adsabs/AstroCLIMB huggingface dataset:
Paper: Power-spectrum Space Decomposition of Frequency Tomographic Data for Intensity-mapping Experiments
Authors: Chang Feng, Filipe B. Abdalla
Figure caption: (Left) Representative k-mode H I power spectra at ν =  980 MHz. We only use the power spectra at 50 < ℓ < 500, which correspond to k-wavelets 1–6, as indicated by the ℓ–k relation. (Right) ℓ–k space mapping for the power spectra at 50 < ℓ < 500 for all frequencies. The red vertical lines indicate the k-wavelets that are considered in this work.
Paper: Power-spectrum Space Decomposition of Frequency Tomographic Data for Intensity-mapping Experiments
Authors: Chang Feng, Filipe B. Abdalla
Figure caption: Raw power spectra of different components at all frequencies with respect to different angular scales. The power-spectrum space can be split into a cross-power-spectrum subspace (×) and an auto-power-spectrum subspace (∘) by imposing a frequency correlation length Δν < Δν* [MHz]. The frequency coherence length considered in this work is Δν* = 20 [MHz]. This plot only shows the “AUTO” subspace because the “CROSS” is very similar except that the H I is null. Here, Dℓ = ℓ(ℓ + 1)/(2π)Cℓ.
Paper: Power-spectrum Space Decomposition of Frequency Tomographic Data for Intensity-mapping Experiments
Authors: Chang Feng, Filipe B. Abdalla
Figure caption: Simulated foreground contaminants, H I signals, and noise components at frequency ν = 1000 MHz in equatorial coordinates. Foreground contaminants are generated by the Python Sky Model with a HEALPix pixelization at a resolution Nside = 512. The mock data assume a Southern Hemisphere observation with the Galactic plane excluded, covering 35% of the full sky. The noise realization shown in this plot corresponds to the interferometric IM survey. “AME” and “CMB” refer to anomalous microwave emission and the cosmic microwave background, respectively.
Paper: Power-spectrum Space Decomposition of Frequency Tomographic Data for Intensity-mapping Experiments
Authors: Chang Feng, Filipe B. Abdalla
Figure caption: Frequency correlation matrix for both neutral hydrogen signals (left) and overall foreground contaminants (right) at the broad band b = 162. The axis is arranged by the indices of all the frequency pairs {νAνB}. The foreground is strongly correlated among different frequency bands whereas the H I is only correlated at neighboring bands.
Paper: Power-spectrum Space Decomposition of Frequency Tomographic Data for Intensity-mapping Experiments
Authors: Chang Feng, Filipe B. Abdalla
Figure caption: Posterior distribution functions for the radio sky model parameter set in Equation (12) for an interferometric IM experiment. All the parameters peak around the input values labeled by the vertical and horizontal lines, indicating that all the components are correctly reconstructed from the Bayesian analysis in Equation (16).
Paper: Power-spectrum Space Decomposition of Frequency Tomographic Data for Intensity-mapping Experiments
Authors: Chang Feng, Filipe B. Abdalla
Figure caption: Reconstruction validations of different H I signals. H I signals with shapes and amplitudes modulated in different ways can be correctly reconstructed from the Bayesian analysis in Equation (16) for interferometric IM experiments (left) and for single-dish-like IM experiments (right). The fiducial value of ﹩{A}_{k}^{(i)}=1﹩ without modulation. The multiplicative number is used to enlarge the error bars for visualization purposes.
Paper: Power-spectrum Space Decomposition of Frequency Tomographic Data for Intensity-mapping Experiments
Authors: Chang Feng, Filipe B. Abdalla
Figure caption: Posterior distribution functions for the parameter set of the radio sky model in Equation (12) for a single-dish-like IM experiment.
Paper: Impact of Interacting Parameters on Dark Matter in an Interacting Dark Energy Model
Authors: Himanshu Chaudhary, Ritika Nagpal, S. K. J. Pacif, G. Mustafa
Figure caption: The evolution of the Hubble difference as a function of redshift is presented for the ΛCDM model (black line), the interacting model (red line), and the noninteracting model (blue line). These are compared against the observational Hubble measurements, represented by purple dots with corresponding error bars shown as magenta lines.
Paper: Impact of Interacting Parameters on Dark Matter in an Interacting Dark Energy Model
Authors: Himanshu Chaudhary, Ritika Nagpal, S. K. J. Pacif, G. Mustafa
Figure caption: The evolution of the Hubble parameter as a function of redshift is presented for the ΛCDM model (black line), the interacting model (red line), and the noninteracting model (blue line). These are compared against the observational Hubble measurements, represented by purple dots with corresponding error bars shown as magenta lines.
Paper: Impact of Interacting Parameters on Dark Matter in an Interacting Dark Energy Model
Authors: Himanshu Chaudhary, Ritika Nagpal, S. K. J. Pacif, G. Mustafa
Figure caption: The confidence contours at the 68% (1σ) and 95% (2σ) levels based on constraints for the noninteracting model.
Paper: Impact of Interacting Parameters on Dark Matter in an Interacting Dark Energy Model
Authors: Himanshu Chaudhary, Ritika Nagpal, S. K. J. Pacif, G. Mustafa
Figure caption: The confidence contours at the 68% (1σ) and 95% (2σ) levels based on constraints for the interacting model.
Paper: Impact of Interacting Parameters on Dark Matter in an Interacting Dark Energy Model
Authors: Himanshu Chaudhary, Ritika Nagpal, S. K. J. Pacif, G. Mustafa
Figure caption: Comparison of matter and energy distribution: interacting vs. noninteracting cosmological models.
Paper: Impact of Interacting Parameters on Dark Matter in an Interacting Dark Energy Model
Authors: Himanshu Chaudhary, Ritika Nagpal, S. K. J. Pacif, G. Mustafa
Figure caption: The evolution of the distance modulus difference as a function of redshift is presented for the ΛCDM model (black line), the interacting model (red line), and the noninteracting model (blue line). These are compared against the observational Hubble measurements, represented by purple dots with corresponding error bars shown as magenta lines.
Paper: Impact of Interacting Parameters on Dark Matter in an Interacting Dark Energy Model
Authors: Himanshu Chaudhary, Ritika Nagpal, S. K. J. Pacif, G. Mustafa
Figure caption: The evolution of the distance modulus as a function of redshift is presented for the ΛCDM model (black line), the interacting model (red line), and the noninteracting model (blue line). These are compared against the observational Hubble measurements, represented by purple dots with corresponding error bars shown as magenta lines.
Paper: Impact of Interacting Parameters on Dark Matter in an Interacting Dark Energy Model
Authors: Himanshu Chaudhary, Ritika Nagpal, S. K. J. Pacif, G. Mustafa
Figure caption: The evolution of deceleration parameter as a function of redshift (z).
Paper: Impact of Interacting Parameters on Dark Matter in an Interacting Dark Energy Model
Authors: Himanshu Chaudhary, Ritika Nagpal, S. K. J. Pacif, G. Mustafa
Figure caption: The evolution of snap parameter as a function of redshift (z).
Paper: Impact of Interacting Parameters on Dark Matter in an Interacting Dark Energy Model
Authors: Himanshu Chaudhary, Ritika Nagpal, S. K. J. Pacif, G. Mustafa
Figure caption: The evolution of jerk parameter as a function of redshift (z).
Paper: Impact of Interacting Parameters on Dark Matter in an Interacting Dark Energy Model
Authors: Himanshu Chaudhary, Ritika Nagpal, S. K. J. Pacif, G. Mustafa
Figure caption: Evolution of the Om(z) diagnostic as a function of redshift z.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The comparison of the intrinsic colors of dwarf stars (4 < ﹩{\rm{log}}\,g﹩< 4.5) derived from this work (x-axis) and the PARSEC stellar model (y-axis). The color of the dots represents [Fe/H], and the black line indicates the line of equality between x and y. The inset shows the distribution of the differences.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The change of the color index with Tefffor the stars with −0.1 < [Fe/H] < 0 and 4 < ﹩{\rm{log}}\,g\,﹩< 4.5. The gray dots denote all the stars, the blue dots denote the selected zero-/low-extinction sources, and the red crosses represent the median of zero-/low-extinction sources in each Teff bin of 100 K.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The same as Figure 4 but for giant stars (2.5 < log g < 3).
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The variation of the intrinsic color indices ﹩{C}_{{G}_{{\rm{BP}}},{G}_{{\rm{RP}}}}^{0}﹩ (top left), ﹩{C}_{{\rm{NUV}},{G}_{{\rm{BP}}}}^{0}﹩ (middle left), ﹩{C}_{{\rm{FUV}},{G}_{{\rm{BP}}}}^{0}﹩ (bottom left), ﹩{C}_{uvw1,{G}_{{\rm{BP}}}}^{0}﹩ (top right), ﹩{C}_{wum2,{G}_{{\rm{BP}}}}^{0}﹩ (middle right), and ﹩{C}_{uvw2,{G}_{{\rm{BP}}}}^{0}﹩ (bottom right) with Teff and [Fe/H] at ﹩{\rm{log}}\,g﹩ = 4 dex.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The distribution of color excess differences between Z23 and common sources from LAMOST (red), GALAH (green), and APOGEE (blue), respectively. The median and dispersion of the color excess differences are labeled in each panel.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The distribution of color excess errors, as well as the number of color excess values and the median color excess error, are labeled in each panel.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The same as Figure 2 but for the variation of the intrinsic color indices with Teff and ﹩{\rm{log}}\,g﹩ at [Fe/H] = 0 dex.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The linear fitting of color excesses ﹩{E}_{\lambda ,{G}_{\mathrm{BP}}}﹩ to ﹩{E}_{{G}_{\mathrm{BP}},{G}_{\mathrm{RP}}}﹩ for different Teff ranges. Points in different colors represent different Teff ranges. The black lines indicate the best linear fit, with the fit results displayed above the corresponding fitting lines in each panel.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: Gridding map by the HEALPix method of ﹩{E}_{{G}_{{\rm{BP}}},{G}_{{\rm{RP}}}}﹩ (top left), ﹩{E}_{\mathrm{NUV},{G}_{\mathrm{BP}}}﹩ (top middle), ﹩{E}_{\mathrm{FUV},{G}_{\mathrm{BP}}}﹩ (top right), ﹩{E}_{uvw1,{G}_{\mathrm{BP}}}﹩ (bottom left), ﹩{E}_{uvm2,{G}_{\mathrm{BP}}}﹩ (bottom middle), and ﹩{E}_{uvw2,{G}_{\mathrm{BP}}}﹩ (bottom right).
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: Color excesses ﹩{E}_{\lambda ,{G}_{\mathrm{BP}}}/{E}_{{G}_{\mathrm{BP}},{G}_{\mathrm{RP}}}﹩ as a function of Teff. Red points with error bars represent the CERs and uncertainties from this study. Blue points indicate the simulated CERs, considering an effective wavelength shift of ﹩{E}_{{G}_{{\rm{BP}}},{G}_{{\rm{RP}}}}﹩ = 0 and applying the F99 for RV = 3.1 extinction law. Green points represent the CERs from ZY23 for GALEX-related bands.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The 2D RV map. The colored HEALPix points represent the median RV with E(B − V) > 0.1 mag for each pixel. The uncolored regions indicate areas with insufficient stars for analysis.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The diagram of ﹩{E}_{{G}_{{\rm{BP}}},{G}_{{\rm{RP}}}}﹩ vs. ﹩{E}_{uvw2,{G}_{{\rm{BP}}}}﹩ for stars in the range of 7000 K ≤ Teff ≤ 7500 K before (blue points) and after (green points) curvature correction.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The histogram of the number of sources in each HEALPix pixel for ﹩{E}_{{G}_{{\rm{BP}}},{G}_{{\rm{RP}}}}﹩ (top left), ﹩{E}_{\mathrm{NUV},{G}_{\mathrm{BP}}}﹩ (top middle), ﹩{E}_{\mathrm{FUV},{G}_{\mathrm{BP}}}﹩ (top right), ﹩{E}_{uvw1,{G}_{\mathrm{BP}}}﹩ (bottom left), ﹩{E}_{uvm2,{G}_{\mathrm{BP}}}﹩ (bottom middle), and ﹩{E}_{uvw2,{G}_{\mathrm{BP}}}﹩ (bottom right).
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The comparison of ﹩{E}_{{G}_{{\rm{BP}}},{G}_{{\rm{RP}}}}﹩ derived in this work with EG19 (the reddening) from G19. The red plus signs and error bars represent the median and dispersion of color excess for each 0.005 mag bin of ﹩{E}_{{G}_{{\rm{BP}}},{G}_{{\rm{RP}}}}﹩. The inset shows the distribution of the differences.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: The comparison of ﹩{E}_{{G}_{\mathrm{BP}},{G}_{\mathrm{RP}}}﹩, ﹩{E}_{\mathrm{NUV},{G}_{\mathrm{BP}}}﹩, and ﹩{E}_{\mathrm{FUV},{G}_{\mathrm{BP}}}﹩ derived in Z23 with those from S21. The blue line indicates the line of equality between x and y, and the inset shows the distribution of the differences.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: Comparison of UV extinction maps from this work (left) and extinction maps from G19 (right) in the region −30° < l < 90° and 20° < b < 60° at distance d = 0.5 kpc.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: Comparison of the 2D RV distribution between the UV common sources of this work and ZYC23 and ZG25. The first panel: the RV distribution (﹩{R}_{{\rm{V}}}^{{\rm{UV\; +V}}}﹩) based on UV and Gaia optical band measurements of this work. The second panel: the RV distribution (﹩{R}_{{\rm{V}}}^{{\rm{V\; +IR}}}﹩) primarily based on IR and optical bands of this work. The third panel: the RV distribution (﹩{R}_{{\rm{V}}}^{{\rm{ZY\; C23}}}﹩) of ZYC23. The fourth panel: the RV distribution (﹩{R}_{{\rm{V}}}^{{\rm{ZG25}}}﹩) of ZG25.
Paper: Massive Acquisition of Ultraviolet Color Excess Information from GALEX and UVOT Bands
Authors: Dongliang Yang, 栋梁 杨, Mingxu Sun, 明旭 孙, Biwei Jiang, 碧沩 姜, Wenyuan Cui, 文元 崔, Ruoyi Zhang, 若羿 张, Luyao Shi, 璐瑶 史, Jiachen Wei, 嘉辰 魏
Figure caption: Comparison of RV values derived in this work with those from ZYC23 and ZG25 for the same HEALPix pixels. Top panels: comparison of RV values derived from UV and Gaia optical band measurements in this work with those from ZYC23 (left) and ZG25 (right). Bottom panels: comparison of RV values primarily derived from IR and optical bands in this work with those from ZYC23 (left) and ZG25 (right).
Paper: Monitoring AGNs with Hβ Asymmetry. V. Long-term Variation and Evolution of the Broad Hβ Emission-line Profiles
Authors: Feng-Na Fang, Pu Du, Michael S. Brotherton, Jacob N. McLane, T. E. Zastrocky, Kianna A. Olson, Dong-Wei Bao, Shuo Zhai, Hua-Rui Bai, Yi-Xin Fu, Bi-Xuan Zhao, Yong-Jie Chen, Yue-Chang Peng, Yu-Yang Songsheng, Yan-Rong Li, Chen Hu, Ming Xiao, Bo-Wei Jiang, Yi-Lin Wang, Hao Zhang, Yu Zhao, Jia-Qi Feng, Yi-Peng Zhao, David H. Kasper, William T. Chick, My L. Nguyen, Jaya Maithil, H. A. Kobulnicky, D. A. Dale, Derek Hand, C. Adelman, Z. Carter, G. M. Murphree, M. Oeur, S. Schonsberg, T. Roth, Hartmut Winkler, Paola Marziani, Mauro D'Onofrio, Keith Horne, Luis C. Ho, Jin-Ming Bai, Jian-Min Wang
Figure caption: Correlations between Hβ flux and FWHM after subtracting the long-term contribution from the radiation pressure.
Paper: Monitoring AGNs with Hβ Asymmetry. V. Long-term Variation and Evolution of the Broad Hβ Emission-line Profiles
Authors: Feng-Na Fang, Pu Du, Michael S. Brotherton, Jacob N. McLane, T. E. Zastrocky, Kianna A. Olson, Dong-Wei Bao, Shuo Zhai, Hua-Rui Bai, Yi-Xin Fu, Bi-Xuan Zhao, Yong-Jie Chen, Yue-Chang Peng, Yu-Yang Songsheng, Yan-Rong Li, Chen Hu, Ming Xiao, Bo-Wei Jiang, Yi-Lin Wang, Hao Zhang, Yu Zhao, Jia-Qi Feng, Yi-Peng Zhao, David H. Kasper, William T. Chick, My L. Nguyen, Jaya Maithil, H. A. Kobulnicky, D. A. Dale, Derek Hand, C. Adelman, Z. Carter, G. M. Murphree, M. Oeur, S. Schonsberg, T. Roth, Hartmut Winkler, Paola Marziani, Mauro D'Onofrio, Keith Horne, Luis C. Ho, Jin-Ming Bai, Jian-Min Wang
Figure caption: Comparisons between different timescales and the time delays of the long-term trends in A (orange dots) and FWHM (green squares). The orange background exhibits the observational period covered by the campaign. The data points with reduced chi-square larger than 5.0 are marked in gray.
Paper: Monitoring AGNs with Hβ Asymmetry. V. Long-term Variation and Evolution of the Broad Hβ Emission-line Profiles
Authors: Feng-Na Fang, Pu Du, Michael S. Brotherton, Jacob N. McLane, T. E. Zastrocky, Kianna A. Olson, Dong-Wei Bao, Shuo Zhai, Hua-Rui Bai, Yi-Xin Fu, Bi-Xuan Zhao, Yong-Jie Chen, Yue-Chang Peng, Yu-Yang Songsheng, Yan-Rong Li, Chen Hu, Ming Xiao, Bo-Wei Jiang, Yi-Lin Wang, Hao Zhang, Yu Zhao, Jia-Qi Feng, Yi-Peng Zhao, David H. Kasper, William T. Chick, My L. Nguyen, Jaya Maithil, H. A. Kobulnicky, D. A. Dale, Derek Hand, C. Adelman, Z. Carter, G. M. Murphree, M. Oeur, S. Schonsberg, T. Roth, Hartmut Winkler, Paola Marziani, Mauro D'Onofrio, Keith Horne, Luis C. Ho, Jin-Ming Bai, Jian-Min Wang
Figure caption: Correlations between Hβ flux and asymmetry A after subtracting the long-term contribution from the radiation pressure.
Paper: Discerning Misclassified Flat-spectrum Radio Quasars from Low-frequency-peaked BL Lacertae Objects
Authors: S. Liang, W. G. Yang, Y. G. Zheng, S. J. Kang
Figure caption: The spectrum of NVSS J112903+375655. This image represents the spectral analysis of the quasar NVSS J112903+375655, located at coordinates (R.A., decl.) = (172.263520, 37.949090) with a redshift of z = 4.0901. The plot highlights the Lyα and C IV emission lines, with data points and fitted lines indicated. The spectral features are overlaid on a continuum model, with line broadening and other details marked. The flux density is denoted by f1 (10−17 erg s−1 cm−2 A−1), and the rest-frame wavelength is plotted on the x-axis in angstroms. The specific values of χ2 = 0.19 and χ2 = 0.24 likely refer to parameters related to the Gaussian fitting of the emission lines. Key emission lines such as C IV and C III are labeled, and the plot captures the detailed structure of the quasar’s spectrum, essential for understanding its physical properties and redshift.
Paper: Discerning Misclassified Flat-spectrum Radio Quasars from Low-frequency-peaked BL Lacertae Objects
Authors: S. Liang, W. G. Yang, Y. G. Zheng, S. J. Kang
Figure caption: The spectral fitting of quasar 4C+56.27 at redshift z = 0.6640, observed at coordinates (R.A., decl.) = (85.739000, 26.081000). In the upper panel, the black line represents the total dereddened spectrum, while yellow represents the continuum component. Cyan denotes the Fe II emission templates, blue represents the combined emission lines, red indicates broad-line components, and green indicates narrow-line components. The purple line represents the host-galaxy contribution, the gray line represents the quasar component, and the pink line denotes the spectrum reconstructed from the host and quasar components via principal component analysis (PCA). In the lower panel, the Mg II line at 2800 Å is highlighted with its equivalent width (EW) labeled, showing details of the emission-line fitting.
Paper: Discerning Misclassified Flat-spectrum Radio Quasars from Low-frequency-peaked BL Lacertae Objects
Authors: S. Liang, W. G. Yang, Y. G. Zheng, S. J. Kang
Figure caption: (a) The distribution of the gamma-ray photon spectral index. (b) The distribution of ﹩\mathrm{log}{\nu }_{\mathrm{peak}}^{\mathrm{syn}}﹩. (c) The distribution of CD. In each, the red solid line depicts the histogram of LBLs, while the blue solid line represents that of FSRQs. The black dashed line indicates the value obtained through Gaussian fitting of the histogram of the FSRQs and within the 1σ confidence interval. This value is closer to one side of the histogram of the LBLs. In the end, we drew the following dividing lines: ﹩{\Gamma }_{\gamma }=2.267,\,\mathrm{log}{\nu }_{\mathrm{peak}}^{\mathrm{syn}}=13.597,\,\mathrm{CD}=0.776﹩.
Paper: Discerning Misclassified Flat-spectrum Radio Quasars from Low-frequency-peaked BL Lacertae Objects
Authors: S. Liang, W. G. Yang, Y. G. Zheng, S. J. Kang
Figure caption: The spectrum of PKS 2354-021. Example of spectral fitting for the quasar PKS 2354-021 at z = 0.8120. Black lines denote the total dereddened spectrum, yellow lines denote the continuum (modeled by a power-law function and a third-order polynomial), cyan lines denote the Fe II emission template, blue lines denote the entire emission-line profile, red lines denote the broad-line components, and green lines denote the narrow-line components. In the panels at the bottom of this figure, we can see the obvious broad-emission-line composition of Mg II, and the EW of its emission line is calculated to be 3.501 Å by fitting.
Paper: Discerning Misclassified Flat-spectrum Radio Quasars from Low-frequency-peaked BL Lacertae Objects
Authors: S. Liang, W. G. Yang, Y. G. Zheng, S. J. Kang
Figure caption: Example of spectral fitting for the quasar OJ 448 at z = 0.5481. Black lines denote the total dereddened spectrum, yellow lines denote the continuum (modeled by a power-law function and a third-order polynomial), cyan lines denote the Fe II emission template, blue lines denote the entire emission-line profile, red lines denote the broad-line components, and green lines denote the narrow-line components. In the panels at the bottom of this figure, we can see the obvious broad-emission-line composition of Mg II, and the EW of its emission line is calculated to be 1.603 Å by fitting.