adsabs/AstroCLIMB huggingface dataset:
Paper: New Symbiotic Stars or Candidates in LAMOST Low-resolution Spectra
Authors: Yabing Zhao, Sufen Guo, Guoliang Lü, Chunhua Zhu, Jiao Li, Jianrong Shi
Figure caption: Color–magnitude Hertzsprung–Russell diagram. The gray points represent background stars within 125 pc from Gaia. The green points denote 355 known symbiotic stars (J. Merc et al. 2020). The blue points correspond to 3675 late-type giants (S. Li et al. 2022). The red region indicates the area where symbiotic stars and giants mostly overlap, with GBP − GRP ranging from 0.95 to 4.05 and absolute magnitude MG constrained by ﹩-10\lt {M}_{G}\lt {\rm{\min }}(1.8\times ({G}_{{\rm{BP}}}-{G}_{{\rm{RP}}})-3.4)﹩ mag, which is taken as the screening criterion for late-type giants.
Paper: Kinematically Complex Circumgalactic Gas Around a Low-mass Galaxy: Filamentary Inflow and Counterrotation in J0910b
Authors: Zeren Lin, D. Christopher Martin, Mateusz Matuszewski, James D. Neill, Drew M. Miles, Vincent Picouet, Nikolaus Z. Prusinski, Keri Hoadley, Rosalie McGurk
Figure caption: Adaptive smoothing process. Upper left: the ratio ﹩f=\frac{{{\rm{SNR}}}_{{\rm{\min }}}+{{\rm{SNR}}}_{{\rm{\max }}}}{{{\rm{SNR}}}_{{\rm{med}}}}﹩ is plotted against the smoothing step. Throughout the entire process, f > 1, indicating that the cube has been undersmoothed. Upper right: spectral and spatial smoothing scales used during the adaptive smoothing process. Lower left: detected pixels are shown here. The number of detected pixels varies with the SNR threshold; lowering the threshold increases the count, while raising it decreases the count. We adopt a detection threshold of ﹩{{\rm{SNR}}}_{{\rm{th}}}={{\rm{SNR}}}_{{\rm{\min }}}=2.5﹩, consistent with the radial binning method described in Section 3.1.
Paper: New Symbiotic Stars or Candidates in LAMOST Low-resolution Spectra
Authors: Yabing Zhao, Sufen Guo, Guoliang Lü, Chunhua Zhu, Jiao Li, Jianrong Shi
Figure caption: The low-resolution LAMOST spectrum of ZTF J005917.52+315605.4. We took four wavelength segments containing the characteristic emission lines of symbiotic stars for amplification. The emission lines are indicated in red and the absorption lines in green. The details are discussed in Section 4.1.1.
Paper: New Symbiotic Stars or Candidates in LAMOST Low-resolution Spectra
Authors: Yabing Zhao, Sufen Guo, Guoliang Lü, Chunhua Zhu, Jiao Li, Jianrong Shi
Figure caption: The low-resolution LAMOST spectrum of the symbiotic star EM* StHA 190. The black line and the red line represent the spectrum and continuum of the object, respectively.
Paper: Two-stage Nature of a Solar Flare with Parallel and Semicircular Ribbons
Authors: Ruifei Huang, Hao Ning, Ze Zhong, Ye Qiu, Zhenyong Hou, Yang Su, Chuan Li, Xiangliang Kong, Yao Chen
Figure caption: Schematic maps of the flare magnetic configuration around t1 (14:15:44 UT), t2 (14:16:40 UT), and t3 (14:16:53 UT) in panels (a)–(c), respectively. The white (black) area in the bottom represents the positive (negative) polarity. The fading yellow patches and red arrows show the the sequential brightening of flare ribbons. Green and orange lines have the same meanings as those in Figure 7(b). Cyan and red field lines in Figure 7(c) are changed into dashed lines here. The null point is marked with an asterisk in panel (b). Red and pink solid lines depict the cross section of the rising flux rope.
Paper: Two-stage Nature of a Solar Flare with Parallel and Semicircular Ribbons
Authors: Ruifei Huang, Hao Ning, Ze Zhong, Ye Qiu, Zhenyong Hou, Yang Su, Chuan Li, Xiangliang Kong, Yao Chen
Figure caption: (a) GOES SXRs at 1–8 Å (red) and ASO-S/HXI X-ray light curves in 10–20 (blue), 20–30 (green), and 30–50 (pink) keV. Three vertical dashed lines represent the moments of t1 (14:15:44 UT), t2 (14:16:40 UT), and t3 (14:16:53 UT), corresponding to the two major peaks and the trough of the HXR light curves in 30–50 keV. The two stages of this event (stage 1: 14:14:41–14:16:40 UT; stage 2: 14:16:40–14:18:36 UT) are shaded in gray, separated by t2.
Paper: Two-stage Nature of a Solar Flare with Parallel and Semicircular Ribbons
Authors: Ruifei Huang, Hao Ning, Ze Zhong, Ye Qiu, Zhenyong Hou, Yang Su, Chuan Li, Xiangliang Kong, Yao Chen
Figure caption: Selected field lines from the potential field extrapolation. (a) Yellow field lines depict a dome-like configuration, and green field lines show another connectivity. The bottom boundary maps the distribution of the signed log(Q). The white and black contours show the photospheric vertical magnetic field of ±300 G. (b) and (c) Two groups of null-point reconnection configuration. Orange lines in panel (b) and red lines in panel (c) represent field lines before the null-point reconnection, while green lines in panel (b) and cyan lines in panel (c) represent field lines after it. The null point is marked as “NP.”
Paper: Two-stage Nature of a Solar Flare with Parallel and Semicircular Ribbons
Authors: Ruifei Huang, Hao Ning, Ze Zhong, Ye Qiu, Zhenyong Hou, Yang Su, Chuan Li, Xiangliang Kong, Yao Chen
Figure caption: (a) HMI line-of-sight magnetogram overlaid with red contours at the 90% intensity level of AIA 1600 Å image at 14:17:02 UT. Cyan rectangles mark ribbon regions R1–R6. Arcade 1 and 2 are delineated by yellow dashed lines. (b) AIA 1600 Å light curves in regions R1 (purple) and R2 (red) and 30–50 keV HXR flux (pink) from 14:13:26 to 14:20:38 UT. The gray shading represents the two-stage time interval, identical to that in Figure 1. (c) Same as (b) but for regions R3 (cyan), R4 (dark green), R3+R4 (brown), R5 (light green), and R6 (orange).
Paper: From Wide Triples to Ultracompact X-ray Binaries: Multimessenger Signatures of Dynamically Formed Black Hole–White Dwarf Systems in the LISA Band
Authors: Zeyuan Xuan, Cheyanne Shariat, Smadar Naoz
Figure caption: The X-ray detectable time of a representative UCXB source, as a function of its distance. Here, we consider a mass-transferring BH–WD system with initial mass m1 = 10 M⊙, m2 = 0.6 M⊙, and computed its total detectable lifetime in X-ray, assuming a detector sensitivity of FX,crit = 10−15,  10−14, 10−13 erg cm−2 s−1, respectively (from left to right).
Paper: From Wide Triples to Ultracompact X-ray Binaries: Multimessenger Signatures of Dynamically Formed Black Hole–White Dwarf Systems in the LISA Band
Authors: Zeyuan Xuan, Cheyanne Shariat, Smadar Naoz
Figure caption: Comparison between tidal angular momentum and energy transfer rate, ﹩{\dot{J}}_{{\rm{tide}}}﹩ and ﹩{\dot{E}}_{{\rm{tide}}}﹩, as functions of the WD spin. Here, we consider a 10 − 0.6 M⊙ BH–WD system with e = 0.9,  rp = 3 × 10−3 au, ﹩\hat{F}(\omega )\,=150{\omega }^{5}﹩, and plot ﹩{\dot{J}}_{{\rm{tide}}}﹩ and ﹩{\dot{E}}_{{\rm{tide}}}﹩ as functions of the ratio between the WD spin angular frequency, Ωs, and orbital pericenter frequency, Ωp.
Paper: Reconstructing PSP/ISOIS Pitch-angle-resolved Intensities Using Unsupervised Learning
Authors: Spiridon Kasapis, Manuel E. Cuesta, Leng Ying Khoo, Hameedullah A. Farooki, Sungmin Pak, Jamey R. Szalay, Mitchell M. Shen, Jamie Rankin, Dionysios Christopoulos, George Livadiotis, David J. McComas
Figure caption: Percentage of missing PAD data for the 15 different pitch-angle ranges included in the IS⊙IS EPI-Lo Level 3 dataset. Each box shows the missing data distribution across the 28 SEP events, with the box edges representing the interquartile range, the whisker edges the upper and lower bounds of the distribution, the orange line the median, and the circles the outlier values. The inset shows the EPI-Lo instrument’s side view, with the x-axis being the mounting plane (spacecraft’s deck).
Paper: Bright Siren without an Electromagnetic Counterpart Detected by the LISA-Taiji-TianQin Network
Authors: Yejing Zhan, David Izquierdo-Villalba, Xiao Guo, Qing Yang, Daniele Spinoso, Fa-Yin Wang
Figure caption: The sky map of fractional distance uncertainty (left column) and sky location uncertainty from equal-mass MBHBs of 106M⊙ at a distance of 104 Mpc, comparing single detectors and their network. The top three panels in each column represent the single detectors, and the bottom panel represents their network. The sky maps in each column share the same color bar. While the distance uncertainty exhibits only weak sky angular sensitivity, varying by less than an order of magnitude across the sky, the sky location uncertainty is highly sensitive to sky location, varying by factors of 102–104. Taiji provides the best constraint on both distances and sky locations, due to its longest arm length. LISA ranks second, while TianQin has the worst constraint. The network enhances the accuracy of the distance uncertainty by a factor of <2 for a single detector. Additionally, the network highly improves the sky location accuracy by a factor of ∼102.
Paper: Bright Siren without an Electromagnetic Counterpart Detected by the LISA-Taiji-TianQin Network
Authors: Yejing Zhan, David Izquierdo-Villalba, Xiao Guo, Qing Yang, Daniele Spinoso, Fa-Yin Wang
Figure caption: The identification horizon for the detector network with the uniform GND (0.02 Mpc−3) at the polar point (left figure) and equatorial point (right figure) for MBHBs with different masses. The maximum identification horizon for both points is reached at the equal-mass system with masses of ∼106M⊙. The identification horizons get closer with a lower or higher mass and a lower mass ratio.
Paper: Bright Siren without an Electromagnetic Counterpart Detected by the LISA-Taiji-TianQin Network
Authors: Yejing Zhan, David Izquierdo-Villalba, Xiao Guo, Qing Yang, Daniele Spinoso, Fa-Yin Wang
Figure caption: The same as Figure 5 for the detector network, but with z-dependent GND (n8,9(z), n9,14(z)). The left figure represents the identification horizon at the polar point, while the right one represents that at the equatorial point. The identification horizon shows similar patterns to Figure 5, but the horizon is further.
Paper: Bright Siren without an Electromagnetic Counterpart Detected by the LISA-Taiji-TianQin Network
Authors: Yejing Zhan, David Izquierdo-Villalba, Xiao Guo, Qing Yang, Daniele Spinoso, Fa-Yin Wang
Figure caption: The distribution of fractional uncertainty on H0 across realizations. The averaged uncertainties for each population model are plotted in colored dashed lines. Figure (a) represents the constraints with the uniform GND. The fractional uncertainty for the LightSeed-Nodelay, HeavySeed-Delay, and HeavySeed-Nodelay models spans a range of approximately 0.6%–10% with uniform GND, whereas the QY25 model produces tighter constraints, spanning 0.3%–6%. In contrast, the IV24 model exhibits significantly greater variation under both GND assumptions, with most realizations constraining H0 to better than 1%, though a small number exceed 10%.
Paper: Bright Siren without an Electromagnetic Counterpart Detected by the LISA-Taiji-TianQin Network
Authors: Yejing Zhan, David Izquierdo-Villalba, Xiao Guo, Qing Yang, Daniele Spinoso, Fa-Yin Wang
Figure caption: The sky map of the volume uncertainty with an equal mass of 106M⊙ at a distance of 104 Mpc, comparing individual detectors and their network. The top panels represent the individual detectors, and the bottom panel represents their network. All the sky maps share the same color bar. The sky location uncertainty reaches its minimum at the celestial equator and its maximum at the celestial pole. We choose the equatorial point (θs = 10∘, ϕs = 90∘) for subsequent calculation, representing the most accurate case. We set the decl. θs = 10∘ to prevent the extinction effects from the Galactic plane. Conversely, to represent the most uncertain case, we choose the polar point (90∘, 89∘).
Paper: Bright Siren without an Electromagnetic Counterpart Detected by the LISA-Taiji-TianQin Network
Authors: Yejing Zhan, David Izquierdo-Villalba, Xiao Guo, Qing Yang, Daniele Spinoso, Fa-Yin Wang
Figure caption: The dependence of the identification horizons under uniform GND of 0.02 Mpc−3 on inclination angle ι (orange line), the polarization angle ψ (blue line), and the coalescence time tc (green line). The inset provides a magnified view of the blue curve. The horizon is most sensitive to ι, reaching a maximum of z ∼ 1.2 at ι = 0 and a minimum of z ∼ 0.95 at ι = π/2 (changed by 25%). In comparison, the horizon shows significantly weaker dependence on tc, varying by less than 15%. It is even less sensitive to ψ, with variations confined to less than 1%.
Paper: Bright Siren without an Electromagnetic Counterpart Detected by the LISA-Taiji-TianQin Network
Authors: Yejing Zhan, David Izquierdo-Villalba, Xiao Guo, Qing Yang, Daniele Spinoso, Fa-Yin Wang
Figure caption: The identification horizons from single detectors at equatorial points with the uniform GND (left) and z-dependent GND (right). All figures share the same color bar. The identification horizons show the same pattern as Figures 5 and 6. Taiji has the farthest identification horizon, and LISA ranks second, followed by TianQin, which consists of the result of volume uncertainty.
Paper: Continuous Gravitational Waves from Magnetized White Dwarfs: Quantifying the Detection Plausibility by LISA
Authors: Mayusree Das, Banibrata Mukhopadhyay, Tomasz Bulik
Figure caption: Same as Figure 4, except for WD1+BP but without a magnetosphere. As χ → 0, the decays are shown in log scale too in the inset in the top panel.
Paper: Continuous Gravitational Waves from Magnetized White Dwarfs: Quantifying the Detection Plausibility by LISA
Authors: Mayusree Das, Banibrata Mukhopadhyay, Tomasz Bulik
Figure caption: Characteristic strains using Equation (17) for WDs like WD1+BP (﹩{B}_{\max }^{\mathrm{Toroidal}}=4\times 1{0}^{13}﹩ G, ﹩{B}_{p}^{\mathrm{Poloidal}}=8\times 1{0}^{8}﹩ G, initial ν = 0.05 Hz and initial χ = 3∘, d = 1 kpc) at young (t ∼ 0) and old (near the end of the active timescale, t = 105 yr) ages are shown along with detector sensitivities.
Paper: Continuous Gravitational Waves from Magnetized White Dwarfs: Quantifying the Detection Plausibility by LISA
Authors: Mayusree Das, Banibrata Mukhopadhyay, Tomasz Bulik
Figure caption: Top panel: characteristic strain from ZTF J1901+1458 for a 4 yr mission with present (initial) χ ∼ 30° and ν = 1/416 Hz. Bottom panel: SNR of ZTF J1901+1458 for various detectors for a 4 yr long mission. The orange line corresponds to SNRth = 8. The SNRs are shown only for the detectors in the relevant frequency range.
Paper: Continuous Gravitational Waves from Magnetized White Dwarfs: Quantifying the Detection Plausibility by LISA
Authors: Mayusree Das, Banibrata Mukhopadhyay, Tomasz Bulik
Figure caption: Top panel: SNR of WD1+BP (of M = 1.83 M⊙) for various detectors as a function of integration time assuming d = 1 kpc. Bottom panel: same as the top panel, except for WD3 (of M = 1.42 M⊙)—a WD with a weaker toroidal magnetic field. The orange line corresponds to SNRth = 8.
Paper: Continuous Gravitational Waves from Magnetized White Dwarfs: Quantifying the Detection Plausibility by LISA
Authors: Mayusree Das, Banibrata Mukhopadhyay, Tomasz Bulik
Figure caption: Density isocontour (top panel) and magnetic field isocontour (bottom panel) of the ZTF J1901+1458 model.
Paper: Continuous Gravitational Waves from Magnetized White Dwarfs: Quantifying the Detection Plausibility by LISA
Authors: Mayusree Das, Banibrata Mukhopadhyay, Tomasz Bulik
Figure caption: Same as Figure 6, except that the WD1 has a subdominant nonzero multipolar field.
Paper: Continuous Gravitational Waves from Magnetized White Dwarfs: Quantifying the Detection Plausibility by LISA
Authors: Mayusree Das, Banibrata Mukhopadhyay, Tomasz Bulik
Figure caption: Observed probability distribution of a WD’s various spin frequency from A. Kawka (2020).
Paper: Continuous Gravitational Waves from Magnetized White Dwarfs: Quantifying the Detection Plausibility by LISA
Authors: Mayusree Das, Banibrata Mukhopadhyay, Tomasz Bulik
Figure caption: A 2D representation of Figure 10: variations of d with χ for various ν.
Paper: Disentangling Thermal and Abundance Characteristics in a Solar Flare Using SDO/AIA, Hinode/XRT, and MinXSS-1 Observations
Authors: Xiaoyan Xie, Anna Chen, Crisel Suarez, Katharine K. Reeves, Soumya Roy, Christopher S. Moore, Nishu Karna, Joy Velasquez
Figure caption: Evolution of the temperature (top row) and EM (bottom row) of the flare from AIA observations. Squares at 01:48:07 UT mark the locations of the plasma cloud (P), northern loops (NL), and southern loops (SL) for plotting temperature as a function of time in Figure 6. Crosses mark the locations for checking DEM–temperature distributions at 01:55:19 in Figure 8.
Paper: Disentangling Thermal and Abundance Characteristics in a Solar Flare Using SDO/AIA, Hinode/XRT, and MinXSS-1 Observations
Authors: Xiaoyan Xie, Anna Chen, Crisel Suarez, Katharine K. Reeves, Soumya Roy, Christopher S. Moore, Nishu Karna, Joy Velasquez
Figure caption: DEM–temperature distributions at 01:55:19 UT in the locations marked as crosses in Figure 5. Solid curves indicate DEMs derived from AIA channels with coronal (black), hybrid (blue), and photospheric (red) abundance models. Green dotted curves indicate DEMs derived from the combination of XRT and AIA channels with the coronal abundance model. The uncertainties of the black solid and green dotted curves are indicated by the same colored shadows. The uncertainties of the red and blue curves are shown in Appendix A to avoid confusion. The DEM-weighted average temperature with the coronal and photospheric abundance model for the AIA-only case (TCo and TPh) and combining additional XRT filters (TXRT) at each location is indicated in each panel.
Paper: Disentangling Thermal and Abundance Characteristics in a Solar Flare Using SDO/AIA, Hinode/XRT, and MinXSS-1 Observations
Authors: Xiaoyan Xie, Anna Chen, Crisel Suarez, Katharine K. Reeves, Soumya Roy, Christopher S. Moore, Nishu Karna, Joy Velasquez
Figure caption: The position-versus-time stack plots of temperature and EM distributions along the paths of C1 (top row) and C2 (bottom row) indicated in Figure 2. The distance increment corresponds to the arrow direction indicated on the paths C1 and C2. The dotted lines ca, cb, cc, and cd correspond to the crosses indicated in Figure 2. S2 indicates high-temperature drift in the plasma cloud.
Paper: Disentangling Thermal and Abundance Characteristics in a Solar Flare Using SDO/AIA, Hinode/XRT, and MinXSS-1 Observations
Authors: Xiaoyan Xie, Anna Chen, Crisel Suarez, Katharine K. Reeves, Soumya Roy, Christopher S. Moore, Nishu Karna, Joy Velasquez
Figure caption: Temperature as a function of time in the regions indicated by squares of the plasma cloud (P), northern loops (NL), and southern loops (SL) in Figure 5.
Paper: Disentangling Thermal and Abundance Characteristics in a Solar Flare Using SDO/AIA, Hinode/XRT, and MinXSS-1 Observations
Authors: Xiaoyan Xie, Anna Chen, Crisel Suarez, Katharine K. Reeves, Soumya Roy, Christopher S. Moore, Nishu Karna, Joy Velasquez
Figure caption: Temperature and EM distributions at 01:55:19 UT derived from AIA data. We apply photospheric (left) and hybrid (right) abundance models for the comparison with the third column in Figure 5.
Paper: Disentangling Thermal and Abundance Characteristics in a Solar Flare Using SDO/AIA, Hinode/XRT, and MinXSS-1 Observations
Authors: Xiaoyan Xie, Anna Chen, Crisel Suarez, Katharine K. Reeves, Soumya Roy, Christopher S. Moore, Nishu Karna, Joy Velasquez
Figure caption: Ratio of DEMs with photospheric abundances to DEMs with coronal abundances versus temperature at 01:55:19 UT in the locations marked by crosses in Figure 5. Gray and orange dashed lines indicate values equaling 1 and 3.98, respectively.
Paper: Disentangling Thermal and Abundance Characteristics in a Solar Flare Using SDO/AIA, Hinode/XRT, and MinXSS-1 Observations
Authors: Xiaoyan Xie, Anna Chen, Crisel Suarez, Katharine K. Reeves, Soumya Roy, Christopher S. Moore, Nishu Karna, Joy Velasquez
Figure caption: χ2 with coronal and photospheric models at 01:55:19 UT. Panel (a) corresponds to Figure 5 at 01:55:19 UT, and panel (b) corresponds to the left column of Figure 9. It shows that, for loops, χ2 with coronal abundances is generally lower than that with photospheric abundances.
Paper: Disentangling Thermal and Abundance Characteristics in a Solar Flare Using SDO/AIA, Hinode/XRT, and MinXSS-1 Observations
Authors: Xiaoyan Xie, Anna Chen, Crisel Suarez, Katharine K. Reeves, Soumya Roy, Christopher S. Moore, Nishu Karna, Joy Velasquez
Figure caption: χ2 distributions with different factors multiplying the XRT response function when combining XRT filters with AIA channels to calculate DEMs at 01:55:19 UT.
Paper: Disentangling Thermal and Abundance Characteristics in a Solar Flare Using SDO/AIA, Hinode/XRT, and MinXSS-1 Observations
Authors: Xiaoyan Xie, Anna Chen, Crisel Suarez, Katharine K. Reeves, Soumya Roy, Christopher S. Moore, Nishu Karna, Joy Velasquez
Figure caption: Evolution of the temperature (top row) and EM (bottom row) from DEMs that combine the XRT and AIA channels.
Paper: Measuring Star Formation Histories from Asymptotic Giant Branch Stars. I. A Demonstration in M31
Authors: Abigail J. Lee, Daniel R. Weisz, Yi Ren, Alessandro Savino, Andrew E. Dolphin
Figure caption: (Left) CMD of the M31 PHAT optical data analyzed in W17 for d > 11 kpc. (Right) CMD of our M31 UKIRT data that overlaps with the PHAT footprint analyzed in W17 for d > 11 kpc. Color indicates the number of stars in each CMD bin. The gray box shows our selection criteria for the AGB stars, which also corresponds to the gray box in Figure 2, shifted to M31’s distance. In both CMDs, isochrones of 100 Myr, 1 Gyr, and 8 Gyr with a metallicity of [M/H] = 0.0 dex are overlaid with the TP-AGB evolutionary phase highlighted in red. The PHAT optical CMD contains ∼47 million stars, of which ∼33 million stars are above the 50% completeness limit (F814W ≈ 26.5 mag). Our NIR CMD contains ∼35,000 stars and an average 50% completeness limit of J = 18.7 mag. Our selection region contains ∼7700 AGB stars from which we measure our SFH. Typical CMD features, such as BHeB (Blue Helium-Burning) stars, RHeB (Red Helium-Burning) stars, AGB stars, RGB stars, MS (Main Sequence) stars, RC stars, and MW foreground stars are labeled.
Paper: Measuring Star Formation Histories from Asymptotic Giant Branch Stars. I. A Demonstration in M31
Authors: Abigail J. Lee, Daniel R. Weisz, Yi Ren, Alessandro Savino, Andrew E. Dolphin
Figure caption: Hertzsprung–Russell diagram for four different PARSEC-COLIBRI isochrones with metallicity [M/H] = 0.0 dex. The TP-AGB evolutionary stage is shown in red, the E-AGB phase is shown in blue, and the RGB phase is shown in orange. The red helium-burning (RHeB) evolutionary phase is also labeled. The top panel shows AGB models with the number of AGB star thermal pulse cycles, ninTPC = 0, and the bottom panel shows AGB models with ninTPC = 20.
Paper: Measuring Star Formation Histories from Asymptotic Giant Branch Stars. I. A Demonstration in M31
Authors: Abigail J. Lee, Daniel R. Weisz, Yi Ren, Alessandro Savino, Andrew E. Dolphin
Figure caption: Simulated CMDs using PARSEC-COLIBRI models that demonstrate the power of AGB stars (highlighted within the gray box) as age indicators from ∼50 Myr to ∼10 Gyr. All CMDs were constructed using a constant star formation rate of 0.1 M⊙ yr−1 with a constant metallicity of [M/H] = 0.0 dex. The legend shows the log(age) ranges of each SSP.
Paper: Measuring Star Formation Histories from Asymptotic Giant Branch Stars. I. A Demonstration in M31
Authors: Abigail J. Lee, Daniel R. Weisz, Yi Ren, Alessandro Savino, Andrew E. Dolphin
Figure caption: (Left) Hess diagrams for our AGB star SFH fit for the observed data (left panel), best-fit linear combination of SSPs (middle panel), and residual CMDs (right panel). The residuals are expressed in Poisson standard deviations. (Middle) Comparison between our measured cumulative stellar mass formed and the W17 measurement using the PARSEC models. (Right) Comparison between our star formation rate (SFR) measured from AGB stars and the SFR measured in W17.