adsabs/AstroCLIMB huggingface dataset:
Paper: Hierarchical Bayesian Atmospheric Retrieval Modeling for Population Studies of Exoplanet Atmospheres: A Case Study on the Habitable Zone
Authors: Jacob Lustig-Yaeger, Kristin S. Sotzen, Kevin B. Stevenson, Rodrigo Luger, Erin M. May, L. C. Mayorga, Kathleen Mandt, and Noam R. Izenberg
Figure caption: Standard deviation among the spectra shown in Figure 1 with varying CO2 (black) compared with the 1σ observational uncertainties for 10 (magenta) and 100 (orange) stacked transits of TRAPPIST-1e with JWST’s NIRSpec Prism. The spectroscopic differences caused by the silicate weathering CO2 trend are less than 10 ppm for Earth-sized exoplanets transiting TRAPPIST-1, indicating that approximately 100 stacked transits may be necessary to clearly resolve the deviations in CO2 mixing ratios across HZ instellations.
Paper: Hierarchical Bayesian Atmospheric Retrieval Modeling for Population Studies of Exoplanet Atmospheres: A Case Study on the Habitable Zone
Authors: Jacob Lustig-Yaeger, Kristin S. Sotzen, Kevin B. Stevenson, Rodrigo Luger, Erin M. May, L. C. Mayorga, Kathleen Mandt, and Noam R. Izenberg
Figure caption: Corner plot showing the 1D and 2D marginalized posterior distributions (histograms and contours) for the five planetary parameters retrieved from fitting the transmission spectrum using the smarter model. The subplots along the diagonal show the input atmospheric profiles as a function of pressure that were used to generate the synthetic spectrum for comparison against the vertically homogeneous (isothermal and evenly mixed) atmospheric models that were retrieved. The upper right inset shows the median retrieved spectrum bounded by 1σ and 3σ credible intervals derived from posterior samples. This particular retrieval result was for the case with ∼ 83% CO2 and is representative of similar results obtained for the other planets in our synthetic sample.
Paper: Hierarchical Bayesian Atmospheric Retrieval Modeling for Population Studies of Exoplanet Atmospheres: A Case Study on the Habitable Zone
Authors: Jacob Lustig-Yaeger, Kristin S. Sotzen, Kevin B. Stevenson, Rodrigo Luger, Erin M. May, L. C. Mayorga, Kathleen Mandt, and Noam R. Izenberg
Figure caption: Corner plot showing 1D and 2D marginalized posterior distributions for the four hyperparameters used to describe the carbonate–silicate weathering feedback population-level trend for rocky HZ exoplanets. The median inferred population trend is displayed in the upper right inset (solid purple line) with shading to denote 1σ and 3σ credible intervals. Using the importance sampling HBAR method, we are able to retrieve statistically robust constraints on the parameters characterizing the silicate weathering population trend in CO2 abundance with stellar irradiation.
Paper: Hierarchical Bayesian Atmospheric Retrieval Modeling for Population Studies of Exoplanet Atmospheres: A Case Study on the Habitable Zone
Authors: Jacob Lustig-Yaeger, Kristin S. Sotzen, Kevin B. Stevenson, Rodrigo Luger, Erin M. May, L. C. Mayorga, Kathleen Mandt, and Noam R. Izenberg
Figure caption: Comparison between multiple population-level models. The ΔBIC assessment indicates that the “Gaussian-like” model is strongly preferred over the other models.
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: The flow chart of lensed quasar mock catalog generation process.
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: The comparison between the derived VDFs of the CosmoDC2 catalog and the observed VDF at z < 1.5. Left: the local (z < 0.1) VDF. The VDF of the CosmoDC2 catalog accurately matches the spectroscopically measured VDF in Sohn et al. (2017) and Hasan & Crocker (2019). Right: the VDF at 0.3 < z < 1.5. The gray area marks the region where Bezanson et al. (2012) suggest that their galaxy sample has a low completeness. The CosmoDC2 VDF is in good agreement with the observed VDF up to z = 1.5. At the less massive end, the CosmoDC2 catalog gives a higher number density than the observation, which can be explained by the incompleteness of the observed galaxy sample.
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: QLFs adopted by this work. We use the QLF from Ross et al. (2013) to model quasars at z < 3.5, and compile a number of literature to construct the QLF at z > 3.5 (see text for details). Left: the Ross et al. (2013) QLFs. Right: the high-redshift QLFs we use from the literature. At z ≳ 4, the values of M*, α and β do not show strong redshift evolution, suggesting that a linear interpolation between the redshifts is adequate.
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: A gallery of mock lensed quasars. We show several typical cases for both the low-redshift and the high-redshift sample. The synthetic magnitudes are in LSST ugrizy, UKIDSS JHK, and WISE W1, W2 bands. The mock lensed quasars show a large diversity in observational features in magnitudes, colors, lensing separations, etc. It is worth noticing that (1) the deflector galaxy is always at the center of the image, and is usually blended with the fainter lensed image in doubly-lensed systems; (2) the low-redshift example of a “marginally discoverable” lens (third row, left) has a small lensing separation of 0.″5, and the high-redshift example (third row, right) has a marginally detectable fainter image (which is blended with the deflector galaxy). See Section 3 for the definition of discoverable lenses.
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: Predicted number of discoverable lensed quasars in LSST and PS1 survey, as a function of redshift. See Section 3 for the definition of a discoverable lensed quasar. Left: the low-redshift (zqso < 5) sample. We run 50 realizations which is equivalent to an all-sky area, and scale the predicted number of discoverable lenses according to the survey area (listed in Table 4). There are ∼900 discoverable lensed quasars in the PS1 survey, and LSST will increase this number to about 2.4 × 103. Note that there is a bump at zqso ∼ 4 in lensed quasar numbers, where we switch from the low-redshift QLF to the high-redshift one. The faint-end values of the two QLFs are not fully consistent at this redshift. Right: the high-redshift (zqso > 5) sample. We run 1,000 realizations to reduce the statistical error since the number density of high-redshift quasars is low. The mock catalog suggests that only a handful of lensed quasars at zqso > 5 are discoverable in current imaging surveys like PS1, and there will be ∼45 discoverable in LSST. At z ≳ 6.5, there are effectively no discoverable lensed quasars even for LSST.
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: The distribution of the image separations of lensed quasars. The dashed line marks the limit above which the mock catalog is complete. About ∼ 50% of the lensed quasars have separation Δθ > 1″, and ∼ 80% of them have Δθ > 0.″5.
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: Comparison between this work and OM10. Left: the QLF adopted in this work and OM10. The two QLFs are nearly identical for quasars at z ≲ 2.5 with M1450 < − 24. Middle: the VDF adopted in this work and OM10. We show the CosmoDC2 VDF at z < 1.5 which covers the majority of deflector galaxies for zqso ≲ 2.5. OM10 uses the local VDF in Choi et al. (2007) and assumes no redshift evolution. The local VDF of the CosmoDC2 catalog is close to the one used by OM10, and the OM10 VDF is slightly higher than the CosmoDC2 VDF at higher redshift. Right: the predicted number of lensed quasars at z < 3. We only select lensed quasars with Δθ > 0.″5 and M1450 < − 24, at which the QLFs used by OM10 and this work are close to each other. Our mock catalog predicts slightly smaller numbers of lensed quasars than OM10 when only restricted to these parameter ranges, and the different can be fully explained by the adopted QLFs and VDFs (see text for details).
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: Left: the number of discoverable quadruply-lensed quasars as a function of survey depth. We also include doubly-lensed quasars and unlensed quasars for comparison. We use the LSST survey area and seeing condition when computing the numbers. The magnitudes correspond to the second brightest image for doubly-lensed quasars, and the third brightest image for quad lenses. The fraction of quadruply-lensed quasars among all lenses is ∼ 10% − 15% at mi ≲ 25. This fraction drops quickly at mi ≳ 26, which is a result of the absolute magnitude cutoff (Mi < − 20). Right: the probabilistic distribution of the deflector ellipticity, egalaxy, for the CosmoDC2 mock galaxies and the one adopted by OM10. The two distributions are generally similar, with some difference at the low- and high-ellipticity end.
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: The magnitude difference and the time delays of the mock lensed quasars. The subscripts represent the order of arrival, e.g., m1 is the magnitude of the image that arrives first. Most lensed quasars have time lags ∼ 101–103 days. For doubly imaged quasars, the brighter image usually arrives earlier than the fainter one. For quad lenses, the first-arriving image is the second or third brightest in most cases.
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: The distribution of deflector redshifts. The y axis denotes the probability for a background source to be lensed by a foreground deflector at a certain redshift. The gray histogram represents all the simulated lensed quasars, which peaks at ∼0.7 and has a median of 0.87. The distribution drops to a negligible level at zd > 2.5. We also include two samples of background sources at zs = 2 and zs = 5 for comparison.
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: Left: the i-band magnitudes of the deflector galaxies of LSST-discoverable lensed quasars. Nearly all of them are beyond the LSST magnitude limit. The impact of deflector galaxy flux must be considered when selecting lensed quasar candidates. Right: the difference between the magnitude of the deflector galaxy and the magnified magnitude of the quasar. The quasar magnitude corresponds to the total flux of all the lensed images of the background quasar. The magnitude difference spreads over a wide range, which suggests a large diversity in observed features for lensed quasars.
Paper: A Mock Catalog of Gravitationally-lensed Quasars for the LSST Survey
Authors: Minghao Yue, Xiaohui Fan, Jinyi Yang, and Feige Wang
Figure caption: Left: testing the mass-dependence term in the velocity dispersion. We use the M*–Mdyn relation in Auger et al. (2010) to calculate the velocity dispersion of CosmoDC2 mock galaxies. The resulting local VDF does not match the observations. Right: testing the redshift-evolution term in the velocity dispersion. We add the redshift evolution from Beifiori et al. (2014) to the velocity dispersion inferred by Equation (2) for mock galaxies. The redshift evolution is subtle, and the inferred VDF is consistent with observation at z < 1. However, at z > 1, the redshift evolution term starts to overpredict the number of galaxies at the massive end.
Paper: Far-ultraviolet to FIR Spectral-energy Distribution Modeling of the Stellar Formation History of the M31 Bulge
Authors: Denis Leahy, Noah Seminoff, and Cameron Leahy
Figure caption: UVIT F148W (150 nm) image (observations A and B merged) of Field 1 containing the M31 bulge (the central ∼7′) and the inner spiral arms which are aligned along the NE–SW direction. The scale is square root, with scale bar at bottom edge. The units of the scale bar are counts per pixel, where the pixels are square with side of 0.″4168.
Paper: Far-ultraviolet to FIR Spectral-energy Distribution Modeling of the Stellar Formation History of the M31 Bulge
Authors: Denis Leahy, Noah Seminoff, and Cameron Leahy
Figure caption: Diagram showing locations of quarter elliptical annuli used for photometry for all bands listed in Table 1. The annuli are overlaid on the UVIT F148W image of the ≃6.′5 by 6.′5 region containing the bulge.
Paper: Far-ultraviolet to FIR Spectral-energy Distribution Modeling of the Stellar Formation History of the M31 Bulge
Authors: Denis Leahy, Noah Seminoff, and Cameron Leahy
Figure caption: Top: FUV–NUV-optical-NIR-IR data band fluxes for Annulus 01 (purple circles with error bars) compared to CIGALE model band fluxes (red circles). The model flux density is the black solid line. Contributions from attenuated and unatttenuated stars, gas (nebular), and dust are shown by the yellow, blue, green, and red lines. Bottom: relative residuals, (data—model)/data. All figures with wavelength as abscissa are on logarithmic scale. The maximum and minimum wavelengths are different for different figures because the range of wavelengths varies greatly.
Paper: Far-ultraviolet to FIR Spectral-energy Distribution Modeling of the Stellar Formation History of the M31 Bulge
Authors: Denis Leahy, Noah Seminoff, and Cameron Leahy
Figure caption: Two-SSP model fit to the FUV–NUV-optical-NIR SED of annulus 1 of the M31 bulge. The data points are the yellow circles (with error bars smaller than the symbol size), the blue line shows the model fluxes for the old stellar population, the red line shows the model fluxes for the young stellar population, and the green line shows the sum of the two model fluxes.
Paper: Far-ultraviolet to FIR Spectral-energy Distribution Modeling of the Stellar Formation History of the M31 Bulge
Authors: Denis Leahy, Noah Seminoff, and Cameron Leahy
Figure caption: Three-SSP model fit to the FUV–NUV-optical-NIR SED of annulus one of the M31 bulge. The data points are the yellow circles (error bars smaller than the symbols), the red line shows the model fluxes for the old stellar population, the red line for the intermediate age population, the purple line for the young population, and the green line for the sum of the three populations.
Paper: Far-ultraviolet to FIR Spectral-energy Distribution Modeling of the Stellar Formation History of the M31 Bulge
Authors: Denis Leahy, Noah Seminoff, and Cameron Leahy
Figure caption: Left panel: CIGALE Best-fit E(B–V)lines vs. effective radius (Reff) of each annulus. Right panel: Best-fit E(B–V)stars vs. effective radius (Reff) of each annulus.
Paper: Far-ultraviolet to FIR Spectral-energy Distribution Modeling of the Stellar Formation History of the M31 Bulge
Authors: Denis Leahy, Noah Seminoff, and Cameron Leahy
Figure caption: CIGALE Best-fit δpowerlaw of dust attenuation law vs. effective radius (Reff) of each annulus.
Paper: Far-ultraviolet to FIR Spectral-energy Distribution Modeling of the Stellar Formation History of the M31 Bulge
Authors: Denis Leahy, Noah Seminoff, and Cameron Leahy
Figure caption: CIGALE Best-fit mass of the old stellar population vs. effective radius (Reff) of each annulus.
Paper: Far-ultraviolet to FIR Spectral-energy Distribution Modeling of the Stellar Formation History of the M31 Bulge
Authors: Denis Leahy, Noah Seminoff, and Cameron Leahy
Figure caption: Left panel: best-fit mass of the old stellar population vs. effective radius (Reff) for the SSP models. The three-SSP model applies for Ann1 to Ann4, the two-SSP model for Ann5 to Ann10 (see text). Right panel: best-fit mass fraction of the young stellar populations (Myoung/Mold) vs. Reff.
Paper: Far-ultraviolet to FIR Spectral-energy Distribution Modeling of the Stellar Formation History of the M31 Bulge
Authors: Denis Leahy, Noah Seminoff, and Cameron Leahy
Figure caption: Left panel: best-fit age of the young stellar populations vs. effective radius (Reff) for the SSP models. Right panel: best-fit metallicity of the stellar populations vs. Reff.
Paper: Dynamical Implantation of Blue Binaries in the Cold Classical Kuiper Belt
Authors: David Nesvorný, David Vokrouhlický, and Wesley C. Fraser
Figure caption: The implantation probability to an orbit with 42 < a < 47 au, i < 5° and q > 36 au as a function of the starting orbital radius. The implantation probability for r < 30 au is ≲10−4. For r < 38 au, the implantation probabilities are higher in the 10/30 simulation (faster migration of Neptune) than in 30/100 (slower migration). Bodies starting in a cold disk at 42 < r < 47 au have a 30%–40% chance to end up as cold classicals (Nesvorný 2015b).
Paper: Dynamical Implantation of Blue Binaries in the Cold Classical Kuiper Belt
Authors: David Nesvorný, David Vokrouhlický, and Wesley C. Fraser
Figure caption: The number of bodies (nCC,j) implanted from different starting radii on orbits with 42 < a < 47 au, i < 5° and q > 36 au. We normalize nCC,j such that nCC,8 = 104. The blue and red lines show the results for faster (10/30) and slower (30/100) migration of Neptune, respectively. The solid and dashed lines are the exponential and truncated disks, respectively.
Paper: Dynamical Implantation of Blue Binaries in the Cold Classical Kuiper Belt
Authors: David Nesvorný, David Vokrouhlický, and Wesley C. Fraser
Figure caption: The dynamical survival of binaries as function of their starting orbital radius and separation. The surviving fraction of wide binaries is relatively low because they are more susceptible to gravitational perturbations during planetary encounters. The surviving fraction increases with the starting orbital radius because fewer encounters happen during the implantation stage for these initially more distant bodies. The yellow line corresponding to 40–42 au (zone 7) is missing in the left panel, because we did not have sufficient statistics in this case.
Paper: Dynamical Implantation of Blue Binaries in the Cold Classical Kuiper Belt
Authors: David Nesvorný, David Vokrouhlický, and Wesley C. Fraser
Figure caption: The ratio of blue binaries to blue singles (Rb/s) expected from the implantation process as a function of the LR-to-VR transition radius, r*. In each case, we assumed a monodisperse distribution of binary separations: ab/Rb = 10 (red), 100 (green), and 1000 (blue). The initial binary fraction throughout the original planetesimal disk was assumed to be 100% (no initial singles). We evaluate the proportion of surviving and dissolved binaries in each case and plot the expected blue binary-to-single ratio in the CC population. The results for the exponential disk profile are shown here. The profiles for the truncated disk, where the implanted population is dominated by bodies starting with r < 30 au, are less plausible.
Paper: Determining the Timescale over Which Stellar Feedback Drives Turbulence in the Interstellar Medium: A Study of Four Nearby Dwarf Irregular Galaxies
Authors: Laura Congreve Hunter, Liese van Zee, Kristen B. W. McQuinn, Ray Garner, and Andrew E. Dolphin
Figure caption: NGC 4068 H I moment maps from VLA observations. Left: H I column density in 1021 hydrogen atoms cm−2. Center: H I velocity map with isovelocity contours spaces every 10 km s−1. Right: H I velocity dispersion map with isovelocity contours at 2.25 km s−1 spacing. The beam size (11.″83 × 11.″29) of the H I data cube used is shown in the bottom left of the left panel.
Paper: Determining the Timescale over Which Stellar Feedback Drives Turbulence in the Interstellar Medium: A Study of Four Nearby Dwarf Irregular Galaxies
Authors: Laura Congreve Hunter, Liese van Zee, Kristen B. W. McQuinn, Ray Garner, and Andrew E. Dolphin
Figure caption: NGC 4163 H I moment maps from VLA observations. Left: H I column density in 1021 hydrogen atoms cm−2. Center: H I velocity map with isovelocity contours spaces every 5 km s−1. Right: H I velocity dispersion map with isovelocity contours at 2 km s−1 spacing. The beam size (13.″80 × 12.″96) of the H I data cube used is shown in the bottom left of the left panel.
Paper: Determining the Timescale over Which Stellar Feedback Drives Turbulence in the Interstellar Medium: A Study of Four Nearby Dwarf Irregular Galaxies
Authors: Laura Congreve Hunter, Liese van Zee, Kristen B. W. McQuinn, Ray Garner, and Andrew E. Dolphin
Figure caption: NGC 6789 H I moment maps from VLA observations. Left: H I column density in 1021 hydrogen atoms cm−2. Center: H I velocity map with isovelocity contours spaces every 10 km s−1. Right: H I velocity dispersion map with isovelocity contours at 2.5 km s−1 spacing. The beam size (11.″92 × 10.″52) of the H I data cube used is shown in the bottom left of the left panel.
Paper: Determining the Timescale over Which Stellar Feedback Drives Turbulence in the Interstellar Medium: A Study of Four Nearby Dwarf Irregular Galaxies
Authors: Laura Congreve Hunter, Liese van Zee, Kristen B. W. McQuinn, Ray Garner, and Andrew E. Dolphin
Figure caption: UGC 9128 H I moment maps from VLA observations. Left: H I column density in 1021 hydrogen atoms cm−2. Center: H I velocity map with isovelocity contours spaces every 5 km s−1. Right: H I velocity dispersion map with isovelocity contours at 2.5 km s−1 spacing. The beam size (9.″64 × 6.″35) of the H I data cube used is shown in the bottom left of the left panel.
Paper: Determining the Timescale over Which Stellar Feedback Drives Turbulence in the Interstellar Medium: A Study of Four Nearby Dwarf Irregular Galaxies
Authors: Laura Congreve Hunter, Liese van Zee, Kristen B. W. McQuinn, Ray Garner, and Andrew E. Dolphin
Figure caption: NGC 4068 maps from observations with the SparsePak IFU on the WIYN 3.5 m telescope, with Hα line measurements from PAN. Left: Hα on a log scale in units of 10−17 erg s−1 cm−1. Center: Hα line centers map. Right: Hα velocity dispersion (σHα) map. Each filled circle corresponds to a fiber’s size and position on the sky. For reference to where the Sparsepak fibers fall on the galaxy compared with the H I and optical distributions, see Figure 9.
Paper: Determining the Timescale over Which Stellar Feedback Drives Turbulence in the Interstellar Medium: A Study of Four Nearby Dwarf Irregular Galaxies
Authors: Laura Congreve Hunter, Liese van Zee, Kristen B. W. McQuinn, Ray Garner, and Andrew E. Dolphin
Figure caption: NGC 4163 maps from observations with the SparsePak IFU on the WIYN 3.5 m telescope, with Hα line measurements from PAN. Left: Hα on a log scale in units of 10−17 erg s−1 cm−1. Center: Hα line centers map. Right: Hα velocity dispersion (σHα) map. Each filled circle corresponds to a fiber’s size and position on the sky. For reference to where the Sparsepak fibers fall on the galaxy compared with the H I and optical distributions, see Figure 10.
Paper: Determining the Timescale over Which Stellar Feedback Drives Turbulence in the Interstellar Medium: A Study of Four Nearby Dwarf Irregular Galaxies
Authors: Laura Congreve Hunter, Liese van Zee, Kristen B. W. McQuinn, Ray Garner, and Andrew E. Dolphin
Figure caption: NGC 6789 maps from observations with the SparsePak IFU on the WIYN 3.5 m telescope, with Hα line measurements from PAN. Left: Hα on a log scale in units of 10−17 erg s−1 cm−1. Center: Hα line centers map. Right: Hα velocity dispersion (σHα) map. Each filled circle corresponds to a fiber’s size and position on the sky. For reference to where the Sparsepak fibers fall on the galaxy compared with the H I and optical distributions, see Figure 11.