adsabs/AstroCLIMB huggingface dataset:
Paper: A Low-mass Pre-main-sequence Eclipsing Binary in Lower Centaurus Crux Discovered with TESS
Authors: Keivan G. Stassun, Guillermo Torres, Marina Kounkel, Dax L. Feliz, Luke G. Bouma, Steve B. Howell, Crystal L. Gnilka, E. Furlan
Figure caption: Strength of Hα emission as a function of orbital phase for the primary (black symbols) and secondary (red symbols) eclipsing stars. Equivalent width (EW) variations (top) do not exhibit periodic or other clear behavior with orbital phase. Full-width (FW) at 10% intensity variations (middle) of the secondary do exhibit statistically significant periodic behavior, represented by a best-fit sinusoid (red dashed curve); a best-fit sinusoid for the primary (black dashed curve) is also shown for comparison. Bottom: same as middle, except curves represent theoretical predictions from the simulations of Artymowicz & Lubow (1996) for the relative accretion rate of circumbinary disk material onto the two stars. The vertical scale for the model curves is arbitrary but the curves have been normalized to preserve the relative accretion rate changes in the model. The black curve representing the model accretion variations for the primary has been shifted by 0.5 phase relative to that for the secondary (red) to simulate the effect of seeing only one longitudinal hemisphere (or “side”) of each star at each orbital quadrature; see the text.
Paper: A Low-mass Pre-main-sequence Eclipsing Binary in Lower Centaurus Crux Discovered with TESS
Authors: Keivan G. Stassun, Guillermo Torres, Marina Kounkel, Dax L. Feliz, Luke G. Bouma, Steve B. Howell, Crystal L. Gnilka, E. Furlan
Figure caption: Schematic top-down representation of accretion onto the eclipsing stars in 2M1222−57 via streams crossing the inner hole in the circumbinary disk. Small circles representing the two stars are to scale relative to their separation. The size of the cavity relative to the orbital semimajor axis is also to scale, inspired by the simulations of Artymowicz & Lubow (1996). Insets represent the accretion footpoints on the two stars as seen by the observer at the two quadrature phases (taken from the modeling of Espaillat et al. 2021 for the accretion footpoints observed in the young star GM Aur). The observer is in the direction of the bottom of the sketch.
Paper: A Low-mass Pre-main-sequence Eclipsing Binary in Lower Centaurus Crux Discovered with TESS
Authors: Keivan G. Stassun, Guillermo Torres, Marina Kounkel, Dax L. Feliz, Luke G. Bouma, Steve B. Howell, Crystal L. Gnilka, E. Furlan
Figure caption: Comparison of Li abundances measured for the primary (left) and secondary (right) eclipsing stars in the 2M1222−57 system vs. PMS evolutionary model predictions as a function of age; the adopted age of 2M1222−57 is represented by the vertical swath. Measured abundances are represented as horizontal swaths for both LTE and NLTE cases (see Section 3.3). Evolutionary tracks for standard PMS models (dashed curves; Baraffe et al. 2015) predict significantly more Li depletion than observed, by ≳2 dex, whereas magnetic PMS models (solid curves; Feiden 2016) are able to much more nearly match the measured values. It is possible to match the Li abundances even better by adjusting the magnetic models with additional parameters, such as with different field strengths for the two stars, represented here by the SPOTS models (Somers et al. 2020) with spot coverage fractions of 24% and 28% for the primary and secondary, respectively (long-dashed green curves).
Paper: A Low-mass Pre-main-sequence Eclipsing Binary in Lower Centaurus Crux Discovered with TESS
Authors: Keivan G. Stassun, Guillermo Torres, Marina Kounkel, Dax L. Feliz, Luke G. Bouma, Steve B. Howell, Crystal L. Gnilka, E. Furlan
Figure caption: Same as Figure 13 (and on the same scale), now comparing the properties of 2M1222−57 before (open symbols) and after (solid symbols) applying the chromospheric activity corrections of Stassun et al. (2012) to the measured temperatures and radii. Now both the radii and temperatures of the two components are well matched by standard theory at an age of ≈17 Myr, the same age suggested by the magnetic models (Figure 14). For clarity, the temperatures and radii represented by the solid symbols are not the “true” values; rather, these are what the temperatures and radii would be if the stars were not magnetically active.
Paper: A Low-mass Pre-main-sequence Eclipsing Binary in Lower Centaurus Crux Discovered with TESS
Authors: Keivan G. Stassun, Guillermo Torres, Marina Kounkel, Dax L. Feliz, Luke G. Bouma, Steve B. Howell, Crystal L. Gnilka, E. Furlan
Figure caption: Variability residuals in the TESS light-curve data in Sectors 10–11 (top) and Sectors 37–38 (bottom).
Paper: Deblending Galaxies with Generative Adversarial Networks
Authors: Shoubaneh Hemmati, Eric Huff, Hooshang Nayyeri, Agnès Ferté, Peter Melchior, Bahram Mobasher, Jason Rhodes, Abtin Shahidi, Harry Teplitz
Figure caption: Photometry of sources with and without the GAN’s deblended positions on the right and left panels respectively. Contours show 1σ and 2σ distributions and the dashed white line shows the 1:1 line. The bottom panels plot the magnitude difference between the input and measured photometry as a function of the input magnitude with the Gaussian process regression overplotted (see Section 2.2 of Williams & Rasmussen 2006 for detailed equations of GP regression). The darker orange shaded region corresponds to the predictive variance around the predictive mean assuming noise-free data. The brighter orange and green shaded regions correspond to two levels of noise variance from the data points added to the predictive variance. The inset plots show the variance of Δmagnitude plotted as a function of magnitude with exponential functions of the form ﹩y=a\times \exp ({bx})+c﹩ overplotted corresponding to the median (orange) and including 68% of the data points (green).
Paper: Deblending Galaxies with Generative Adversarial Networks
Authors: Shoubaneh Hemmati, Eric Huff, Hooshang Nayyeri, Agnès Ferté, Peter Melchior, Bahram Mobasher, Jason Rhodes, Abtin Shahidi, Harry Teplitz
Figure caption: Performance of a GAN in deblending as a function of distance and sizes of the two objects as well as their magnitude and redshift difference (respectively from left to right). Yellow, gray, and dark blue shaded regions correspond to the fractions in which two peaks are successfully found in the high-, GAN-, and low-resolution cutouts, respectively. The histograms on the bottom row show the numbers of simulated blends in each bin.
Paper: Deblending Galaxies with Generative Adversarial Networks
Authors: Shoubaneh Hemmati, Eric Huff, Hooshang Nayyeri, Agnès Ferté, Peter Melchior, Bahram Mobasher, Jason Rhodes, Abtin Shahidi, Harry Teplitz
Figure caption: A self-organizing map trained on the distance, flux ratio, ΣFWHM, and Δz of 5000 simulated blended samples. The 32 × 24 grids in the first row show how the four-dimensional parameter space projects onto two dimensions. The second row shows successful peaks found as a function of position on the two-dimensional parameter space in high-, low-, and GAN-resolution images (left to right). Yellow, gray, and dark blue respectively are where two peaks were found (deblend successful), one peak was found (blended), and where no object was detected.
Paper: Deblending Galaxies with Generative Adversarial Networks
Authors: Shoubaneh Hemmati, Eric Huff, Hooshang Nayyeri, Agnès Ferté, Peter Melchior, Bahram Mobasher, Jason Rhodes, Abtin Shahidi, Harry Teplitz
Figure caption: Peak finder on different resolutions of the simulated blend sample. The first (leftmost) and second columns are randomly drawn HST F775W cutouts of two galaxies moved to a random off-center position and orientation. The third column adds the first two to create the blended sample in high resolution. The downgraded image that is fed to the GAN is shown in the fourth column. The fifth column shows the GAN output improving the resolution of the downgraded image. Crosses on the first two columns correspond to main sources we want to detect. Red dots on the last three columns show peaks found in each cutout.
Paper: Deblending Galaxies with Generative Adversarial Networks
Authors: Shoubaneh Hemmati, Eric Huff, Hooshang Nayyeri, Agnès Ferté, Peter Melchior, Bahram Mobasher, Jason Rhodes, Abtin Shahidi, Harry Teplitz
Figure caption: Five examples of a GAN improving the resolution of cutouts from Subaru HSC resolution to HST. The first (leftmost) column shows high-resolution HST F775W cutouts. The downgraded image to Subaru HSC resolution and pixel scale, which is fed to the GAN, is shown in the second column. The third column shows the GAN output improving the resolution of the downgraded image. The difference between the first and third columns is shown in the fourth column.
Paper: Deblending Galaxies with Generative Adversarial Networks
Authors: Shoubaneh Hemmati, Eric Huff, Hooshang Nayyeri, Agnès Ferté, Peter Melchior, Bahram Mobasher, Jason Rhodes, Abtin Shahidi, Harry Teplitz
Figure caption: The architecture diagrams of the GAN frameworks used in this study. The figure legend shown in the top panel specifies the symbols used in the convolution, normalization, and activation layers. The second panel corresponds to the vanilla GAN where the input to the generator is a noise vector. The third and fourth panels show the conditional GANs with single and multiple wave bands with the low-resolution and downgraded input images.
Paper: Deblending Galaxies with Generative Adversarial Networks
Authors: Shoubaneh Hemmati, Eric Huff, Hooshang Nayyeri, Agnès Ferté, Peter Melchior, Bahram Mobasher, Jason Rhodes, Abtin Shahidi, Harry Teplitz
Figure caption: GAN with a simple architecture and no input. We trained the network with 3000 sample cutouts in the HST ACS F775W centered on GOODS South galaxies. First and third rows are generated with the GAN and the second row shows examples from the training set.
Paper: Thermal Energy Budget of Electrons in the Inner Heliosphere: Parker Solar Probe Observations
Authors: Joel B. Abraham, Daniel Verscharen, Robert T. Wicks, Jeffersson A. Agudelo Rueda, Christopher J. Owen, Georgios Nicolaou, Seong-Yeop Jeong
Figure caption: Determination of the polytropic relationship of solar wind electrons. Blue dots show the total thermal electron pressure as a function of the total electron density in double-logarithmic space. The red line represents the best-fitted straight line given in the box in the bottom right-hand corner.
Paper: Black Hole Images as Tests of General Relativity: Effects of Plasma Physics
Authors: Feryal Özel, Dimitrios Psaltis, Ziri Younsi
Figure caption: Sample snapshots from a SANE GRMHD simulation of accretion around a black hole with spin a = 0.9, showing two transient events that generate ring-like structures that are disjoint from the black hole shadow (after Chan et al. 2015a). In both cases, the boundary of the shadow is displayed with a red curve. The left panel shows an Einstein ring generated when a very localized structure in the accretion flow crosses a caustic behind the black hole. The right panel shows a structure generated by an azimuthally stretched flux tube that has been lensed above and below the equatorial plane. Both structures, albeit plausible, are very short-lived and inconsistent with the inferred stability of the black hole image at the center of the M87 galaxy.
Paper: Black Hole Images as Tests of General Relativity: Effects of Plasma Physics
Authors: Feryal Özel, Dimitrios Psaltis, Ziri Younsi
Figure caption: Radial profile of the ion temperature for radiatively inefficient accretion flows around Kerr black holes, for different values of the model parameters. Here n  r  is the power-law index of the radial velocity profile and λ is the angular momentum eigenvalue of the solution. The ion temperature has been normalized by the factor in the square brackets in Equation (A13) in order to highlight the effects of relativity and the inner boundary conditions. The temperature in a radiatively inefficient flow increases inward because of the combined effects of “viscous” and compressional heating.
Paper: Searching for Extremely Blue UV Continuum Slopes at z = 7–11 in JWST/NIRCam Imaging: Implications for Stellar Metallicity and Ionizing Photon Escape in Early Galaxies
Authors: Michael W. Topping, Daniel P. Stark, Ryan Endsley, Adele Plat, Lily Whitler, Zuyi Chen, Stéphane Charlot
Figure caption: (a) Rest-UV continuum slope β as a function of age and metallicity measured from models constructed using BEAGLE. These models assume a constant SFH, solar abundance patterns, and ﹩\mathrm{log}(U)=-2.5﹩, and they contain no dust attenuation. Shown here are results from models of stellar light only (dashed lines) and those with self-consistently computed nebular continuum emission (solid lines). As described in Section 2, the addition of nebular emission reddens the UV continuum by δ β ∼ 0.6 at the youngest ages and lowest metallicities and has a decreasing effect toward older galaxies and higher metallicities. (b) Same as panel (a) except the UV slopes are calculated using models produced using Prospector. We note that while we display UV slopes of models with ages up to 1 Gyr for reference, this extends beyond the age of the universe at the redshifts considered in this study.
Paper: Effects of Supra-arcade Downflows Interacting with the Postflare Arcade
Authors: Arun Kumar Awasthi, Rui Liu, Tingyu Gou
Figure caption: EUV intensity oscillations exhibited by the postflare loop arcade generated due to the collision of void case #4 and case #5, presented in the top and bottom panels, respectively. (a)–(c) Sequence of running-difference images in the 94 Å observations showing the generation and expansion of intensity perturbations. (d) Intensity profiles in 94 Å as obtained by averaging the emission within two square regions 6″ wide, placed 10″ apart (shown in panel (c)). Intensity oscillation corresponding to the bottom region (blue) is delayed by 24 s (as determined from the lag analysis) from that obtained from the higher (red) region, thus revealing the propagation speed of oscillations along the loop to be 322.2 km s−1. The oscillation period is estimated to be 139.6 s, shown using a representative sinusoidal pattern plotted in gray. Similarly, the bottom panels show the sequence of running-difference images (e)–(g) as well as intensity profiles in 94 Å (h) corresponding to SAD case #5. Here the propagation speed of intensity oscillations is estimated to be 546.8 km s−1. The vertical green line marks respective times of the SAD’s collision with the top of the postflare loop arcade.
Paper: Effects of Supra-arcade Downflows Interacting with the Postflare Arcade
Authors: Arun Kumar Awasthi, Rui Liu, Tingyu Gou
Figure caption: Thermal characteristics of the SAD cases #3, 4, and 6 in the top, middle, and bottom panels, respectively. 131 Å images (a) and the running-difference image (b) have been utilized to identify the SAD’s location (shown by a yellow “+” symbol). (c) and (d) show EM[T] maps at 5–7 MK and 7–12 MK. (e) The evolution of EM[T] at 5–7 MK and 7–12 MK across the SAD (along the dotted horizontal line drawn in (a) and (b)). The vertical double-headed arrow in (e) represents the level of depression (R EM), and the estimated value is also annotated. Similarly, the middle and bottom panels show the thermal characteristics of the SAD cases #4 and 6, respectively.
Paper: Searching for Extremely Blue UV Continuum Slopes at z = 7–11 in JWST/NIRCam Imaging: Implications for Stellar Metallicity and Ionizing Photon Escape in Early Galaxies
Authors: Michael W. Topping, Daniel P. Stark, Ryan Endsley, Adele Plat, Lily Whitler, Zuyi Chen, Stéphane Charlot
Figure caption: Fraction of the total flux that is the nebular continuum as a function of rest wavelength. We show the results for models of 1, 10, and 100 Myr in panels (a), (b), and (c), respectively. In each panel, we display continuum fractions calculated for five different assumed metallicities. The nebular continuum is strongest at the youngest ages and lowest metallicities and decreases in strength toward older ages and higher metallicities.
Paper: Effects of Supra-arcade Downflows Interacting with the Postflare Arcade
Authors: Arun Kumar Awasthi, Rui Liu, Tingyu Gou
Figure caption: Emission at the ribbon location due to the SAD’s interaction with the postflare loop arcade. Images in 1700 Å (a) and 131 Å (b) with the regions corresponding to the upper (lower) ribbon marked in blue (red), over which the intensity profiles are derived. Time profiles of emission in 1700 Å (c) and 131 Å (d), averaged over the marked regions, from which a smoothed background of 20 minutes is subtracted, and normalized to the peak value. Grey shaded regions correspond to the duration of different cases of SAD’s propagation until submergence in the postflare loops in the 131 Å images.
Paper: Conditions for Proton Temperature Anisotropy to Drive Instabilities in the Solar Wind
Authors: Simon Opie, Daniel Verscharen, Christopher H. K. Chen, Christopher J. Owen, Philip A. Isenberg
Figure caption: Polar plots of the distributions of the four categories of data points as functions of θ  BV . The three panels show (a) all data (blue) with stable data (orange) overlaid, (b) oblique firehose unstable data (green), and (c) mirror-mode unstable data (magenta). Both (b) and (c) are normalized according to Equation (5). The gray concentric circles are spaced in increments of (a) 2500, (b) 0.02, and (c) 0.005, starting from zero. 0° is the direction of  V . The distributions are binned at 3° resolution.
Paper: Conditions for Proton Temperature Anisotropy to Drive Instabilities in the Solar Wind
Authors: Simon Opie, Daniel Verscharen, Christopher H. K. Chen, Christopher J. Owen, Philip A. Isenberg
Figure caption: We identify unstable intervals and calculate their persistence interval (Δ j ) by aggregating the length scales (δ  i ) of each measurement interval i in appropriate dimensionless units, where δ  i  = V  i  τ/ρ  pi , V  i  is the bulk velocity in interval i, ρ  pi  is the proton gyroradius in interval i, and τ is the interval duration (4 s). We also calculate δ  i  in units of inertial length (dpi ) where ρ  pi  is replaced by dpi . We label sets of consecutive unstable intervals with the number j and calculate their length Δ j  with Equations (3) and (4).
Paper: Conditions for Proton Temperature Anisotropy to Drive Instabilities in the Solar Wind
Authors: Simon Opie, Daniel Verscharen, Christopher H. K. Chen, Christopher J. Owen, Philip A. Isenberg
Figure caption: Data distribution in the T ⊥/T ∥–β ∥ plane. We overplot the instability thresholds according to Equation (1) for γ  m  = 10−2Ω p . The color-coding indicates the PDF of data points in each bin.
Paper: Conditions for Proton Temperature Anisotropy to Drive Instabilities in the Solar Wind
Authors: Simon Opie, Daniel Verscharen, Christopher H. K. Chen, Christopher J. Owen, Philip A. Isenberg
Figure caption: PDF of the angular distribution of our four data categories: all data (blue), stable (orange), oblique firehose unstable (green), mirror-mode unstable (magenta). The orange histogram is mostly obscured by the blue. The PDFs, calculated according to Equation (6), are binned at 5° resolution.
Paper: The JCMT BISTRO-2 Survey: Magnetic Fields of the Massive DR21 Filament
Authors: Tao-Chung Ching, Keping Qiu, Di Li, Zhiyuan Ren, Shih-Ping Lai, David Berry, Kate Pattle, Ray Furuya, Derek Ward-Thompson, Doug Johnstone, Patrick M. Koch, Chang Won Lee, Thiem Hoang, Tetsuo Hasegawa, Woojin Kwon, Pierre Bastien, Chakali Eswaraiah, Jia-Wei Wang, Kyoung Hee Kim, Jihye Hwang, Archana Soam, A-Ran Lyo, Junhao Liu, Valentin J. M. Le Gouellec, Doris Arzoumanian, Anthony Whitworth, James Di Francesco, Frédérick Poidevin, Tie Liu, Simon Coudé, Mehrnoosh Tahani, Hong-Li Liu, Takashi Onaka, Dalei Li, Motohide Tamura, Zhiwei Chen, Xindi Tang, Florian Kirchschlager, Tyler L. Bourke, Do-Young Byun, Mike Chen, Huei-Ru Vivien Chen, Wen Ping Chen, Jungyeon Cho, Yunhee Choi, Youngwoo Choi, Minho Choi, Antonio Chrysostomou, Eun Jung Chung, Y. Sophia Dai, Pham Ngoc Diep, Yasuo Doi, Yan Duan, Hao-Yuan Duan, David Eden, Lapo Fanciullo, Jason Fiege, Laura M. Fissel, Erica Franzmann, Per Friberg, Rachel Friesen, Gary Fuller, Tim Gledhill, Sarah Graves, Jane Greaves, Matt Griffin, Qilao Gu, Ilseung Han, Saeko Hayashi, Martin Houde, Charles L. H. Hull, Tsuyoshi Inoue, Shu-ichiro Inutsuka, Kazunari Iwasaki, Il-Gyo Jeong, Vera Könyves, Ji-hyun Kang, Miju Kang, Janik Karoly, Akimasa Kataoka, Koji Kawabata, Francisca Kemper, Jongsoo Kim, Mi-Ryang Kim, Shinyoung Kim, Hyosung Kim, Kee-Tae Kim, Gwanjeong Kim, Jason Kirk, Masato I. N. Kobayashi, Takayoshi Kusune, Jungmi Kwon, Kevin Lacaille, Chi-Yan Law, Sang-Sung Lee, Hyeseung Lee, Jeong-Eun Lee, Chin-Fei Lee, Yong-Hee Lee, Guangxing Li, Hua-bai Li, Sheng-Jun Lin, Sheng-Yuan Liu, Xing Lu, Steve Mairs, Masafumi Matsumura, Brenda Matthews, Gerald Moriarty-Schieven, Tetsuya Nagata, Fumitaka Nakamura, Hiroyuki Nakanishi, Nguyen Bich Ngoc, Nagayoshi Ohashi, Geumsook Park, Harriet Parsons, Nicolas Peretto, Felix Priestley, Tae-Soo Pyo, Lei Qian, Ramprasad Rao, Mark Rawlings, Jonathan Rawlings, Brendan Retter, John Richer, Andrew Rigby, Sarah Sadavoy, Hiro Saito, Giorgio Savini, Masumichi Seta, Yoshito Shimajiri, Hiroko Shinnaga, Ya-Wen Tang, Kohji Tomisaka, Le Ngoc Tram, Yusuke Tsukamoto, Serena Viti, Hongchi Wang, Jintai Wu, Jinjin Xie, Meng-Zhe Yang, Hsi-Wei Yen, Hyunju Yoo, Jinghua Yuan, Hyeong-Sik Yun, Tetsuya Zenko, Chuan-Peng Zhang, Yapeng Zhang, Guoyin Zhang, Jianjun Zhou, Lei Zhu, Ilse de Looze, Philippe André, C. Darren Dowell, Stewart Eyres, Sam Falle, Jean-François Robitaille, Sven van Loo
Figure caption: Planck 850 μm magnetic field segments overlaid on the τ 353 map toward the DR21 filament. The black segments represent the magnetic field orientations with a unified length. The red box at the center marks the area of Figure 1. At the bottom left corner, the red stripe represents the galactic disk plane, and the Planck 5′ beam is shown.