adsabs/AstroCLIMB huggingface dataset:
Paper: The Parallel Ionizing Emissivity Survey (PIE). I. Survey Design and Selection of Candidate Lyman Continuum Leakers at 3.1 < z < 3.5
Authors: Alexander Beckett, Marc Rafelski, Claudia Scarlata, Wanjia Hu, Keunho Kim, Ilias Goovaerts, Matthew A. Malkan, Wayne Webb, Harry Teplitz, Matthew Hayes, Vihang Mehta, Anahita Alavi, Andrew J. Bunker, Annalisa Citro, Nimish Hathi, Alaina Henry, Alexandra Le Reste, Alessia Moretti, Michael J. Rutkowski, Maxime Trebitsch, Anita Zanella
Figure caption: The filters used in this work. The primary PIE survey covers LyC emission in F336W, and measures optical colors using F625W and F814W for 37 fields. PIE+ adds F475W for 18 of these fields, which helps constrain the redshift. We show an illustrative spectrum with the Lyman break and Lyα emission clearly visible.
Paper: The Parallel Ionizing Emissivity Survey (PIE). I. Survey Design and Selection of Candidate Lyman Continuum Leakers at 3.1 < z < 3.5
Authors: Alexander Beckett, Marc Rafelski, Claudia Scarlata, Wanjia Hu, Keunho Kim, Ilias Goovaerts, Matthew A. Malkan, Wayne Webb, Harry Teplitz, Matthew Hayes, Vihang Mehta, Anahita Alavi, Andrew J. Bunker, Annalisa Citro, Nimish Hathi, Alaina Henry, Alexandra Le Reste, Alessia Moretti, Michael J. Rutkowski, Maxime Trebitsch, Anita Zanella
Figure caption: Detection completeness of our sample, estimated using the fraction of mock sources that are detected at the 3σ level when searching the implanted images. Vertical lines indicate the magnitude at which we achieve ≈50% completeness in F625W.
Paper: The Parallel Ionizing Emissivity Survey (PIE). I. Survey Design and Selection of Candidate Lyman Continuum Leakers at 3.1 < z < 3.5
Authors: Alexander Beckett, Marc Rafelski, Claudia Scarlata, Wanjia Hu, Keunho Kim, Ilias Goovaerts, Matthew A. Malkan, Wayne Webb, Harry Teplitz, Matthew Hayes, Vihang Mehta, Anahita Alavi, Andrew J. Bunker, Annalisa Citro, Nimish Hathi, Alaina Henry, Alexandra Le Reste, Alessia Moretti, Michael J. Rutkowski, Maxime Trebitsch, Anita Zanella
Figure caption: Comparison of the mock galaxy sizes (left panel) and Sérsic indices (right panel) with catalogs measured from the COSMOS field. Note that the PIE images have a different pixel scale than the COSMOS images, so here our mock sizes are scaled to match.
Paper: The Parallel Ionizing Emissivity Survey (PIE). I. Survey Design and Selection of Candidate Lyman Continuum Leakers at 3.1 < z < 3.5
Authors: Alexander Beckett, Marc Rafelski, Claudia Scarlata, Wanjia Hu, Keunho Kim, Ilias Goovaerts, Matthew A. Malkan, Wayne Webb, Harry Teplitz, Matthew Hayes, Vihang Mehta, Anahita Alavi, Andrew J. Bunker, Annalisa Citro, Nimish Hathi, Alaina Henry, Alexandra Le Reste, Alessia Moretti, Michael J. Rutkowski, Maxime Trebitsch, Anita Zanella
Figure caption: Color selection using the JAGUAR and PIE mock data described in Section 4. Top panels: color selection based on F336W, F625W, and F814W data, which will be used for fields for which only these filters are available. Bottom panels: additional selection criteria that will be used to find 3.1 < z < 3.5 galaxies for fields with F475W PIE+ data in addition to the three PIE filters. In the top panels, red points are galaxies at 2.7 < z < 4, whereas in the bottom panels, these are galaxies at 3.1 < z < 3.5. In both cases, blue crosses are galaxies that would be selected using the color cuts shown by the green lines and given in the text, but are outside this redshift range. Galaxies that would be selected using our three-filter cuts but are removed by the additional cuts are shown in green in the lower panels. Other galaxies, lying outside the target redshift range and outside our selection window, are shown in black points, with crosses denoting those that lie inside the PIE+ cuts but were already rejected using the PIE 3-band cuts.
Paper: The Parallel Ionizing Emissivity Survey (PIE). I. Survey Design and Selection of Candidate Lyman Continuum Leakers at 3.1 < z < 3.5
Authors: Alexander Beckett, Marc Rafelski, Claudia Scarlata, Wanjia Hu, Keunho Kim, Ilias Goovaerts, Matthew A. Malkan, Wayne Webb, Harry Teplitz, Matthew Hayes, Vihang Mehta, Anahita Alavi, Andrew J. Bunker, Annalisa Citro, Nimish Hathi, Alaina Henry, Alexandra Le Reste, Alessia Moretti, Michael J. Rutkowski, Maxime Trebitsch, Anita Zanella
Figure caption: The effect of adding LyC emission to our mock galaxies as described in Section 6.2. Left panel: the color selection using the three PIE filters, as in the top row of Figure 8. Right panel: the color selection utilizing the F475W PIE+ data, as shown in the bottom row of Figure 8. We show JAGUAR galaxies that lie at 3.1 < z < 3.5, with F336W flux added corresponding to different values of Robs, denoted by the different colors. Points show galaxies that would be detected in F336W, while crosses show points for which only upper limits would be measured. Points lying outside the region bounded by the green line would not be selected for spectroscopic follow-up.
Paper: The Parallel Ionizing Emissivity Survey (PIE). I. Survey Design and Selection of Candidate Lyman Continuum Leakers at 3.1 < z < 3.5
Authors: Alexander Beckett, Marc Rafelski, Claudia Scarlata, Wanjia Hu, Keunho Kim, Ilias Goovaerts, Matthew A. Malkan, Wayne Webb, Harry Teplitz, Matthew Hayes, Vihang Mehta, Anahita Alavi, Andrew J. Bunker, Annalisa Citro, Nimish Hathi, Alaina Henry, Alexandra Le Reste, Alessia Moretti, Michael J. Rutkowski, Maxime Trebitsch, Anita Zanella
Figure caption: Redshift dependence of galaxies selected by the color cuts shown in Figure 8, where we vary the optical (F625W) magnitude required for a galaxy to be included. These are shown in redshift bins of Δz = 0.2. Left panel: fraction of galaxies in each redshift bin that are selected by the color cuts. Right panel: fraction of galaxies selected by the color cuts that lie in each redshift bin. Shaded regions in both panels represent the 2.7 < z < 4.0 range for which we optimize the three-band cuts (yellow), and the 3.1 < z < 3.5 redshift range that we target with the four-band cuts (red).
Paper: The Parallel Ionizing Emissivity Survey (PIE). I. Survey Design and Selection of Candidate Lyman Continuum Leakers at 3.1 < z < 3.5
Authors: Alexander Beckett, Marc Rafelski, Claudia Scarlata, Wanjia Hu, Keunho Kim, Ilias Goovaerts, Matthew A. Malkan, Wayne Webb, Harry Teplitz, Matthew Hayes, Vihang Mehta, Anahita Alavi, Andrew J. Bunker, Annalisa Citro, Nimish Hathi, Alaina Henry, Alexandra Le Reste, Alessia Moretti, Michael J. Rutkowski, Maxime Trebitsch, Anita Zanella
Figure caption: Redshift dependence of galaxies selected by the color cuts shown in Figure 8. These are shown in redshift bins of Δz = 0.2. Left panel: fraction of galaxies in each redshift bin that are selected by the color cuts. Right panel: fraction of galaxies selected by the color cuts that lie in each redshift bin. Shaded regions in both panels represent the 2.7 < z < 4.0 range for which we optimize the three-band cuts (yellow), and the 3.1 < z < 3.5 target redshift range which we aim for with the four-band cuts (red). Solid lines show the results using the three-band color selection, and dashed lines show results when the F475W filter is also used.
Paper: The Parallel Ionizing Emissivity Survey (PIE). I. Survey Design and Selection of Candidate Lyman Continuum Leakers at 3.1 < z < 3.5
Authors: Alexander Beckett, Marc Rafelski, Claudia Scarlata, Wanjia Hu, Keunho Kim, Ilias Goovaerts, Matthew A. Malkan, Wayne Webb, Harry Teplitz, Matthew Hayes, Vihang Mehta, Anahita Alavi, Andrew J. Bunker, Annalisa Citro, Nimish Hathi, Alaina Henry, Alexandra Le Reste, Alessia Moretti, Michael J. Rutkowski, Maxime Trebitsch, Anita Zanella
Figure caption: Example spectrum from our Keck/LRIS observations, of a galaxy at z = 2.987. The spectrum is smoothed using a Gaussian with 1 pixel standard deviation. The spectral ranges covered by the Lyβ and Lyα forests, and the UV continuum are colored. The left panels show the HST F625W and F336W imaging of this source, with the slit location marked in blue. The lower panels show zoomed-in regions of the spectra around some spectral features. Regions that are affected by strong sky residuals are zeroed-out and shaded in gray.
Paper: The Parallel Ionizing Emissivity Survey (PIE). I. Survey Design and Selection of Candidate Lyman Continuum Leakers at 3.1 < z < 3.5
Authors: Alexander Beckett, Marc Rafelski, Claudia Scarlata, Wanjia Hu, Keunho Kim, Ilias Goovaerts, Matthew A. Malkan, Wayne Webb, Harry Teplitz, Matthew Hayes, Vihang Mehta, Anahita Alavi, Andrew J. Bunker, Annalisa Citro, Nimish Hathi, Alaina Henry, Alexandra Le Reste, Alessia Moretti, Michael J. Rutkowski, Maxime Trebitsch, Anita Zanella
Figure caption: The fraction of 3.1 < z < 3.5 galaxies that will be selected in both of our color cuts as a function of stellar age and fesc, assuming the distribution of IGM opacities discussed in Section 4.3. Thus, a completeness of 0.9 indicates that there is a 10% chance that a galaxy with the shown escape fraction and stellar age would be shifted outside of our color selection and missed from the follow-up spectroscopic survey.
Paper: The Parallel Ionizing Emissivity Survey (PIE). I. Survey Design and Selection of Candidate Lyman Continuum Leakers at 3.1 < z < 3.5
Authors: Alexander Beckett, Marc Rafelski, Claudia Scarlata, Wanjia Hu, Keunho Kim, Ilias Goovaerts, Matthew A. Malkan, Wayne Webb, Harry Teplitz, Matthew Hayes, Vihang Mehta, Anahita Alavi, Andrew J. Bunker, Annalisa Citro, Nimish Hathi, Alaina Henry, Alexandra Le Reste, Alessia Moretti, Michael J. Rutkowski, Maxime Trebitsch, Anita Zanella
Figure caption: Color selection diagrams of sources detected in the PIE fields (left panel: three-band cuts; right panel: additional cuts for fields with F475W). Our selection window is outlined in green in both panels. Target galaxies (based on both color cuts where available) are shown as red points, sized depending on the signal-to-noise in the F336W image. Other galaxies are black points, and stars are shown in green.
Paper: The Parallel Ionizing Emissivity Survey (PIE). I. Survey Design and Selection of Candidate Lyman Continuum Leakers at 3.1 < z < 3.5
Authors: Alexander Beckett, Marc Rafelski, Claudia Scarlata, Wanjia Hu, Keunho Kim, Ilias Goovaerts, Matthew A. Malkan, Wayne Webb, Harry Teplitz, Matthew Hayes, Vihang Mehta, Anahita Alavi, Andrew J. Bunker, Annalisa Citro, Nimish Hathi, Alaina Henry, Alexandra Le Reste, Alessia Moretti, Michael J. Rutkowski, Maxime Trebitsch, Anita Zanella
Figure caption: Observed magnitude distribution of detected sources in each PIE filter with m(F625W) < 26. We show sources classified as stars, and those selected by our color cuts, showing that stars are more likely to be brighter than galaxies, and most of our color-selected galaxies are fainter than m(F625W) = 23, consistent with our mock predictions.
Paper: The Physical Properties of Four Double-lined Detached Eclipsing Binaries with Similar Components and Third Bodies from the LAMOST Medium-resolution Survey
Authors: Bin Zhang, Yi-Dan Gao, Chun-Qian Li, Xing-Hao Chen, Gang Zhao, Wen-Jun Xiao, Xu-Dong Zhang, Jing-Kun Zhao, Jia Zhang, Zhen Zhong
Figure caption: The distribution of four targets in the Hertzsprung−Russell diagram. The primary and secondary components are marked with red and blue circle dots, respectively. For V644 Aur, the primary and secondary components are almost in the same position. The zero-age main-sequence line and the terminal-age main-sequence line with Z = 0.001 and Z = 0.015 are computed with the one-dimensional stellar evolution code MESA (version 24.08.1; B. Paxton et al. 2011, 2013, 2015, 2018, 2019; A. S. Jermyn et al. 2023) with a configuration file posted to Zenodo: 10.5281/zenodo.17089284. Luminosities L are taken from our analysis, while the values of the Teff of the primary components are taken from the Gaia. The metallicity and log g we referenced were from the low-resolution spectra of LAMOST for NSVS 07453183—these two parameters come from Gaia. The initial stellar mass ranged from 0.4 to 2.0 M⊙ with an increment of ΔM = 0.1M⊙; the input physics is the same as that of X. Chen et al. (2025).
Paper: The Physical Properties of Four Double-lined Detached Eclipsing Binaries with Similar Components and Third Bodies from the LAMOST Medium-resolution Survey
Authors: Bin Zhang, Yi-Dan Gao, Chun-Qian Li, Xing-Hao Chen, Gang Zhao, Wen-Jun Xiao, Xu-Dong Zhang, Jing-Kun Zhao, Jia Zhang, Zhen Zhong
Figure caption: Required energies (solid lines) for the primary (red lines) and secondary components (blue lines), and the available energies (short-dotted lines) provided by the primary and secondary stars calculated by the revised model proposed by C. S. Brinkworth et al. (2006). For NSVS 07453183, we only plotted the the relationship of required energies and available energies in the period of 12.78 yr.
Paper: The Physical Properties of Four Double-lined Detached Eclipsing Binaries with Similar Components and Third Bodies from the LAMOST Medium-resolution Survey
Authors: Bin Zhang, Yi-Dan Gao, Chun-Qian Li, Xing-Hao Chen, Gang Zhao, Wen-Jun Xiao, Xu-Dong Zhang, Jing-Kun Zhao, Jia Zhang, Zhen Zhong
Figure caption: RV data and fitted curves of NSVS 07453183, V644 Aur, V912 Per, and V1250 Tau. Blue circles stand for the observed RVs of V1 (primary star), and red circles represent the V2 (secondary star). Red and blue solid lines represent the best-fitting curves. The final fitting residuals are plotted in the bottom panel.
Paper: The Physical Properties of Four Double-lined Detached Eclipsing Binaries with Similar Components and Third Bodies from the LAMOST Medium-resolution Survey
Authors: Bin Zhang, Yi-Dan Gao, Chun-Qian Li, Xing-Hao Chen, Gang Zhao, Wen-Jun Xiao, Xu-Dong Zhang, Jing-Kun Zhao, Jia Zhang, Zhen Zhong
Figure caption: The final O − C diagrams for our systems, all of which show periodic changes. The (O − C)1 (or (O − C)) values are calculate from the linear ephemeris listed in Table 7, and the (O − C)2 values are calculated from the fitting correction ephemeris. For NSVS 07453183, the blue sinusoidal curve stands for the LTTE with a period of about 422 days, and the red solid line represents a long period of 12 yr caused probably by a fourth body. The fitting residuals are plotted in the bottom panel.
Paper: The Physical Properties of Four Double-lined Detached Eclipsing Binaries with Similar Components and Third Bodies from the LAMOST Medium-resolution Survey
Authors: Bin Zhang, Yi-Dan Gao, Chun-Qian Li, Xing-Hao Chen, Gang Zhao, Wen-Jun Xiao, Xu-Dong Zhang, Jing-Kun Zhao, Jia Zhang, Zhen Zhong
Figure caption: The LCs of the four binaries. The solid lines in the upper part are the theoretical LC, while the different colored dots and circles are the actual observed LCs. The difference between observation and theory is plotted in the lower panel (O − C).
Paper: Multifidelity Emulator for Large-scale 21 cm Lightcone Images: A Few-shot Transfer Learning Approach with Generative Adversarial Network
Authors: Kangning Diao, Yi Mao
Figure caption: Same as Figure 14 but for the large-scale GAN trained conventionally using only 80 simulation samples.
Paper: Multifidelity Emulator for Large-scale 21 cm Lightcone Images: A Few-shot Transfer Learning Approach with Generative Adversarial Network
Authors: Kangning Diao, Yi Mao
Figure caption: Same as Figure 4 but for the large-scale GAN trained conventionally using only 80 simulation samples.
Paper: Multifidelity Emulator for Large-scale 21 cm Lightcone Images: A Few-shot Transfer Learning Approach with Generative Adversarial Network
Authors: Kangning Diao, Yi Mao
Figure caption: FSD with j = 0, 2, 4 for the small-scale GAN with 10,000 simulations as a function of the training iterations.
Paper: Multifidelity Emulator for Large-scale 21 cm Lightcone Images: A Few-shot Transfer Learning Approach with Generative Adversarial Network
Authors: Kangning Diao, Yi Mao
Figure caption: An illustration of a ResNet block.
Paper: Analysis of Short-term Solar Activity Variability and Estimating the Timings of the Next Enhanced Bursts
Authors: Juie Shetye, Mausumi Dikpati
Figure caption: Zoomed-in burst-envelope forecasts from 2024 January to 2026 April. Top: the Northern Hemisphere SSN with inferred RF burst properties. Middle: the Southern Hemisphere counterpart. Bottom: total (Northern Hemisphere + Southern Hemisphere) SSN, highlighting the same burst timings and amplitudes.
Paper: Analysis of Short-term Solar Activity Variability and Estimating the Timings of the Next Enhanced Bursts
Authors: Juie Shetye, Mausumi Dikpati
Figure caption: Comparison of solar burst properties between the Northern and Southern Hemispheres. (a) Distribution of amplitudes for Northern and Southern Hemispheres bursts. (b) Distribution of durations (in months) for Southern Hemisphere bursts. (c) Violin plot comparison of amplitudes relative to SC phase and hemisphere. (d) Violin plot comparison of duration to SC phase and hemisphere. All panels aggregate bursts over SC12–SC25 (1878–2025).
Paper: Analysis of Short-term Solar Activity Variability and Estimating the Timings of the Next Enhanced Bursts
Authors: Juie Shetye, Mausumi Dikpati
Figure caption: Top panel: Northern Hemisphere monthly SSN, from 1878–2026. Second panel from the top: Southern Hemisphere monthly SSN, from 1878–2026. Third panel from the top: forecasted monthly SSN for SC25, Northern Hemisphere, zoomed to 2026 March. Bottom panel: forecasted monthly SSN for SC25, Southern Hemisphere, zoomed to 2026 March. In the top two panels, dotted lines indicate training data, solid lines denote the hindcast test intervals (Northern Hemisphere: 2024 July–2025 January; Southern Hemisphere: 2024 November–2025 January); subsequent segments show the forecast. Background shading marks the training (gray), test (blue), and forecast (tan) periods. Axes are SSN (y) vs. calendar year (x). In the third and bottom panels, the solid blue and orange curves are the Northern and Southern Hemisphere forecasts, respectively. Vertical dashed lines mark key epochs: SC25 start (2019 December, gray), test-interval start (Northern Hemisphere: 2024 July; Southern Hemisphere: 2024 November, blue and orange, respectively), and forecast start (2025 February, green).
Paper: Analysis of Short-term Solar Activity Variability and Estimating the Timings of the Next Enhanced Bursts
Authors: Juie Shetye, Mausumi Dikpati
Figure caption: TNO period as function of field strength is displayed as the blue curve. In addition to field strength, a wide range of parameters like tachocline differential rotation, the amount of possible subadiabiticity, and latitude location of the magnetic band give rise to changes (increase or decrease) in the TNO period; the range of TNO periods has been captured by the spread displayed in the light green shade. The TNO periods follow the x-axis going from left to right during the rising phase since the sunspot number (as well as spot area and magnetic flux), which are a proxy of tachocline magnetic fields, increase sinusoidally.
Paper: Analysis of Short-term Solar Activity Variability and Estimating the Timings of the Next Enhanced Bursts
Authors: Juie Shetye, Mausumi Dikpati
Figure caption: Hemispheric SSN from the start of SC23 to 2025 for the north (top) and south (bottom). Curves show Gaussian smooths with FWHMs of 3, 4, and 6 months; no detrending is applied. Shaded bands indicate SC23–SC25.
Paper: Analysis of Short-term Solar Activity Variability and Estimating the Timings of the Next Enhanced Bursts
Authors: Juie Shetye, Mausumi Dikpati
Figure caption: Example of Gaussian fitting to bursts observed in the time series. The blue line shows the 4 month smoothed SSN data, and the red line shows the fitted Gaussian function plus a linear background.
Paper: Multifidelity Emulator for Large-scale 21 cm Lightcone Images: A Few-shot Transfer Learning Approach with Generative Adversarial Network
Authors: Kangning Diao, Yi Mao
Figure caption: The ST coefficient S1(j, l) of the 21 cm signal emulated with the small-scale GAN (dashed line) and that of the test set images (solid line) at three representative redshifts of the center slice (from top to bottom) z = 7.933, 9.384, and 11.221, respectively. We show the results with different values of reionization parameters (in different colors). Each set of reionization parameter is calculated with 6400 clips of size (2,64,64) from the raw image. The lower subpanel in each panel shows the relative error between the GAN-emulated ST and the test set, εrel. For visualization, the 10% error level is indicated with the gray dotted–dashed line, while neglecting the data points at which the statistics for the test set are nearly zero.
Paper: Multifidelity Emulator for Large-scale 21 cm Lightcone Images: A Few-shot Transfer Learning Approach with Generative Adversarial Network
Authors: Kangning Diao, Yi Mao
Figure caption: Same as Figure 6 but for S2(j1, l1, j2, l2). The indices (j1, j2) take the value of (0, 2), (0, 4) and (2, 4). For each combination of (j1, j2), the indices (l1, l2) run from l1 = 0, 1, 2, 3 and l2 = 0, 1, 2, 3, i.e., (l1, l2) take 16 values of (0, 0), (0, 1), (0, 2), (0, 3), (1, 0), (1, 1)…(3, 3), respectively.
Paper: Multifidelity Emulator for Large-scale 21 cm Lightcone Images: A Few-shot Transfer Learning Approach with Generative Adversarial Network
Authors: Kangning Diao, Yi Mao
Figure caption: (Top) The global 21 cm signal emulated with the small-scale GAN, with the mean (dashed line) and 2σ scatter (shallow shaded region). We show the results with different values of reionization parameters (in different colors). Each set of reionization parameter is calculated with 6400 image samples. For comparison, we show the results of test set images, with the mean (solid line) and 2σ scatter (thick shaded region). (Bottom) Relative error between the GAN-emulated global signal and the test set. For visualization, the 10% error level is indicated with the dotted–dashed line, while neglecting the data points at which the statistics for the test set are nearly zero.
Paper: Multifidelity Emulator for Large-scale 21 cm Lightcone Images: A Few-shot Transfer Learning Approach with Generative Adversarial Network
Authors: Kangning Diao, Yi Mao
Figure caption: An illustration of the StyleGAN2 generator architecture. Our generator consists of a mapping network f, which modifies the convolution kernel according to astrophysical parameters and random vectors, and a synthesis network g, which generates images progressively, with noise injection for multiple times.
Paper: Multifidelity Emulator for Large-scale 21 cm Lightcone Images: A Few-shot Transfer Learning Approach with Generative Adversarial Network
Authors: Kangning Diao, Yi Mao
Figure caption: Examples of the emulated images using the small-scale GAN (left), in comparison with the simulated images using 21cmFAST in the test set (right). In each panel, we show the 21 cm brightness temperature (Tb) field (the upper half) and the matter overdensity (δm) field (the lower half). The LoS is along the x-axis.
Paper: Multifidelity Emulator for Large-scale 21 cm Lightcone Images: A Few-shot Transfer Learning Approach with Generative Adversarial Network
Authors: Kangning Diao, Yi Mao
Figure caption: An illustration of CDC. We generate a set of samples with both small-scale GAN and large-scale GAN, calculate the similarity between each image pair generated by the same GAN, normalize the similarity vector of each GAN with softmax, and compute the KL divergence as the CDC.