adsabs/AstroCLIMB huggingface dataset:
Paper: Follow-up Timing of 12 Pulsars Discovered in Commensal Radio Astronomy FAST Survey
Authors: D. Zhao, J. P. Yuan, N. Wang, D. Li, P. Wang, M. Y. Xue, W. W. Zhu, C. C. Miao, W. M. Yan, J. B. Wang, J. M. Yao, Q. D. Wu, S. Q. Wang, S. N. Sun, F. F. Kou, Y. T. Chen, S. J. Dang, Y. Feng, Z. J. Liu, X. L. Miao, L. Q. Meng, M. Yuan, C. H. Niu, J. R. Niu, L. Qian, S. Wang, X. Y. Xie, Y. F. Xiao, Y. L. Yue, S. P. You, X. H. Yu, R. S. Zhao, R. Yuen, X. Zhou, L. Zhang, M. Xie, Y. X. Li, Y. B. Wang, Z. K. Luo, Z. Y. Gan, Z. Y. Sun, M. M. Chi, C. J. Wang
Figure caption: The 2DFS for the PSR J1840+2843. The left panel shows significant peaks between 0.1246 and 0.1254 cycles per period, indicating that the pulsar exhibits strong periodic intensity variations. The bottom panel is asymmetric at the 0 axis, suggesting the presence of drifting phenomena in this pulsar.
Paper: Follow-up Timing of 12 Pulsars Discovered in Commensal Radio Astronomy FAST Survey
Authors: D. Zhao, J. P. Yuan, N. Wang, D. Li, P. Wang, M. Y. Xue, W. W. Zhu, C. C. Miao, W. M. Yan, J. B. Wang, J. M. Yao, Q. D. Wu, S. Q. Wang, S. N. Sun, F. F. Kou, Y. T. Chen, S. J. Dang, Y. Feng, Z. J. Liu, X. L. Miao, L. Q. Meng, M. Yuan, C. H. Niu, J. R. Niu, L. Qian, S. Wang, X. Y. Xie, Y. F. Xiao, Y. L. Yue, S. P. You, X. H. Yu, R. S. Zhao, R. Yuen, X. Zhou, L. Zhang, M. Xie, Y. X. Li, Y. B. Wang, Z. K. Luo, Z. Y. Gan, Z. Y. Sun, M. M. Chi, C. J. Wang
Figure caption: Pulse energy distributions for the on-pulse (black solid histogram) and off-pulse (red dashed histogram) regions for five pulsars. The energies are normalized by the mean on-pulse energy.
Paper: Follow-up Timing of 12 Pulsars Discovered in Commensal Radio Astronomy FAST Survey
Authors: D. Zhao, J. P. Yuan, N. Wang, D. Li, P. Wang, M. Y. Xue, W. W. Zhu, C. C. Miao, W. M. Yan, J. B. Wang, J. M. Yao, Q. D. Wu, S. Q. Wang, S. N. Sun, F. F. Kou, Y. T. Chen, S. J. Dang, Y. Feng, Z. J. Liu, X. L. Miao, L. Q. Meng, M. Yuan, C. H. Niu, J. R. Niu, L. Qian, S. Wang, X. Y. Xie, Y. F. Xiao, Y. L. Yue, S. P. You, X. H. Yu, R. S. Zhao, R. Yuen, X. Zhou, L. Zhang, M. Xie, Y. X. Li, Y. B. Wang, Z. K. Luo, Z. Y. Gan, Z. Y. Sun, M. M. Chi, C. J. Wang
Figure caption: Integrated polarization profiles and viewing geometry of PSR J1602−0611, PSR J1854−0514, and PSR J1907−1018. The points in the upper panel of each subplot are the polarization PAs, and the errors are given. The red line on the upper panel represents the best fit result of the RVM model. Polarization PA of four pulsars is >4 times the PA errors.
Paper: Follow-up Timing of 12 Pulsars Discovered in Commensal Radio Astronomy FAST Survey
Authors: D. Zhao, J. P. Yuan, N. Wang, D. Li, P. Wang, M. Y. Xue, W. W. Zhu, C. C. Miao, W. M. Yan, J. B. Wang, J. M. Yao, Q. D. Wu, S. Q. Wang, S. N. Sun, F. F. Kou, Y. T. Chen, S. J. Dang, Y. Feng, Z. J. Liu, X. L. Miao, L. Q. Meng, M. Yuan, C. H. Niu, J. R. Niu, L. Qian, S. Wang, X. Y. Xie, Y. F. Xiao, Y. L. Yue, S. P. You, X. H. Yu, R. S. Zhao, R. Yuen, X. Zhou, L. Zhang, M. Xie, Y. X. Li, Y. B. Wang, Z. K. Luo, Z. Y. Gan, Z. Y. Sun, M. M. Chi, C. J. Wang
Figure caption: The mean pulse profiles of the two distinct modes of PSR J1854−0514.
Paper: Complex Organics Surrounding the FU Ori–type Object V1057 Cyg Indicative of Sublimated Ices
Authors: Jenny K. Calahan, Edwin A. Bergin, Merel van't Hoff, Alice S. Booth, Karin Öberg, Ke Zhang, Nuria Calvet, Lee Hartmann
Figure caption: Column densities of CH3OH in V1057 Cyg (based on five transitions) and V2472 Cyg (based on two transitions) and derived upper limits from the nondetections toward the three other sources (top). The ratio between the CH3OH column density or upper limit and a derived H2CO column density (middle) and C17O column density (bottom). Stars indicate that detected line(s) are used to determine the column density. A triangle indicates an upper limit, and a diamond utilized both an upper limit on the methanol and a H2CO column density based on just two transitions.
Paper: Complex Organics Surrounding the FU Ori–type Object V1057 Cyg Indicative of Sublimated Ices
Authors: Jenny K. Calahan, Edwin A. Bergin, Merel van't Hoff, Alice S. Booth, Karin Öberg, Ke Zhang, Nuria Calvet, Lee Hartmann
Figure caption: An example of the spectra of the central pixel of each source between 218.2 and 219 GHz. This region shows how V1057 Cyg is markedly more line rich than each of the other sources.
Paper: Complex Organics Surrounding the FU Ori–type Object V1057 Cyg Indicative of Sublimated Ices
Authors: Jenny K. Calahan, Edwin A. Bergin, Merel van't Hoff, Alice S. Booth, Karin Öberg, Ke Zhang, Nuria Calvet, Lee Hartmann
Figure caption: The full lower and upper sideband coverage of V1057 Cyg. Lines identified with a question mark are tentative detections, mostly due to only one transition identified and it being a rare molecule to be detected in protoplanetary disks.
Paper: Complex Organics Surrounding the FU Ori–type Object V1057 Cyg Indicative of Sublimated Ices
Authors: Jenny K. Calahan, Edwin A. Bergin, Merel van't Hoff, Alice S. Booth, Karin Öberg, Ke Zhang, Nuria Calvet, Lee Hartmann
Figure caption: Column density ratios across protostars, outbursting sources, a protoplanetary disk, and abundance ratio from a comet of molecules with respect to CH3OH. IRAS 16293-2422 is a binary system, and both A and B are plotted along the same x-value.
Paper: Stacking and Analyzing MOSDEF Galaxies by Spectral Types: Implications for Dust Geometry and Galaxy Evolution
Authors: Brian Lorenz, Mariska Kriek, Alice E. Shapley, Ryan L. Sanders, Alison L. Coil, Joel Leja, Bahram Mobasher, Erica Nelson, Sedona H. Price, Naveen A. Reddy, Jordan N. Runco, Katherine A. Suess, Irene Shivaei, Brian Siana, Daniel R. Weisz
Figure caption: Overview of basic properties of the galaxy groups (color, with the same size and symbols as Figure 3) compared to the individual galaxies (gray). Top left: UVJ diagram. Galaxies follow the expected mass trend, with mass increasing toward the upper right, but the highest-mass group is lower in V − J and moving toward the quiescent box. Top right: sSFR vs. stellar mass, with SFR derived from Hα. Individual galaxies are only shown if the have a 3σ detection in Hα. Our trend is in strong agreement with the trends found by J. Leja et al. (2022) using SED SFRs from 3D-HST. Bottom left: BPT diagram, along with the L. J. Kewley et al. (2013) line (black) and A. E. Shapley et al. (2015) fit (gray) to MOSDEF galaxies. Our composite SEDs are in strong agreement with this fit, and they follow the expected trend with mass increasing toward the lower right. Bottom right: metallicity vs. mass, with a comparison to the MOSDEF z = 1.5 relation from M. W. Topping et al. (2021; dotted line) and MOSDEF z = 2.3 relation from R. L. Sanders et al. (2018; dashed line) for the individual MOSDEF galaxies. Our sample, with mean z = 1.9, falls between these lines. In the BPT and mass–metallicity diagrams, we only show individual galaxies with 3σ detections in all four lines.
Paper: Stacking and Analyzing MOSDEF Galaxies by Spectral Types: Implications for Dust Geometry and Galaxy Evolution
Authors: Brian Lorenz, Mariska Kriek, Alice E. Shapley, Ryan L. Sanders, Alison L. Coil, Joel Leja, Bahram Mobasher, Erica Nelson, Sedona H. Price, Naveen A. Reddy, Jordan N. Runco, Katherine A. Suess, Irene Shivaei, Brian Siana, Daniel R. Weisz
Figure caption: Overview of properties for the 20 galaxy groups, sorted by the median mass of the galaxies in the group. For each group, from left to right we show: (a) Composite SED points (color) and all contributing galaxy SEDs (gray). The composite SEDs are normalized for viewing such that flux is 1 at 5000 Å. We also show the number of galaxies in the group (N) and average similarity (S) between the individual galaxy SEDs and composite; (b) stacked spectrum, zoomed on emission-line regions. For viewing, the spectra are normalized such that peak Hα flux is 1; (c) SFR vs. mass, with lines of constant sSFR shown (yellow). The number of galaxies in the group with Hα and Hβ detections is listed in the top left; (d) UVJ diagram, showing the top-left enclosed region for quiescent galaxies; and (e) BPT diagram, with the L. J. Kewley et al. (2013) line (black) and A. E. Shapley et al. (2015) MOSDEF fit (gray) shown. In the top-right we list the number of galaxies in the group with 3σ detections on all four emission lines. For (c), (d), and (e), we show the entire sample used in this work (gray) with reliable measurements, the galaxies in a particular group (black), and the measurement from the composite SED and stacked spectrum (colored symbol). Points representing the group in panels (c), (d), and (e) scale in size with the number of galaxies in the group and are colored by mass (see Figure 3). These points will remain consistent throughout the paper. (a) The next seven groups, sorted by sSFR. Note that group eight has lower limits on its SFR measurement due to noisy Hβ. (b) The final seven groups, sorted by sSFR. Note that groups 19 and 20 have lower limits on their SFR measurements, and their Hβ lines are not perceptible above the noise.
Paper: Stacking and Analyzing MOSDEF Galaxies by Spectral Types: Implications for Dust Geometry and Galaxy Evolution
Authors: Brian Lorenz, Mariska Kriek, Alice E. Shapley, Ryan L. Sanders, Alison L. Coil, Joel Leja, Bahram Mobasher, Erica Nelson, Sedona H. Price, Naveen A. Reddy, Jordan N. Runco, Katherine A. Suess, Irene Shivaei, Brian Siana, Daniel R. Weisz
Figure caption: Prospector SFR derived from composite SEDs vs. Balmer decrement-corrected Hα SFR from the stacked spectra. Point size scales with the number of galaxies in the group, squares denote the three groups for which we have insignificant Hβ measurements, and points are colored by stellar mass. A one-to-one line is shown in red, suggesting reasonable agreement in the SFR predicted by the SED and measured by dust-corrected Hα. Group 20 has a much higher Hα SFR than SED-based SFR, potentially indicating a nonstellar contribution to Hα.
Paper: Stacking and Analyzing MOSDEF Galaxies by Spectral Types: Implications for Dust Geometry and Galaxy Evolution
Authors: Brian Lorenz, Mariska Kriek, Alice E. Shapley, Ryan L. Sanders, Alison L. Coil, Joel Leja, Bahram Mobasher, Erica Nelson, Sedona H. Price, Naveen A. Reddy, Jordan N. Runco, Katherine A. Suess, Irene Shivaei, Brian Siana, Daniel R. Weisz
Figure caption: Top row: stellar A V (derived from Prospector composite SED fits) vs. mass (left), SFR (center), and metallicity (right) for the 20 galaxy groups. Bottom row: nebular A V (derived from stacked-spectra Balmer decrement) vs. mass (left), SFR (center), and metallicity (right). Symbols and colors are the same as in Figure 3. Correlation coefficients are listed in the top left of each panel. For the nebular A V vs. mass and SFR (lower left and lower middle), we also show linear fits (black dashed line) and corresponding bootstrapped one-sigma uncertainties (gray shaded region). For the lower-middle panel, uncertainties are shown as ellipses due to the dependence of SFR on nebular A V. We also compare our findings with A. E. Shapley et al. (2022; black squares) and J. N. Runco et al. (2022; gray diamonds) in the lower-left panel. We see a clear trend of stellar A V increasing with increasing mass, and a potential turnover at high masses. For nebular A V, we find tight relations with increasing mass and SFR.
Paper: Stacking and Analyzing MOSDEF Galaxies by Spectral Types: Implications for Dust Geometry and Galaxy Evolution
Authors: Brian Lorenz, Mariska Kriek, Alice E. Shapley, Ryan L. Sanders, Alison L. Coil, Joel Leja, Bahram Mobasher, Erica Nelson, Sedona H. Price, Naveen A. Reddy, Jordan N. Runco, Katherine A. Suess, Irene Shivaei, Brian Siana, Daniel R. Weisz
Figure caption: SFR vs. mass for the composite groups, color-coded by nebular attenuation. Point sizes scale with the number of galaxies in the group, as in Figure 3. The gray squares have both lower limits on SFR and on A V,neb. Nebular attenuation increases along the star-forming sequence, toward the upper right.
Paper: Stacking and Analyzing MOSDEF Galaxies by Spectral Types: Implications for Dust Geometry and Galaxy Evolution
Authors: Brian Lorenz, Mariska Kriek, Alice E. Shapley, Ryan L. Sanders, Alison L. Coil, Joel Leja, Bahram Mobasher, Erica Nelson, Sedona H. Price, Naveen A. Reddy, Jordan N. Runco, Katherine A. Suess, Irene Shivaei, Brian Siana, Daniel R. Weisz
Figure caption:  Prospector fits to all 20 composite SED groups, ordered and colored by stellar mass (see Figure 4). The Prospector 16th to 84th percentile fit is indicated by the shaded gray region. The regions left of 1500 Å (red) are not included in the fits due to Lyα forest absorption.
Paper: Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors
Authors: Berthy T. Feng, Katherine L. Bouman, William T. Freeman
Figure caption: Image reconstructions from simulated data. A sample (one sample from each mode if the posterior is bimodal) is shown from each estimated posterior. Qualitatively, the CIFAR-10 prior adds the least amount of bias, producing reasonable reconstructions of each image in this data set. The GRMHD prior strongly prefers a centered ring in the image. The RIAF prior prefers a centered ring- or disklike structure in the image. The CelebA prior struggles to recover these source images, in some cases adding face features, and it leads to the most multimodal posteriors. However, it performs decently well on certain images like the Crescent and GRMHD images. When the source image is known to be well approximated by a GRMHD or RIAF model, the more constrained GRMHD or RIAF prior may be the best choice.
Paper: Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors
Authors: Berthy T. Feng, Katherine L. Bouman, William T. Freeman
Figure caption: Reducing the CIFAR-10 bias toward horizontal lines and vertical lines. For example, given simulated data of the Crescent image from Figure 3, this bias results in posterior images containing a boxy object, even though the actual Crescent is a ring without any straight edges. This is likely due to the statistics of the CIFAR-10 data set, which contains mostly man-made objects and animals. Such images include many sharp corners and lines arising from boxy objects like cars, the legs of standing animals, or horizon lines. Although CIFAR-10 is our choice of a generic natural-image prior, it is possible to define an alternative natural-image prior with less preference for vertically or horizontally oriented edges. We tested a prior trained on CIFAR-10 images that underwent warped random affine transforms and a prior trained on 32 × 32 images with power spectral density proportional to 1/f 2 (since the power spectra of natural images have been shown to follow a 1/f  α  trend, where f is the spatial frequency in cycles per image (A. van der Schaaf & J. van Hateren 1996), and α is typically between 1 and 3). The CIFAR-10, Warped CIFAR-10, and 1/f 2 priors were all trained with the same number of training images (45K), with the same tapering effect described in Section 3.1, and for the same number of iterations (100K). (a) Nine training samples and the average log power spectrum of 10K training samples (without the taper) for each prior. The average spectral power of CIFAR-10 images is relatively high in the horizontal and vertical frequencies. Warping the CIFAR-10 images seems to reduce the preference for vertical frequencies, but a large presence of horizontal frequencies remains (perhaps in part because horizons are still distinguishable after warping, as can be seen in some of the training samples). The 1/f 2 noise images have isotropically distributed spectral power. (b) Results of imaging the Crescent simulated data under the different priors. A posterior sample and the average of 128 posterior samples are shown for each prior. With the regular CIFAR-10 prior, there is a sharp corner at the top right of the ringlike object that makes it look squarish. This artifact is not present in the Warped CIFAR-10 reconstructions, which more resemble a smooth ring. The 1/f 2 prior, which does not have a preference for any frequency orientation, also recovers an object that resembles a smooth ring.
Paper: Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors
Authors: Berthy T. Feng, Katherine L. Bouman, William T. Freeman
Figure caption: Method illustration. The CIFAR-10 prior was used for these examples; images are shown as 32 × 32 pixels on a [0, 1] scale. At a high level, we optimize a variational distribution q  ϕ  to approximate the image posterior p  θ ( · ∣ y ) given a score-based prior p  θ  and log likelihood based on EHT measurements. Panel (a) illustrates our particular variational distribution: a RealNVP with parameters ϕ. At each optimization iteration i, the measurement log likelihood (Equation (2)) and the log density under the score-based prior of each sample  x  from ﹩{q}_{\phi }={q}_{{\phi }^{(i)}}﹩ are evaluated. The average gradient is computed with respect to ϕ to update ϕ (i). In other words, q  ϕ  is optimized to produce samples that have high probability under both measurement likelihood and prior. Panel (b) zooms in to the score-based prior. A score-based prior is based on a score-based diffusion model, a deep generative model with parameters θ, that is trained on images from a target prior. Once trained, the diffusion model generates samples from a generative image distribution p  θ . There is an analytical formula for computing the ELBO b  θ ( x ) of the log probability ﹩\mathrm{log}{p}_{\theta }({\boldsymbol{x}})﹩ for any image  x , even for out-of-distribution images and images of pure noise.
Paper: Stacking and Analyzing MOSDEF Galaxies by Spectral Types: Implications for Dust Geometry and Galaxy Evolution
Authors: Brian Lorenz, Mariska Kriek, Alice E. Shapley, Ryan L. Sanders, Alison L. Coil, Joel Leja, Bahram Mobasher, Erica Nelson, Sedona H. Price, Naveen A. Reddy, Jordan N. Runco, Katherine A. Suess, Irene Shivaei, Brian Siana, Daniel R. Weisz
Figure caption: Symbols and colors are the same as in Figure 3. Left: nebular A V vs. stellar A V. The properties are well correlated, with nebular A V being larger than stellar A V by roughly a factor of 2 for all groups with Hβ detections. Middle: nebular A V—stellar A V (A V excess) vs. mass. Right: A V excess vs. SFR. Uncertainties are shown as error ellipses due to the dependence of nebular A V on SFR. A V excess is more strongly related with SFR than with mass. This SFR dependence of A V excess is in agreement with N. A. Reddy et al. (2015). The strong correlation with SFR suggests that nebular attenuation may be dominated by a different component than stellar attenuation, and the relative importance of these components changes with galaxy SFR.
Paper: Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors
Authors: Berthy T. Feng, Katherine L. Bouman, William T. Freeman
Figure caption: M87* posterior samples. A random posterior image is shown for each observation day and prior. The CIFAR-10 prior was trained on images of everyday objects and makes no assumptions of black hole structure, yet it recovers a ringlike structure for all four observation days. The GRMHD prior assumes a fluid-flow model of black holes, which helps it recover visually striking images of a thin ring with wisps. The RIAF prior assumes a simplified crescent model of black holes, which results in simplified crescent images of M87*. The CelebA prior was trained on images of human faces, so its preferred images are presumably far away from the true source image. Even with its incorrect and strong biases, the CelebA prior recovers a ringlike structure, here favoring an eye from the face prior to explain the ring. These images under various priors all fit the EHT observations but incorporate different visual biases.
Paper: Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors
Authors: Berthy T. Feng, Katherine L. Bouman, William T. Freeman
Figure caption: Mean and std. dev. of simulated-data posteriors. We find that uncertainty decreases with a stronger prior (i.e., maximum std. dev. decreases from CIFAR-10 to GRMHD to RIAF). CIFAR-10 exhibits the most uncertainty given that it is the most flexible of the priors. Compared to the individual samples in Figure 3, the mean images appear much cleaner.
Paper: Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors
Authors: Berthy T. Feng, Katherine L. Bouman, William T. Freeman
Figure caption: Score-based priors used in this work. Nine samples from each learned prior are shown.
Paper: Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors
Authors: Berthy T. Feng, Katherine L. Bouman, William T. Freeman
Figure caption: Mean and std. dev. of simulated-data posteriors under the CelebA prior. The CelebA prior is the only one that gives rise to bimodal posteriors. For each posterior, a one- or two-component Gaussian mixture model (one for a single-mode posterior and two for a bimodal posterior) was fit to 128 samples. The mean, pixel-wise std. dev., and weight of each Gaussian component are shown. For the Ring, Double, and GRMHD 1 data, one of the two modes is quite similar to the ground-truth image, while the other is not.
Paper: No Redshift Evolution in the Fe II/Mg II Flux Ratios of Quasars across Cosmic Time
Authors: Danyang Jiang, Masafusa Onoue, Linhua Jiang, Samuel Lai, Eduardo Bañados, George D. Becker, Manuela Bischetti, Sarah E. I. Bosman, Rebecca L. Davies, Valentina D'Odorico, Emanuele Paolo Farina, Martin G. Haehnelt, Chiara Mazzucchelli, Jan-Torge Schindler, Fabian Walter, Yongda Zhu
Figure caption: Fe II/Mg II line flux ratios at redshift from z = 0 to 7. The top panel shows the observed flux ratios. The middle panel shows the same ratios after correcting the Eddington ratio dependence (see details in Section 4.2). The bottom panel shows the median and ±1σ scatter of each sample. The filled symbols show the samples analyzed in this work (red: E-XQR-30, green: XQ-100, blue: low-redshift SDSS), and the open symbols show the samples in the literature. The different colors and symbols are described in the legend on the top. The subpanels in the lower right corners of the top and middle panels show the typical measurement errors in the logarithmic scale. The gray contours (with a step of 0.2 dex in the logarithmic scale) and gray dots represent the low-redshift sample of H. Sameshima et al. (2017). Their median Fe II/Mg II flux ratios at six redshift bins (a step of Δz = 0.15) are shown as the black crosses. Those with Eddington ratios over 0.9 are shown as the purple dots, and the median of this subsample is shown as the purple cross. The dashed line and its shaded region are the median value of the SDSS sample and its ±1σ range as our baseline at low redshift. The figure shows no apparent evolution of the line flux ratio with redshift.
Paper: No Redshift Evolution in the Fe II/Mg II Flux Ratios of Quasars across Cosmic Time
Authors: Danyang Jiang, Masafusa Onoue, Linhua Jiang, Samuel Lai, Eduardo Bañados, George D. Becker, Manuela Bischetti, Sarah E. I. Bosman, Rebecca L. Davies, Valentina D'Odorico, Emanuele Paolo Farina, Martin G. Haehnelt, Chiara Mazzucchelli, Jan-Torge Schindler, Fabian Walter, Yongda Zhu
Figure caption: Correlation between the Eddington ratio and Fe II/Mg II line flux ratio. The upper panel shows the observed correlation and the lower panel shows the correlation after correcting for the dependence of the Eddington ratio (Section 4.2). The symbols and colors are the same as in Figure. 4. The side panels show the normalized histograms. The dashed lines are the linear regressions of the shown data points, and the results are log(Fe II/Mg II) = 0.26 × log(L bol/L Edd)+0.77 in the upper panel and log(Fe II/Mg II)c = −0.02 × log(L bol/L Edd)+0.64 in the lower panel. The uncertainty ranges of the linear regressions are obtained by the least-square method, and shown as the shaded regions. The weak negative slope of corrected Fe II/Mg II in the lower panel is insignificant.