adsabs/AstroCLIMB huggingface dataset:
Paper: Quantifying Poynting Flux in the Quiet Sun Photosphere
Authors: Dennis Tilipman, Maria Kazachenko, Benoit Tremblay, Ivan Milić, Valentin Martínez Pillet, Matthias Rempel
Figure caption: Left panels, (a)–(d): IMaX Stokes vector maps at t = 1430 s. Right panels, (e)–(h): IMaX magnetogram and LOS velocity map derived using Milne–Eddington inversions. For the LOS velocity, a correction is applied to account for the systematic bias introduced by the IMaX Fabry–Perot sensor. The bias scales as a function of distance from the FOV center. The green square in the four right panels (e)–(h) outlines the region of interest (ROI), which contains the strongest magnetic field concentration. A close-up view of the ROI is shown in Figure 4. See Section 3.1.1 for a detailed discussion. The full FOV is 836 × 836 pixels, the ROI is 100 × 100 pixels, and each pixel is 48 km across.
Paper: Quantifying Poynting Flux in the Quiet Sun Photosphere
Authors: Dennis Tilipman, Maria Kazachenko, Benoit Tremblay, Ivan Milić, Valentin Martínez Pillet, Matthias Rempel
Figure caption: Outputs of a MURaM simulation at the geometrical surface z = 0, which corresponds to optical depth ﹩\overline{\tau }=1.1﹩, averaged over the FOV. The top right panel is a blowup of the red square in the top center panel. Arrows represent the orientation of transverse magnetic fields. The vertical and horizontal Poynting fluxes S  z  and S  h  are computed using the ideal MHD method (for details, see Section 3).
Paper: Interstellar Carbonaceous Dust Erosion Induced by X-Ray Irradiation of Water Ice in Star-forming Regions
Authors: K.-J. Chuang, C. Jäger, N.-E. Sie, C.-H. Huang, C.-Y. Lee, Y.-Y. Hsu, Th. Henning, Y.-J. Chen
Figure caption: Abundance evolution of the product 12CO2 (upper) and 13CO2 (bottom) obtained from the X-ray irradiation of H2O ice on the same a-13C dust over an X-ray photons fluence of (7.6–8.0) ×1018 photon cm−2 (i.e., (7.0–7.4) ×1020 eV cm−2). The dashed line indicates the photon fluence of ∼5 × 1017 photon cm−2. The solid lines are only present as guidance.
Paper: Interstellar Carbonaceous Dust Erosion Induced by X-Ray Irradiation of Water Ice in Star-forming Regions
Authors: K.-J. Chuang, C. Jäger, N.-E. Sie, C.-H. Huang, C.-Y. Lee, Y.-Y. Hsu, Th. Henning, Y.-J. Chen
Figure caption: The X-ray photon flux and H2O transmittance as a function of photon energy.
Paper: Interstellar Carbonaceous Dust Erosion Induced by X-Ray Irradiation of Water Ice in Star-forming Regions
Authors: K.-J. Chuang, C. Jäger, N.-E. Sie, C.-H. Huang, C.-Y. Lee, Y.-Y. Hsu, Th. Henning, Y.-J. Chen
Figure caption: CASINO simulation for the energy deposition distribution (left panel) and accumulated deposited energy distribution (right panel) for electron energies of 200, 400, 600, 800, and 1000 eV as a function of penetration depth. The applied H2O density is 0.87 g cm−3; 1 nm = 2.91 ML.
Paper: Interstellar Carbonaceous Dust Erosion Induced by X-Ray Irradiation of Water Ice in Star-forming Regions
Authors: K.-J. Chuang, C. Jäger, N.-E. Sie, C.-H. Huang, C.-Y. Lee, Y.-Y. Hsu, Th. Henning, Y.-J. Chen
Figure caption: Scanning electron microscope images of the original carbon material (left) and after ice deposition and subsequent irradiation with X-rays (right). The original thickness of a-13C dust is ∼300 nm. Left: the carbon grains are 3–5 nm in size and form fractal entities that finally produce a very porous, 3D layer. Right: the erosion of carbon is clearly visible by a strong flattening of the carbon structure.
Paper: Interstellar Carbonaceous Dust Erosion Induced by X-Ray Irradiation of Water Ice in Star-forming Regions
Authors: K.-J. Chuang, C. Jäger, N.-E. Sie, C.-H. Huang, C.-Y. Lee, Y.-Y. Hsu, Th. Henning, Y.-J. Chen
Figure caption: Abundance evolution of the products 13CO2 (left) and 13CO (right) obtained from the X-ray irradiation of O2 ice on two a-13C dust samples with a thickness of ∼100 and ∼300 nm over photon fluence of (7.6–7.9) ×1018 photon cm−2. The dashed lines show the total fitting results.
Paper: Interstellar Carbonaceous Dust Erosion Induced by X-Ray Irradiation of Water Ice in Star-forming Regions
Authors: K.-J. Chuang, C. Jäger, N.-E. Sie, C.-H. Huang, C.-Y. Lee, Y.-Y. Hsu, Th. Henning, Y.-J. Chen
Figure caption: IR spectra of a-13C obtained after deposition and exposure to air. The spectra are offset for clarity.
Paper: Carbon Stars as Standard Candles: An Empirical Test for the Reddening, Metallicity, and Age Sensitivity of the J-region Asymptotic Giant Branch (JAGB) Method
Authors: Abigail J. Lee
Figure caption: Location of the 12 regions superimposed on the Draine et al. (2014) emission-based reddening map of M31, which is discussed in Section 3.2. The 12 regions cover approximately 13 to 18 kpc of M31's northeast outer disk. The 12 regions were explicitly chosen to cover the most extreme range of reddening possible.
Paper: Carbon Stars as Standard Candles: An Empirical Test for the Reddening, Metallicity, and Age Sensitivity of the J-region Asymptotic Giant Branch (JAGB) Method
Authors: Abigail J. Lee
Figure caption: UKIRT/WFCam color–magnitude diagram for stars in M31's outer disk at 18 < d < 40 kpc. The JAGB stars are located in the color range 1.5 < (J − K) < 2.0 mag between the dotted lines. The smoothed LF in black is plotted over the binned LF in gray in the right panel, with the modal magnitude denoted by the dotted black line. The smoothing parameter was chosen to be σ  s  = 0.38 mag for visualization purposes; the choice of smoothing parameter varied the JAGB apparent magnitude by at most ±0.02 mag.
Paper: Carbon Stars as Standard Candles: An Empirical Test for the Reddening, Metallicity, and Age Sensitivity of the J-region Asymptotic Giant Branch (JAGB) Method
Authors: Abigail J. Lee
Figure caption: Mode, skewness (medcouple), and median absolute deviation σ parameters versus N AGB/N RGB, a proxy for the average AGB star age in a region. The Spearman’s rank correlation coefficient and corresponding p-value are displayed in the bottom lefthand corner of each plot. Error bars were derived from 10,000 bootstrapped realizations. We show results for the reddening-uncorrected photometry on the top panels and the corrected photometry on the bottom panels.
Paper: Carbon Stars as Standard Candles: An Empirical Test for the Reddening, Metallicity, and Age Sensitivity of the J-region Asymptotic Giant Branch (JAGB) Method
Authors: Abigail J. Lee
Figure caption: Mode, skewness (medcouple), and median absolute deviation σ parameters versus metallicities derived from Gregersen et al. (2015). The Spearman’s rank correlation coefficient and corresponding p-value are displayed in the bottom lefthand corner of each plot. Error bars were derived from 10,000 bootstrapped realizations. We show results for the reddening-uncorrected photometry on the top panels and the corrected photometry on the bottom panels.
Paper: Carbon Stars as Standard Candles: An Empirical Test for the Reddening, Metallicity, and Age Sensitivity of the J-region Asymptotic Giant Branch (JAGB) Method
Authors: Abigail J. Lee
Figure caption: Map of our average AGB star population age proxy N AGB/N RGB in a given region. This ratio is expected to be lower in populations with a higher fraction of old stars (and thus an average older age) because TP-AGB stars have shorter lifetimes than RGB stars. For example, the darker purple areas represent older stellar populations with more relative numbers of RGB stars, where the most massive stars have already evolved through the AGB phase.
Paper: Carbon Stars as Standard Candles: An Empirical Test for the Reddening, Metallicity, and Age Sensitivity of the J-region Asymptotic Giant Branch (JAGB) Method
Authors: Abigail J. Lee
Figure caption: F110W versus (F814W−F110W) color–magnitude diagrams and smoothed luminosity functions for the 12 regions. The black dotted line marks the mode for the least reddened region 7. The locations of the 12 regions are visually displayed in Figure 4.
Paper: Carbon Stars as Standard Candles: An Empirical Test for the Reddening, Metallicity, and Age Sensitivity of the J-region Asymptotic Giant Branch (JAGB) Method
Authors: Abigail J. Lee
Figure caption: Mode, skewness (medcouple), and median absolute deviation σ parameters versus line-of-sight reddening derived from Draine et al. (2014). The Spearman’s rank correlation coefficient and corresponding p-value are displayed in the bottom lefthand corner of each plot. Error bars were derived from 10,000 bootstrapped realizations.
Paper: Carbon Stars as Standard Candles: An Empirical Test for the Reddening, Metallicity, and Age Sensitivity of the J-region Asymptotic Giant Branch (JAGB) Method
Authors: Abigail J. Lee
Figure caption: Photometric uncertainty as a function of J- and K-band magnitudes. Quality cuts are shown in red, with the sources passing the given restriction in black and the sources not passing the restriction in gray.
Paper: Carbon Stars as Standard Candles: An Empirical Test for the Reddening, Metallicity, and Age Sensitivity of the J-region Asymptotic Giant Branch (JAGB) Method
Authors: Abigail J. Lee
Figure caption: Map of the Gregersen et al. (2015) metallicities.
Paper: Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models
Authors: M. M. Fausnaugh, P. J. Vallely, M. A. Tucker, C. S. Kochanek, B. J. Shappee, K. Z. Stanek, George R. Ricker, Roland Vanderspek, Manan Agarwal, Tansu Daylan, Rahul Jayaraman, Rebekah Hounsell, Daniel Muthukrishna
Figure caption: An example of our background trimming procedure from Appendix A.1. A low background FFI is shown in the top panels, and an FFI with bright scattered light is shown in the bottom panels. The leftmost column shows the original FFIs. The second column shows the difference images. ISIS fits and subtracts a 2D polynomial to remove the global background during difference imaging, which leaves behind high-frequency background variations in the bottom row. The 4 x 4 “grid effect” in the bottom row is caused by the 16 subimages used in the difference imaging (see Appendix A). The background correction is not forced to be continuous across subimages. The position of SN2020tld is shown with the blue dot, and the third column shows a 23 × 23 pixel zoom-in of the difference image around SN2020tld. The red dots show the annulus in which we calculate a local background correction in the difference image. The rightmost column shows the SN light curve (top) and local background estimates from the annulus (bottom), with vertical dashed lines marking the epochs of the two FFIs (“FIN” stands for “FFI index number”). The gradient across the SN background causes large systematic errors in FIN 127712, and we removed epochs such as these from the light curves with three rounds of 5σ clipping on the local background (the red light curve in the bottom-right panel). The shaded regions show the time windows removed by this procedure.
Paper: Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models
Authors: M. M. Fausnaugh, P. J. Vallely, M. A. Tucker, C. S. Kochanek, B. J. Shappee, K. Z. Stanek, George R. Ricker, Roland Vanderspek, Manan Agarwal, Tansu Daylan, Rahul Jayaraman, Rebekah Hounsell, Daniel Muthukrishna
Figure caption: An example of our “background correction” procedure described in Appendix A.1. The left column shows a 33 × 33 pixel zoom-in around SN2020jjh in the reference image of Sector 25 (top) and a model of the PSF used for photometry (bottom). The position of SN2020jjh is marked by the blue dot. The second column shows an FFI difference image with a low background (top) and the same image after filtering with a 100 pixel median along rows and columns (bottom). The red dots show the annulus in which we calculated a local background correction. The images in the third column are the same as for the second column, but for an FFI difference image with a high background level. The fourth column shows the light curve for PSF photometry at the location of the SN in the FFI difference images (top panel) and filtered images (bottom panel). After removing the SN and star residuals in the difference images with the median filter, the blue light curve measures residual errors in the photometric aperture. The cyan line shows a smoothed version of the blue light curve (to reduce statistical noise). We refer to this smoothed light curve as the “background model,” which, in some cases, identifies residual systematic errors in our light curves. In the right column, the top panel shows the original SN light curve with the background model light curve (the gray and cyan data are identical to the data in the fourth column). The bottom-right panel shows the original SN light curve minus the “background model” light curve (gray points minus cyan line), which better captures the shape of SN2020jjh around peak.
Paper: Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models
Authors: M. M. Fausnaugh, P. J. Vallely, M. A. Tucker, C. S. Kochanek, B. J. Shappee, K. Z. Stanek, George R. Ricker, Roland Vanderspek, Manan Agarwal, Tansu Daylan, Rahul Jayaraman, Rebekah Hounsell, Daniel Muthukrishna
Figure caption: Light-curve noise metric rmsGauss/rmsobserved as a function of the Bayes factor K and the differences in Bayesian information criterion (ΔBIC). Larger values of K or ΔBIC indicate a preference for adding a companion interaction model to the curved power-law model, while smaller values disfavor the addition of a companion interaction. The vertical dashed lines show ﹩| \mathrm{ln}K| \gt 3.4﹩ and ∣ΔBIC∣ > 10. Between these lines, the data cannot clearly distinguish between the two models. The noise metric quantifies the departure of the light curve from random Gaussian noise, with values near 1 approaching Gaussian statistics (see Section 4). The horizontal dashed lines show a break in the distribution at rmsGauss/rmsobserved = 0.36, which we use as a threshold for reporting candidates that favor or disfavor companion interactions. The bottom two panels are the same as the top panels, but with a restricted range on the horizontal axis to better visualize the data near zero. SN2020tld and SN2022eyw robustly disfavor the addition of companion interaction models. On the other hand, SN2020abqu, SN2021ahmz, and SN2022ajw show a weak preference for companion interactions based on the Bayes factor (SN2022ajw is just below the threshold with ﹩\mathrm{ln}K=3.01﹩). However, the preference for a companion interaction model is not robust when using ΔBIC. See Section 4.2 for details.
Paper: Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models
Authors: M. M. Fausnaugh, P. J. Vallely, M. A. Tucker, C. S. Kochanek, B. J. Shappee, K. Z. Stanek, George R. Ricker, Roland Vanderspek, Manan Agarwal, Tansu Daylan, Rahul Jayaraman, Rebekah Hounsell, Daniel Muthukrishna
Figure caption: Kernel density estimates (KDE) of the underlying distribution of power-law index β 1 and rise time t rise = (t peak − t 0)/(1 + z) for the subsamples shown in Figure 4. For the KDE, we used a Gaussian kernel and bandwidth of 0.63, and the data were weighted by the inverse square of the uncertainties in Table 3. The estimates of the underlying distributions from various subsets are consistent with each other. For β 1, the distribution is well characterized by a Gaussian with mean 2.29 and width 0.34, and a long tail that extends below 1.0. For t rise, the distribution is well characterized by a Gaussian with mean 15.89 days and width 3.82 days.
Paper: Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models
Authors: M. M. Fausnaugh, P. J. Vallely, M. A. Tucker, C. S. Kochanek, B. J. Shappee, K. Z. Stanek, George R. Ricker, Roland Vanderspek, Manan Agarwal, Tansu Daylan, Rahul Jayaraman, Rebekah Hounsell, Daniel Muthukrishna
Figure caption: Simulations that quantify the effect of cadence and signal-to-noise ratio on fitted parameters for typical ground-based light-curve properties. The left panels show simulated light curves with 30 minutes sampling and Gaussian noise with σ equal to 10% of peak flux. The input model is shown in the top panel, and has a time of first light t 0 = 0.0, power-law index β 1 = 2.0, power-law index β 2 = − 0.015, corresponding to a rise time t rise = 17.25 days. In the lower panels, the light curve is binned to 0.33, 1.0, 1.5, 3.0, and 5.3 days (cyan points), and assigned a 10% uncertainty relative to peak. The maximum likelihood models from dynesty are shown with red lines, and the recovered value of t 0 is shown with the vertical dashed red lines. The right panel shows the recovered values of power-law index β 1 as a function of the recovered time of first light t 0, with the true values of the input model shown by dashed black lines. There is a bias in the recovered parameters as the cadence decreases and the uncertainty on the measurements at early times increases.
Paper: Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models
Authors: M. M. Fausnaugh, P. J. Vallely, M. A. Tucker, C. S. Kochanek, B. J. Shappee, K. Z. Stanek, George R. Ricker, Roland Vanderspek, Manan Agarwal, Tansu Daylan, Rahul Jayaraman, Rebekah Hounsell, Daniel Muthukrishna
Figure caption: Cumulative number of SNe as a function of 3σ companion limit. The horizontal dashed lines show the probability that a given number of SNe were all observed at viewing angles greater than 45° and would not show a significant companion interaction signature. The intersection of these lines and the cumulative distribution therefore represents upper limits on typical type Ia SN companion stars. The “No First Light” sample requires extrapolation to the time of first light and so introduces ambiguity into the fits for the companion interaction models. The “High Quality” sample has a noise metric rmsGauss/rmsobserved within a factor of 2 of Gaussian statistics and constitutes a more homogeneous data set, although there are only 10 objects with high enough signal-to-noise to yield unbiased fits (see Section 4).
Paper: Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models
Authors: M. M. Fausnaugh, P. J. Vallely, M. A. Tucker, C. S. Kochanek, B. J. Shappee, K. Z. Stanek, George R. Ricker, Roland Vanderspek, Manan Agarwal, Tansu Daylan, Rahul Jayaraman, Rebekah Hounsell, Daniel Muthukrishna
Figure caption: Constraints on the fraction F of type Ia SNe with companion stars, as a function of companion star Roche lobe radius/orbital separation. Three scenarios are shown. The black line shows the case where the candidate companion interactions from Section 4.2 are considered detections. The red line shows the case where the candidates are false positives, due to TESS systematic errors or physical processes such as 56Ni mixing. The blue line shows a hypothetical case in which we add five additional companion signature detections below 10 R ⊙ (the geometric 2σ limit from Figure 8), to demonstrate the sensitivity of the inferred value of F on the number of detections. The solid lines show the median values of F calculated from a binomial distribution and the shaded regions show the 95% confidence intervals.
Paper: Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models
Authors: M. M. Fausnaugh, P. J. Vallely, M. A. Tucker, C. S. Kochanek, B. J. Shappee, K. Z. Stanek, George R. Ricker, Roland Vanderspek, Manan Agarwal, Tansu Daylan, Rahul Jayaraman, Rebekah Hounsell, Daniel Muthukrishna
Figure caption: Correlations of power-law indices β 1 and β 2, rise time t rise, and absolute magnitude M  T . We only show the 74 SNe in the “High Dynamic Range” sample, and we only show values of t rise for the 46 SNe that TESS observed the peak (see Section 2.1 and Appendix C). We do not find any significant correlations. The solid line shows the analytic relationship between β 2 and t rise (see Section 4.1).
Paper: CLASS Data Pipeline and Maps for 40 GHz Observations through 2022
Authors: Yunyang Li, 云炀 李, Joseph R. Eimer, Keisuke Osumi, John W. Appel, Michael K. Brewer, Aamir Ali, Charles L. Bennett, Sarah Marie Bruno, Ricardo Bustos, David T. Chuss, Joseph Cleary, Jullianna Denes Couto, Sumit Dahal, Rahul Datta, Kevin L. Denis, Rolando Dünner, Francisco Espinoza, Thomas Essinger-Hileman, Pedro Fluxá Rojas, Kathleen Harrington, Jeffrey Iuliano, John Karakla, Tobias A. Marriage, Nathan J. Miller, Sasha Novack, Carolina Núñez, Matthew A. Petroff, Rodrigo A. Reeves, Karwan Rostem, Rui Shi, 瑞 时, Deniz A. N. Valle, Duncan J. Watts, Janet L. Weiland, Edward J. Wollack, Zhilei Xu, 智磊 徐, Lingzhen Zeng
Figure caption: CLASS 40 GHz focal plane layout and the VPM wire grid angle ϕ  P  as seen by each detector. Each circle represents a pair of orthogonal detectors and is plotted by its pointing offsets on the sky. The orientation of the line within each circle denotes the VPM wire direction as seen by that detector, ϕ  P ( × 10), from the geometric modeling; the polarization sensitivity is 45° from the wire direction. ϕ  P  varies by 1.6° across the focal plane. The detectors on the bottom of the plot (shown in green) see the main polarization calibrator Tau A at the nominal 45° elevation, scan at all boresight rotations; the blue detector pairs on either side only have partial Tau A coverage depending on the boresight rotation angle, and the unfilled pairs have no Tau A coverage.
Paper: CLASS Data Pipeline and Maps for 40 GHz Observations through 2022
Authors: Yunyang Li, 云炀 李, Joseph R. Eimer, Keisuke Osumi, John W. Appel, Michael K. Brewer, Aamir Ali, Charles L. Bennett, Sarah Marie Bruno, Ricardo Bustos, David T. Chuss, Joseph Cleary, Jullianna Denes Couto, Sumit Dahal, Rahul Datta, Kevin L. Denis, Rolando Dünner, Francisco Espinoza, Thomas Essinger-Hileman, Pedro Fluxá Rojas, Kathleen Harrington, Jeffrey Iuliano, John Karakla, Tobias A. Marriage, Nathan J. Miller, Sasha Novack, Carolina Núñez, Matthew A. Petroff, Rodrigo A. Reeves, Karwan Rostem, Rui Shi, 瑞 时, Deniz A. N. Valle, Duncan J. Watts, Janet L. Weiland, Edward J. Wollack, Zhilei Xu, 智磊 徐, Lingzhen Zeng
Figure caption: CLASS daily observation efficiencies from 2016 August 31 to 2022 May 19. The gray region is the total detector time recorded when the VPM is working; the yellow region shows the amount of data initially selected at the DataPkg level (Section 3.1), and the green region shows the fraction after the TOD-level selection that is used for mapping (Section 3.2). The time spans for Era 1 and Era 2 are shown in orange at the top; three periods with different VPM grids are shown in blue. The gray hatched regions indicate times when different parts of the forebaffle are blackened. Critical changes to the instrument configuration are marked by the vertical bars, with the text pointing at the direction where the annotation applies. The closeout was first taken off on 2021 September 27 but was occasionally reinstalled to guard against bad weather.