, Wen-Ping Chen, Tae-Soo Pyo, Hsien Shang, Thomas P. Ray, Masaaki Otsuka, Mei-Yin Chou
Figure caption: The same as Figures 1 and 2, but for the blueshifted jet from DG Tau for seven epochs. The positions of the maps and the diagrams are offset from those at the bottom (i.e., those for the most recent epoch) by 0.″15 yr−1, so as to easily identify the moving jet knots that are observed at different epochs. The farthest bright blob seen in the 2013 data appears to be the tail of structure A, but it appears as a knot, due to the imperfect performance of the plotting tool near the edge of the FOV.
Paper: Time-variable Jet Ejections from RW Aur A, RY Tau, and DG Tau 
Authors: Michihiro Takami, Hans Moritz Günther, P. Christian Schneider, Tracy L. Beck, Jennifer L. Karr, Youichi Ohyama, Roberto Galván-Madrid, Taichi Uyama, Marc White, Konstantin Grankin, Deirdre Coffey, Chun-Fan Liu, Misato Fukagawa, Nadine Manset, Wen-Ping Chen, Tae-Soo Pyo, Hsien Shang, Thomas P. Ray, Masaaki Otsuka, Mei-Yin Chou
Figure caption: The same as Figure 6, but with the JD for the horizontal axis. In the top panels, we show the corresponding calendar years.
Paper: Time-variable Jet Ejections from RW Aur A, RY Tau, and DG Tau 
Authors: Michihiro Takami, Hans Moritz Günther, P. Christian Schneider, Tracy L. Beck, Jennifer L. Karr, Youichi Ohyama, Roberto Galván-Madrid, Taichi Uyama, Marc White, Konstantin Grankin, Deirdre Coffey, Chun-Fan Liu, Misato Fukagawa, Nadine Manset, Wen-Ping Chen, Tae-Soo Pyo, Hsien Shang, Thomas P. Ray, Masaaki Otsuka, Mei-Yin Chou
Figure caption: The same as Figure 1, but for the blueshifted jet from RY Tau for seven epochs. The positions of the maps and the diagrams are offset from those at the bottom (i.e., those for the most recent epoch) by 0.″3 yr−1, so as to easily identify the moving jet knots that are observed at different epochs.
Paper: Time-variable Jet Ejections from RW Aur A, RY Tau, and DG Tau 
Authors: Michihiro Takami, Hans Moritz Günther, P. Christian Schneider, Tracy L. Beck, Jennifer L. Karr, Youichi Ohyama, Roberto Galván-Madrid, Taichi Uyama, Marc White, Konstantin Grankin, Deirdre Coffey, Chun-Fan Liu, Misato Fukagawa, Nadine Manset, Wen-Ping Chen, Tae-Soo Pyo, Hsien Shang, Thomas P. Ray, Masaaki Otsuka, Mei-Yin Chou
Figure caption: 1D intensity distributions along the jet axis for the individual knots. We arbitrarily scale the intensity distributions and show them in chronological order, from top to bottom, with each panel being organized around an individual knot. Each of the observed distributions is shown using a black/solid gray/dashed/dotted curve in terms of the measured peak position. For some distributions without a peak (see also Tables 4–6), we determined their zero positions in the plot by using the fitted lines of the knot positions with other epochs of observations (Figure 4).
Paper: Time-variable Jet Ejections from RW Aur A, RY Tau, and DG Tau 
Authors: Michihiro Takami, Hans Moritz Günther, P. Christian Schneider, Tracy L. Beck, Jennifer L. Karr, Youichi Ohyama, Roberto Galván-Madrid, Taichi Uyama, Marc White, Konstantin Grankin, Deirdre Coffey, Chun-Fan Liu, Misato Fukagawa, Nadine Manset, Wen-Ping Chen, Tae-Soo Pyo, Hsien Shang, Thomas P. Ray, Masaaki Otsuka, Mei-Yin Chou
Figure caption: The proper motions measured for the individual knots. The dots with filled symbols are used for fitting. The solid lines show reliable fittings, while the dotted lines are tentative, due to limited epochs of observations. The error bar for each dot is not shown, as there is no straightforward definition relating to the given method of the measurements (see the text).
Paper: Time-variable Jet Ejections from RW Aur A, RY Tau, and DG Tau 
Authors: Michihiro Takami, Hans Moritz Günther, P. Christian Schneider, Tracy L. Beck, Jennifer L. Karr, Youichi Ohyama, Roberto Galván-Madrid, Taichi Uyama, Marc White, Konstantin Grankin, Deirdre Coffey, Chun-Fan Liu, Misato Fukagawa, Nadine Manset, Wen-Ping Chen, Tae-Soo Pyo, Hsien Shang, Thomas P. Ray, Masaaki Otsuka, Mei-Yin Chou
Figure caption: The number distributions of the decay timescales for the [Fe II] 1.644 μm intensity peaks. See the text for details.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: The base functions for the reduced SW model in the PC coordinate system. The base functions in this space are linear combinations of the original Legendre base functions of the SW model, obtained from the transformation matrix to the PC coordinate system. Each of the base functions corresponds to an individual PC, as labeled in the plots.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: The magnitudes of the ACF for the 19 fit parameters of the refitted SW model, plotted as a function of the time lag expressed in years. The numbers above the panels indicate the orders corresponding to the Legendre base in the SW model. The 75% confidence level bands are plotted with the red lines.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: Contributions of individual PCs of the initial SW model to the total variation, expressed in percent.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: Time series of the 19 parameters of the SW initial model transformed into the PCA space.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: Time series of the parameters of the initial SW model for the years 1985–2021 obtained from fitting.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: The left panel shows the relationship of the H α EW and temperature from LAMOST low-resolution spectral survey, in which the red line is the chromospheric activity basal value from Fang et al. (2016). The right panel shows the relationship of the S-index and LAMOST stellar temperature, where the basal lines are the chromospheric zero emission lines determined by the method of Zhao et al. (2015).
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: Distribution of stellar parameters of TESS objects, which are obtained by LAMOST low-resolution spectral survey. The left top panel is the number distribution of the effective temperature. The left bottom panel denotes the number distribution of Fe/H. The right top panel is the log g distribution. The right bottom panel illustrates the distribution of objects as spectral types.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: Examples of continuum spectrum (left panel), Hα emission line (middle panel), and EW variation of Hα (right panel) from LAMOST low-resolution spectral survey.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: The relationship between the H α EW and S-index from CaII HK lines, where the red line represents the linear fit.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: Position distribution of TESS objects observed in LAMOST low-resolution (left panel) and medium-resolution (right) spectral survey DR7. The red and blue points represent the LAMOST spectral survey and TESS survey, respectively.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: Comparisons of log g (left) and T eff (right) obtained from the TESS and LAMOST data. The line represents the best fit of the linear function.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: (a)–(l) Three-perspective views of the 3D structure and evolution of the magnetic flux tube during its emergence. (m)–(p) The isosurface of the flux tube with magnetic field strength B = 0.1B 0.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: Comparison of the SW speeds predicted using the generalized SW model (red), the SW speed model obtained in the previous work by Porowski et al. (2022; blue), and the averaged Ulysses data (black) for the three Ulysses fast latitude scans.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: The evolution of the magnetic energy (E  B , top panel), the magnetic energy flux (F EB, middle panel), and the unsigned magnetic flux (F Bu, bottom panel). The solid black line in the top panel indicates the total magnetic energy, while the dashed line indicates the injection magnetic energy through the surface, which is the sum of the shear term and the emergence term of E  B . The blue and red lines denote the shear term and the emergence term, respectively.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption:  (a)–(c) The evolution of the z-component of the magnetic field (B  z , colors) and the tangent velocities (arrows) on the surface. Panels (d)–(f) show the distribution of the shear angle θ of the emerging magnetic field on the central vertical plane (x = 0). (g)–(i) The yellow and black lines are the same as in Figure 4, while the blue and red lines show the coronal MFR at the position of minimal θ on the central vertical plane.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: The evolution of the block distribution (which contains 83 cells) during the simulation. The whole computation domain is divided into blocks of different sizes, which are shown by the grid lines. Each block further consists of 83 cells (i.e., 8 in each direction), which are not shown in the figure, because they would be too dense to show. The color indicates the distribution of the logarithm of the density ρ on the slice x = 0.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: The evolution of the height (top panel) and velocity (bottom panel) of the apex of the flux tube and the two O-points in the convection zone and corona on the central vertical plane (x = 0). The dashed line in the top panel indicates the height of the surface (z = 0.39), while the dashed line in the bottom panel indicates v  z  = 0.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: The simulation domain, with the different slices denoting the distribution of the density (x = 0) and temperature (y = 0). The flux tube is shown by the field lines.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: The vertical profiles of plasma pressure, density, and temperature, and the magnetic pressure through the central vertical line (x, y) = (0, 0).
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: SW speed data in kilometers per second obtained from IPS analysis, filtered against outliers (circles; Porowski et al. 2022), compared with the reduced SW models (blue lines) and with the generalized SW model (red lines). It is seen that, although the dimensionality of the generalized model is reduced, the SW profiles are almost identical to the initial model in most of the cases. The plots are in the ﹩\cos (\phi )﹩ space.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: Comparison of reduced χ 2 for the initial and reduced SW models as a function of ﹩\cos (\phi )﹩. The reduced SW model is built on the first nine PCs out of the 19 components obtained from the refitted SW model. Since only slight differences between the refitted and the original models are seen, it suggests that the order of the initial model is too high and that the model parameters are redundant.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: The magnitudes of χ 2 of the SW speed profile reconstruction performed using the generalized SW model with respect to the IPS data for different levels of proxy PCs’ filtering. Application of filtering levels above 3 causes deterioration of the fit quality. The filtering levels are marked below the plot; 0 means no filtering.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: The magnitudes of χ 2 of the SW speed profiles fitted to individual solar cycles (SC22, SC23, SC24), compared with a model fitted to a data set of 11 randomly selected years.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: Yearly averages of the proxies listed in Table 1 used in the final analysis.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: The ACF for the proxy PCs. The numbers above the panels indicate the PCs in descending order of their contribution to the total variation.
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: Evolution of the SW speed and density profiles resulting from the model. The white vertical lines divide the maps into the area of predicted values (i.e., based on the proxies for the outside of the IPS years 1976.5–1985.5) and the values obtained directly from the IPS analysis (1985.5–2022).
Paper: On the General Correlation between 3D Solar Wind Speed and Density Model and Solar Proxies
Authors: C. Porowski, M. Bzowski, M. Tokumaru
Figure caption: Predictions of yearly mean profiles of the SW speed for the years 1976–1984 and 2010 obtained using the generalized SW speed model (red line). The shaded area indicates the 95% confidence range.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: (a), (b) Two perspectives of the field lines traced at 20 points uniformly distributed over the height range 0.3L  s  to 0.6L  s  on the central vertical line, at t = 26. (c) With the addition of the slice y = 0. The color indicates the density of the current (J). (d) The current sheets on the central vertical plane (x = 0). The cyan line shows the streamline of the electric current of the current sheet.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: The criterion of magnetic buoyancy instability (the red line) for the front of the tube at each moment. The black line displays the variation of the magnetic field strength of the flux tube with height, while the blue line shows the stratification effect of the atmosphere.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: The evolution of the magnetic field lines of the flux tube. The transparent horizontal slice represents the solar surface.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: The evolution of the current sheet at isosurface J = 8000, with the transparent horizontal slice representing the solar surface.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: The evolution of B  x  at the Ocon-point.
Paper: Numerical Simulation of Solar Magnetic Flux Emergence Using the AMR–CESE–MHD Code
Authors: Zhipeng Liu, Chaowei Jiang, Xueshang Feng, Pingbing Zuo, Yi Wang
Figure caption: (a) The distribution of the current sheets on the central vertical plane (x = 0). (b) The isosurface of the current sheet at J = 300.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: The panel shows the relationship of EW H α and temperature from LAMOST medium-resolution spectral survey, where the red line is the activity judgment line based on the standard star catalog given by Du et al. (2019) and the standard star on the website (Vacca et al. 2003) (https://webarchive.gemini.edu/sciops/instruments/nir/specstandards/index.html/). The right panel shows a plot comparing the EWs from LAMOST mid-resolution survey (red points) and those from low-resolution survey (gray points), where the green and blue lines represent chromospheric zero emission lines of LAMOST low- and middle-resolution surveys, respectively.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: Examples of the Hα emission line, Hα variation, and radial velocity variation in long time interval medium-resolution spectra.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: Examples of the Hα emission line, Hα variation, and radial velocity variation in short time interval medium-resolution spectra.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: The left panel shows the star number with flare events. The right panel shows the rate of stars with flare events.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: Flare energy frequency of the total sample, and stars with different spectral types of FGKM.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: The relationship between ﹩{R}_{{\rm{H}}\alpha }^{{\prime} }﹩ and Rossby number.
Paper: Stellar Parameters and Spectroscopic Properties of TESS Objects Observed in the LAMOST Low- and Medium-resolution Spectral Survey
Authors: Li-yun Zhang, Tianhao Su, Prabhakar Misra, Xianming L. Han, Gang Meng, Qingfeng Pi, Jiawei Yang
Figure caption: The relationship between the H α EW and the amplitude of brightness variation, where the red line represents the linear fit.