adsabs/AstroCLIMB huggingface dataset:
Paper: Accretion Flow Properties of Swift J1727.8–1613 during Its Rising Phase of the Discovery Outburst: Estimation of Mass from Spectrotemporal Study
Authors: Dipak Debnath, Hsiang-Kuang Chang, Sujoy Kumar Nath, Lev Titarchuk
Figure caption: The variation of QPO frequency (νQPO) with (a) SXR (2–4 keV) count rate, (b) photon index (Γ), and (c) HR, defined as the ratio of HXR (2–150 keV) to SXR rates, is shown. In panel (d), the variation of HR with Γ is presented. The power-law model (y = axb), referred to as M1, is used to obtain a crude fit to the correlations (shown as dashed curves). We further fitted the νQPO–Γ correlation using the scaling relation of Equation (6), referred to as M2, and the HR correlations with νQPO and Γ using Equation (8), referred to as M3 (shown as solid curves). In both the M2 and M3 models, the parameter D was frozen at unity.
Paper: Accretion Flow Properties of Swift J1727.8–1613 during Its Rising Phase of the Discovery Outburst: Estimation of Mass from Spectrotemporal Study
Authors: Dipak Debnath, Hsiang-Kuang Chang, Sujoy Kumar Nath, Lev Titarchuk
Figure caption: Photon index (Γ) vs. QPO frequency (νQPO) correlation scaling for the estimation of the mass of BHC Swift J1727.8–1613 using GRO J1655–40 as the known (MBH = 6.3 ± 0.5 M⊙) reference source. Using model-fitted (Equation (6) with parameter D fixed at 1) ﹩{\nu }_{\mathrm{tr}}﹩ values of GRO J1655–40 and Swift J1727.8–1613, the mass of the unknown BHC Swift J1727.8–1613 is estimated to be 13.5 ± 1.9 M⊙. For GRO J1655–40, νQPO and Γ values are adopted from the rising phase data of the 2005 outburst (see S. K. Chakrabarti et al. 2008; D. Debnath et al. 2008).
Paper: Accretion Flow Properties of Swift J1727.8–1613 during Its Rising Phase of the Discovery Outburst: Estimation of Mass from Spectrotemporal Study
Authors: Dipak Debnath, Hsiang-Kuang Chang, Sujoy Kumar Nath, Lev Titarchuk
Figure caption: (a) Fourier-transformed PDSs of the 0.01 s time-binned 10–30 keV HXMT/ME light curves from six observations selected from six different parts of the rising phase (points enclosed in red squares in Figure 1(c)). (b) Detailed Lorentzian model-fitted total (solid red curve) and components (two zero-centric and three QPO-centric; dashed curves) for ObsID = P061433800601.
Paper: Accretion Flow Properties of Swift J1727.8–1613 during Its Rising Phase of the Discovery Outburst: Estimation of Mass from Spectrotemporal Study
Authors: Dipak Debnath, Hsiang-Kuang Chang, Sujoy Kumar Nath, Lev Titarchuk
Figure caption: Broadband spectral fits using Insight-HXMT LE (2–10 keV), ME (10–35 keV), and HE (33–150 keV) data with the tbabs (diskbb+pexrav) model for six representative spectra, each selected from a different part of the rising phase of the 2023–24 outburst of Swift J1727.8−1613.
Paper: Impact of Multimessenger Spectral Modeling on Blazar–Neutrino Associations
Authors: Julian Kuhlmann, Francesca Capel
Figure caption: Analysis of TXS 0506+056 using a power law. The color of dots and lines reflects the posterior-averaged event association probability to TXS 0506+056. Left panel: scatter plots of analyzed events, projected onto the sky. The dots’ size is not connected to energy or angular uncertainty. ROI is centered on TXS, marked by a cross. The alert event IC 170922A is marked by a red circle. Right panel: marginalized neutrino energy posteriors of all events, transformed to ﹩{\mathrm{log}}_{10}({E}_{\nu }/{\rm{GeV}})﹩. The upper axis shows the reconstructed muon energy of events, ﹩\hat{E}﹩. The reconstructed energy and energy posterior of IC 170922A are linked by a dashed line.
Paper: Impact of Multimessenger Spectral Modeling on Blazar–Neutrino Associations
Authors: Julian Kuhlmann, Francesca Capel
Figure caption: Analysis of TXS 0506+056 using the pγ spectrum. Colored bands are 50%, 68%, and 95% credible regions of fluxes. Dark blue, green, and yellow closed contours are 50%, 68%, and 95% credible regions of joint posterior density of Epeak and peak energy flux. Gray line is best-fitting neutrino flux found using SkyLLH, dashed contours are 68% confidence level on Epeak and peak energy flux. Red line is neutrino flux prediction. Left panel: uninformative priors. Right panel: informative Epeak prior. All energies are defined in the detector frame.
Paper: Impact of Multimessenger Spectral Modeling on Blazar–Neutrino Associations
Authors: Julian Kuhlmann, Francesca Capel
Figure caption: Comparison of fits to TXS 0506+056 with different models and priors. Top panel: posterior of expected number of events. Dashed lines show the posterior means. Bottom panel: energy posterior of IC 170922A. Dashed lines show the geometric means of the posteriors.
Paper: Impact of Multimessenger Spectral Modeling on Blazar–Neutrino Associations
Authors: Julian Kuhlmann, Francesca Capel
Figure caption: Joint ﹩\bar{n}﹩ and γ posterior. Filled contours show 68%, 90%, and 95% credible regions from darkest to lightest. Black contours show 68%, 90%, and 95% confidence levels found with SkyLLH. The MLE is marked by a black cross. Top and right panels show marginalized posterior densities of the same credibilities. Black errorbars show MLE and 1σ uncertainties found with SkyLLH.
Paper: Impact of Multimessenger Spectral Modeling on Blazar–Neutrino Associations
Authors: Julian Kuhlmann, Francesca Capel
Figure caption: The contribution to the diffuse flux of the 29 blazars considered here. Also shown are the diffuse fluxes of R. Abbasi et al. (2022b), R. Abbasi et al. (2024), and KM3NeT Collaboration et al. (2025a, derived from the KM3–230213A event) and upper limits of R. Abbasi et al. (2025c).
Paper: Impact of Multimessenger Spectral Modeling on Blazar–Neutrino Associations
Authors: Julian Kuhlmann, Francesca Capel
Figure caption: Top panel: averaged pγ spectrum (blue) and approximation used in this work (orange). Bottom panel: ratio of pγ and approximation.
Paper: Impact of Multimessenger Spectral Modeling on Blazar–Neutrino Associations
Authors: Julian Kuhlmann, Francesca Capel
Figure caption: Point-source energy fluxes. Filled bands show the 68% and 95% credible regions of energy flux using an uninformative prior on the peak energy Epeak (blue) and an informative prior (orange). Solid and dashed lines show the 68% and 95% credible regions of the joint peak energy and peak energy flux posterior.
Paper: Impact of Multimessenger Spectral Modeling on Blazar–Neutrino Associations
Authors: Julian Kuhlmann, Francesca Capel
Figure caption: Marginalized posteriors of high-level point-source parameters. Top (bottom) panels show posteriors obtained with the uninformative (informative) Epeak prior. Prior distributions are shown in gray, where applicable. Epeak is defined in the source frame.
Paper: How Does Feedback Affect the Star Formation Histories of Galaxies?
Authors: Kartheik G. Iyer, Tjitske K. Starkenburg, Greg L. Bryan, Rachel S. Somerville, Juan Pablo Alfonzo, Daniel Anglés-Alcázar, Suchetha Cooray, Romeel Davé, Austen Gabrielpillai, Shy Genel, Sultan Hassan, Lars Hernquist, Christian Kragh Jespersen, Christopher C. Lovell, Boon Kiat Oh, Camilla Pacifici, Lucia A. Perez, Laura Sommovigo, Joshua S. Speagle, 佳士 沈, Sandro Tacchella, Megan T. Tillman, Francisco Villaescusa-Navarro, John F. Wu
Figure caption: Variation in the average SFHs of 100 randomly selected galaxies with stellar masses 109.5 < M* < 1011.5M⊙ caused by varying the cosmology and feedback strengths across the three CAMELS models (ASTRID, TNG, and SIMBA), predicted using the trained normalizing flows. Solid lines and shaded regions show the median SFH and corresponding 1σ uncertainties from the bootstrap sampling used to train the normalizing flow. While some parameters can cause large variations (e.g., ASN2 in TNG), others do not affect the SFHs nearly as much (e.g., AAGN1 in ASTRID).
Paper: How Does Feedback Affect the Star Formation Histories of Galaxies?
Authors: Kartheik G. Iyer, Tjitske K. Starkenburg, Greg L. Bryan, Rachel S. Somerville, Juan Pablo Alfonzo, Daniel Anglés-Alcázar, Suchetha Cooray, Romeel Davé, Austen Gabrielpillai, Shy Genel, Sultan Hassan, Lars Hernquist, Christian Kragh Jespersen, Christopher C. Lovell, Boon Kiat Oh, Camilla Pacifici, Lucia A. Perez, Laura Sommovigo, Joshua S. Speagle, 佳士 沈, Sandro Tacchella, Megan T. Tillman, Francisco Villaescusa-Navarro, John F. Wu
Figure caption: Similar to Figure 4, but breaking down the variations in the average SFHs for 100 galaxies within 0.5 dex halo mass bins predicted with the trained normalizing flows for parameter variations across CAMELS/TNG. Note that, in contrast to Figure 4, the y-scale in these plots is logarithmic to account for the increased dynamic range in the SFHs. The various curves in each panel show the average SFHs for different values of each parameter, with darker colors indicating higher values. There is increased shot noise in the higher-mass bins, where the galaxies tend to be poorly sampled due to the limited volume of the CAMELS boxes.
Paper: How Does Feedback Affect the Star Formation Histories of Galaxies?
Authors: Kartheik G. Iyer, Tjitske K. Starkenburg, Greg L. Bryan, Rachel S. Somerville, Juan Pablo Alfonzo, Daniel Anglés-Alcázar, Suchetha Cooray, Romeel Davé, Austen Gabrielpillai, Shy Genel, Sultan Hassan, Lars Hernquist, Christian Kragh Jespersen, Christopher C. Lovell, Boon Kiat Oh, Camilla Pacifici, Lucia A. Perez, Laura Sommovigo, Joshua S. Speagle, 佳士 沈, Sandro Tacchella, Megan T. Tillman, Francisco Villaescusa-Navarro, John F. Wu
Figure caption: Similar to Figure 5, but for CAMELS/ASTRID.
Paper: How Does Feedback Affect the Star Formation Histories of Galaxies?
Authors: Kartheik G. Iyer, Tjitske K. Starkenburg, Greg L. Bryan, Rachel S. Somerville, Juan Pablo Alfonzo, Daniel Anglés-Alcázar, Suchetha Cooray, Romeel Davé, Austen Gabrielpillai, Shy Genel, Sultan Hassan, Lars Hernquist, Christian Kragh Jespersen, Christopher C. Lovell, Boon Kiat Oh, Camilla Pacifici, Lucia A. Perez, Laura Sommovigo, Joshua S. Speagle, 佳士 沈, Sandro Tacchella, Megan T. Tillman, Francisco Villaescusa-Navarro, John F. Wu
Figure caption: Interactions between different feedback and cosmology channels (thicker lines) can sometimes affect the SFHs beyond the linear additive effects of variations in the individual parameters (thin dashed lines). The three examples illustrate the effects of the interactions between the galactic wind parameters (ASN1 and ASN2) in TNG (top), between cosmology and feedback (Ωm and ASN1) in SIMBA (middle), and between different modes of feedback (ASN2 and AAGN2) in ASTRID (bottom). These interactions show one example from each model of the nonlinear effects, indicating the need to go beyond simply studying one-parameter variations to understand the full effects of feedback. A fuller treatment of this for all combinations of parameters can be found in Appendix B.
Paper: How Does Feedback Affect the Star Formation Histories of Galaxies?
Authors: Kartheik G. Iyer, Tjitske K. Starkenburg, Greg L. Bryan, Rachel S. Somerville, Juan Pablo Alfonzo, Daniel Anglés-Alcázar, Suchetha Cooray, Romeel Davé, Austen Gabrielpillai, Shy Genel, Sultan Hassan, Lars Hernquist, Christian Kragh Jespersen, Christopher C. Lovell, Boon Kiat Oh, Camilla Pacifici, Lucia A. Perez, Laura Sommovigo, Joshua S. Speagle, 佳士 沈, Sandro Tacchella, Megan T. Tillman, Francisco Villaescusa-Navarro, John F. Wu
Figure caption: Motivation: the star formation histories (SFHs) of galaxies act as tracers of the overall gas regulation, which depends sensitively on the adopted prescriptions and strengths of stellar and AGN feedback. By analyzing how the shape of the average SFH at a given mass (described using normalization ϕ, peak/width τ, and rising and falling slopes α, β) depends on the strength and nature of the feedback parameters in CAMELS, we aim to quantify their effects on galaxy evolution.
Paper: How Does Feedback Affect the Star Formation Histories of Galaxies?
Authors: Kartheik G. Iyer, Tjitske K. Starkenburg, Greg L. Bryan, Rachel S. Somerville, Juan Pablo Alfonzo, Daniel Anglés-Alcázar, Suchetha Cooray, Romeel Davé, Austen Gabrielpillai, Shy Genel, Sultan Hassan, Lars Hernquist, Christian Kragh Jespersen, Christopher C. Lovell, Boon Kiat Oh, Camilla Pacifici, Lucia A. Perez, Laura Sommovigo, Joshua S. Speagle, 佳士 沈, Sandro Tacchella, Megan T. Tillman, Francisco Villaescusa-Navarro, John F. Wu
Figure caption: Similar to Figure 5, but for CAMELS/SIMBA.
Paper: How Does Feedback Affect the Star Formation Histories of Galaxies?
Authors: Kartheik G. Iyer, Tjitske K. Starkenburg, Greg L. Bryan, Rachel S. Somerville, Juan Pablo Alfonzo, Daniel Anglés-Alcázar, Suchetha Cooray, Romeel Davé, Austen Gabrielpillai, Shy Genel, Sultan Hassan, Lars Hernquist, Christian Kragh Jespersen, Christopher C. Lovell, Boon Kiat Oh, Camilla Pacifici, Lucia A. Perez, Laura Sommovigo, Joshua S. Speagle, 佳士 沈, Sandro Tacchella, Megan T. Tillman, Francisco Villaescusa-Navarro, John F. Wu
Figure caption: Changes in the average SFHs of galaxies with variations in the double power-law parameters τ (peak/width), α (falling slope), β (rising slope), and ϕ (overall normalization), as described in Equation (13).
Paper: How Does Feedback Affect the Star Formation Histories of Galaxies?
Authors: Kartheik G. Iyer, Tjitske K. Starkenburg, Greg L. Bryan, Rachel S. Somerville, Juan Pablo Alfonzo, Daniel Anglés-Alcázar, Suchetha Cooray, Romeel Davé, Austen Gabrielpillai, Shy Genel, Sultan Hassan, Lars Hernquist, Christian Kragh Jespersen, Christopher C. Lovell, Boon Kiat Oh, Camilla Pacifici, Lucia A. Perez, Laura Sommovigo, Joshua S. Speagle, 佳士 沈, Sandro Tacchella, Megan T. Tillman, Francisco Villaescusa-Navarro, John F. Wu
Figure caption: Median SFHs in different stellar mass bins from the three CAMELS models we use in this work, compiled using the CV data sets. The plots show the SFHs of galaxies starting at 109.25M⊙ in increments of 0.2 dex up to 1010.85M⊙, with darker colors indicating higher-mass bins.
Paper: Dwarf Active Galactic Nuclei from Variability for the Origins of Seeds (DAVOS): Properties of Variability-selected AGN in the Dark Energy Survey Deep Fields
Authors: Yichen Liu, Colin J. Burke, Diego Miura, Xin Liu, Qian Yang, Priyamvada Natarajan, Charlotte A. Ward
Figure caption: Summary of MBH–M* vs. redshift up to z ∼ 4. The DES-SN (circle symbols) and HSC-SSP (triangle symbols) AGNs with reliable black hole mass estimates and reliable stellar masses are plotted in blue symbols with black borders. We include J. Li et al. (2025), Y. Sun et al. (2024), A. Merloni et al. (2010), C. J. Burke et al. (2024b), J. I. H. Li et al. (2023) samples, along with local galaxies (J. E. Greene et al. 2020) and local AGNs (A. E. Reines & M. Volonteri 2015) for comparison. The 1σ range of the local early-type galaxies, late-type galaxies, and AGNs is plotted as red, yellow, and blue spans with dotted, dashed, and solid lines, respectively. Our AGN samples have a larger redshift span, making it easier to compare with different samples.
Paper: Dwarf Active Galactic Nuclei from Variability for the Origins of Seeds (DAVOS): Properties of Variability-selected AGN in the Dark Energy Survey Deep Fields
Authors: Yichen Liu, Colin J. Burke, Diego Miura, Xin Liu, Qian Yang, Priyamvada Natarajan, Charlotte A. Ward
Figure caption: Spectral fitting results for C. J. Burke et al. (2022) ID 697 (upper panel) and ID 399 (bottom panel). The source in the upper panel is the lowest reliable stellar mass in our spectroscopic sample of M* ∼ 1010M⊙. The source in the lower panel is an example of a brighter AGN (showing blueshifted absorption features) with an unreliable stellar mass. The spectral data (black) is plotted with the model fitting components: polynomial+power-law continuum (orange), total line model flux (blue), broad-line model flux (red), narrow-line model flux (green) fitted host+QSO template (pink), and fitted host template (magenta). In both cases, the PCA-derived host fluxes are small. The resulting broad-line black hole mass for the source in the lower panel is MBH ∼ 108.3M⊙ at z = 1.383. The black hole mass for the source in the upper panel is MBH ∼ 107.5M⊙ at z = 0.215.
Paper: Dwarf Active Galactic Nuclei from Variability for the Origins of Seeds (DAVOS): Properties of Variability-selected AGN in the Dark Energy Survey Deep Fields
Authors: Yichen Liu, Colin J. Burke, Diego Miura, Xin Liu, Qian Yang, Priyamvada Natarajan, Charlotte A. Ward
Figure caption: MBH–M* relation for the DES-SN (circle symbols) and HSC-SSP (triangle symbols) AGNs with reliable black hole mass estimates and reliable stellar masses from this work. Points are shaded by redshift. We assume uncertainties of ∼0.4 dex on the black hole masses. The typical uncertainties in our data are shown in the lower right corner. Data for AGN samples are overplotted with different symbols (A. Merloni et al. 2010; J. I. H. Li et al. 2023; C. J. Burke et al. 2024b; Y. Sun et al. 2024; J. Li et al. 2025). The local MBH–M* relation for inactive elliptical galaxies is plotted as a red dotted line and for inactive spiral galaxies as a dashed yellow line (J. E. Greene et al. 2020). The local MBH–M* relation for AGNs is plotted as a solid blue line (A. E. Reines & M. Volonteri 2015).
Paper: Dwarf Active Galactic Nuclei from Variability for the Origins of Seeds (DAVOS): Properties of Variability-selected AGN in the Dark Energy Survey Deep Fields
Authors: Yichen Liu, Colin J. Burke, Diego Miura, Xin Liu, Qian Yang, Priyamvada Natarajan, Charlotte A. Ward
Figure caption: Stellar masses estimated using our improved approach (this work) vs. the stellar masses calculated by C. J. Burke et al. (2022). The gray circles are unreliable stellar masses (χ2 > 5 or star formation excess >1.2 (same as Figure 10). The circles with solid borders are sources with reliable stellar masses with spectroscopic redshifts. The circles without borders are reliable stellar masses with photometric redshifts. The circles are colored by the improvement in fit quality measure ﹩{\rm{\Delta }}{\chi }_{\nu }^{2}﹩ as calculated by C. J. Burke et al. (2022). The bluer colors are more reliable stellar masses, as determined by C. J. Burke et al. (2022). A typical error bar is shown on the right. More of our stellar masses are reliable using the improved approach. A y = x line is plotted in gray.
Paper: Dwarf Active Galactic Nuclei from Variability for the Origins of Seeds (DAVOS): Properties of Variability-selected AGN in the Dark Energy Survey Deep Fields
Authors: Yichen Liu, Colin J. Burke, Diego Miura, Xin Liu, Qian Yang, Priyamvada Natarajan, Charlotte A. Ward
Figure caption: Black hole mass as a function of redshift for DES-SN (circle symbols) and HSC-SSP (triangle symbols) variable AGNs with reliable broad-line black hole mass estimates derived from broadband SED fitting using CIGALE. Each AGN is color shaded according to its DES g-band or HSC i-band apparent magnitude. The gray curve represents the theoretically predicted detection limit, which extends deeper than the black hole mass detection limit.
Paper: Dwarf Active Galactic Nuclei from Variability for the Origins of Seeds (DAVOS): Properties of Variability-selected AGN in the Dark Energy Survey Deep Fields
Authors: Yichen Liu, Colin J. Burke, Diego Miura, Xin Liu, Qian Yang, Priyamvada Natarajan, Charlotte A. Ward
Figure caption: The 2−10 keV X-ray luminosities plotted against our measured broad-line black hole masses. The points are color coded by their stellar mass when it is considered reliable. Black points have unreliable stellar masses. An uncertainty of 0.4 dex is assumed for the black hole masses.
Paper: Dwarf Active Galactic Nuclei from Variability for the Origins of Seeds (DAVOS): Properties of Variability-selected AGN in the Dark Energy Survey Deep Fields
Authors: Yichen Liu, Colin J. Burke, Diego Miura, Xin Liu, Qian Yang, Priyamvada Natarajan, Charlotte A. Ward
Figure caption: Black hole masses estimated from the broad-line luminosity vs. (y-axis) AGN continuum luminosity (x-axis). The black hole masses from the AGN continuum luminosity are susceptible to a few catastrophically underestimated masses when the AGN continuum is not well constrained.
Paper: Dwarf Active Galactic Nuclei from Variability for the Origins of Seeds (DAVOS): Properties of Variability-selected AGN in the Dark Energy Survey Deep Fields
Authors: Yichen Liu, Colin J. Burke, Diego Miura, Xin Liu, Qian Yang, Priyamvada Natarajan, Charlotte A. Ward
Figure caption: Distribution of star formation excess. The region marked as light red (star formation excess <1.2) is considered unreliable because these AGNs are dominated by AGN emission. Left panel: star formation excess vs bolometric luminosity; Right panel: star formation excess vs. black hole mass.
Paper: Machine Learning Inference of Stellar Properties Using Integrated Photometric and Spectroscopic Data
Authors: Ilay Kamai, Alex M. Bronstein, Hagai B. Perets
Figure caption: Upper panel—high-level diagram of the entire model. Lower panels—detailed diagrams of the DualFormer module, the spectra encoder, and the light-curve encoder.
Paper: The Responsivity of Mg II, C IV, Hα, and Hβ Emission Lines in SDSS Quasars
Authors: Wei-Rong Huang, Wei-Jian Lu, Jing Li, Ying-Ru Lin, Yi-Ping Qin
Figure caption: The relationship between logarithmic monochromatic luminosity (﹩\mathrm{log}{L}_{{\rm{mono}}}﹩) and redshift (z) for the four quasar subsamples. The logarithmic monochromatic luminosity and redshift are derived from the mean values of the two observational epochs. The range of the y-bar represents the difference in ﹩\mathrm{log}{L}_{{\rm{mono}}}﹩ between the two observational epochs.(The data used to create this figure are available in the online article.)(The data used to create this figure are available.)
Paper: The Responsivity of Mg II, C IV, Hα, and Hβ Emission Lines in SDSS Quasars
Authors: Wei-Rong Huang, Wei-Jian Lu, Jing Li, Ying-Ru Lin, Yi-Ping Qin
Figure caption: The responsivity (α) as a function of continuum luminosity for Mg II, C IV, Hα, and Hβ, respectively. The luminosity is taken as the mean value of two observational epochs. Each of the four subsamples is divided into six bins. The bar on x-axis represents the bin range, while the bar on y-axis represents the uncertainty of α is estimated from 500 bootstrap resamples. For the third and fourth panels, we merge the fifth and sixth bins into a single bin due to the limited number of quasars in those bins.(The data used to create this figure are available in the online article.)(The data used to create this figure are available.)
Paper: The Responsivity of Mg II, C IV, Hα, and Hβ Emission Lines in SDSS Quasars
Authors: Wei-Rong Huang, Wei-Jian Lu, Jing Li, Ying-Ru Lin, Yi-Ping Qin
Figure caption: The distributions of emission-line luminosity and continuous luminosity for Mg II, C IV, Hα, and Hβ, respectively. Each histogram is fitted with a Gaussian function, with μ and σ indicated in the legend. The logarithmic luminosities are derived from the mean values of the two observational epochs.(The data used to create this figure are available in the online article.)(The data used to create this figure are available.)
Paper: The Responsivity of Mg II, C IV, Hα, and Hβ Emission Lines in SDSS Quasars
Authors: Wei-Rong Huang, Wei-Jian Lu, Jing Li, Ying-Ru Lin, Yi-Ping Qin
Figure caption: The emission-line variations (Δmline) as a function of continuum variations (Δmcont) for Mg II, C IV, Hα, and Hβ, respectively. Three green-colored density contours enclose 20%, 68%, and 95% of the data points, respectively. The uncertainties in the slope and intercept are estimated from 500 bootstrap resamples (B. Efron 1979).(The data used to create this figure are available in the online article.)(The data used to create this figure are available.)
Paper: The Responsivity of Mg II, C IV, Hα, and Hβ Emission Lines in SDSS Quasars
Authors: Wei-Rong Huang, Wei-Jian Lu, Jing Li, Ying-Ru Lin, Yi-Ping Qin
Figure caption: The responsivity (α) as a function of Eddington ratio (λEdd) for Mg II, C IV, Hα, and Hβ, respectively. The λEdd is derived from the mean values of the two observational epochs. The uncertainty of α is estimated from 500 bootstraps resamples. Each of the four subsamples is divided into six bins (see Table 4).(The data used to create this figure are available in the online article.)(The data used to create this figure are available.)