adsabs/AstroCLIMB huggingface dataset:
Paper: From Equipartition to Curvature: The Spectral Evolution of 4FGL Blazars
Authors: Muhammad S. Anjum, Shu-Jin Hou, Liang Chen, Zhigang Li, Minfeng Gu
Figure caption: The relationship between dissipation location Rb and the accretion disk luminosity LD for FSRQs. The solid line shows the best linear regression fit.
Paper: From Equipartition to Curvature: The Spectral Evolution of 4FGL Blazars
Authors: Muhammad S. Anjum, Shu-Jin Hou, Liang Chen, Zhigang Li, Minfeng Gu
Figure caption: An example of log-parabolic polynomial fitting of blazars. The left panel shows the BL Lac source ApLib (4FGL J1517.7-2422), whereas the right panel shows the FSRQ 3C273 (4FGL J1229.0+0202).
Paper: From Equipartition to Curvature: The Spectral Evolution of 4FGL Blazars
Authors: Muhammad S. Anjum, Shu-Jin Hou, Liang Chen, Zhigang Li, Minfeng Gu
Figure caption: The distributions of source EED parameters for BL Lacs (blue) and FSRQs (red).
Paper: From Equipartition to Curvature: The Spectral Evolution of 4FGL Blazars
Authors: Muhammad S. Anjum, Shu-Jin Hou, Liang Chen, Zhigang Li, Minfeng Gu
Figure caption: The relationship between synchrotron peak frequency νs and IC peak frequency νc. BL Lacs are shown by filled blue circles, and FSRQs are shown by filled red circles. The solid lines represent the linear regression fit.
Paper: From Equipartition to Curvature: The Spectral Evolution of 4FGL Blazars
Authors: Muhammad S. Anjum, Shu-Jin Hou, Liang Chen, Zhigang Li, Minfeng Gu
Figure caption: The distributions of jet power for BL Lacs (blue) and FSRQs (red).
Paper: PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars
Authors: Kuang Mao, Zhaorong Tang, Qiuhong Pan, Pei Wang, Huaxi Chen, Scott M. Ransom, Di Li, Xuefei Tang, Qi Wang, Yi Feng, Lei Chen, Donghui Quan, Zujie Ren
Figure caption: Performance comparison between PRESTO C with OpenMP enabled and different GPU-based jerk search methods using multiple concurrent processes on one A100 40G GPU, where p represents the number of concurrent processes, and b denotes the batch size used in PrestoZL and PrestoZL-pipeline, ncpu represents the number of CPU cores that can be utilized by each PRESTO C process for OpenMP acceleration.
Paper: PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars
Authors: Kuang Mao, Zhaorong Tang, Qiuhong Pan, Pei Wang, Huaxi Chen, Scott M. Ransom, Di Li, Xuefei Tang, Qi Wang, Yi Feng, Lei Chen, Donghui Quan, Zujie Ren
Figure caption: Performance comparison between PRESTO C with OpenMP disabled and different GPU-based methods in acceleration search mode using a single process.
Paper: PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars
Authors: Kuang Mao, Zhaorong Tang, Qiuhong Pan, Pei Wang, Huaxi Chen, Scott M. Ransom, Di Li, Xuefei Tang, Qi Wang, Yi Feng, Lei Chen, Donghui Quan, Zujie Ren
Figure caption: The computational workflow of CPU-based jerk search in PRESTO (left) and GPU-based jerk search in PrestoZL (right).
Paper: PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars
Authors: Kuang Mao, Zhaorong Tang, Qiuhong Pan, Pei Wang, Huaxi Chen, Scott M. Ransom, Di Li, Xuefei Tang, Qi Wang, Yi Feng, Lei Chen, Donghui Quan, Zujie Ren
Figure caption: Performance comparison between PRESTO C with OpenMP enabled and different GPU-based jerk search methods using a single jerk search process.
Paper: PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars
Authors: Kuang Mao, Zhaorong Tang, Qiuhong Pan, Pei Wang, Huaxi Chen, Scott M. Ransom, Di Li, Xuefei Tang, Qi Wang, Yi Feng, Lei Chen, Donghui Quan, Zujie Ren
Figure caption: Complex multiplication kernel time comparison between different batch sizes (b).
Paper: PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars
Authors: Kuang Mao, Zhaorong Tang, Qiuhong Pan, Pei Wang, Huaxi Chen, Scott M. Ransom, Di Li, Xuefei Tang, Qi Wang, Yi Feng, Lei Chen, Donghui Quan, Zujie Ren
Figure caption: Power recovery kernel time comparison between different batch sizes (b).
Paper: PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars
Authors: Kuang Mao, Zhaorong Tang, Qiuhong Pan, Pei Wang, Huaxi Chen, Scott M. Ransom, Di Li, Xuefei Tang, Qi Wang, Yi Feng, Lei Chen, Donghui Quan, Zujie Ren
Figure caption: The total kernel times comparison during harmonic summing and candidate search between the jerk search GPU and PrestoZL.
Paper: PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars
Authors: Kuang Mao, Zhaorong Tang, Qiuhong Pan, Pei Wang, Huaxi Chen, Scott M. Ransom, Di Li, Xuefei Tang, Qi Wang, Yi Feng, Lei Chen, Donghui Quan, Zujie Ren
Figure caption: GPU utilization of PrestoZL-pipeline under eight concurrent processes.
Paper: PrestoZL: A GPU-accelerated High-throughput Jerk Search Toolkit for Binary Pulsars
Authors: Kuang Mao, Zhaorong Tang, Qiuhong Pan, Pei Wang, Huaxi Chen, Scott M. Ransom, Di Li, Xuefei Tang, Qi Wang, Yi Feng, Lei Chen, Donghui Quan, Zujie Ren
Figure caption: Three-stage pipeline parallel framework of PrestoZL.
Paper: The TESS Grand Unified Hot Jupiter Survey. III. Thirty More Giant Planets 
Authors: Samuel W. Yee, Joshua N. Winn, Joel D. Hartman, Joseph E. Rodriguez, George Zhou, David W. Latham, Samuel N. Quinn, Allyson Bieryla, Karen A. Collins, Jason D. Eastman, Kevin I. Collins, Dennis M. Conti, Eric L. N. Jensen, David Baker, Khalid Barkaoui, Özgür Baştürk, Matthew P. Battley, Daniel Bayliss, Thomas G. Beatty, Yuri Beletsky, Alexander A. Belinski, Zouhair Benkhaldoun, Paul Benni, Pau Bosch-Cabot, César Briceño, Andrzej Brudny, Matthew R. Burleigh, R. Paul Butler, Stavros Chairetas, Ashley Chontos, Jessie Christiansen, David R. Ciardi, Catherine A. Clark, Ryan Cloutier, Matthew W. Craig, Jeffrey D. Crane, Nicholas Dowling, Courtney D. Dressing, Jehin Emmanuel, Phil Evans, Mark E. Everett, Gareb Fernández-Rodríguez, Jorge Fernández Fernández, Raquel Forés-Toribio, Charles D. Fortenbach, Akihiko Fukui, Elise Furlan, Tianjun Gan, Mourad Ghachoui, Steven Giacalone, Samuel Gill, Michaël Gillon, Kylie Hall, Yuya Hayashi, Christina Hedges, Jesus Higuera, Eric G. Hintz, Lea Hirsch, Rae Holcomb, Keith Horne, Ferran Grau Horta, Andrew W. Howard, Steve B. Howell, Howard Isaacson, Jon M. Jenkins, Taiki Kagetani, Jacob Kamler, Alicia Kendall, Judith Korth, Maxwell A. Kroft, Gaia Lacedelli, Didier Laloum, Nicholas Law, Jerome Pitogo de Leon, Alan M. Levine, Pablo Lewin, Sarah E. Logsdon, Michael B. Lund, Madelyn M. Madsen, Andrew W. Mann, Christopher R. Mann, Nataliia A. Maslennikova, Sandra Matutano, Mason McCormack, Kim K. McLeod, Edward J. Michaels, Ismael Mireles, Mayuko Mori, Jose A. Muñoz, Felipe Murgas, Norio Narita, Sean M. O'Brien, Caroline Odden, Enric Palle, Yatrik G. Patel, Peter Plavchan, Alex S. Polanski, Adam Popowicz, Don J. Radford, Phillip A. Reed, Howard M. Relles, Malena Rice, George R. Ricker, Boris S. Safonov, Arjun B. Savel, Jack Schulte, Richard P. Schwarz, Heidi Schweiker, Sara Seager, Ramotholo Sefako, Stephen A. Shectman, Avi Shporer, Denise C. Stephens, Chris Stockdale, Stephanie Striegel, Thiam-Guan Tan, Johanna K. Teske, Mathilde Timmermans, Solène Ulmer-Moll, Gavin Wang, Peter J. Wheatley, Selçuk Yalcinkaya, Roberto Zambelli, Judah Van Zandt, Carl Ziegler
Figure caption: Gaia color–magnitude diagram for transiting hot Jupiter hosts (P < 10 days, 8 R⊕ < Rp < 24 R⊕ ) from the NASA Exoplanet Archive. Filled yellow squares represent the stellar hosts of the newly confirmed planets in this paper; filled green diamonds and filled orange circles show the systems from previous works in this survey (Papers I and II). Filled navy blue squares show other discoveries from TESS, while all previously known hot Jupiter hosts are plotted in gray. We also plot MIST stellar evolutionary tracks for a range of stellar masses corresponding to a metallicity of [Fe/H] = +0.20 dex, close to the median metallicity of our sample. The absolute magnitude and colors plotted here have not been corrected for the effects of extinction and reddening.
Paper: Microlensing Optical Depth, Event Rate, and Limits on Compact Objects in Dark Matter Based on 20 Yr of OGLE Observations of the Small Magellanic Cloud
Authors: Przemek Mróz, Andrzej Udalski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Radosław Poleski, Jan Skowron, Dorota Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Milena Ratajczak
Figure caption: OGLE-IV fields toward the Small Magellanic Cloud (SMC) are shown with white polygons. The numbers in the center of each polygon in the right panel indicate the field number. The yellow lines mark the regions that were observed during the OGLE-III phase. Detected microlensing events are marked with black circles. The background image of the SMC was generated with BSRENDER written by Kevin Loch, using data from the ESA/Gaia database.
Paper: Microlensing Optical Depth, Event Rate, and Limits on Compact Objects in Dark Matter Based on 20 Yr of OGLE Observations of the Small Magellanic Cloud
Authors: Przemek Mróz, Andrzej Udalski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Radosław Poleski, Jan Skowron, Dorota Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Milena Ratajczak
Figure caption: I-band light curves of detected microlensing events. The solid blue line shows the best-fit microlensing model. The dotted lines for OGLE-SMC-06 and OGLE-SMC-07 present the best-fit PSPL models without microlensing parallax.
Paper: Microlensing Optical Depth, Event Rate, and Limits on Compact Objects in Dark Matter Based on 20 Yr of OGLE Observations of the Small Magellanic Cloud
Authors: Przemek Mróz, Andrzej Udalski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Radosław Poleski, Jan Skowron, Dorota Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Milena Ratajczak
Figure caption: Surface density of source stars brighter than I = 21 mag in the analyzed fields. The black polygons mark the area observed by OGLE-III. The map is presented in an equal-area Hammer projection centered on R.A. = 0h51m, decl. = −73﹩\mathop{.}\limits^{\unicode{x000b0}}﹩1.
Paper: Microlensing Optical Depth, Event Rate, and Limits on Compact Objects in Dark Matter Based on 20 Yr of OGLE Observations of the Small Magellanic Cloud
Authors: Przemek Mróz, Andrzej Udalski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Radosław Poleski, Jan Skowron, Dorota Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Milena Ratajczak
Figure caption: Dereddened color–magnitude diagram (CMD) of the field SMC 726.28. Blue circles mark the positions of the detected microlensing events in the baseline.
Paper: Microlensing Optical Depth, Event Rate, and Limits on Compact Objects in Dark Matter Based on 20 Yr of OGLE Observations of the Small Magellanic Cloud
Authors: Przemek Mróz, Andrzej Udalski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Radosław Poleski, Jan Skowron, Dorota Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Milena Ratajczak
Figure caption: Shown here are 95% upper limits on the fraction of dark matter in the form of PBHs and other compact objects. The shaded red area is excluded at 95% confidence based on the presented observations of the SMC. The solid red line represents the strict limits, whereas the dashed and dotted red lines indicate the relaxed limits for the C. Han & A. Gould (2003) and M. Cautun et al. (2020) Milky Way disk models, respectively. Other limits are taken from P. Tisserand et al. (2007) (EROS), Ł. Wyrzykowski et al. (2011b; OGLE-III), K. Griest et al. (2013; Kepler), H. Niikura et al. (2019; HSC), T. Blaineau et al. (2022; EROS+MACHO), P. Mróz et al. (2024c; OGLE-III + OGLE-IV), and P. Mróz et al. (2024a; OGLE-IV high-cadence).
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: A schematic representation of staggered grid zones in 1-direction. The “a-grid” locations x1a,i correspond to the lower interfaces x1b,i−1/2 of the “b-grid” zones centered on x1b,i, and the “b-grid” locations x1b,i correspond to the upper interfaces x1a,i+1/2 of the “a-grid” zones centered on x1a,i.
Paper: Microlensing Optical Depth, Event Rate, and Limits on Compact Objects in Dark Matter Based on 20 Yr of OGLE Observations of the Small Magellanic Cloud
Authors: Przemek Mróz, Andrzej Udalski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Radosław Poleski, Jan Skowron, Dorota Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Milena Ratajczak
Figure caption: Expected cumulative distribution of event timescales of microlensing events from known stellar populations in the SMC and the foreground Milky Way disk, assuming the Milky Way models of M. Cautun et al. (2020; blue line) and C. Han & A. Gould (2003; red line). The observed cumulative distribution function is shown by the black line.
Paper: Microlensing Optical Depth, Event Rate, and Limits on Compact Objects in Dark Matter Based on 20 Yr of OGLE Observations of the Small Magellanic Cloud
Authors: Przemek Mróz, Andrzej Udalski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Radosław Poleski, Jan Skowron, Dorota Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Milena Ratajczak
Figure caption: Expected distributions of observed event timescales of microlensing events from known stellar populations in the SMC (S. Calchi Novati et al. 2013; blue line) and the foreground Milky Way disk (red line). Left panel: assuming the Milky Way model of C. Han & A. Gould (2003); right panel: M. Cautun et al. (2020).
Paper: Microlensing Optical Depth, Event Rate, and Limits on Compact Objects in Dark Matter Based on 20 Yr of OGLE Observations of the Small Magellanic Cloud
Authors: Przemek Mróz, Andrzej Udalski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Radosław Poleski, Jan Skowron, Dorota Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Milena Ratajczak
Figure caption: Contours of the microlensing optical depth for two self-lensing SMC models: S. Calchi Novati et al. (2013; left panel) and P. Mróz & R. Poleski (2018; right). The filled circles indicate the positions of five microlensing events that are included in the statistical sample analyzed in this paper, while the empty circles represent other known microlensing events.
Paper: Microlensing Optical Depth, Event Rate, and Limits on Compact Objects in Dark Matter Based on 20 Yr of OGLE Observations of the Small Magellanic Cloud
Authors: Przemek Mróz, Andrzej Udalski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Radosław Poleski, Jan Skowron, Dorota Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Milena Ratajczak
Figure caption: Example detection efficiency curves for representative fields SMC726 and SMC734. The solid, dashed, and dashed–dotted lines represent detection efficiencies averaged for sources brighter than I = 21, I = 21.5, and I = 22 mag, respectively.
Paper: Microlensing Optical Depth, Event Rate, and Limits on Compact Objects in Dark Matter Based on 20 Yr of OGLE Observations of the Small Magellanic Cloud
Authors: Przemek Mróz, Andrzej Udalski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Radosław Poleski, Jan Skowron, Dorota Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Milena Ratajczak
Figure caption: Expected number of microlensing events to be detected in the SMC direction if the entire Milky Way’s dark matter halo was composed of compact objects with identical mass.
Paper: Microlensing Optical Depth, Event Rate, and Limits on Compact Objects in Dark Matter Based on 20 Yr of OGLE Observations of the Small Magellanic Cloud
Authors: Przemek Mróz, Andrzej Udalski, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Radosław Poleski, Jan Skowron, Dorota Skowron, Krzysztof Ulaczyk, Mariusz Gromadzki, Krzysztof Rybicki, Patryk Iwanek, Marcin Wrona, Milena Ratajczak
Figure caption: Dependence of inferred upper limits on the limiting magnitude.
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: (a) The locations of the volume centered ρ and e, the face-centered velocity and magnetic fields, and the edge-centered electric fields in the volume cell. (b) A schematic showing in a 2D slice (x1–x2 plane) the evaluation of the electric fields E3, ﹩{E}_{3}^{* }﹩ and the limited current density components J31, J32 at the edge ﹩\left({x}_{1a,i},{x}_{2a,j}\right)﹩ using the v1, B1 and v2, B2 states reconstructed from their defined locations at the cell faces.
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: Shown here is the magnetic field in 3D magnetic field-loop advection test in spherical coordinate at ﹩t=\sqrt{2}﹩. The top panels show vertical slices through the y = 0 plane, and the bottom panels show horizontal slices through the ﹩z=\sqrt{2}/2﹩ plane. The black dashed lines represent the Yin–Yang boundaries. The left panel shows the results obtained with PLM reconstruction, and the right panel shows the results obtained with PDM reconstruction.
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: Shown here is the line profiles of plasma pressure at y = 0.3125 (top) and y = 0.4277(bottom) from four Orszag–Tang simulations at t = 0.5. The results are shown for 256 × 256 grid (red line) and 512 × 512 grid (blue line), PLM reconstruction (solid line) and PDM reconstruction (dashed line).
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: Shown here is the spatial distribution of plasma density of Orszag–Tang simulations at t = 0.5 using different reconstructions and resolutions: 256 × 256 (top) and 512 × 512 (bottom), piecewise linear method (left) and partial donor cell method (right).
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: A schematic of the Yin–Yang grid: two identically sized overlapping partial spherical shell domains with r–θ–ϕ grids (blue grid representative of Yin and red grid representative of Yang) with orthogonal polar axes, which cover the whole sphere.
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: Shown here is the Brio–Wu shock-tube problem using different reconstructions and N = 512 grid cells, with data taken at t = 0.1. The reference result (black solid lines) is obtained using a 1D conservative code.
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: Shown here is the spatial distribution of plasma pressure of Orszag–Tang simulations at t = 1 using a 512 × 512 grid: results obtained with PLM (left) and PDM (right).
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: Shown here is the spatial distribution of B⊥ of nonlinearly circularly polarized Alfvén waves after propagating one wavelength, using the PLM and a grid of 256 × 256 cells .
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: Shown here is the convergence of the nonlinear polarized Alfvén waves test.
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: The density (upper), temperature (middle), and radial velocity (bottom) profiles along a polar flux tube in the final steady-state solar wind solution. The bottom panel also shows the sound speed profile (red curve) along the flux tube. The flow becomes supersonic at roughly 3R⊙, but remains sub-Alfvénic throughout the range to 10R⊙. Note the Alfvén speed is not shown and is mostly above the upper limit of the plot.
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: Shown here is the initial dipole magnetic field lines (left) and the initial temperature profile for the 1D hydrostatic corona (right). The gray scale on the sphere in left panel shows the dipolar normal magnetic field distribution Br on the solar surface.
Paper: The Yin–Yang Magnetic Flux Eruption (Yin–Yang MFE) Code: A Global Corona Magnetohydrodynamic Code with the Yin–Yang Grid
Authors: Hongyang Luo, Yuhong Fan
Figure caption: Strong scaling of the dipole solar wind simulation using a grid of 840(r) × 120(θ) × 360(ϕ) for each Yin and Yang component.
Paper: Evaluating Time-series Augmentation Techniques for Deep Learning–Based Solar Flare Prediction
Authors: Peiyu Li, Omar Bahri, Soukaïna Filali Boubrahimi, Shah Muhammad Hamdi
Figure caption: Confusion matrices for the FCN model comparing the baseline (stratified sampling) with three augmentation methods (PM, SC, and DGW) that showed strong performance in previous evaluations.
Paper: Evaluating Time-series Augmentation Techniques for Deep Learning–Based Solar Flare Prediction
Authors: Peiyu Li, Omar Bahri, Soukaïna Filali Boubrahimi, Shah Muhammad Hamdi
Figure caption: Comparing the augmentation impact (in terms of recall, HSS, TSS, and Gini) by applying different augmentation methods under the ResNet model.
Paper: Evaluating Time-series Augmentation Techniques for Deep Learning–Based Solar Flare Prediction
Authors: Peiyu Li, Omar Bahri, Soukaïna Filali Boubrahimi, Shah Muhammad Hamdi
Figure caption: Comparing the augmentation impact (in terms of recall, HSS, TSS, and Gini) by applying different augmentation methods under the FCN model.
Paper: Evaluating Time-series Augmentation Techniques for Deep Learning–Based Solar Flare Prediction
Authors: Peiyu Li, Omar Bahri, Soukaïna Filali Boubrahimi, Shah Muhammad Hamdi
Figure caption: Comparing the augmentation impact (in terms of recall, HSS, TSS, and Gini) by applying different augmentation methods under the MLSTM-FCN model.
Paper: Evaluating Time-series Augmentation Techniques for Deep Learning–Based Solar Flare Prediction
Authors: Peiyu Li, Omar Bahri, Soukaïna Filali Boubrahimi, Shah Muhammad Hamdi
Figure caption: Comparing the undersampling impact by applying FCN, MLSTM-FCN, and ResNet models.
Paper: Evaluating Time-series Augmentation Techniques for Deep Learning–Based Solar Flare Prediction
Authors: Peiyu Li, Omar Bahri, Soukaïna Filali Boubrahimi, Shah Muhammad Hamdi
Figure caption: The architecture of the multivariate LSTM fully convolutional network. BN = batch normalization.
Paper: Evaluating Time-series Augmentation Techniques for Deep Learning–Based Solar Flare Prediction
Authors: Peiyu Li, Omar Bahri, Soukaïna Filali Boubrahimi, Shah Muhammad Hamdi
Figure caption: The architecture of the fully convolutional neural network.
Paper: Evaluating Time-series Augmentation Techniques for Deep Learning–Based Solar Flare Prediction
Authors: Peiyu Li, Omar Bahri, Soukaïna Filali Boubrahimi, Shah Muhammad Hamdi
Figure caption: The architecture of the residual network.