adsabs/AstroCLIMB huggingface dataset:
Paper: Einstein@Home Searches for Gamma-Ray Pulsars in the Inner Galaxy
Authors: C. J. Clark, M. Di Mauro, J. Wu, B. Allen, O. Behnke, H. B. Eggenstein, B. Machenschalk, L. Nieder, P. M. Saz Parkinson, A. Ashok, P. Bruel, B. McGloughlin, M. A. Papa, F. Camilo, M. Kerr, P. Voraganti Padmanabh, S. M. Ransom
Figure caption: Distance dependence of the inferred properties of PSR J1649−3012. The top panel shows the intrinsic spin-down luminosity (﹩{\dot{E}}_{{\rm{int}}}﹩), after correcting for the Shklovskii effect according to our best-fitting timing model (dashed black line) and also the acceleration in the Galactic potential (solid black line). The gray shaded region shows 1σ uncertainties on the intrinsic spin-down luminosity, propagated from the uncertainty on the total proper motion, which we assume to be much larger than the uncertainty in the Galactic acceleration. The gamma-ray luminosity (Lγ) and 1σ uncertainties according to the observed energy flux (Gγ) from 4FGL-DR4 are shown by the red line and shaded region. The middle panel shows the corresponding gamma-ray efficiency, with the ratio of the red and black lines from the top panel shown by the dashed red and black line. The relative contributions to the efficiency uncertainty from the proper motion and observed flux uncertainties are shown by gray and red shaded regions, respectively. The dotted black line shows a loose upper limit corresponding to 100% efficiency. The bottom panel shows the ratio between the predicted density of MSPs in the putative Galactic bulge population from the model of F. Calore et al. (2016) and in the Galactic disk according to the model of L. Levin et al. (2013).
Paper: On the Properties of Turbulence in the Remnant of the Tycho Supernova
Authors: Oleh Petruk, Taras Kuzyo
Figure caption: Left: X-ray image of the Tycho SNR in the 1.2–4.0 keV range; the surface brightness is given in units of photons per square centimeter per second (ph/(cm2 s)). Right: the SNR’s radio image at 1.4 GHz, in janskys per beam (Jy beam−1). The image sizes are 1220 × 1220 pixels (﹩1{0}^{{\prime} }\times 1{0}^{{\prime} }﹩). The images shown are after background noise removal as described in Appendix A. Crosses correspond to the geometrical center of the SNR (red cross; J. S. Warren et al. 2005; S. Katsuda et al. 2010) and the actual explosion location (yellow cross; Z. Xue & B. E. Schaefer 2015).
Paper: Einstein@Home Searches for Gamma-Ray Pulsars in the Inner Galaxy
Authors: C. J. Clark, M. Di Mauro, J. Wu, B. Allen, O. Behnke, H. B. Eggenstein, B. Machenschalk, L. Nieder, P. M. Saz Parkinson, A. Ashok, P. Bruel, B. McGloughlin, M. A. Papa, F. Camilo, M. Kerr, P. Voraganti Padmanabh, S. M. Ransom
Figure caption: MeerKAT radio images at 1.28 GHz covering the locations of two new gamma-ray pulsars. No plausible radio counterparts are detected. Left panel: cutout from the SARAO MeerKAT Galactic Plane Survey (S. Goedhart et al. 2024) covering the position of PSR J1736−3422. Right panel: cutout from the MeerKAT GC Mosaic (I. Heywood et al. 2022) covering the position of PSR J1748−2815. Inset panels contain the ﹩1^{\prime} \rm{}\,\rm{}\,\times 1^{\prime} \rm{}\,\rm{}\,﹩ region around the pulsars from which we estimated the rms noise level to obtain flux-density upper limits, with the gamma-ray timing positions of the pulsars marked by red crosses. The positional uncertainties are smaller than these markers. The gray scale has the mean intensity subtracted, and a square-root normalization applied, as indicated in the color bar.
Paper: Einstein@Home Searches for Gamma-Ray Pulsars in the Inner Galaxy
Authors: C. J. Clark, M. Di Mauro, J. Wu, B. Allen, O. Behnke, H. B. Eggenstein, B. Machenschalk, L. Nieder, P. M. Saz Parkinson, A. Ashok, P. Bruel, B. McGloughlin, M. A. Papa, F. Camilo, M. Kerr, P. Voraganti Padmanabh, S. M. Ransom
Figure caption: Gamma-ray photon counts maps of the GC region. Each row shows counts maps for logarithmically spaced energy bands, convolved with the Fermi-LAT PSF for the highest energy in that band. The gamma-ray timing position of PSR J1748−2815 is highlighted by black markers. In each row the panels show, from left to right the total photon counts, on-pulse photon counts (divided by the on-pulse phase fraction to maintain the same color scale as the total count maps), off-pulse photon counts (divided by the off-pulse phase fraction), and the difference between the rescaled on- and off-pulse maps in S/N units. Counts maps have a square-root scaling, indicated in the color bars. Contour lines on the difference images are at the 2σ and 3σ levels. The point source visible at (l, b) = (359﹩\mathop{.}\limits^{\unicode{x000b0}}﹩3, −0﹩\mathop{.}\limits^{\unicode{x000b0}}﹩8), highlighted by white markers, is another gamma-ray pulsar, PSR J1747−2958.
Paper: Einstein@Home Searches for Gamma-Ray Pulsars in the Inner Galaxy
Authors: C. J. Clark, M. Di Mauro, J. Wu, B. Allen, O. Behnke, H. B. Eggenstein, B. Machenschalk, L. Nieder, P. M. Saz Parkinson, A. Ashok, P. Bruel, B. McGloughlin, M. A. Papa, F. Camilo, M. Kerr, P. Voraganti Padmanabh, S. M. Ransom
Figure caption: Illustration of timing noise in PSR J1736−3422. The left panel shows the estimated variations in the rotational phase, after subtracting a cubic spin-down model, with the 2σ confidence interval indicated by the blue shaded region. The right panel shows the resulting power spectrum of these phase variations. The black error bars show the 1σ posterior uncertainties on the Fourier powers, marginalized over the underlying timing model and template pulse-profile shape. The blue dotted–dashed lines show the best-fitting models for the two noise components, while the red line and shaded region shows the best-fitting model and uncertainty regions for the full noise model prior. The estimated white-noise level is shown by the black dashed line. The posterior distributions for high frequencies are all below this level, and closely follow the priors as a result.
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) Variations of the observed QPO frequencies with time (in days) from shaded parts (1–5) of Figure 1, in the rising phase of the outburst with the fitted POS model (dashed curve), are shown. (b) Variations of the shock location (in Schwarzschild radius rS) and shock compression ratio (R) are shown. The model-fitted Δχ variation is shown in the middle panel. Here points A–F mark the start, end, or major transition phases of the evolution.
Paper: Einstein@Home Searches for Gamma-Ray Pulsars in the Inner Galaxy
Authors: C. J. Clark, M. Di Mauro, J. Wu, B. Allen, O. Behnke, H. B. Eggenstein, B. Machenschalk, L. Nieder, P. M. Saz Parkinson, A. Ashok, P. Bruel, B. McGloughlin, M. A. Papa, F. Camilo, M. Kerr, P. Voraganti Padmanabh, S. M. Ransom
Figure caption: Photon phases and pulse profiles for the new gamma-ray pulsars discovered in this work. Lower panels show the phases for individual photons according to our best-fitting gamma-ray timing models, with the photon probability weights indicated by the gray scale. Upper panels show the integrated pulse profiles. The dashed blue lines show the estimated background level, calculated from the photon weights as ∑jwj(1 − wj)/Nbins (A. A. Abdo et al. 2013). Flux below these lines is attributed to the diffuse background or other nearby point sources. The period of enhanced exposure toward the GC is visible here as darker bands containing more photons between MJDs 56600 and 57000.
Paper: Impact of Multimessenger Spectral Modeling on Blazar–Neutrino Associations
Authors: Julian Kuhlmann, Francesca Capel
Figure caption: Event-wise analyses of fits. Left (right) column shows results using an uninformative (informative) E0 prior. Position of alert events included in IceCube Collaboration (2021) are marked by a magenta circle, their 90% angular uncertainty is shown as a gray circle. A box enclosing the 90% likelihood contour of associated IceCat-1 events is plotted in light blue. The alert events’ reconstructed energy is linked to their respective energy posterior by a dashed line.
Paper: The Role of Spiral Arms in Galaxies. II. Similarities amid Diversity
Authors: Bingqing Sun, Daniela Calzetti, Andrew J. Battisti
Figure caption: Parameter maps for NGC 1097. From top to bottom rows: SFR; stellar mass; and specific star formation rate (sSFR). In each row, the three panels from left to right are best-fit values of all spaxels with S/N ≥ 3 in IRAC 3.6 μm band (including include bulge spaxels); arm spaxels; and interarm spaxels, with the bulge spaxels excluded.
Paper: The Role of Spiral Arms in Galaxies. II. Similarities amid Diversity
Authors: Bingqing Sun, Daniela Calzetti, Andrew J. Battisti
Figure caption: SFE vs. sSFR in all galaxies. Left: all spaxels in six galaxies. Middle: all arm spaxels in six galaxies. Right: all interarm spaxels in six galaxies. The straight lines are the linear fit of log(sSFR/yr−1) and log(SFE/yr−1).
Paper: Impact of Multimessenger Spectral Modeling on Blazar–Neutrino Associations
Authors: Julian Kuhlmann, Francesca Capel
Figure caption:                         Comparison of power-law fits (left double column) to Fit #2 (right double column). See Figure A1 for details.
Paper: The Role of Spiral Arms in Galaxies. II. Similarities amid Diversity
Authors: Bingqing Sun, Daniela Calzetti, Andrew J. Battisti
Figure caption: sSFR distributions for arm and interarm spaxels across six galaxies. The median values are −0.681 (arm) and –0.937 (interarm). The median ratio is 1.800. The black dotted lines are the Gaussian fits of all arm/interarm spaxels. The solid lines are the Gaussian fits of the right side of the distribution, centered on the median values, using the same color coding of the two distributions.
Paper: Impact of Multimessenger Spectral Modeling on Blazar–Neutrino Associations
Authors: Julian Kuhlmann, Francesca Capel
Figure caption: Prior dependency tests on fit results.
Paper: A Novel Test for MOND: Gravitational Lensing by Disk Galaxies
Authors: Christopher Harvey-Hawes, Marco Galoppo
Figure caption: A comparison of lensing cross section predictions with varying inclination angle for the same disk galaxy in MOND and the conventional DM scenario. The disk galaxy parameters are Md = 1011 M⊙, Rd = 3.5 kpc, zd = 0.35 kpc, and Mb = 109 M⊙, and rb = 0.7 kpc. The DM halo is taken as an NSIS profile with parameters ρ0 = 2.51 · 107 M⊙ kpc−3, and r0 = 5.48 kpc. The lens and source are placed at redshift zL = 0.5 and zS = 2.0, respectively. The shaded areas represent the one standard deviation uncertainties around the obtained SGL cross section curves.
Paper: A Novel Test for MOND: Gravitational Lensing by Disk Galaxies
Authors: Christopher Harvey-Hawes, Marco Galoppo
Figure caption: A comparison of lensing cross sections predictions with varying inclination angle, for the same disk galaxy, in the MONDian and the conventional DM scenario. Here, the MOND interpolating function is taken to give an infinitely sharp transition to the dMOND regime. The disk galaxy parameters are Md = 1011 M⊙, Rd = 3.5 kpc, zd = 0.35 kpc, and Mb = 109 M⊙, and rb = 0.7 kpc. The DM halo is taken as an NSIS profile with parameters ρ0 = 2.51 · 107 M⊙ kpc−3, and r0 = 5.48 kpc. The lens and source are placed at redshift zL = 0.5 and zS = 2.0, respectively. The shaded areas represent the one standard deviation uncertainties around the obtained SGL cross section curves.
Paper: A Novel Test for MOND: Gravitational Lensing by Disk Galaxies
Authors: Christopher Harvey-Hawes, Marco Galoppo
Figure caption: Impact of bulge mass Mb on lensing cross section σ with varying inclination angle within the MOND scenario. The other corresponding lens galaxy parameters are Md = 1011 M⊙, Rd = 3.5 kpc, zd = 0.35 kpc, and rb = 0.7 kpc. The lens and source are placed at redshift zL = 0.5 and zS = 2.0, respectively. The shaded areas represent the one standard deviation uncertainties around the obtained SGL cross section curves.
Paper: A Novel Test for MOND: Gravitational Lensing by Disk Galaxies
Authors: Christopher Harvey-Hawes, Marco Galoppo
Figure caption: A comparison of lensing cross section predictions with varying inclination angle for the same disk galaxy in MOND for different choices of interpolating functions. For the sigmoid interpolating functions (see Equation (23)), we have chosen ﹩{\tilde{a}}_{{\rm{N}},{\rm{trans}}}=2,\,5﹩. The disk galaxy parameters are Md = 1011 M⊙, Rd = 3.5 kpc, zd = 0.35 kpc, and Mb = 109 M⊙, and rb = 0.7 kpc. The shaded areas represent the one standard deviation uncertainties around the obtained SGL cross section curves.
Paper: A Novel Test for MOND: Gravitational Lensing by Disk Galaxies
Authors: Christopher Harvey-Hawes, Marco Galoppo
Figure caption: Impact of disk thickness zd on lensing cross section σ with varying inclination angle within the MOND scenario. The other corresponding lens galaxy parameters are Md = 1011 M⊙, Rd = 3.5 kpc, Mb = 109 M⊙, and rb = 0.7 kpc. The lens and source are placed at redshift zL = 0.5 and zS = 2.0, respectively. The shaded areas represent the one standard deviation uncertainties around the obtained SGL cross section curves.
Paper: The AURORA Survey: Tracing Galactic Outflows at z ≳ 2.5 with JWST/NIRSpec Near-ultraviolet Absorption Lines
Authors: Emily Kehoe, Alice E. Shapley, Ryan L. Sanders, Naveen A. Reddy, Michael W. Topping, Natalie Lam, Leonardo Clarke, Fergus Cullen, Richard S. Ellis, N. M. Förster Schreiber, Tucker Jones, Ali Ahmad Khostovan, Derek J. McLeod, Ross J. McLure, Desika Narayanan, Pascal Oesch, Anthony J. Pahl
Figure caption: Example of AURORA spectra at three different redshifts that are continuum normalized: COSMOS-8363 at z = 3.247511 (top), GOODSN-17940 at z = 4.11541 (middle), and GOODSN-100067 at z = 5.187539 (bottom). The error spectra are plotted as gray shaded regions. Blue labels indicate absorption lines that we use to analyze outflow velocities from Fe II. Red labels indicate the Mg II doublet. Green labels indicate emission lines. The orange label indicates the Mg I absorption line.
Paper: A Novel Test for MOND: Gravitational Lensing by Disk Galaxies
Authors: Christopher Harvey-Hawes, Marco Galoppo
Figure caption: A comparison of MONDian rotation curve predictions with the best-fit DM alternative. The solid black line shows the MONDian rotation curve prediction for a disk galaxy with parameters: Md = 1011 M⊙, Rd = 3.5 kpc, zd = 0.35 kpc, and Mb = 109 M⊙, and rb = 0.7 kpc. The dashed red line shows the corresponding Newtonian fit of a DM halo, which is taken as an NSIS profile with parameters ρ0 = 2.51 · 107 M⊙ kpc−3, and r0 = 5.48 kpc.
Paper: A Novel Test for MOND: Gravitational Lensing by Disk Galaxies
Authors: Christopher Harvey-Hawes, Marco Galoppo
Figure caption: A comparison between the numerically obtained PDM (black line) and analytical prediction (dashed purple line) for a Plummer profile with M⊙, and rb = 0.7 kpc. The MOND interpolating function selected is the one displayed in Equation (21).
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: Inferring the CAMELS box parameters (both cosmology and feedback strengths) from a sample of 100 SFHs using SBI across the three models. Top: corner plots showing the inferred posteriors for a single sample of SFHs corresponding to a realization of cosmology and feedback strength. Bottom: average results of 1000 realizations across the full CAMELS parameter space. The cosmology is well constrained, as are the ASN1, ASN2 parameters, while AAGN1 and AAGN2 are not well constrained except for in ASTRID. Since the feedback parameters do not always denote the same quantity across the models, caution needs to be exercised while interpreting absolute values. However, relative trends across galaxy populations will still provide robust estimates of how feedback changes across galaxy demographics. This represents a proof of concept, and application to real data will require forward modeling of noise and systematic effects.
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: The impact of varying cosmology and feedback strengths on the gas-phase metallicity of galaxies as a function of halo mass at z ∼ 0 in the three models.
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: Validation plots comparing median (solid lines) and 16th–84th percentiles (shaded regions) of the SFHs sampled from the trained normalizing flows (labeled NN) against SFHs from the CAMELS 1P data set that vary a single parameter in the CAMELS box while keeping the others fixed at the fiducial value. The different panels show the 1P data set for all six CAMELS box parameters. While the 1P data set shows a single realization of SFHs, the normalizing flow returns a distribution of SFHs corresponding to each set of parameters.
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: The distribution of ﹩{\chi }_{\mathrm{SFH}}^{2}﹩ values across the CAMELS parameter space when comparing the SFHs varying two parameters to the linear combination of the corresponding one-parameter variations for the three CAMELS models: TNG (blue), SIMBA (red), and ASTRID (green). Values in each cell show the ﹩{\chi }_{\mathrm{SFH}}^{2}﹩, which also correspond to the intensity of the color maps.
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 22, but for the mean duty cycle of the SFHs (i.e., how much time an SFH spends actively forming stars).
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 17, the plots here show the effects on the baryon fraction and stellar-to-gas mass ratio while varying the CAMELS parameters for all three models, for halos 1011.5 < Mh < 1012.5M⊙. The black lines show lines of constant baryon fraction to stellar-to-gas mass ratio.
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 22, but for the fraction of quenched galaxies at z ∼ 0.
Paper: α-MC: Self-consistent α-enhanced Stellar Population Models Covering a Wide Range of Age, Metallicity, and Wavelength
Authors: Minjung Park, Charlie Conroy, Benjamin D. Johnson, Joel Leja, Aaron Dotter, Phillip A. Cargile
Figure caption: An example grid of the MIST v2.5 isochrones at [Fe/H] = –1.0 (left) and 0.0 (right) for a wide range of ages. Different colors indicate [α/Fe] values at fixed [Fe/H].
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: Left panel: an example SED-fitting result for an AGN-dominated source (C. J. Burke et al. (2022) ID = 43). In this case, including a stellar emission component does not significantly improve the fit, meaning that the stellar emission and related parameters, such as stellar mass and star formation history, cannot be reliably constrained. Right panel: an example SED-fitting result for a source that is not AGN dominated (C. J. Burke et al. (2022) ID = 265). Here, adding a stellar emission component improves the best-fit ﹩{\chi }_{\nu }^{2}﹩, and the resulting best-fit stellar emission shows a significant excess over the AGN continuum emission near ∼1.2 μm, allowing for a reliable stellar mass estimate. The uncertainties on the stellar mass are statistical only, as provided by CIGALE. The vertical red line near 1.2 μm marks the region where AGN emission is at a minimum. The red number is the monochromatic flux ratio of the star formation emission component (blue) in the best-fit model SF+AGN model and the total AGN-dominated model (gray). Both redshifts are spectroscopic.
Paper: α-MC: Self-consistent α-enhanced Stellar Population Models Covering a Wide Range of Age, Metallicity, and Wavelength
Authors: Minjung Park, Charlie Conroy, Benjamin D. Johnson, Joel Leja, Aaron Dotter, Phillip A. Cargile
Figure caption: SSPs around individual Lick indices with [Fe/H] = +0.0 and varying [α/Fe] (shown as different colors) for fixed age of 4 Gyr. Each panel zooms in around each Lick index. The gray, blue, and red shades indicate the index bandpass and blue and red pseudo-continua defined in S. C. Trager et al. (1998). The SSP spectra are smoothed to 8.4 Å (FWMH) resolution. The flux of SSP spectra with varying [α/Fe] is normalized to the midpoint of the blue continuum of solar-scaled SSP spectra.