adsabs/AstroCLIMB huggingface dataset:
Paper: Limits on the Density of the Lunar Ionosphere: ARTEMIS Observations
Authors: Han-Wen Shen, Jasper S. Halekas, Andrew R. Poppe
Figure caption: Measurements from the ARTEMIS P2 probe for the nightside event on 2014 February 27. The interval between the two black vertical dotted lines shows when the probe reaches altitudes below 30 km. Panels (a) and (b) present the ion and electron energy flux spectra, respectively. Panel (c) shows the spacecraft potential. Panel (d) displays the ion and electron density moments measured by the ESA. The left-hand orange vertical solid line indicates the time when the probe crossed from sunlight to shadow, and the right-hand one indicates the crossing from shadow to sunlight. The vertical dashed lines near the left-hand (right-hand) vertical solid line indicate 8 (2) minutes before and 2 (8) minutes after the time of crossing from sunlight (shadow) to shadow (sunlight). Panel (e) depicts the electric field power spectra (using Fast Fourier Transforms) observed by the EFI, and the red curve in this panel indicates the plasma frequency inferred from the measured electron density moment (Ne_mom). Panels (f)–(i) show the same variables as Figures 2(d)–(g).
Paper: Limits on the Density of the Lunar Ionosphere: ARTEMIS Observations
Authors: Han-Wen Shen, Jasper S. Halekas, Andrew R. Poppe
Figure caption: Measurements from the ARTEMIS P2 probe for the dayside event on 2013 May 10. The interval between the two black vertical dotted lines shows when the probe reaches altitudes below 30 km. Panels (a) and (b) show the ion and electron omnidirectional energy flux spectra, respectively. The black line in panel (b) indicates the spacecraft potential. Panel (c) displays the electron density (Ne_scpot) derived from the spacecraft potential and the ion and electron density moments (Ni_mom and Ne_mom) measured by the ESA. Panels (d) and (e) show variations of the magnetic field strength and ion velocity measured from the FGM and ESA, respectively. The variations in altitude and local time of the probe are presented in panels (f) and (g), respectively.
Paper: Limits on the Density of the Lunar Ionosphere: ARTEMIS Observations
Authors: Han-Wen Shen, Jasper S. Halekas, Andrew R. Poppe
Figure caption: Plasma density profiles with altitude and lunar local time derived from ARTEMIS measurements during 2012–2021. The left-hand panels show the profiles as a function of altitude for four local-time sectors, and the right-hand panels show the profiles as a function of local time for four altitude ranges. One should note the different scale in panel (a).
Paper: Limits on the Density of the Lunar Ionosphere: ARTEMIS Observations
Authors: Han-Wen Shen, Jasper S. Halekas, Andrew R. Poppe
Figure caption: Dependences of plasma density on selenographic longitude and crustal magnetic field strength. The density samples are at altitudes below 60 km on the dawn (06:00–08:00) and dusk (16:00–18:00) sides. The plus and triangle symbols in the top panel indicate samples of Ni_mom and Ne_mom, respectively. The left-hand and right-hand red rectangles in the bottom panel represent the distribution ranges of samples on the dusk and dawn sides, respectively.
Paper: Limits on the Density of the Lunar Ionosphere: ARTEMIS Observations
Authors: Han-Wen Shen, Jasper S. Halekas, Andrew R. Poppe
Figure caption: Schematic illustration showing the effects of spacecraft potential on measurements of the electron energy spectrum. Measured electron spectra are illustrated for three different conditions of spacecraft potential. In each spectrum, the blue dashed curve indicates the energy distribution function of the ambient electrons (which is the same in all three cases, but shifted in energy due to the spacecraft potential). In the spectrum for positive spacecraft potential, the red curve indicates the energy distribution function of spacecraft-generated (i.e., nongeophysical) photoelectrons, and the gray vertical line indicates the spacecraft potential (U S/C).
Paper: Limits on the Density of the Lunar Ionosphere: ARTEMIS Observations
Authors: Han-Wen Shen, Jasper S. Halekas, Andrew R. Poppe
Figure caption: Scatter plot of plasma density vs. altitude near the lunar surface. The plus symbols in different colors indicate different types of all density measurements at altitudes below 50 km from the ARTEMIS mission during 2012–2021.
Paper: JWST's TEMPLATES for Star Formation: The First Resolved Gas-phase Metallicity Maps of Dust-obscured Star-forming Galaxies at z ∼ 4
Authors: Jack E. Birkin, Taylor A. Hutchison, Brian Welch, Justin S. Spilker, Manuel Aravena, Matthew B. Bayliss, Jared Cathey, Scott C. Chapman, Anthony H. Gonzalez, Gayathri Gururajan, Christopher C. Hayward, Gourav Khullar, Keunho J. Kim, Guillaume Mahler, Matthew A. Malkan, Desika Narayanan, Grace M. Olivier, Kedar A. Phadke, Cassie Reuter, Jane R. Rigby, J. D. T. Smith, Manuel Solimano, Nikolaus Sulzenauer, Joaquin D. Vieira, David Vizgan, Axel Weiss
Figure caption: Spaxel-by-spaxel (0.″1, ∼ 0.7 kpc) variation of 380 μm flux (top), [C I] line flux (middle), and [C I]/380 μm flux ratio (bottom) as a function of [N II]/Hα line ratio for the two SPT DSFGs. On the top axes we show the corresponding oxygen abundances according to the calibration of M13. On the right axes we show the corresponding dust mass surface density Σdust, gas mass surface density Σgas, and gas-to-dust ratio δ GDR, using the conversions described in Section 3.3. We plot a binned median (gray line) with 1σ scatter (gray region), and color code points by Hα FWHM. We also indicate solar metallicity (Asplund et al. 2021) and shade the region where [N II]/Hα > 0.8, the latter of which is likely to be contaminated to some extent by AGN emission. Notably, in this region Hα emission is broadest when compared to the rest of the source. In both sources the gas-to-dust ratio appears to decline with increasing metallicity, although this trend is more prominent in SPT2147-50. In the bottom panels we also show models from Rémy-Ruyer et al. (2014) and Aniano et al. (2020), which are discussed further in Section 3.3.
Paper: JWST's TEMPLATES for Star Formation: The First Resolved Gas-phase Metallicity Maps of Dust-obscured Star-forming Galaxies at z ∼ 4
Authors: Jack E. Birkin, Taylor A. Hutchison, Brian Welch, Justin S. Spilker, Manuel Aravena, Matthew B. Bayliss, Jared Cathey, Scott C. Chapman, Anthony H. Gonzalez, Gayathri Gururajan, Christopher C. Hayward, Gourav Khullar, Keunho J. Kim, Guillaume Mahler, Matthew A. Malkan, Desika Narayanan, Grace M. Olivier, Kedar A. Phadke, Cassie Reuter, Jane R. Rigby, J. D. T. Smith, Manuel Solimano, Nikolaus Sulzenauer, Joaquin D. Vieira, David Vizgan, Axel Weiss
Figure caption: Oxygen abundance 12 + log(O/H) estimated from the [N II]/Hα ratio, using the M13 calibration (see Section 3.1), vs. stellar mass estimated from SED fitting. As comparison samples we include galaxies from the KMOS3D survey (Wisnioski et al. 2015), and z ∼ 1.5–2.5 DSFGs also observed with KMOS (Birkin 2022). From C20 we display the MZR (red shaded) and the FMR for the SFRs of the two galaxies (yellow for SPT0418-47, blue for SPT2147-50). The open points show how far down the points would move if we were to exclude pixels with [N II]/Hα > 0.5 conservatively to account for AGN (the points are also shifted horizontally for visual clarity). Both DSFGs are consistent with the MZR, and are also consistent with the upper end of the FMR, particularly when we account for potential AGN emission.
Paper: Mass Ratio Distribution of Hierarchical Triple Systems from the LAMOST-MRS Survey
Authors: Tongyu He, Jiangdan Li, Xuefei Chen, Rong-jia Yang, Lin Xiao, Zhanwen Han
Figure caption: Proportion of observed ST candidates displayed against orbital period for different P out/P in values for a given number of observational epochs. The x-axes are the inner binary periods of the triple systems. For 1, 2, and 4 observational epochs, thick solid, dashed, and dotted lines are shown; for 8, 16, and 32 observational epochs, thin solid, dashed, and dotted lines are shown.
Paper: Reconstruction of a Scale-dependent Gravitational Phase Transition
Authors: Marzieh Farhang, Nima Khosravi
Figure caption: The reconstructed perturbations in μ(k) and γ(k) in the GEM scenario, with the first five eigenmodes, for the two data combinations P18+BAO+R21 and P18+H 073.
Paper: Mass Ratio Distribution of Hierarchical Triple Systems from the LAMOST-MRS Survey
Authors: Tongyu He, Jiangdan Li, Xuefei Chen, Rong-jia Yang, Lin Xiao, Zhanwen Han
Figure caption: Probability that the RV of the third star (M 3) is in the middle of the inner binary (M 1, M 2) for hierarchical triple systems. The black line represents that the value of the inner-to-outer period ratio (P out/P in) is greater than 50.
Paper: Mass Ratio Distribution of Hierarchical Triple Systems from the LAMOST-MRS Survey
Authors: Tongyu He, Jiangdan Li, Xuefei Chen, Rong-jia Yang, Lin Xiao, Zhanwen Han
Figure caption: The coordinates of the triple candidate depicted in the top panel are R.A. = 134.1496, decl. = 12.59047, while the coordinates of the triple candidate illustrated in the bottom panel are R.A. = 292.718, decl. = 41.922. The x-axis is the RV1, and the y-axis is the RV2. The black line represents the fitted equation, with the parameters given at the top. The intersection points of the two black dashed lines represent the systemic velocities γ dyn.
Paper: Reconstruction of a Scale-dependent Gravitational Phase Transition
Authors: Marzieh Farhang, Nima Khosravi
Figure caption: The posterior probability distribution of H 0 for three data combinations. The shaded green regions illustrate the R21 measurement of H 0. Left: the background evolution is assumed to be the same as in ΛCDM. Right: the background evolves according to Equation (1).
Paper: Mass Ratio Distribution of Hierarchical Triple Systems from the LAMOST-MRS Survey
Authors: Tongyu He, Jiangdan Li, Xuefei Chen, Rong-jia Yang, Lin Xiao, Zhanwen Han
Figure caption: Number of detected ST candidates vs. number of observations.
Paper: Reconstruction of a Scale-dependent Gravitational Phase Transition
Authors: Marzieh Farhang, Nima Khosravi
Figure caption: The first three GEMs, or k-dependent GEMs, for μ and γ, with various data sets. The background is allowed to experience a phase transition as in Equation (1).
Paper: Tracing the Total Stellar Mass and Star Formation of High-redshift Protoclusters
Authors: Roxana Popescu, Alexandra Pope, Kyoung-Soo Lee, Stacey Alberts, Yi-Kuan Chiang, Sowon Lee, Mark Brodwin, Jed McKinney, Vandana Ramakrishnan
Figure caption: The rest-frame SED of the full sample of stacked PC15 protocluster candidates and the best-fit model of the spectrum to the SED from CIGALE (assuming z = 2). The data points used to fit the SED are shown by filled red circles, while the open red circles show the W3 and W4 points, which are not used in the fit. AGN and star-forming galaxy templates, AGN4 and SFG3, from the comprehensive library of Kirkpatrick et al. (2015) are plotted and normalized to the best-fit model at 83 μm (250 μm observed frame). The SED of the stack of the brighter half of the protocluster candidates from Kubo et al. (2019) are plotted in gray.
Paper: Tracing the Total Stellar Mass and Star Formation of High-redshift Protoclusters
Authors: Roxana Popescu, Alexandra Pope, Kyoung-Soo Lee, Stacey Alberts, Yi-Kuan Chiang, Sowon Lee, Mark Brodwin, Jed McKinney, Vandana Ramakrishnan
Figure caption: Radial surface brightness profiles of the WISE and SPIRE stacks of the PC15 protoclusters, with the best-fit Gaussian model plotted in red. The dotted gray line indicates the profile of the Planck beam, normalized to the peak of the best-fit Gaussian model. The FWHM of the beam in each band is indicated in brackets. The bottom right panel shows the surface brightness profiles normalized to the peak value of the bands, which trace stellar mass (W1 and W2), and dust-obscured star formation (SPIRE 250, SPIRE 350, and SPIRE 500). The comoving (top x-axis) scale is calculated for z = 2.
Paper: Tracing the Total Stellar Mass and Star Formation of High-redshift Protoclusters
Authors: Roxana Popescu, Alexandra Pope, Kyoung-Soo Lee, Stacey Alberts, Yi-Kuan Chiang, Sowon Lee, Mark Brodwin, Jed McKinney, Vandana Ramakrishnan
Figure caption: Total star formation rates as a function of total stellar masses for different studies of protoclusters and clusters. Red indicates our total light measurement for PC15 protoclusters corrected for line-of-sight interlopers. We also plot individual protoclusters (Casey 2016) that contain DSFGs (square points), and a confirmed Planck-selected protocluster from the PHz catalog (Polletta et al. 2021) indicated by the circular point. We also show z ∼ 4 protoclusters (Hill et al. 2020; Long et al. 2020; Hill et al. 2022) and the z = 1.4 cluster sample from Alberts et al. (2021). The main sequence at z = 2 from Speagle et al. (2014) is extrapolated to higher stellar masses and shown in gray.
Paper: Tracing the Total Stellar Mass and Star Formation of High-redshift Protoclusters
Authors: Roxana Popescu, Alexandra Pope, Kyoung-Soo Lee, Stacey Alberts, Yi-Kuan Chiang, Sowon Lee, Mark Brodwin, Jed McKinney, Vandana Ramakrishnan
Figure caption: Weighted mean stacks of the PC15 protoclusters showing extended emission from 3.4 to 500 μm. The top panel shows the stacks and the offset stacks in the WISE bands. The offset stacks are created to verify that the extended emission does not appear when stacking random areas of the sky background. The bottom panel shows the stacks in the SPIRE bands. The size of the image point-spread function FWHM is indicated by a red circle at the bottom left corner of each image. The measured half-light radii of the protoclusters are indicated by the dashed red circles.
Paper: Tracing the Total Stellar Mass and Star Formation of High-redshift Protoclusters
Authors: Roxana Popescu, Alexandra Pope, Kyoung-Soo Lee, Stacey Alberts, Yi-Kuan Chiang, Sowon Lee, Mark Brodwin, Jed McKinney, Vandana Ramakrishnan
Figure caption: IR flux distribution of cosmic structures constructed from the WebSky simulation are shown along four Planck-beam-sized sightlines. Flux densities of individual structures are indicated in blue while the dominant structure with the highest flux density is marked in red with its fractional contribution indicated at the top left corner of each panel. The top panels show the two brightest sources in the simulation while the bottom panels show two randomly drawn from the sample of simulated PC15 protoclusters (see Section 4 for more detail).
Paper: Tracing the Total Stellar Mass and Star Formation of High-redshift Protoclusters
Authors: Roxana Popescu, Alexandra Pope, Kyoung-Soo Lee, Stacey Alberts, Yi-Kuan Chiang, Sowon Lee, Mark Brodwin, Jed McKinney, Vandana Ramakrishnan
Figure caption: Cumulative and differential flux profiles for both the original stacked images (orange) and for those with background oversubtraction added back in (blue). The red vertical line indicates 7′, the size of the aperture used to measure the total flux.
Paper: Tracing the Total Stellar Mass and Star Formation of High-redshift Protoclusters
Authors: Roxana Popescu, Alexandra Pope, Kyoung-Soo Lee, Stacey Alberts, Yi-Kuan Chiang, Sowon Lee, Mark Brodwin, Jed McKinney, Vandana Ramakrishnan
Figure caption: The star formation rate density (SFRD) of the PC15 protocluster candidates, including lower-z and higher-z subsamples, and the LBG selected Hyper Suprime-Cam protocluster candidates (Kubo et al. 2019) in comparison to the projected SFRD for protoclusters with a z = 0 halo mass of scaled from Chiang et al. (2017) and the observational measurements of field galaxies (Madau & Dickinson 2014). This figure is adapted from Alberts & Noble (2022).
Paper: Tracing the Total Stellar Mass and Star Formation of High-redshift Protoclusters
Authors: Roxana Popescu, Alexandra Pope, Kyoung-Soo Lee, Stacey Alberts, Yi-Kuan Chiang, Sowon Lee, Mark Brodwin, Jed McKinney, Vandana Ramakrishnan
Figure caption: Surface brightness profiles in the W1 band of the PC15 protoclusters (black) and of the clusters studied by Alberts et al. (2021) in redshift bins of z = 0.5–0.7, z = 0.7–1.0, z = 1.0–1.3, and z = 1.3–1.6 (colored lines).
Paper: X-Ray Spectral Variations of Circinus X-1 Observed with NICER throughout an Entire Orbital Cycle
Authors: Mayu Tominaga, Masahiro Tsujimoto, Ken Ebisawa, Teruaki Enoto, Kimitake Hayasaki
Figure caption: Phase-dependent change of the best-fit parameters for the continuum model: (a) T in and (b) normalization of the disk blackbody emission and (c) ﹩{N}_{{\rm{H}}}^{(\mathrm{cov})}﹩ and (d) f (cov) of the partial covering material. (e) The reduced χ 2 value of the fitting is also given. The green symbols represent the results without constraining the normalization parameter values, whereas the red symbols, except for the early dip period, are those with normalization values constrained along the global trend. Lighter colors are for those with unacceptable fitting with a reduced χ 2 greater than 1.5, which we ignore when investigating the overall spectral change.
Paper: X-Ray Spectral Variations of Circinus X-1 Observed with NICER throughout an Entire Orbital Cycle
Authors: Mayu Tominaga, Masahiro Tsujimoto, Ken Ebisawa, Teruaki Enoto, Kimitake Hayasaki
Figure caption: Proposed view of the system: edge-on views during the (a) dip (early), (b) dip (late)/flaring, and (c) stable phases. The local blocking medium has some spatial structures depending on the disk azimuth, making changes in the line of sight as a function of the orbital phase.
Paper: X-Ray Spectral Variations of Circinus X-1 Observed with NICER throughout an Entire Orbital Cycle
Authors: Mayu Tominaga, Masahiro Tsujimoto, Ken Ebisawa, Teruaki Enoto, Kimitake Hayasaki
Figure caption: Normalization (×10−3 s−1 cm−2) of the line (positive for emission and negative for absorption) for He-like (blue) and H-like (orange) ions using the Heα and Lyα lines of Mg, Si, S, and Fe. We omit the snapshots with either a reduced χ 2 greater than 1.5 or a line normalization consistent with zero.
Paper: X-Ray Spectral Variations of Circinus X-1 Observed with NICER throughout an Entire Orbital Cycle
Authors: Mayu Tominaga, Masahiro Tsujimoto, Ken Ebisawa, Teruaki Enoto, Kimitake Hayasaki
Figure caption: Best-fit ionization parameter (ξ) by comparing the observed and simulated line ratios of the Lyα and Heα lines for snapshots, in which both features are significantly detected. Blue symbols indicate values obtained using the emission line pairs, and purple symbols indicate those using absorption line pairs.
Paper: Predicting the Radiation Field of Molecular Clouds Using Denoising Diffusion Probabilistic Models
Authors: Duo Xu, Stella S. R. Offner, Robert Gutermuth, Michael Y. Grudić, Dávid Guszejnov, Philip F. Hopkins
Figure caption: Synthetic dust observations, including images and SEDs, for simulations at various evolutionary stages and with different feedback configurations. The first column illustrates the SEDs of the synthetic observations. The second and third columns showcase the three-color synthetic dust images at 4.5 (blue), 24 (green), and 250 (red) μm wavelengths, utilizing different radiative transfer configurations. The fourth column presents the projected radiation field strength obtained from the simulations, measured in erg cm−3.
Paper: Predicting the Radiation Field of Molecular Clouds Using Denoising Diffusion Probabilistic Models
Authors: Duo Xu, Stella S. R. Offner, Robert Gutermuth, Michael Y. Grudić, Dávid Guszejnov, Philip F. Hopkins
Figure caption: Demonstration of the diffusion process (reverse) on a sample in the test set. In the upper row, the first panel represents the input (condition) for the diffusion model, while in the lower row, the first panel represents the corresponding target (ground truth). The initial status is denoted as T 1000, which corresponds to the random Gaussian noise. The final states of the reverse Markov chain, representing the final predictions by the diffusion model, are indicated as T 0. The intermediate steps of the reverse Markov chain, ranging from T = 0 to 1000, are depicted in the remaining panels.
Paper: Predicting the Radiation Field of Molecular Clouds Using Denoising Diffusion Probabilistic Models
Authors: Duo Xu, Stella S. R. Offner, Robert Gutermuth, Michael Y. Grudić, Dávid Guszejnov, Philip F. Hopkins
Figure caption: Collection of all of the synthetic dust SEDs, where the intensity of the color is proportional to the number of stacked SEDs. Blue dots represent observations in the Spitzer (3.5, 4.5, 5.8, 8.0, and 24 μm) and Herschel (250, 350, and 500 μm) bands within MonR2.
Paper: Searching for Novel Chemistry in Exoplanetary Atmospheres Using Machine Learning for Anomaly Detection
Authors: Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu
Figure caption: The same as Figure 1, but for the planet temperature T (top right panel) and the log-mixing ratios ﹩\mathrm{log}({X}_{i})﹩, i ∈ {CH4, NH3, H2O, CO2, CO}.
Paper: Searching for Novel Chemistry in Exoplanetary Atmospheres Using Machine Learning for Anomaly Detection
Authors: Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu
Figure caption: Distributions of selected stellar and planet physical parameters over the ABC data set. Blue histograms represent the entire population in the ABC data set, while orange histograms show the effect of the preselection cut discussed in Section 2.2.
Paper: Searching for Novel Chemistry in Exoplanetary Atmospheres Using Machine Learning for Anomaly Detection
Authors: Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu
Figure caption: Scatterplot of all entries in the ABC database, vs. the mean transit depth (x-axis) and the feature height (y-axis). Points are color coded by the value of the noise floor σ that would result in S/N = 7. The horizontal lines mark the cutoff values for σ = 10 ppm (dotted–dashed), σ = 20 ppm (dashed), σ = 30 ppm (dotted), and σ = 50 ppm (loosely dotted).
Paper: Searching for Novel Chemistry in Exoplanetary Atmospheres Using Machine Learning for Anomaly Detection
Authors: Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu
Figure caption: Illustration of the impact of the instrumental noise on an ideal TauRex3 spectrum (solid lines). The left panel shows a typical planet in the modified database (feature height equal to the median value of 6.3 × 10−4), while the right panel shows the planet closest to the selection cut (feature height equal to 2.100005 × 10−4). The dotted–dashed, dashed, and dotted lines show the effect of including instrumental noise at the level of 10 ppm, 20 ppm, and 30 ppm, respectively.
Paper: Searching for Novel Chemistry in Exoplanetary Atmospheres Using Machine Learning for Anomaly Detection
Authors: Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu
Figure caption: Distributions of the relative concentrations r  i , i ∈ {CH4, NH3, H2O, CO2, CO}, over the restricted ABC data set. In each experiment, spectra with relative concentrations to the left of the dashed line are considered normal, spectra to the right of the dotted line are considered anomalous, while spectra that fall between the two lines are not considered in that particular experiment, but may still appear as normal or anomalous in one of the other experiments.
Paper: Searching for Novel Chemistry in Exoplanetary Atmospheres Using Machine Learning for Anomaly Detection
Authors: Roy T. Forestano, Konstantin T. Matchev, Katia Matcheva, Eyup B. Unlu
Figure caption: Scatterplots of the normal instances (blue points on the left) and the anomalous instances (orange points on the right) in the plane of the corresponding log-mixing ratio ﹩\mathrm{log}({X}_{i})﹩ vs. temperature T, for each of the four experiments discussed in the text.