adsabs/AstroCLIMB huggingface dataset:
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: The stellar mass scatter at fixed halo mass ﹩\sigma ({\mathrm{log}}_{10}({M}_{* }| {M}_{h}))﹩ as a function of black hole mass scatter at fixed halo mass ﹩\sigma ({\mathrm{log}}_{10}({M}_{\mathrm{BH}}| {M}_{h})﹩. Here, we adopt the instantaneous AGN feedback model, where the only change we make is the way black hole masses are calculated. Each purple line with dots shows a different halo mass bin. The purple squares and stars show DARK SAGE fiducial and SMBH seeding data respectively. The blue triangles show TNG data. In all data points, the bolder the color, the higher the halo mass bins. The black dashed line is a one-to-one line. When seeding SMBH in DARK SAGE, there is a slight increase in the scatter in stellar mass at the low-mass bins. When implementing the conditional black hole mass model, the scatter in stellar mass worsens for the lowest halo mass bins, when assuming a zero black hole mass scatter.
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: Turning off AGN for all galaxies and turning off cooling for galaxies with black hole mass above 108 M ⊙: Stellar-to-halo mass relation colored by the quenched fraction for the same black hole models as in Figure 5. We see a decrease in the scatter in stellar mass at fixed halo mass, more so for the conditional black hole model. There is also a clear vertical transition between active and passive galaxies, more apparent for our fixed conditional distribution models.
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: Instantaneous AGN feedback model: Stellar-to-halo mass relation colored by the quenched fraction for the same black hole models as in Figure 5. We find that the overall scatter in stellar mass is not reduced by the change in black hole seeding for this particular feedback model. We do not see a significant change in the stellar mass scatter when increasing the scatter in black hole mass.
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: Black hole mass as a function of halo mass colored by the quenched fraction for the same black hole models as in Figure 5. We see small differences in the quenching fractions in comparison to Figure 5 although the black hole mass–halo mass σ 0.2 dex run best resembles TNG prediction in terms of scatter and quenched fraction transition.
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: Same as Figure 7, except that, in this model, we turn off AGN feedback and turn off cooling for galaxies with black hole masses above 108 M ⊙. When adapting different black hole seeding, we see a significant reduction in the scatter in stellar mass at low halo mass bins.
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: No AGN, turning off cooling, and removing cold gas reservoir for galaxies with black hole masses above 108 M ⊙: Stellar-to-halo mass relation colored by the quenched fraction for the same black hole models as in Figure 5. We see that the scatter in stellar mass is significantly reduced like in Figure 9, but there is also less galaxies in transition from being active to passive.
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: No AGN, turning off cooling, and removing cold gas reservoir for galaxies with black hole masses above 108 M ⊙: black hole mass as a function of halo mass colored by the quenched fraction for the same black hole models as in Figure 5. We see the sharpest quenching transition of all AGN quenching models, where everything right above black hole masses above 108 M ⊙ is quenched.
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: Same as Figure 10, except that, in this model, we also remove all cold gas reservoir for galaxies with black hole masses above 108 M ⊙. Although the scatter in stellar mass is significantly reduced like in Figure 10, in the SMBH seeding case, the scatter in stellar mass is slightly different for the lower halo mass bins, where the black hole mass scatter is 0.2 dex.
Paper: Accurate, Precise, and Physically Self-consistent Ages and Metallicities for 400,000 Solar Neighborhood Subgiant Branch Stars
Authors: David M. Nataf, Kevin C. Schlaufman, Henrique Reggiani, Isabel Hahn
Figure caption: We show our color–magnitude selection function (thick gray lines) overplotted on the Gaia Catalog of Nearby Stars (small black points) with MIST isochrones for the main sample (top) and the metal-poor annex (bottom).
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: The stellar mass scatter—computed as half the 16th–84th interpercentile range—at fixed halo mass for the SMBH seeding (top) and the fixed conditional distribution (bottom) BH growth models at different halo mass bins for the three different AGN feedback models: DARK SAGE instantaneous AGN feedback (pink), turning off AGN feedback while also turning off cooling for galaxies with black hole masses above 108 M ⊙ (orange), and lastly, doing the former while also removing all the cold gas mass (red). We compare our experiments with observational data used in Figure 2, DARK SAGE fiducial (purple), and TNG (blue). In the bottom panel, we only display the models with a black hole mass scatter of 0.2 dex.
Paper: Accurate, Precise, and Physically Self-consistent Ages and Metallicities for 400,000 Solar Neighborhood Subgiant Branch Stars
Authors: David M. Nataf, Kevin C. Schlaufman, Henrique Reggiani, Isabel Hahn
Figure caption: A comparison between our astro-photometric metallicity determinations and those from four major spectroscopic surveys. Legends show the median difference in [Fe/H], where a positive value denotes a higher metallicity for the spectroscopic determination, and the median absolute deviation between the metallicity determinations. The black lines denote the lines of equality between the metallicity determinations. This comparison to data from four surveys demonstrates that our astro-photometric estimates of metallicity are largely consistent with the spectroscopically inferred values.
Paper: Accurate, Precise, and Physically Self-consistent Ages and Metallicities for 400,000 Solar Neighborhood Subgiant Branch Stars
Authors: David M. Nataf, Kevin C. Schlaufman, Henrique Reggiani, Isabel Hahn
Figure caption: We show various photometric scatters for stars on or near the subgiant branch. The [Fe/H] measurements (S. Buder et al. 2021) are color coded, as are the predictions from the MIST isochrones. The effects of increasing the extinction by ΔA  V  = 0.50 mag and ΔT eff = 500 K are approximated by the black and gray arrows, respectively, and representative photometric uncertainties are shown by the cyan error bars. The association between the spectroscopically inferred metallicities and color–color relations is consistent with the theoretical prediction.
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: The SMHMR (top) and stellar mass scatter at fixed halo mass (bottom) for DARK SAGE fiducial, where we use the original total stellar mass of galaxies (purple), DARK SAGE fiducial, where we include a fraction between 25% and 100% of the intracluster star mass in the stellar mass of the galaxy (M *, violet), and TNG for reference (blue). We see that not including part of the intracluster star mass into the total stellar mass results in galaxies at all halo masses having a higher scatter in stellar mass at fixed halo mass.
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: Same as Figure 2, except that, here, we use 1σ standard deviation to calculate the stellar mass scatter. We find that using the standard deviation instead of the 16–84th interpercentile range shows no significant difference in the stellar mass scatter.
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: Same as Figure 14, except that, here, we change the bin size of the halo mass to 1 dex. We find that the stellar mass scatter looks larger with wider bin sizes.
Paper: Why Do Semianalytic Models Predict Higher Scatter in the Stellar Mass–Halo Mass Relation Than Cosmological Hydrodynamic Simulations?
Authors: Antonio J. Porras-Valverde, John C. Forbes, Rachel S. Somerville, Adam R. H. Stevens, Kelly Holley-Bockelmann, Andreas A. Berlind, Shy Genel
Figure caption: The ratio of intracluster stars to the total stellar mass in central galaxies at z = 0 for the corrected DARK SAGE fiducial (purple) and the scatter. For comparison, we show the range of observations of the ratio of mass of stars between 10 and 100 kpc to the stellar mass between 0 and 100 kpc for massive elliptical galaxies from S. Huang et al. (2018; red dashed lines).
Paper: Could the Interband Lag of Active Galactic Nucleus Vary Randomly?
Authors: Zhen-Bo Su, Zhen-Yi Cai, Jun-Xian Wang, Tinggui Wang, Yongquan Xue, Min-Xuan Cai, Lulu Fan, Hengxiao Guo, Zhicheng He, Zizhao He, Xu-Fan Hu, Ji-an Jiang, Ning Jiang, Wen-Yong Kang, Lei Lei, Guilin Liu, Teng Liu, Zhengyan Liu, Zhenfeng Sheng, Mouyuan Sun, Wen Zhao
Figure caption: Left-hand panel: Relative to the WFST-g band, the lag-wavelength relations for N5548-like AGNs predicted by the thermal fluctuation scenario are compared to the measured one (open circles) adopting the ∼6 month ugriz LCs of NGC 5548 from M. M. Fausnaugh et al. (2016). The predicted lag-wavelength relations are derived from 200 independent ideal simulations (gray thin solid lines) for N5548-like AGNs monitored over 6 months duration (﹩{ \mathcal M }=6﹩) within one year (﹩{ \mathcal Y }=1﹩) and with a very fine cadence of 0.1 day (﹩{ \mathcal C }=0.1﹩) in the five WFST-ugriz bands. Here, the ideal case is considered without photometric uncertainty (σ e = 0 or SNR σ  = ∞). Accordingly, the median (thick solid line), mean (thin dashed line), and 16%–84% percentile ranges (thin dotted–dashed lines) of the 200 ideal lag-wavelength relations are shown. Although the 1σ dispersion of lags, σ ideal, is larger at longer wavelengths, similar relative scatters of lags are found for all bands as indicated by similar σ ideal/μ ideal (filled circles in the lower panel), where μ ideal is the corresponding mean lag. Right-hand panel: Same as the left-hand panel, but for the prediction of the reprocessing model with DCE. We note that the relative scatters of the lags predicted by the reprocessing model with DCE are smaller than the thermal fluctuation model.
Paper: Equilibrium States of Galactic Atmospheres. II. Interpretation and Implications
Authors: G. Mark Voit, Christopher Carr, Drummond B. Fielding, Viraj Pandya, Greg L. Bryan, Megan Donahue, Benjamin D. Oppenheimer, Rachel S. Somerville
Figure caption: Approximate ranges of specific supernova feedback energy (﹩{\varepsilon }_{\mathrm{fb}}={\eta }_{E}{\varepsilon }_{\mathrm{SN}}/{\eta }_{M}﹩) implemented in cosmological numerical simulations. Each colored band shows how the scaled specific energy ﹩{\varepsilon }_{\mathrm{fb}}/{v}_{{\rm{c}}}^{2}﹩ depends on the approximate circular velocity v c of a galaxy’s halo in the range 100–250 km s−1. A horizontal blue-green stripe represents the original Illustris simulations. A diagonal purple stripe represents EAGLE. The gold region represents the IllustrisTNG simulations, in which ﹩{\varepsilon }_{\mathrm{fb}}/{v}_{{\rm{c}}}^{2}\propto {H}^{-2/3}(z)﹩, and labeled brown stripes show ﹩{\varepsilon }_{\mathrm{fb}}/{v}_{{\rm{c}}}^{2}﹩ at particular values of redshift z. The red, blue, and gray shaded regions correspond to the expanding, contracting, and fountain regions of Figure 1. According to Paper I’s minimalist regulator model, coupled supernova-driven outflows with greater values of ﹩{\varepsilon }_{\mathrm{fb}}/{v}_{{\rm{c}}}^{2}﹩ should result in more expansion of the CGM without changing a halo’s stellar baryon very much, as long as ε fb significantly exceeds ε acc. The CGM properties of low-mass halos in Illustris, EAGLE, and IllustrisTNG qualitatively align with that prediction.
Paper: Could the Interband Lag of Active Galactic Nucleus Vary Randomly?
Authors: Zhen-Bo Su, Zhen-Yi Cai, Jun-Xian Wang, Tinggui Wang, Yongquan Xue, Min-Xuan Cai, Lulu Fan, Hengxiao Guo, Zhicheng He, Zizhao He, Xu-Fan Hu, Ji-an Jiang, Ning Jiang, Wen-Yong Kang, Lei Lei, Guilin Liu, Teng Liu, Zhengyan Liu, Zhenfeng Sheng, Mouyuan Sun, Wen Zhao
Figure caption: The potentially varied lag-wavelength relations observed in two AGNs. Left-hand panel: Relative to the Swift-UVW2 band at 2055 Å, the lag-wavelength relations for Fairall 9 are measured in three distinct periods by M. Pal et al. (2017, from 2013 April to 2015 April), J. V. Hernández Santisteban et al. (2020, from 2018 May to 2019 February) and R. Edelson et al. (2024, from 2018 May to 2020 February). Only the Swift bands are shown as R. Edelson et al. (2024). The black solid line indicates the SSD-predicted lag-wavelength relation for Fairall 9 using a BH mass of 2.6 × 108 M ⊙ and an Eddington ratio of 0.02 (R. V. Vasudevan & A. C. Fabian 2009). Right-hand panel: Relative to the g band, the lag-wavelength relations for NGC 4395 are measured in three nights by I. M. McHardy et al. (2023, 2.2 hr in 2018 April) and J. W. Montano et al. (2022, 6.7 and 6.2 hr in 2022 April 26 and 27, respectively). The black solid line is the SSD-predicted lag-wavelength relation implied by a BH mass of 1.7 × 104 M ⊙ (H. Cho et al. 2021) and a bolometric luminosity of 5.3 × 1040 erg s−1 (E. C. Moran et al. 2005). Here, the SSD-predicted lag-wavelength relations are simply given by Equation (12) of M. M. Fausnaugh et al. (2016) assuming η = 0.1, κ = 1, and X = 5.04 (S. S. Tie & C. S. Kochanek 2018).
Paper: Could the Interband Lag of Active Galactic Nucleus Vary Randomly?
Authors: Zhen-Bo Su, Zhen-Yi Cai, Jun-Xian Wang, Tinggui Wang, Yongquan Xue, Min-Xuan Cai, Lulu Fan, Hengxiao Guo, Zhicheng He, Zizhao He, Xu-Fan Hu, Ji-an Jiang, Ning Jiang, Wen-Yong Kang, Lei Lei, Guilin Liu, Teng Liu, Zhengyan Liu, Zhenfeng Sheng, Mouyuan Sun, Wen Zhao
Figure caption: Effects of diverse observational conditions on the lag measurement in terms of the thermal fluctuation model. For each case, the τ  g  distribution is shown as a violin plot, overlaid by the median (open circle) and 16%–84% percentile ranges (the vertical bar). The hatched violin plot in each panel refers to the reference case for a combination of {WFST-gri, ﹩{ \mathcal C }=1﹩, SNR σ  = 3, ﹩{ \mathcal M }=6﹩, ﹩{ \mathcal Y }=1﹩}. Each panel illustrates the effect of solely changing one of the conditions compared to the reference case: (a) passband, (b) cadence, (c) variation significance, (d) duration, and (e) baseline.
Paper: Could the Interband Lag of Active Galactic Nucleus Vary Randomly?
Authors: Zhen-Bo Su, Zhen-Yi Cai, Jun-Xian Wang, Tinggui Wang, Yongquan Xue, Min-Xuan Cai, Lulu Fan, Hengxiao Guo, Zhicheng He, Zizhao He, Xu-Fan Hu, Ji-an Jiang, Ning Jiang, Wen-Yong Kang, Lei Lei, Guilin Liu, Teng Liu, Zhengyan Liu, Zhenfeng Sheng, Mouyuan Sun, Wen Zhao
Figure caption: Illustration on how sparse sampling and photometric uncertainty would add scatter to the intrinsic dispersion of the lag in terms of the thermal fluctuation model. In each band, the left-hand portion of the violin plot displays the distribution of 200 ideal lags inferred from the ideal LCs with a very fine cadence and without photometric uncertainty (Figure 2), while the right-hand portion shows that of 200 mock lags inferred from the mock LCs with sparse sampling (﹩{ \mathcal C }=1﹩) and moderate photometric uncertainty (SNR σ  ≃ 3). The median (thick solid line) and 16%–84% percentile ranges (thin dotted–dashed lines) of the mocked lags are compared to the median (thin dashed line) of the ideal lags. This comparison suggests that the median lag-wavelength relations inferred from the mock and ideal LCs are comparable, regardless of the sparse sampling and photometric uncertainty, both of which indeed increase the dispersion of the lag. Dispersion of the mock lags (crosses) and ideal lags (circles) are compared in the lower panel.
Paper: Could the Interband Lag of Active Galactic Nucleus Vary Randomly?
Authors: Zhen-Bo Su, Zhen-Yi Cai, Jun-Xian Wang, Tinggui Wang, Yongquan Xue, Min-Xuan Cai, Lulu Fan, Hengxiao Guo, Zhicheng He, Zizhao He, Xu-Fan Hu, Ji-an Jiang, Ning Jiang, Wen-Yong Kang, Lei Lei, Guilin Liu, Teng Liu, Zhengyan Liu, Zhenfeng Sheng, Mouyuan Sun, Wen Zhao
Figure caption: Correlations between the lag of the x band relative to the g band, τ  gx , and the g-band variation amplitude, σ rms,g , where x takes u (top left-hand panel), r (top right-hand panel), i (bottom left-hand panel), and z (bottom right-hand panel), respectively. Values of τ  gx  and σ rms,g  from individual simulations are depicted by the small solid symbols, while the corresponding median lag and 16%–84% percentile ranges are shown as the large open symbols with vertical bars in even bins of 0.04 mag. Only bins containing more than 10 data points are shown. Circles are for the thermal fluctuation model, while squares are for the reprocessing model with DCE. The thermal fluctuation model predicts a clear positive correlation between the variation amplitude and the lag (i.e., the larger the variation amplitude, the longer the lag), while the reprocessing model with DCE does not predict such a correlation.
Paper: Could the Interband Lag of Active Galactic Nucleus Vary Randomly?
Authors: Zhen-Bo Su, Zhen-Yi Cai, Jun-Xian Wang, Tinggui Wang, Yongquan Xue, Min-Xuan Cai, Lulu Fan, Hengxiao Guo, Zhicheng He, Zizhao He, Xu-Fan Hu, Ji-an Jiang, Ning Jiang, Wen-Yong Kang, Lei Lei, Guilin Liu, Teng Liu, Zhengyan Liu, Zhenfeng Sheng, Mouyuan Sun, Wen Zhao
Figure caption: An illustration of the simulated 10 yr ideal LCs (g band vs. z band) for the thermal fluctuation model (panel a) and the reprocessing model with DCE (panel b). Using part of LCs blanketed by a moving window of 6 months (or 2 yr) to measure the interband lags between g and z bands, the evolution of τ  gz  with time for both models are presented in panel (c) (or panel (d)). Being consistent with the results shown in Figure 2, the lag evolution implied by the thermal fluctuation model exhibits larger variation than the reprocessing model with DCE. As the size of the moving window increases, the lag evolution becomes less variable for both models.
Paper: Could the Interband Lag of Active Galactic Nucleus Vary Randomly?
Authors: Zhen-Bo Su, Zhen-Yi Cai, Jun-Xian Wang, Tinggui Wang, Yongquan Xue, Min-Xuan Cai, Lulu Fan, Hengxiao Guo, Zhicheng He, Zizhao He, Xu-Fan Hu, Ji-an Jiang, Ning Jiang, Wen-Yong Kang, Lei Lei, Guilin Liu, Teng Liu, Zhengyan Liu, Zhenfeng Sheng, Mouyuan Sun, Wen Zhao
Figure caption: For the thermal fluctuation model, the accuracy of the true lag-wavelength relation obtained by averaging the observed lag-wavelength relations of N AGNs with comparable physical properties for different sampling cadences (﹩{ \mathcal C }﹩ ≃ 1, 3, 5) and photometric uncertainties (SNR σ  ≃ 1, 3, 9).
Paper: The First Catalog of Candidate White Dwarf–Main-sequence Binaries in Open Star Clusters: A New Window into Common Envelope Evolution
Authors: Steffani M. Grondin, Maria R. Drout, Jason Nordhaus, Philip S. Muirhead, Joshua S. Speagle, 佳士 沈, Ryan Chornock
Figure caption: An example set of spectra (left panels) and observed photometry (right panels) for three high-probability candidate WD+MS binaries in our catalog. For each system, we show an observed spectrum/photometry (colored), a best-fit A. J. Pickles (1998) M-dwarf model (black), and a residual spectrum (gray). Photometric bands for Pan-STARRS1 and 2MASS along with Balmer absorption features (H β, H γ, H δ) are plotted for reference. Top: Alessi12-c1 (the bluest source in our catalog); this observed spectrum was obtained with the Kast spectrograph at the Lick Observatory. For reference, we plot both the raw and smoothed spectrum. A large blue continuum flux excess and clear Balmer absorption features are present, indicating the presence of a WD in the system. At redder wavelengths, Alessi12-c1 nicely fits the shape of a M3V star. Hence, Alessi12-c1 is a clear WD+MS binary. Middle: Pleiades-c1 (the reddest source in our catalog); this observed spectrum was obtained with the GMOS at the Gemini-North Telescope. While less dramatic than Alessi12-c1, Pleiades-c1 also exhibits an excess blue continuum flux and broad Balmer absorption features in its spectrum. While there is a slight infrared excess, Pleiades-c1 matches an M3V star at redder wavelengths. Bottom: Pleiades-c2; like Pleiades-c1, this observed spectrum was obtained with the GMOS at the Gemini-North Telescope. Neither Balmer absorption lines nor a blue continuum flux excess are observed; however, both the spectrum and photometry match that of an M4V Pickles model star.