adsabs/AstroCLIMB huggingface dataset:
Paper: Turbulent Structure in Supernova Remnants G46.8−0.3 and G39.2−0.3 from THOR Polarimetry
Authors: Russell Shanahan, Jeroen M. Stil, Loren Anderson, Henrik Beuther, Paul Goldsmith, Ralf S. Klessen, Michael Rugel, Juan D. Soler
Figure caption: Depolarization across wavelengths expected from turbulence cells within the synthesized beam according to the modeling in Burn (1966) and Tribble (1991; see Section 5.1 for details). The red curves represent Tribble (solid) and Burn (dashed) for σ  ϕ  = 67 rad m−2. The blue curves represent Tribble (solid) and Burn (dashed) for σ  ϕ  = 30 rad m−2. The green dots indicate where σ  ϕ  λ 2 = 1 in each case. The black dots are data from the subregion at (ℓ, b) = (39.°238, −0.°372), for which we find σ  ϕ  = 42.6 ± 5.3 rad m−2. The vertical black dashed line shows where λ = 6 cm.
Paper: Turbulent Structure in Supernova Remnants G46.8−0.3 and G39.2−0.3 from THOR Polarimetry
Authors: Russell Shanahan, Jeroen M. Stil, Loren Anderson, Henrik Beuther, Paul Goldsmith, Ralf S. Klessen, Michael Rugel, Juan D. Soler
Figure caption: Simulated RM SFs. The red, green, and blue data points correspond to γ = −2.1, −2.5, and −3, respectively. The dots are SFs from individual pixels. The crosses are SFs after averaging Q and U over the 16″ beam (represented by the vertical black dashed line), as explained in the text. The colored dashed lines are power-law fits to the crosses. The solid lines are the dashed lines plus a constant term. This constant term is the amplitude of each single-pixel SF at 1/3 the beam.
Paper: Hunting Gamma-Ray-emitting FR0 Radio Galaxies in Wide-field Sky Surveys
Authors: Meghana Pannikkote, Vaidehi S. Paliya, D. J. Saikia
Figure caption: The BPT diagnostic diagram of the FR0CAT sources (red circles) and objects studied in this work (black stars). For a comparison, we also show SDSS galaxies studied by the group from the Max Planck Institute for Astrophysics, and The Johns Hopkins University (MPA-JHU; Brinchmann et al. 2004). The red and blue lines show the relations proposed to classify emission-line galaxies (Kewley et al. 2006). Black stars with green boundaries are rejected from the analysis.
Paper: Hunting Gamma-Ray-emitting FR0 Radio Galaxies in Wide-field Sky Surveys
Authors: Meghana Pannikkote, Vaidehi S. Paliya, D. J. Saikia
Figure caption: Top: the WISE color–color diagram showing γ-ray-detected blazars, radio galaxies, and FR0 sources as labeled. Bottom: the γ-ray luminosity vs. photon index plane for Fermi-LAT–detected AGN.
Paper: Hunting Gamma-Ray-emitting FR0 Radio Galaxies in Wide-field Sky Surveys
Authors: Meghana Pannikkote, Vaidehi S. Paliya, D. J. Saikia
Figure caption: The VLASS contours overplotted on PanSTARRS r-band images of γ-ray-emitting FR0 radio galaxies. The contour levels start at 3×rms×(﹩-\sqrt{2}﹩, −1, 1) and increase in multiples of ﹩\sqrt{2}﹩. The optical spectrum of each source is also shown.
Paper: Identification of 1RXS J165424.6-433758 as a Polar Cataclysmic Variable
Authors: B. O'Connor, J. Brink, D. A. H. Buckley, K. Mukai, C. Kouveliotou, E. Göğüş, S. B. Potter, P. Woudt, A. Lien, A. Levan, O. Kargaltsev, M. G. Baring, E. Bellm, S. B. Cenko, P. A. Evans, J. Granot, C. Hailey, F. Harrison, D. Hartmann, A. J. van der Horst, D. Huppenkothen, L. Kaper, J. A. Kennea, P. O. Slane, D. Stern, E. Troja, R. A. M. J. Wijers, G. Younes
Figure caption: SED of the UV, optical, and IR counterpart to J1654. The solid black line connects photometry (diamonds) obtained during the high state, whereas the dashed black line (and squares) shows the low state. The data are not corrected for extinction; downward triangles represent 3σ upper limits. The thick, solid blue line shows the best-fit stellar model from ARIADNE (K dwarf), and the solid gray line is a less-extinct M dwarf (see Section 3.3). The dotted blue line represents the addition of a WD with T = 120,000 K and radius R = 0.01 R ⊙, modeled as a simple blackbody, with an extinction of A  V  ∼ 4.9 mag. The dotted gray line represents a WD with T = 12,000 and extinction of A  V  ∼ 0.5 mag. The red dashed line is the addition of cyclotron emission from a polar with a magnetic field strength of 3.5 MG.
Paper: Identification of 1RXS J165424.6-433758 as a Polar Cataclysmic Variable
Authors: B. O'Connor, J. Brink, D. A. H. Buckley, K. Mukai, C. Kouveliotou, E. Göğüş, S. B. Potter, P. Woudt, A. Lien, A. Levan, O. Kargaltsev, M. G. Baring, E. Bellm, S. B. Cenko, P. A. Evans, J. Granot, C. Hailey, F. Harrison, D. Hartmann, A. J. van der Horst, D. Huppenkothen, L. Kaper, J. A. Kennea, P. O. Slane, D. Stern, E. Troja, R. A. M. J. Wijers, G. Younes
Figure caption: Top: long-term light curve (0.3–10 keV) of all X-ray observations included in this work. Vertical lines mark known times of high (blue) and low states (red) based on archival optical/IR observations. Bottom: background-subtracted NuSTAR light curve of J1654 in the 3–79 keV energy range. We combined the count rates from both FPMA and FPMB. The time bin is 150 s.
Paper: Identification of 1RXS J165424.6-433758 as a Polar Cataclysmic Variable
Authors: B. O'Connor, J. Brink, D. A. H. Buckley, K. Mukai, C. Kouveliotou, E. Göğüş, S. B. Potter, P. Woudt, A. Lien, A. Levan, O. Kargaltsev, M. G. Baring, E. Bellm, S. B. Cenko, P. A. Evans, J. Granot, C. Hailey, F. Harrison, D. Hartmann, A. J. van der Horst, D. Huppenkothen, L. Kaper, J. A. Kennea, P. O. Slane, D. Stern, E. Troja, R. A. M. J. Wijers, G. Younes
Figure caption: RGB image of the field of J1654 using three UVOT filters (left: red = uvw1, green = uvm2, and blue = uvw2) and three VVV filters (right: red = K  s , green = H, and blue = J). The archival Chandra localization (1.″0; 95% CL) is displayed by the magenta circle. In the top right a zoom in on the position of the counterpart is shown. North is up and east is to the left.
Paper: Identification of 1RXS J165424.6-433758 as a Polar Cataclysmic Variable
Authors: B. O'Connor, J. Brink, D. A. H. Buckley, K. Mukai, C. Kouveliotou, E. Göğüş, S. B. Potter, P. Woudt, A. Lien, A. Levan, O. Kargaltsev, M. G. Baring, E. Bellm, S. B. Cenko, P. A. Evans, J. Granot, C. Hailey, F. Harrison, D. Hartmann, A. J. van der Horst, D. Huppenkothen, L. Kaper, J. A. Kennea, P. O. Slane, D. Stern, E. Troja, R. A. M. J. Wijers, G. Younes
Figure caption: Mean spectrum of J1654 obtained with SALT. We have labeled the primary emission features: Balmer lines in blue, He I lines in red, He II lines in orange, and other features in black, including the Bowen blend (BB; N III/C III). Chips gaps are located at 5000 Å and 8250 Å. Gray vertical regions mark telluric features.
Paper: Identification of 1RXS J165424.6-433758 as a Polar Cataclysmic Variable
Authors: B. O'Connor, J. Brink, D. A. H. Buckley, K. Mukai, C. Kouveliotou, E. Göğüş, S. B. Potter, P. Woudt, A. Lien, A. Levan, O. Kargaltsev, M. G. Baring, E. Bellm, S. B. Cenko, P. A. Evans, J. Granot, C. Hailey, F. Harrison, D. Hartmann, A. J. van der Horst, D. Huppenkothen, L. Kaper, J. A. Kennea, P. O. Slane, D. Stern, E. Troja, R. A. M. J. Wijers, G. Younes
Figure caption: X-ray spectra of J1654 in the high state from Swift and NuSTAR. The best-fit model (con∗tbabs∗bremss) is shown. The spectra have been rebinned for display purposes. There is a hint of an Fe Kα line at 6.7 keV in the NuSTAR spectra.
Paper: Identification of 1RXS J165424.6-433758 as a Polar Cataclysmic Variable
Authors: B. O'Connor, J. Brink, D. A. H. Buckley, K. Mukai, C. Kouveliotou, E. Göğüş, S. B. Potter, P. Woudt, A. Lien, A. Levan, O. Kargaltsev, M. G. Baring, E. Bellm, S. B. Cenko, P. A. Evans, J. Granot, C. Hailey, F. Harrison, D. Hartmann, A. J. van der Horst, D. Huppenkothen, L. Kaper, J. A. Kennea, P. O. Slane, D. Stern, E. Troja, R. A. M. J. Wijers, G. Younes
Figure caption: Optical light curves of J1654 from the 1 m SAAO telescope obtained on different nights, labeled by their barycentric Julian date (BJD). The photometry is measured as differential instrumental magnitudes, dependent on the observing conditions on each night. The inset displays the periodogram for each night.
Paper: Identification of 1RXS J165424.6-433758 as a Polar Cataclysmic Variable
Authors: B. O'Connor, J. Brink, D. A. H. Buckley, K. Mukai, C. Kouveliotou, E. Göğüş, S. B. Potter, P. Woudt, A. Lien, A. Levan, O. Kargaltsev, M. G. Baring, E. Bellm, S. B. Cenko, P. A. Evans, J. Granot, C. Hailey, F. Harrison, D. Hartmann, A. J. van der Horst, D. Huppenkothen, L. Kaper, J. A. Kennea, P. O. Slane, D. Stern, E. Troja, R. A. M. J. Wijers, G. Younes
Figure caption: Lomb–Scargle periodogram of the combined optical data obtained with the SAAO. The orbital period Ω (main peak) and its harmonic are observed. The inset shows a zoom in on the frequency corresponding to the orbital period of 2.87 hr, and its aliases.
Paper: Identification of 1RXS J165424.6-433758 as a Polar Cataclysmic Variable
Authors: B. O'Connor, J. Brink, D. A. H. Buckley, K. Mukai, C. Kouveliotou, E. Göğüş, S. B. Potter, P. Woudt, A. Lien, A. Levan, O. Kargaltsev, M. G. Baring, E. Bellm, S. B. Cenko, P. A. Evans, J. Granot, C. Hailey, F. Harrison, D. Hartmann, A. J. van der Horst, D. Huppenkothen, L. Kaper, J. A. Kennea, P. O. Slane, D. Stern, E. Troja, R. A. M. J. Wijers, G. Younes
Figure caption: Corner plot of secondary star parameters derived from modeling the low-state SED with ARIADNE.
Paper: Identification of 1RXS J165424.6-433758 as a Polar Cataclysmic Variable
Authors: B. O'Connor, J. Brink, D. A. H. Buckley, K. Mukai, C. Kouveliotou, E. Göğüş, S. B. Potter, P. Woudt, A. Lien, A. Levan, O. Kargaltsev, M. G. Baring, E. Bellm, S. B. Cenko, P. A. Evans, J. Granot, C. Hailey, F. Harrison, D. Hartmann, A. J. van der Horst, D. Huppenkothen, L. Kaper, J. A. Kennea, P. O. Slane, D. Stern, E. Troja, R. A. M. J. Wijers, G. Younes
Figure caption: Radial velocity vs. orbital phase for the Hα, Hβ, Hγ, He II λ4686, and He I λ5876 emission lines.
Paper:  LIMpy: A Semianalytic Approach to Simulating Multiline Intensity Maps at Millimeter Wavelengths
Authors: Anirban Roy, Dariannette Valentín-Martínez, Kailai Wang, Nicholas Battaglia, Alexander van Engelen
Figure caption: We illustrate the assumed SFR models as a function of halo mass, three different redshifts: z ∼ 1 (left), z ∼ 4 (middle), and z ∼ 6 (right). The scatter points represent the star formation histories of individual halos in the TNG300 simulations (Springel et al. 2018; Nelson et al. 2019), while the brown and red solid lines depict the best-fit curves based on the TNG100 and TNG300 simulations. The shaded cyan region represents the 2σ contours of the fitted scattered data of SFR from TNG300 simulations. For comparison, we show the interpolated SFR from Behroozi et al. (2019), and analytic models of SFR taken from Silva et al. (2015) and Fonseca et al. (2017). This plot captures the complex picture of SFH in halos, as all dark matter halos with the same mass do not form the same amount of stars. The uncertainty in the SFR can propagate to the luminosity of the various emission lines. Careful consideration of the uncertainties in the SFR is necessary when interpreting intensity mapping observations and making predictions about the underlying astrophysical processes that drive the formation and evolution of galaxies over cosmic time.
Paper:  LIMpy: A Semianalytic Approach to Simulating Multiline Intensity Maps at Millimeter Wavelengths
Authors: Anirban Roy, Dariannette Valentín-Martínez, Kailai Wang, Nicholas Battaglia, Alexander van Engelen
Figure caption: The power spectra of the C II 158 line at redshifts 7.6, 5.8, 4.4, and 3.6. The dashed lines in each panel show the contribution to the signal from the clustering term alone, while the solid lines represent the total signal, including both the clustering and shot noise terms. The solid red lines in each panel denote the mean line of all the models, representing the average signal predicted by the different theoretical models that we consider here. The shaded gray region represents the scales where the dominant term is shot noise, while the yellow-shaded area roughly corresponds to the scales where the clustering term is larger than the shot noise term. The shape and amplitude of the C II 158 have important implications for studying interstellar medium physics and structure formation at high redshift, as they provide insights into the large-scale structure of matter in the Universe and the properties of the sources that generate the C II 158 signal.
Paper:  LIMpy: A Semianalytic Approach to Simulating Multiline Intensity Maps at Millimeter Wavelengths
Authors: Anirban Roy, Dariannette Valentín-Martínez, Kailai Wang, Nicholas Battaglia, Alexander van Engelen
Figure caption: We display simulated maps of the C II 158 (first row), O III 88 (second row), CO (7–6) (third row) line intensities at redshifts corresponding to the central frequencies of the FYST’s EoR-Spec experiment. The simulation boxes are generated from the 21cmFAST package for a 544 cMpc/h box, and we keep fixed the same initial condition for all the simulations at different redshifts. The columns correspond to the specific observational frequency, as indicated by the column titles. The fourth row of the plot compares the dimensionless power spectra of these lines based on the Tng300 star formation model and the Visbal10 line luminosity model (Visbal & Loeb 2010). For visualization purposes, Gaussian beam convolutions were applied to the maps with FWHM beam sizes of 58″, 45″, 37″, and 32″ from left to right.
Paper:  LIMpy: A Semianalytic Approach to Simulating Multiline Intensity Maps at Millimeter Wavelengths
Authors: Anirban Roy, Dariannette Valentín-Martínez, Kailai Wang, Nicholas Battaglia, Alexander van Engelen
Figure caption: Schematic flowchart of the LIMpy package. Several built-in star formation models and multiline luminosity models are implemented as inputs to the code. Based on these input choices, the package will calculate the power spectrum relying on either the halo model approach or painting the line luminosities on an externally provided halo catalog. The package can make line intensity maps, and if the specification of an experiment is provided, it can calculate the S/N. Furthermore, LIMpy can be used for parameter estimation based on MCMC or Fisher matrix methods. These methods incorporate observational data to infer the parameters that best describe the underlying astrophysical processes.
Paper:  LIMpy: A Semianalytic Approach to Simulating Multiline Intensity Maps at Millimeter Wavelengths
Authors: Anirban Roy, Dariannette Valentín-Martínez, Kailai Wang, Nicholas Battaglia, Alexander van Engelen
Figure caption: Redshift evolution of the C II 158, CO76, and O III 88 luminosities based on the models mentioned in the legends. Solid and dashed lines represent the line luminosities for the halo mass 1010 M ⊙/h and 1011 M ⊙/h, respectively. Here, we demonstrate the relationship between various line luminosities and their corresponding host halo masses across a wide range of models. The vertical-shaded regions represent the redshift coverage of these lines corresponding to the frequency bandwidths of the EoR-Spec on FYST.
Paper:  LIMpy: A Semianalytic Approach to Simulating Multiline Intensity Maps at Millimeter Wavelengths
Authors: Anirban Roy, Dariannette Valentín-Martínez, Kailai Wang, Nicholas Battaglia, Alexander van Engelen
Figure caption: Percentage difference in the C II 158 power spectrum due to the use of a HOD model. For this example, we calculate the power spectrum based on the Silva15 star formation model and Fonseca16 line luminosity model of C II 158. It shows that the inclusion of the HOD model is more important for the power spectrum of C II 158 at low redshift.
Paper:  LIMpy: A Semianalytic Approach to Simulating Multiline Intensity Maps at Millimeter Wavelengths
Authors: Anirban Roy, Dariannette Valentín-Martínez, Kailai Wang, Nicholas Battaglia, Alexander van Engelen
Figure caption: Redshift evolution of different atomic and molecular lines of interest in the redshift-frequency space. The four horizontal lines show the central frequencies of EoR-Spec on FYST, ν cen, and the corresponding shaded regions represent the frequency bandwidths, Δν. Dashed lines show the rotational transitions of CO from the J up to the (J up − 1) level.
Paper:  LIMpy: A Semianalytic Approach to Simulating Multiline Intensity Maps at Millimeter Wavelengths
Authors: Anirban Roy, Dariannette Valentín-Martínez, Kailai Wang, Nicholas Battaglia, Alexander van Engelen
Figure caption: We compare the power spectra of C II 158 lines at four different redshifts between the halo model and simulations. The figure also shows the error bars for C II 158 lines forecasted based on the halo model approach for the different frequency bands of the EoR-Spec on the FYST experiment.
Paper:  LIMpy: A Semianalytic Approach to Simulating Multiline Intensity Maps at Millimeter Wavelengths
Authors: Anirban Roy, Dariannette Valentín-Martínez, Kailai Wang, Nicholas Battaglia, Alexander van Engelen
Figure caption: The power spectra of O III 88 lines at redshifts 14.5, 11.2, 8.7, and 7.3. Dashed lines show the signal from the clustering term only, and solid lines describe the total signal comprising both the clustering and shot noise terms. The solid red lines at each panel denote the best-fit (mean) line of all these models.
Paper:  LIMpy: A Semianalytic Approach to Simulating Multiline Intensity Maps at Millimeter Wavelengths
Authors: Anirban Roy, Dariannette Valentín-Martínez, Kailai Wang, Nicholas Battaglia, Alexander van Engelen
Figure caption: We show the power spectra of CO(7–6) lines obtained using various models. The Silva15 SFR model is used to determine the signal at all redshifts to maintain consistency in the analysis.
Paper: YunMa: Enabling Spectral Retrievals of Exoplanetary Clouds
Authors: Sushuang Ma, Yuichi Ito, Ahmed Faris Al-Refaie, Quentin Changeat, Billy Edwards, Giovanna Tinetti
Figure caption: Validation of radiative-transfer simulations obtained with YunMa against the open-source code PyMieScatt (Sumlin et al. 2018). The extinction coefficients for cloud particles with different sizes are estimated from the theory of Bohren & Huffman (2008). To address the computational limitations of retrievals, we precalculated the extinction coefficients used in Equation (8) to estimate the cross sections of the cloud particles. The precalculated list includes values for particle radii from 1 × 10−7 to 1 × 10−2 μm, equally spaced in the logarithm space. Here, we show only six examples in the top panel. Bottom panels: residuals obtained by subtracting the extinction coefficients as estimated by the two codes, YunMa and PyMieScatt. The maximum discrepancy, corresponding to the largest particle radius simulated here (r = 1 ×  102), is negligible, i.e., ±0.002.
Paper: YunMa: Enabling Spectral Retrievals of Exoplanetary Clouds
Authors: Sushuang Ma, Yuichi Ito, Ahmed Faris Al-Refaie, Quentin Changeat, Billy Edwards, Giovanna Tinetti
Figure caption: Comparison of YunMa's results against simulations by Charnay et al. (2021b) for the 100× solar metallicity scenario at the substellar point (see Figure 6(a) in the original paper). The condensate (blue) and vapor (cyan) MMRs are simulated by YunMa using the A-M approach with K = 102 m 2 s−1. The cross section of the two shaded areas indicates the range of cloud MMR and location simulated by Laboratoire de Météorologie Dynamique Generic GCM (LMDG) in Charnay et al. (2021b). LMDG is derived from the LMDZ Earth (Hourdin et al. 2006) and Mars (Forget et al. 1999) GCMs.
Paper: YunMa: Enabling Spectral Retrievals of Exoplanetary Clouds
Authors: Sushuang Ma, Yuichi Ito, Ahmed Faris Al-Refaie, Quentin Changeat, Billy Edwards, Giovanna Tinetti
Figure caption: Validation of the YunMa cloud microphysics model against the Jovian ammonia clouds in Ackerman & Marley (2001). q c corresponding to different sedimentation efficiencies (f sed) are shown. Solid lines: results from YunMa. Dashed lines: results from Figure 1 in Ackerman & Marley (2001). Dotted line: T–p profile.
Paper: YunMa: Enabling Spectral Retrievals of Exoplanetary Clouds
Authors: Sushuang Ma, Yuichi Ito, Ahmed Faris Al-Refaie, Quentin Changeat, Billy Edwards, Giovanna Tinetti
Figure caption: Sketch of the A-M micophysical approach adopted in YunMa. Cloud particles may form when the mixing ratio of the condensable gas exceeds the saturation mixing ratio, which is derived from its saturation vapor pressure (SVP). The vertical distribution of the cloud particle sizes (VDCP) is derived from the balance between the sedimentation of the cloud particles and the atmospheric turbulent mixing.
Paper: YunMa: Enabling Spectral Retrievals of Exoplanetary Clouds
Authors: Sushuang Ma, Yuichi Ito, Ahmed Faris Al-Refaie, Quentin Changeat, Billy Edwards, Giovanna Tinetti
Figure caption: Validation of YunMa (solid lines) against the A-M model in Gao et al. (2018; dashed lines). Top: condensate mixing ratios. Bottom: cloud particle effective mean radii.
Paper: Asteroseismology Sheds Light on the Origin of Carbon-deficient Red Giants: Likely Merger Products and Linked to the Li-rich Giants
Authors: Sunayana Maben, Simon W. Campbell, Yerra Bharat Kumar, Bacham E. Reddy, Gang Zhao
Figure caption: Top panel: ﹩\mathrm{log}(L/{L}_{\odot })﹩ as a function of asteroseismic radius, mass, Δν, and ﹩{\nu }_{\max }﹩. Bottom panel: ﹩\mathrm{log}(L/{L}_{\odot })﹩ as a function of the carbon, nitrogen, oxygen, and sodium abundances. Kernel density histograms are included to show the distributions for the RC CDGs, with the color scheme following the sample. The horizontal dashed line at ﹩\mathrm{log}(L/{L}_{\odot })\,=1.925﹩ dex, denotes the cut we use to define two different luminosity groups of our RC CDG sample (see the text for details). The large filled red triangles and open blue circles show our overluminous-RC CDGs and normal-luminosity-RC CDGs, respectively. Large black squares are the known wGb stars that have asteroseismic parameters from Hon et al. (2021) and the small black circles are the rest of the known wGb stars from the literature. The abundances of the known wGb stars are from high-resolution optical spectra (Adamczak & Lambert 2013; Palacios et al. 2016). In order to compare the abundances of the known wGb with those of our CDG sample, they need to be on the same scale. We apply average offsets of +0.02, −0.15, −0.12, −0.11, and −0.03 dex to the [C/Fe], [N/Fe], [O/Fe], [Na/Fe], and [Fe/H] values of known wGb, respectively, to account for the systematic difference between the abundances from IR and optical spectra (Jönsson et al. 2020). The top and right panels of all of the subplots show kernel density histograms for the RC CDGs (dashed blue lines and large red dots) and known wGb stars with asteroseismic parameters (small black dots). We use the solar abundance of C, N, O, and Na as derived by Grevesse et al. (2007).
Paper: Asteroseismology Sheds Light on the Origin of Carbon-deficient Red Giants: Likely Merger Products and Linked to the Li-rich Giants
Authors: Sunayana Maben, Simon W. Campbell, Yerra Bharat Kumar, Bacham E. Reddy, Gang Zhao
Figure caption: (a) The Hertzsprung–Russell diagram. (b) The mass–radius diagram. (c) The seismic quantity ﹩{{\nu }_{\max }}^{0.75}/{\rm{\Delta }}\nu ﹩ vs. ﹩{\nu }_{\max }﹩. The RC stars classified based on asteroseismic analysis form the background from Mosser et al. (2014) and Yu et al. (2018; small filled gray and silver circles, respectively). The helium subflash stars from Mosser et al. (2014) are represented by small filled green circles. The underluminous stars from Li et al. (2022) are shown by orange squares, the known wGb stars are shown by black squares, and the normal-luminosity-RC CDGs and the overluminous-RC CDGs from our study are shown by blue circles and red triangles, respectively.