adsabs/AstroCLIMB huggingface dataset:
Paper: Photometric Mapping of Carbonaceous/Siliceous Dust and Water Ice in the ISM with JWST: Applications to the Dense Sightlines
Authors: Burcu Günay, Karl D. Gordon, Joshua E. G. Peek, Marjorie Decleir, Dries Van De Putte, Kirill Tchernyshyov, Michael G. Burton
Figure caption: Spectral models were generated with continua having continuum profiles with different slopes. An optical depth range of τ0 = 0–1 was applied. Photometric optical depths at 3.0 μm, 3.35 μm, and 10.0 μm were obtained and compared with the reference optical depths to explore continuum-related differences (Δτcont.). The optical depths obtained using models with polynomial continua derived from the observational spectra set ([G04]) are shown (in gray), alongside those obtained using models that include BBs at T = 500 K, 3000 K, and 10,000 K and a flat continuum.
Paper: Photometric Mapping of Carbonaceous/Siliceous Dust and Water Ice in the ISM with JWST: Applications to the Dense Sightlines
Authors: Burcu Günay, Karl D. Gordon, Joshua E. G. Peek, Marjorie Decleir, Dries Van De Putte, Kirill Tchernyshyov, Michael G. Burton
Figure caption: The set of continuum profile templates: normalized blackbody curves (BBs) with temperatures ranging from T = 100–10,000 K, used for continuum modeling, is illustrated. The throughput functions of the NIRCam and MIRI filters are also presented with the color code at the bottom.
Paper: Photometric Mapping of Carbonaceous/Siliceous Dust and Water Ice in the ISM with JWST: Applications to the Dense Sightlines
Authors: Burcu Günay, Karl D. Gordon, Joshua E. G. Peek, Marjorie Decleir, Dries Van De Putte, Kirill Tchernyshyov, Michael G. Burton
Figure caption: The absorption feature templates at 3.0 μm, 3.35 μm, and 10.0 μm used in the standard model spectra (gray curves) are shown alongside those in the optimal models (gray dashed curves), which were obtained by adjusting the CW and FWHM parameters to achieve optimal calibration for the observational spectra set from E. L. Gibb et al. (2004). The central wavelengths (vertical lines) and the half-power passband wavelengths of the filters are also indicated.
Paper: Photometric Mapping of Carbonaceous/Siliceous Dust and Water Ice in the ISM with JWST: Applications to the Dense Sightlines
Authors: Burcu Günay, Karl D. Gordon, Joshua E. G. Peek, Marjorie Decleir, Dries Van De Putte, Kirill Tchernyshyov, Michael G. Burton
Figure caption: The photometric fluxes are shown on the spectra set from the literature (E. L. Gibb et al. 2004), with colored dots indicating the employed JWST filters. The throughput functions of the NIRCam and MIRI filters used for the photometric flux measurements are also presented at the bottom.
Paper: Photometric Mapping of Carbonaceous/Siliceous Dust and Water Ice in the ISM with JWST: Applications to the Dense Sightlines
Authors: Burcu Günay, Karl D. Gordon, Joshua E. G. Peek, Marjorie Decleir, Dries Van De Putte, Kirill Tchernyshyov, Michael G. Burton
Figure caption: The model spectra are generated using BBs with temperatures ranging from T = 100–10,000 K. Photometric optical depths at 3.0 μm, 3.35 μm, and 10.0 μm were obtained, employing the Filter Sets listed in Table 2 and compared with the reference optical depths (τ0) to evaluate the accuracy of the photometric method with linear continuum fit estimation. The efficiency of the Filter Sets in estimating continuum fluxes is tested with τ0 = 0 (upper panels), while their ability to constrain absorption features is evaluated with τ0 = 1 (lower panels).
Paper: Photometric Mapping of Carbonaceous/Siliceous Dust and Water Ice in the ISM with JWST: Applications to the Dense Sightlines
Authors: Burcu Günay, Karl D. Gordon, Joshua E. G. Peek, Marjorie Decleir, Dries Van De Putte, Kirill Tchernyshyov, Michael G. Burton
Figure caption: Optical depths at 3.0 μm, 3.35 μm, and 10.0 μm are derived from literature spectra (E. L. Gibb et al. 2004). Polynomial fits (colored dots) show the correlation between photometric and spectroscopic optical depths, with the gray dotted line representing equal τp and τs values.
Paper: Photometric Mapping of Carbonaceous/Siliceous Dust and Water Ice in the ISM with JWST: Applications to the Dense Sightlines
Authors: Burcu Günay, Karl D. Gordon, Joshua E. G. Peek, Marjorie Decleir, Dries Van De Putte, Kirill Tchernyshyov, Michael G. Burton
Figure caption: The photometric optical depths and spectroscopic optical depths at 3.0 μm, 3.35 μm, and 10.0 μm are measured using standard spectral models (to represent ideal conditions) and compared to investigate methodological biases. The gray dotted line represents equal τp and τs values.
Paper: Searching for Low-mass Exoplanets amid Stellar Variability with a Fixed Effects Linear Model of Line-by-line Shape Changes
Authors: Joseph Salzer, Jessi Cisewski-Kehe, Eric B. Ford, Lily L. Zhao
Figure caption: Heat maps of the NEID solar RV measurements over time. The x-axis represents the 330 days with measurements (in order, but not scaled by time). The black vertical line is at the day when the detector was shut off due to the Contreras Fire and subsequently brought back online. The top subplot displays the unadjusted distribution of RVs for each line (note that around 4% of the observations fall outside the limits of this plot). The bottom subplot displays the RV minus the mean RV for each line and temporal group pairing. Note that around 2% of the observations fall outside the limits of this plot. The colors indicate the number of RV measurements from absorption lines within each bin (orange = fewer lines, blue = more lines). Bins are vertical so that there is no overlap between days.
Paper: Searching for Low-mass Exoplanets amid Stellar Variability with a Fixed Effects Linear Model of Line-by-line Shape Changes
Authors: Joseph Salzer, Jessi Cisewski-Kehe, Eric B. Ford, Lily L. Zhao
Figure caption: Time series and pairs plots of the contaminated RV and change in depth for four spectral lines. Each column displays the results for a single spectral line. The title of each subplot shows the central wavelength (in units of Å) of the line followed by its mean depth. The first row displays the contaminated RV, the second displays the change in depth (from the line’s mean depth), and the bottom row plots the RV vs. the change in depth. Points are colored according to their day of observation.
Paper: Searching for Low-mass Exoplanets amid Stellar Variability with a Fixed Effects Linear Model of Line-by-line Shape Changes
Authors: Joseph Salzer, Jessi Cisewski-Kehe, Eric B. Ford, Lily L. Zhao
Figure caption: Time series of the line-by-line cleaned RV standard errors from the LOOMCV procedure on a log10 scale (see Equation (22)). The Baseline Model–OLS is denoted by blue squares, the Baseline–IRLS by gray circles, the Full Model–OLS by orange triangles, and the Full Model–IRLS by green diamonds.
Paper: Searching for Low-mass Exoplanets amid Stellar Variability with a Fixed Effects Linear Model of Line-by-line Shape Changes
Authors: Joseph Salzer, Jessi Cisewski-Kehe, Eric B. Ford, Lily L. Zhao
Figure caption: Time series of the cleaned RV minus true planetary signal (left plot) and kernel density estimate (right plot). This figure displays a zoomed-in version of the y-axis as in Figure 3. Displayed in this figure are the results from the Full Model with OLS (orange triangles, dashed line) and Full Model with IRLS (green diamonds, solid line).
Paper: Searching for Low-mass Exoplanets amid Stellar Variability with a Fixed Effects Linear Model of Line-by-line Shape Changes
Authors: Joseph Salzer, Jessi Cisewski-Kehe, Eric B. Ford, Lily L. Zhao
Figure caption: Time series of the cleaned RV minus true planetary signal (left plot) and kernel density estimate (right plot). Displayed are the results from the Baseline Model (blue squares, solid line) and Full Model (orange triangles, dashed line) using the OLS estimators. For this data set, the true planetary signal is 0 m s−1.
Paper: Searching for Low-mass Exoplanets amid Stellar Variability with a Fixed Effects Linear Model of Line-by-line Shape Changes
Authors: Joseph Salzer, Jessi Cisewski-Kehe, Eric B. Ford, Lily L. Zhao
Figure caption: Scatterplot of each line’s mean SNR (calculated via the photon noise across the line’s pixels) vs. mean depth. These are colored by the weight of that line learned via the IRLS algorithm for the Full Model.
Paper: Searching for Low-mass Exoplanets amid Stellar Variability with a Fixed Effects Linear Model of Line-by-line Shape Changes
Authors: Joseph Salzer, Jessi Cisewski-Kehe, Eric B. Ford, Lily L. Zhao
Figure caption: Standard errors for the OLS estimators of the cleaned RVs for the Full Model. The black points represent bootstrap standard errors, while the red dashed black line is at the mean MLE standard error.
Paper: Delayed and Displaced: The Impact of Binary Interactions on Core-collapse SN Feedback
Authors: Tom Wagg, Julianne J. Dalcanton, Mathieu Renzo, Katelyn Breivik, Matthew E. Orr, Adrian M. Price-Whelan, Akaxia Cruz, Alyson Brooks, Ulrich P. Steinwandel, Eric C. Bellm
Figure caption: Top panel: binary stars produce a significantly different distribution of SNe times and locations than single stars. The main panel shows a 2D kernel density estimation of the distribution of SNe for single star population in blue. The gray hatched contour shows the 98% region for a binary star population. Marginal histograms are shown in each side panel. Bottom panel: the timing and location of SNe relative to their parent cluster are strongly correlated and a function of their progenitor type. Gray filled contours show the full 2D density distribution, while colored contours indicate the region within which 90% of each subpopulation is contained. Marginal histograms are the same distributions as the top panels of Figure 1.
Paper: Delayed and Displaced: The Impact of Binary Interactions on Core-collapse SN Feedback
Authors: Tom Wagg, Julianne J. Dalcanton, Mathieu Renzo, Katelyn Breivik, Matthew E. Orr, Adrian M. Price-Whelan, Akaxia Cruz, Alyson Brooks, Ulrich P. Steinwandel, Eric C. Bellm
Figure caption: The same as Figure 4, except varying different choices of initial conditions. Variations of the initial mass function (IMF) and initial orbital period distribution can affect SNe timing, but initial conditions do not strongly impact SN spatial locations. An interactive version of this data is available in Figure 4.
Paper: Delayed and Displaced: The Impact of Binary Interactions on Core-collapse SN Feedback
Authors: Tom Wagg, Julianne J. Dalcanton, Mathieu Renzo, Katelyn Breivik, Matthew E. Orr, Adrian M. Price-Whelan, Akaxia Cruz, Alyson Brooks, Ulrich P. Steinwandel, Eric C. Bellm
Figure caption: The same as Figure 4, except varying different choices of galaxy settings. SNe timing is unaffected by galaxy settings, but SNe location is strongly dependent on the choice of initial cluster velocity dispersion (though a tail of distant ejected secondary SNe still exists with a low dispersion). An interactive version of this data is available in Figure 4.
Paper: Delayed and Displaced: The Impact of Binary Interactions on Core-collapse SN Feedback
Authors: Tom Wagg, Julianne J. Dalcanton, Mathieu Renzo, Katelyn Breivik, Matthew E. Orr, Adrian M. Price-Whelan, Akaxia Cruz, Alyson Brooks, Ulrich P. Steinwandel, Eric C. Bellm
Figure caption: Top panel: a comparison of our analytic model for the distribution of ejection velocities (Equation (7), shown in black) to our fiducial simulation for the subset of SN progenitors that are ejected with vej ≥ 5 km s−1 (shown in red, with the lower-velocity region shaded in gray). Bottom panel: the metallicity dependence of our analytic model for the ejection velocity distribution. Lower-metallicity binaries typically produce higher ejection velocities. An interactive version of this data is available in Figure 9.
Paper: Delayed and Displaced: The Impact of Binary Interactions on Core-collapse SN Feedback
Authors: Tom Wagg, Julianne J. Dalcanton, Mathieu Renzo, Katelyn Breivik, Matthew E. Orr, Adrian M. Price-Whelan, Akaxia Cruz, Alyson Brooks, Ulrich P. Steinwandel, Eric C. Bellm
Figure caption: The same as Figure 4, except varying average population metallicity. Decreasing the metallicity of simulated binary stars leads to a systematic increase in both SNe times and locations. An interactive version of this data is available in Figure 4.
Paper: Delayed and Displaced: The Impact of Binary Interactions on Core-collapse SN Feedback
Authors: Tom Wagg, Julianne J. Dalcanton, Mathieu Renzo, Katelyn Breivik, Matthew E. Orr, Adrian M. Price-Whelan, Akaxia Cruz, Alyson Brooks, Ulrich P. Steinwandel, Eric C. Bellm
Figure caption: A comparison of the joint distribution of our analytic model to the fiducial simulation, which shows good agreement. Each panel shows a 2D histogram with the supernova time on the x-axis and the maximum distance traveled (i.e., the product of the SN time and velocity) on the y-axis. The top panel shows the distribution of the fiducial simulation, while the middle shows the analytic model, and the bottom gives the fractional difference in each bin from the top two panels. The solid contour lines in each panel show the 98% regime for the fiducial simulation.
Paper: Delayed and Displaced: The Impact of Binary Interactions on Core-collapse SN Feedback
Authors: Tom Wagg, Julianne J. Dalcanton, Mathieu Renzo, Katelyn Breivik, Matthew E. Orr, Adrian M. Price-Whelan, Akaxia Cruz, Alyson Brooks, Ulrich P. Steinwandel, Eric C. Bellm
Figure caption: The distribution of metallicities of stars in our fiducial m11h simulation, compared to those in the changar442 simulation with a factor of 2 increased metallicity. The boxes at the top indicate the interquartile range, with the median shown with a line in the box. As noted in Section 4.5, the average metallicity is very similar between the simulations, with a slight difference in the width of the distribution.
Paper: A Massive Yellow Supergiant in the Far Outer Disk of M31: Evidence for in Situ Massive Star Formation beyond the Optical Radius
Authors: Pinjian Chen, Bingqiu Chen, Haibo Yuan, Xuan Fang, Xiaodian Chen, Chao-Wei Tsai, Kai Zhang, Xiaowei Liu
Figure caption: H-R diagram showing the position of J0048+4154 (red symbol with 2σ error bars). Solid lines represent MIST evolutionary tracks (J. Choi et al. 2016; A. Dotter 2016) for stars with initial masses between 12 and 28 M⊙ at solar metallicity (Z = 0.0142), assuming an initial rotation of 40% of the critical velocity. Colored dots mark evolutionary steps at 104 yr intervals. Dashed and dashed–dotted lines show 18 M⊙ tracks at subsolar (Z = 0.008) and super-solar (Z = 0.025) metallicities, respectively. Spectroscopically confirmed YSGs in M31 from G16 are shown as yellow diamonds. The gray shaded region indicates the instability strip from G. A. Tammann et al. (2003).
Paper: A Massive Yellow Supergiant in the Far Outer Disk of M31: Evidence for in Situ Massive Star Formation beyond the Optical Radius
Authors: Pinjian Chen, Bingqiu Chen, Haibo Yuan, Xuan Fang, Xiaodian Chen, Chao-Wei Tsai, Kai Zhang, Xiaowei Liu
Figure caption: Left: integrated H I brightness temperature (moment 0) map of the region surrounding J0048+4154, shown on a square-root scale. Contours indicate levels of [5, 10, 15, 20, 25, 30, 40, and 60]2 K km s−1. The spatial resolution is ∼3﹩\mathop{.}\limits^{{\rm{^{\prime} }}}﹩4﹩^{\prime} ﹩, and the position of J0048+4154 is marked by a red asterisk. Middle: same as left, but showing the flux-weighted velocity (moment 1) map. Right: H I spectrum at the location of J0048+4154. The average radial velocity of J0048+4154 (∼−204 km s−1) is indicated by a red dashed line. All data are from FAST observations (K. Zhang et al. 2025, in preparation).
Paper: A Massive Yellow Supergiant in the Far Outer Disk of M31: Evidence for in Situ Massive Star Formation beyond the Optical Radius
Authors: Pinjian Chen, Bingqiu Chen, Haibo Yuan, Xuan Fang, Xiaodian Chen, Chao-Wei Tsai, Kai Zhang, Xiaowei Liu
Figure caption: U − B versus B − V color–color diagram. Small black dots represent stars from the LGGS catalog (P. Massey et al. 2006, 2016) with V ≤ 19.5 mag, while yellow circles indicate spectroscopically confirmed YSGs from M. S. Gordon et al. (2016). The red asterisk marks the position of J0048+4154. The intrinsic color sequences of dwarf stars (cyan line) and Ia supergiants (dark blue line) from M. P. Fitzgerald (1970) are shown, with the latter reddened by E(B − V) = 0.13 mag. The reddening vector, calculated by the extinction law from J. A. Cardelli et al. (1989) with RV = 3.1, is indicated by the black arrow in the lower left.
Paper: A Massive Yellow Supergiant in the Far Outer Disk of M31: Evidence for in Situ Massive Star Formation beyond the Optical Radius
Authors: Pinjian Chen, Bingqiu Chen, Haibo Yuan, Xuan Fang, Xiaodian Chen, Chao-Wei Tsai, Kai Zhang, Xiaowei Liu
Figure caption: Multiwavelength images of J0048+4154. Four nearby UV-bright stars are marked with red circles. The scale bar of 15″ corresponds a projected distance of 57 pc. Each panel is 1﹩\mathop{.}\limits^{{\rm{^{\prime} }}}﹩5 across, with north up and east to the left.
Paper: Reidentification of Redshifts of SDSS Galaxies Overlapped with Galactic Objects
Authors: Masafumi Yagi, Masanori Iye, Hideya Fukumoto
Figure caption: Examples postage stamps of visually rejected candidates. The images were obtained from the SDSS DR16 Skyserver Image Cutout service. From left to right, double star, very bright star halo, possible satellite trail (or meteor), and possible residual of deblending. SpecObjIDs are 1007778591338948608, 1344459499171244032, 1305056575274117120, and 585532586252593152, respectively.
Paper: A Massive Yellow Supergiant in the Far Outer Disk of M31: Evidence for in Situ Massive Star Formation beyond the Optical Radius
Authors: Pinjian Chen, Bingqiu Chen, Haibo Yuan, Xuan Fang, Xiaodian Chen, Chao-Wei Tsai, Kai Zhang, Xiaowei Liu
Figure caption: Spectral energy distribution (SED) fit for J0048+4154. Circles with error bars indicate observed fluxes from multiple surveys, color-coded by different filter sets. Red crosses represent model-predicted fluxes integrated over the corresponding filter transmission curves (shaded regions). The black line shows the best-fit model.
Paper: A Massive Yellow Supergiant in the Far Outer Disk of M31: Evidence for in Situ Massive Star Formation beyond the Optical Radius
Authors: Pinjian Chen, Bingqiu Chen, Haibo Yuan, Xuan Fang, Xiaodian Chen, Chao-Wei Tsai, Kai Zhang, Xiaowei Liu
Figure caption: ZTF optical light curves of J0048+4154 in the g and r bands. Magnitudes are offset for clarity.
Paper: Reidentification of Redshifts of SDSS Galaxies Overlapped with Galactic Objects
Authors: Masafumi Yagi, Masanori Iye, Hideya Fukumoto
Figure caption: A galaxy behind a Galactic planetary nebula from the SDSS DR16 finding chart (left: default scale; right: zoomed out).
Paper: Reidentification of Redshifts of SDSS Galaxies Overlapped with Galactic Objects
Authors: Masafumi Yagi, Masanori Iye, Hideya Fukumoto
Figure caption: (Left) Redshift vs. apparent r-band magnitude plot. Red open circles show the redshift by SDSS DR16, and black filled circles show the measurements in this study. Background shows a number contour of all SDSS DR16 galaxies (photometric type = GALAXY) with spectroscopic redshift in 0 < r < 18 and 0.002 < z < 0.35. Green open rectangles show outliers. (right) SDSS DR16 finding charts around the outliers in the left panel.
Paper: Reidentification of Redshifts of SDSS Galaxies Overlapped with Galactic Objects
Authors: Masafumi Yagi, Masanori Iye, Hideya Fukumoto
Figure caption: Fit to SDSS spectra around Hα of four galaxies, which would have wrong redshift in SDSS DR7. The green broken lines show the emissions at our fitted redshift. All of them show good fit with Hα, [N II] and [S II]. The red dashed lines show titled features at the redshift of SDSS DR7.
Paper: Reidentification of Redshifts of SDSS Galaxies Overlapped with Galactic Objects
Authors: Masafumi Yagi, Masanori Iye, Hideya Fukumoto
Figure caption: The number fraction of galaxies with corrected redshift as a function of redshifts.
Paper: Reidentification of Redshifts of SDSS Galaxies Overlapped with Galactic Objects
Authors: Masafumi Yagi, Masanori Iye, Hideya Fukumoto
Figure caption: Similarly to Figure 3, green lines show our redshift, while red lines show redshift in Simbad.
Paper: Velocity Shift and Signal-to-Noise Ratio Limits for High-resolution Spectroscopy of Hot Jupiters Using Keck/KPIC
Authors: Kevin S. Hong, Luke Finnerty, Michael P. Fitzgerald
Figure caption: 100 × 100 detection strength grids for each planet model and grid case. The left column shows the fixed-phase simulations and the right column shows the fixed-Kp simulations. The first row shows the WASP-33 b grids, the middle row shows the HD 189733 b grids, and the last row shows the HD 149026 b grids. All grids have the same colorbar scale, with an upper bound of 15σ to highlight the contrast of lower values. We plot the best-fit contours based on Equation (5) (white) and the numerical contours from matplotlib (green), which correspond closely except in the intermediate region of Δvpl and SNR. The WASP-33 b model produces the strongest detection and thus lowest detection limits of all three planet models.
Paper: Velocity Shift and Signal-to-Noise Ratio Limits for High-resolution Spectroscopy of Hot Jupiters Using Keck/KPIC
Authors: Kevin S. Hong, Luke Finnerty, Michael P. Fitzgerald
Figure caption: Kp−vsys diagrams for the 2021 November 21 observations of WASP-33 b (top; L. Finnerty et al. 2023) and for simulated WASP-33 b data with observed parameters Δvpl = 140 km s−1 and SNR = 650 that closely match observation (bottom). The red dashed lines mark the true velocities of WASP-33 b (Δvsys = 0, Kp = 226). The orange dashed line show the estimated degeneracy between Δvsys and Kp based on the observed and simulated phase range (Equation (1)). Note that the colorbar scale is the same between both grids. The simulated data produce a detection strength estimate of 10.1σ, which is slightly larger than the 8.9σ detection in the observed data.
Paper: Velocity Shift and Signal-to-Noise Ratio Limits for High-resolution Spectroscopy of Hot Jupiters Using Keck/KPIC
Authors: Kevin S. Hong, Luke Finnerty, Michael P. Fitzgerald
Figure caption: 6σ best-fit contour lines from the 100 × 100 detection grids for each planet model and grid case. The fixed-phase grid contours are shown as the solid lines and the fixed-Kp grid contours are shown as the dashed lines. The WASP-33 b (ultrahot Jupiter) model provides lower Δvpl and SNR limits than the other two models. The Δvpl and SNR of Keck/KPIC observations of WASP-33 b, HD 189733 b, and HD 149026 b are also plotted (as stars). The observed parameters for WASP-33 b and HD 189733 b fall above the 6σ contours, suggesting that these observations will provide significant detections.
Paper: Velocity Shift and Signal-to-Noise Ratio Limits for High-resolution Spectroscopy of Hot Jupiters Using Keck/KPIC
Authors: Kevin S. Hong, Luke Finnerty, Michael P. Fitzgerald
Figure caption: 3 × 3 grid of Kp−vsys diagrams of simulated HD 189733 b detections for Δvpl = 10, 50, and 90 km s−1 and total SNR = 150, 750, and 1350. These diagrams are from the fixed-phase grid case using a consistent orbital phase range ϕ = 0.52–0.58  (Δϕ = 0.06). The colorbar is scaled to a maximum of 6σ to emphasize the nondetections of the low Δvpl and SNR regime. The red dashed lines indicate the true Kp and vsys for a given simulation, with the true velocity detection strength shown. The maximum nearby detection strength is shown as the red dot and red text. The orange dashed lines indicate the estimated correlation between Kp and vsys given the Δvpl and phase range (Equation (2)). Note that the colorbar scale is the same for all diagrams. We can see that the two detection strength methods produce consistent results for high Δvpl and SNR, but deviates at lower Δvpl and SNR.