adsabs/AstroCLIMB huggingface dataset:
Paper: Radial Evolution of Non-Maxwellian Electron Populations Derived from Quasi-thermal Noise Spectroscopy: Parker Solar Probe Observations
Authors: Xianming Zheng, Mihailo M. Martinović, Viviane Pierrard, Kristopher G. Klein, Mingzhe Liu, Joel B. Abraham, Yong Liu, Jingting Luo, Xiaodong Lin, Guoqing Liu, Jingchun Li
Figure caption: Example of eVDF fitting procedure. The blue dots represent the SPAN-E observational results. The fitting range is indicated by the black square dots, while the red and purple dots depict the results of the kappa and Maxwellian fittings, respectively. That shows in this case the n  e  = 522.02 ± 0.2 cm−3, T  c  = 29.05 ± 0.01 eV for Maxwellian and for kappa eVDF the n  e  = 542.02 ± 0.5 cm−3, T  e  = 32.23 e ± 0.01 V, kappa = 5.79 ± 0.1. It is important to highlight that measurements become unreliable for channels with energies below 30 eV, attributed to secondary contamination of the data by instrument (the 30 eV energy line is delineated by a vertical red line in this graph).
Paper: Evolution of Cataclysmic Variables with Binary-driven Mass Loss during Nova Eruptions
Authors: Wen-Shi Tang, Xiang-Dong Li, Zhe Cui
Figure caption: Distributions of the WD mass (left) and orbital period (right), compared with the observed CVs (red curves). In each panel, the black and sky blue curves correspond to the FW model and the FW+BDML model, respectively. The black dashed vertical lines in the right panel represent the lower (2.15 ± 0.03 hr) and upper boundaries (3.18 ± 0.04 hr) of the period gap given by C. Knigge et al. (2011), while the green one is the lower boundary of the gap estimated by M. R. Schreiber et al. (2024). The data of the WD masses and orbital periods are taken from A. F. Pala et al. (2022) and K. Inight et al. (2023), respectively.
Paper: Evolution of Cataclysmic Variables with Binary-driven Mass Loss during Nova Eruptions
Authors: Wen-Shi Tang, Xiang-Dong Li, Zhe Cui
Figure caption: Comparison of the mass transfer rates in CVs between theory and observation. The left and right panels show the results in the FW+BDML model and the FW model, respectively. In each panel, the purple dots represent the observed sources with measured mean mass accretion rate from A. F. Pala et al. (2022).
Paper: Evolution of Cataclysmic Variables with Binary-driven Mass Loss during Nova Eruptions
Authors: Wen-Shi Tang, Xiang-Dong Li, Zhe Cui
Figure caption: Detailed evolution of a CV during a few nova cycles with M WD,i = 0.6 M ⊙. The left and right panels show the mass transfer rate and the orbital period as a function of time, respectively. In each panel, the red dots mark the location of nova eruptions, the blue dots are the evolutionary data points, linked by the green lines.
Paper: Evolution of Cataclysmic Variables with Binary-driven Mass Loss during Nova Eruptions
Authors: Wen-Shi Tang, Xiang-Dong Li, Zhe Cui
Figure caption: Ratio of ﹩\langle {\dot{J}}_{\mathrm{ML}}\rangle ﹩ to ﹩{\dot{J}}_{\mathrm{GR}}﹩ as a function of the companion mass. The blue and orange curves stand for the FW+BDML and FW models, respectively. The dotted line denotes ﹩{\dot{J}}_{\mathrm{ML}}=1.47{\dot{J}}_{\mathrm{GR}}﹩.
Paper: Sun-as-a-Star Spectral Line Variability in the 300–2390 nm Wavelength Range
Authors: Sergey V. Marchenko, Antje Ludewig, Serena Criscuoli, Khaled Al Moulla, Debi P. Choudhary, Matthew T. DeLand, Greg Kopp, Erwin Loots, Emiel van der Plas, Pepijn Veefkind
Figure caption: The normalized TROPOMI irradiances from 2022 May 20 (black line) are compared to the normalized, scaled, and shifted (for clarity) solar-standard spectrum (pink line). The vertical dotted and dashed lines mark the Fe I 2315 nm, 2317 nm line cores and the relatively line-free areas (Table 1) used in the line-index estimates.
Paper: Sun-as-a-Star Spectral Line Variability in the 300–2390 nm Wavelength Range
Authors: Sergey V. Marchenko, Antje Ludewig, Serena Criscuoli, Khaled Al Moulla, Debi P. Choudhary, Matthew T. DeLand, Greg Kopp, Erwin Loots, Emiel van der Plas, Pepijn Veefkind
Figure caption: NNLSSI1 bolometric scaling coefficients (BSC). The alternating vertical dotted–dashed lines mark the borders of spectral regions used in the analysis, “340 nm,” “430 nm,” “720 nm,” and “SWIR,” respectively.
Paper: Sun-as-a-Star Spectral Line Variability in the 300–2390 nm Wavelength Range
Authors: Sergey V. Marchenko, Antje Ludewig, Serena Criscuoli, Khaled Al Moulla, Debi P. Choudhary, Matthew T. DeLand, Greg Kopp, Erwin Loots, Emiel van der Plas, Pepijn Veefkind
Figure caption: Shown are the bottom parts of the Ca II K profile from 2020 February 10 (a low-activity day, with the individual-FOV TROPOMI measurements marked by black dots) and 2022 May 20 (green dots, a high-activity epoch). Full lines follow the oversampled average profiles constructed from the individual-FOV measurements: the cyan line for 2020 February 10, and the pink line for 2022 May 20. All shown data are normalized to the line-flank fluxes (an average of the left-wing and right-wing samples from Table 1). The vertical dotted lines delimit the line-core sample (Table 1).
Paper: Sun-as-a-Star Spectral Line Variability in the 300–2390 nm Wavelength Range
Authors: Sergey V. Marchenko, Antje Ludewig, Serena Criscuoli, Khaled Al Moulla, Debi P. Choudhary, Matthew T. DeLand, Greg Kopp, Erwin Loots, Emiel van der Plas, Pepijn Veefkind
Figure caption: In the upper row, the Fe I line 430 nm indices are plotted vs. the dark and Ca II indices. The lower row shows the Fe I 430 nm fluxes. The shown data sample the high-activity epoch (Table 2). Each metric is normalized, 81 days de-trended, then additionally normalized by the respective standard deviation.
Paper: Sun-as-a-Star Spectral Line Variability in the 300–2390 nm Wavelength Range
Authors: Sergey V. Marchenko, Antje Ludewig, Serena Criscuoli, Khaled Al Moulla, Debi P. Choudhary, Matthew T. DeLand, Greg Kopp, Erwin Loots, Emiel van der Plas, Pepijn Veefkind
Figure caption: Response functions to temperature fluctuations of the line-cores of three Fe I transitions. Continuous lines follow the FAL-C model (quiet Sun), and dashed lines show the FAL-P model (hot facula).
Paper: Sun-as-a-Star Spectral Line Variability in the 300–2390 nm Wavelength Range
Authors: Sergey V. Marchenko, Antje Ludewig, Serena Criscuoli, Khaled Al Moulla, Debi P. Choudhary, Matthew T. DeLand, Greg Kopp, Erwin Loots, Emiel van der Plas, Pepijn Veefkind
Figure caption: The upper panel compares the observed-calculated SL differences averaged over 200 central FOVs of the CCD detector. The lower panel shows a typical solar spectrum captured by TROPOMI, with some of the transitions marked by vertical lines. Note the difference in the y-scales of the panels.
Paper: Sun-as-a-Star Spectral Line Variability in the 300–2390 nm Wavelength Range
Authors: Sergey V. Marchenko, Antje Ludewig, Serena Criscuoli, Khaled Al Moulla, Debi P. Choudhary, Matthew T. DeLand, Greg Kopp, Erwin Loots, Emiel van der Plas, Pepijn Veefkind
Figure caption: The normalized (to 340 nm values) amplitudes of the TSIS-1 fluxes at the rotational (pink line) and solar-cycle (black line) timescales. The dotted blue line follows the rotational Fe I line-index amplitudes taken from Table 3.
Paper: Constraining the Location of the γ-Ray Emission Region in Radio-loud AGN 3C 380
Authors: Sanna Gulati, Debbijoy Bhattacharya, P. Sreekumar
Figure caption: Unbinned monthly averaged γ-ray light curve taken from the Fermi Light Curve Repository. The vertical line marks the time when AstroSat observed the source.
Paper: Multiphase Gas Nature in the Sub-parsec Region of the Active Galactic Nuclei. III. Eddington Ratio Dependence on the Structures of Dusty and Dust-free Outflows
Authors: Yuki Kudoh, Keiichi Wada, Nozomu Kawakatu, Mariko Nomura
Figure caption: From top to bottom, the spatial distributions denote the magnitude of outflow velocity, gas temperature, and number density for four models with different Eddington ratios, ﹩\mathrm{log}\left({\gamma }_{\mathrm{Edd}}\right)=0,-1,-2,﹩ and −3, respectively, at t = 4180 yr. The black curves represent the dust sublimation radius, which is invisible for ﹩\mathrm{log}({\gamma }_{\mathrm{Edd}})=-3﹩.
Paper: Multiphase Gas Nature in the Sub-parsec Region of the Active Galactic Nuclei. III. Eddington Ratio Dependence on the Structures of Dusty and Dust-free Outflows
Authors: Yuki Kudoh, Keiichi Wada, Nozomu Kawakatu, Mariko Nomura
Figure caption: (a) Models of the input AGN SEDs. The black lines are total SEDs for the Eddington ratio (γ Edd). The blue and red lines are the accretion disk and the disk corona components, respectively. (b) Same as (a), but for the angular dependence. The black lines are θ = 90° (pole-on), 60°, 20°, and 5◦ (mostly edge-on).
Paper: Mining for Protoclusters at z ∼ 4 from Photometric Data Sets with Deep Learning
Authors: Yoshihiro Takeda, Nobunari Kashikawa, Kei Ito, Jun Toshikawa, Rieko Momose, Kent Fujiwara, Yongming Liang, Rikako Ishimoto, Takehiro Yoshioka, Junya Arita, Mariko Kubo, Hisakazu Uchiyama
Figure caption: Detection performance per protocluster at z ∼ 4. The horizontal and vertical axes represent completeness and purity, respectively. The solid lines connecting the dots show the transition of the protocluster detection performance when the threshold for detecting protoclusters is varied as σ th = 1.5, 2.0, 2.5, 3.0, 3.5, and 4.0. The orange and blue, respectively, represent PCFNet and 2DBM, and the darker color indicates a higher threshold of detecting protoclusters. The smaller dots indicate each of the b = 100 bootstrap samples.
Paper: Mining for Protoclusters at z ∼ 4 from Photometric Data Sets with Deep Learning
Authors: Yoshihiro Takeda, Nobunari Kashikawa, Kei Ito, Jun Toshikawa, Rieko Momose, Kent Fujiwara, Yongming Liang, Rikako Ishimoto, Takehiro Yoshioka, Junya Arita, Mariko Kubo, Hisakazu Uchiyama
Figure caption: The architecture of PCFNet. The rounded squares represent each layer, and the numbers at the bottom show the input and output dimensions of the features. The squares represent the data at each stage, and the dimensions of the matrix are written inside. Prior is a single-layer shared-weight perceptron, and Classifier is a three-layer multilayer perceptron.
Paper: Mining for Protoclusters at z ∼ 4 from Photometric Data Sets with Deep Learning
Authors: Yoshihiro Takeda, Nobunari Kashikawa, Kei Ito, Jun Toshikawa, Rieko Momose, Kent Fujiwara, Yongming Liang, Rikako Ishimoto, Takehiro Yoshioka, Junya Arita, Mariko Kubo, Hisakazu Uchiyama
Figure caption: PR curve for protocluster member detection at z ∼ 4. The horizontal and vertical axes represent the recall and precision, respectively. The solid orange line represents the PR curve of PCFNet, the blue line represents that of the 2DBM, and the yellow line represents that of the 3DBM. The orange dotted line represents the recall and precision at 4σ for 2DBM. The orange star with black lines represents the point of PCFNet at σ th = 2.5.
Paper: Mining for Protoclusters at z ∼ 4 from Photometric Data Sets with Deep Learning
Authors: Yoshihiro Takeda, Nobunari Kashikawa, Kei Ito, Jun Toshikawa, Rieko Momose, Kent Fujiwara, Yongming Liang, Rikako Ishimoto, Takehiro Yoshioka, Junya Arita, Mariko Kubo, Hisakazu Uchiyama
Figure caption: Distribution of the halo mass of protoclusters at z = 0 in the simulation data. The solid lines represent the distribution of maximum halo masses at z = 0 of the protocluster candidates detected by each model, with orange and blue histograms representing PCFNet and 2DBM, respectively. The dashed pink line represents the distribution of maximum halo masses at z = 0 of actual protoclusters in the evaluation data. The gray region indicates that the halo mass at z = 0 is lower than the protocluster threshold.
Paper: Mining for Protoclusters at z ∼ 4 from Photometric Data Sets with Deep Learning
Authors: Yoshihiro Takeda, Nobunari Kashikawa, Kei Ito, Jun Toshikawa, Rieko Momose, Kent Fujiwara, Yongming Liang, Rikako Ishimoto, Takehiro Yoshioka, Junya Arita, Mariko Kubo, Hisakazu Uchiyama
Figure caption: The ratio of the protocluster member probabilities of the mock data with (p mask) and without (p) masked regions. The horizontal axis represents the percentage of the mask within the field of view (within a ﹩5^{\prime} ﹩ radius), and the vertical axis represents the ratio to the case without any masked regions. The orange line shows the fitting curve as a cubic function.
Paper: Mining for Protoclusters at z ∼ 4 from Photometric Data Sets with Deep Learning
Authors: Yoshihiro Takeda, Nobunari Kashikawa, Kei Ito, Jun Toshikawa, Rieko Momose, Kent Fujiwara, Yongming Liang, Rikako Ishimoto, Takehiro Yoshioka, Junya Arita, Mariko Kubo, Hisakazu Uchiyama
Figure caption: Sky distribution of the predicted probabilities of protocluster member galaxies and protocluster candidates at z ∼ 4 in the Deep and UltraDeep layers. Each point represents a galaxy, and the color indicates the probability of being a protocluster member galaxy predicted by PCFNet. The blue circles and cyan squares indicate the positions of the detected protocluster candidates by PCFNet and J. Toshikawa et al. (2024), respectively.
Paper: Mining for Protoclusters at z ∼ 4 from Photometric Data Sets with Deep Learning
Authors: Yoshihiro Takeda, Nobunari Kashikawa, Kei Ito, Jun Toshikawa, Rieko Momose, Kent Fujiwara, Yongming Liang, Rikako Ishimoto, Takehiro Yoshioka, Junya Arita, Mariko Kubo, Hisakazu Uchiyama
Figure caption: The MDN predictions z best vs. true distances z true in the simulation data. The color of each point represents the number of galaxies. The g-dropout galaxies in the HSC-SSP UltraDeep layer with known spectroscopic redshifts are marked with red stars.
Paper: Mining for Protoclusters at z ∼ 4 from Photometric Data Sets with Deep Learning
Authors: Yoshihiro Takeda, Nobunari Kashikawa, Kei Ito, Jun Toshikawa, Rieko Momose, Kent Fujiwara, Yongming Liang, Rikako Ishimoto, Takehiro Yoshioka, Junya Arita, Mariko Kubo, Hisakazu Uchiyama
Figure caption: Diagram of a merger tree. Each circle represents a halo merging from top to bottom. Larger circles indicate more massive halos. The red circle shows the cluster that is the root of the merger tree, and the blue circle shows the halo containing the core galaxy at z = 4. The gray area surrounded by the dashed line is the main branch in the merger tree, and the core galaxies are always included in the main branch.
Paper: Mining for Protoclusters at z ∼ 4 from Photometric Data Sets with Deep Learning
Authors: Yoshihiro Takeda, Nobunari Kashikawa, Kei Ito, Jun Toshikawa, Rieko Momose, Kent Fujiwara, Yongming Liang, Rikako Ishimoto, Takehiro Yoshioka, Junya Arita, Mariko Kubo, Hisakazu Uchiyama
Figure caption: The distributions of the number (left) and the maximal significance (right) of members of protocluster candidates at z ∼ 4 in the HSC-SSP Deep and UltraDeep layers.
Paper: Multiple Components of the Outflow in the Protostellar System HH 212: Outer Outflow Shell, Rotating Wind, Shocked Wind, and Jet
Authors: J. A. López-Vázquez, Chin-Fei Lee, Hsien Shang, Sylvie Cabrit, Ruben Krasnopolsky, Claudio Codella, Chun-Fan Liu, Linda Podio, Somnath Dutta, A. Murphy, Jennifer Wiseman
Figure caption: Composite images of the HH 212 protostellar system of the ALMA moment zero or integrated intensity of CO, SiO, and SO LV lines together with the 358 GHz continuum map of the disk. (a) All lines and continuum obtained with low-angular resolution data, ∼0.″37. (b) A zoomed-in image to the center of the system of all molecules and continuum obtained with high-angular resolution data, ∼0.″05. (c) A zoomed-in image of the center of the system of the CO and SiO molecular line emission, together with a continuum map. (d) A zoomed-in image of the center of the system of the CO and SO (LV) molecular line emission, together with a continuum map. Color codes are consistent across all labels. White contours start from 3σ in steps of 3σ, 6σ, 9σ, and 12σ, where σ = 1.24 mJy beam−1 for low-angular resolution data and σ = 0.15 mJy beam−1 for high-angular resolution data. The synthesized beams are shown in the lower left corner of all panels.
Paper: Multiple Components of the Outflow in the Protostellar System HH 212: Outer Outflow Shell, Rotating Wind, Shocked Wind, and Jet
Authors: J. A. López-Vázquez, Chin-Fei Lee, Hsien Shang, Sylvie Cabrit, Ruben Krasnopolsky, Claudio Codella, Chun-Fan Liu, Linda Podio, Somnath Dutta, A. Murphy, Jennifer Wiseman
Figure caption: The CO maps of the outflow associated with HH 212. (a) Blueshifted emission integrated from 1.7 to 12.7 km s−1. (b) Redshifted emission integrated from −9.3 to 1.7 km s−1. (c) Full range of the emission ±11 km s−1 around the systemic velocity. The contour levels start from 3σ in steps of 3σ, 6σ, 9σ, 12σ, and 15σ, where σ = 8.48 mJy beam−1 km s−1 and σ = 8.01 mJy beam−1 km s−1 for panels (a) and (b), respectively. While in panel (c), the contour levels start from 3σ in steps of 2σ, 4σ, 6σ, 8σ, 10σ, 12σ, and 14σ, where σ = 13.92 mJy beam−1 km s−1. The black arrows mark the position of the CO knots and the shocked wind, while the other components of the protostellar system, such as the CO shell and wind, are depicted by the red dashed lines and red arrows, respectively. The synthesized beams are shown in the lower left corner of all panels.
Paper: Multiple Components of the Outflow in the Protostellar System HH 212: Outer Outflow Shell, Rotating Wind, Shocked Wind, and Jet
Authors: J. A. López-Vázquez, Chin-Fei Lee, Hsien Shang, Sylvie Cabrit, Ruben Krasnopolsky, Claudio Codella, Chun-Fan Liu, Linda Podio, Somnath Dutta, A. Murphy, Jennifer Wiseman
Figure caption: Zoom around the jet of the CO maps of the HH 212 protostellar system of the CO molecular line emission. Green contours represent ALMA moment zero of the SiO molecular line emission. Red points show the position of the CO knots. The contours labels start from 10σ in steps of 1σ, 2σ, 3σ, 4σ, 5σ, 6σ, 7σ, and 8σ, where σ = 13.92 mJy beam−1 km s−1 for the CO emission and start from 9σ in steps of 2σ, 4σ, 6σ, and 8σ, where σ = 9.57 mJy beam−1 km s−1 for the SiO emission. The synthesized beams are shown in the lower left corner.
Paper: Multiple Components of the Outflow in the Protostellar System HH 212: Outer Outflow Shell, Rotating Wind, Shocked Wind, and Jet
Authors: J. A. López-Vázquez, Chin-Fei Lee, Hsien Shang, Sylvie Cabrit, Ruben Krasnopolsky, Claudio Codella, Chun-Fan Liu, Linda Podio, Somnath Dutta, A. Murphy, Jennifer Wiseman
Figure caption: The width of the CO knots' positions as a function of the projected distance to the central source. (a) Detected knots in the northern component. (b) Detected knots in the southern component. Green points depicted the SiO knots taken from C.-F. Lee et al. (2017a). The error bars show the uncertainties in the width and the position.
Paper: Intergalactic Medium Rotation Measure of Primordial Magnetic Fields
Authors: Salome Mtchedlidze, Paola Domínguez-Fernández, Xiaolong Du, Ettore Carretti, Franco Vazza, Shane Patrick O'Sullivan, Axel Brandenburg, Tina Kahniashvili
Figure caption: Evolution of RMIGM for all PMF models and corresponding logarithmic fits (gray dashed–dotted lines). Red dotted, dashed, and dashed–dotted lines show the RM-rms trends of the k102 model from the 5123 and 5123–10 nG normalization runs and the 10243–10 nG simulation, respectively.
Paper: Intergalactic Medium Rotation Measure of Primordial Magnetic Fields
Authors: Salome Mtchedlidze, Paola Domínguez-Fernández, Xiaolong Du, Ettore Carretti, Franco Vazza, Shane Patrick O'Sullivan, Axel Brandenburg, Tina Kahniashvili
Figure caption: Constraints on the magnetic field strength when their different correlation lengths are considered. Upper limits derived in this work, and in Planck Collaboration et al. (2016) are shown with filled black and gray markers, respectively. We note that for Planck Collaboration et al. (2016), λ B indicates the smoothing scale, and not the correlation length of the magnetic field.
Paper: Intergalactic Medium Rotation Measure of Primordial Magnetic Fields
Authors: Salome Mtchedlidze, Paola Domínguez-Fernández, Xiaolong Du, Ettore Carretti, Franco Vazza, Shane Patrick O'Sullivan, Axel Brandenburg, Tina Kahniashvili
Figure caption: Redshift depth evolution of the ∣RM∣ (excluding clusters) PDF for different PMF models with lognormal (red dashed) and Gaussian functions overplotted (green solid lines). The ∣RM∣ PDF in the inset panel has been obtained for one (z = 2) snapshot from our simulations.
Paper: Intergalactic Medium Rotation Measure of Primordial Magnetic Fields
Authors: Salome Mtchedlidze, Paola Domínguez-Fernández, Xiaolong Du, Ettore Carretti, Franco Vazza, Shane Patrick O'Sullivan, Axel Brandenburg, Tina Kahniashvili
Figure caption: ∣RM∣ PDF for different FOVs (solid and dashed lines) and different seedings (inset panels) for the uniform, stochastic scale-invariant, and stochastic k50 models. PDFs are obtained for z = 0.782 depth. At this redshift, the proper width of our simulated volume is 112.73 Mpc; the given statistics for the 6° and 8° FOVs correspond to 166.1 Mpc and 221.5 Mpc, respectively. For the latter statistics, we replicated the simulation data.
Paper: Intergalactic Medium Rotation Measure of Primordial Magnetic Fields
Authors: Salome Mtchedlidze, Paola Domínguez-Fernández, Xiaolong Du, Ettore Carretti, Franco Vazza, Shane Patrick O'Sullivan, Axel Brandenburg, Tina Kahniashvili
Figure caption: Magnetic field power spectrum at redshifts z = 2 (solid lines) and z = 0.494 (dashed lines) for different PMF models.
Paper: Proton Acceleration in Low-β Magnetic Reconnection with Energetic Particle Feedback
Authors: Jeongbhin Seo, Fan Guo, Xiaocan Li, Hui Li
Figure caption: (Left) The energy spectrum of nonthermal fluid at t = 0.5 with P NT,i  = 1P  g,i  (blue solid), P NT,i  = 0.5P  g,i  (red solid), and P NT,i  = 0P  g,i  (green solid). The dashed lines represent the analytic solutions for the respective shock compression ratios. (Right) The density profile around the shock region at t = 0.5. The color code used is the same as in the left panel.
Paper: Proton Acceleration in Low-β Magnetic Reconnection with Energetic Particle Feedback
Authors: Jeongbhin Seo, Fan Guo, Xiaocan Li, Hui Li
Figure caption: The magnetohydrodynamic shock tube with relativistic nonthermal fluid simulation yields results at t = 0.08 for (a) nonthermal fluid density in the rarefaction range, (b) nonthermal fluid density in the contact discontinuity and slow shock, (c) nonthermal fluid pressure in the same range, and (d) total pressure in the same range. The color code depends on the κ model and spatial diffusion coefficient as follows: no spatial diffusion (black), Bohm diffusion with κ ⊥/κ ∥ = 0.01 (blue), diffusion in MHD turbulence with κ ⊥/κ ∥ = 0.01 (red), Bohm diffusion with κ ⊥/κ ∥ = 1 (yellow), and diffusion in MHD turbulence with κ ⊥/κ ∥ = 1 (green).
Paper: Proton Acceleration in Low-β Magnetic Reconnection with Energetic Particle Feedback
Authors: Jeongbhin Seo, Fan Guo, Xiaocan Li, Hui Li
Figure caption: Left panels: The distribution of nonthermal fluid ∇ ·  v  for (a) CASE1, (b) CASE2, and (c) CASE3 at t/τ  A  = 7.8. The regions indicating reconnection exhaust and island merging are denoted by dotted and dotted–dashed red boxes. The merging of the magnetic islands induces pressure disturbances in the upstream region, which eventually evolve into slow shocks. (Right panels) The distribution of pressure for (d) CASE1, (e) CASE2, and (f) CASE3 at t/τ  A  = 7.8. Note that the color bar range is adjusted for (d) due to the dynamic range of P NT.
Paper: Proton Acceleration in Low-β Magnetic Reconnection with Energetic Particle Feedback
Authors: Jeongbhin Seo, Fan Guo, Xiaocan Li, Hui Li
Figure caption: 2D hydrodynamic shock tube with relativistic nonthermal fluid simulation results for (a) density of the plasma (blue dot) and nonthermal fluid (cyan dot), (b) v  x , (c) thermal plasma pressure (red dot) and total pressure (black dot), and (d) nonthermal fluid pressure at t = 0.1. Solid black lines indicate the analytic Riemann solution.