adsabs/AstroCLIMB huggingface dataset:
Paper: Unveiling the Dynamics of Dense Cores in Cluster-forming Clumps: A 3D Magnetohydrodynamics Simulation Study of Angular Momentum and Magnetic Field Properties
Authors: Shinichi. W. Kinoshita, Fumitaka Nakamura
Figure caption: Histograms of the ratio of the freefall time t ff to the magnetic braking timescale t L ≡ σ/2ρ ext v A for all bound cores in different models. Vertical dashed lines indicate the t ff/t L = 1.0. For most cores, t ff/t L is lower than 1.0, suggesting that the effect of magnetic braking is not large.
Paper: Unveiling the Dynamics of Dense Cores in Cluster-forming Clumps: A 3D Magnetohydrodynamics Simulation Study of Angular Momentum and Magnetic Field Properties
Authors: Shinichi. W. Kinoshita, Fumitaka Nakamura
Figure caption: Same as Figure 24 except for Collision Setup models. Fast collision velocity cases with θ 0 = 0° are shown in the left panel and those of θ 0 = 45° are shown in the middle panel. Slow collision velocity cases are shown in the right panel. ﹩\measuredangle [{{\boldsymbol{L}}}_{\mathrm{core}},{{\boldsymbol{B}}}_{\mathrm{core}}]﹩ does not depend on either E mag/∣E grav∣ and E kin/∣E grav∣.
Paper: Unveiling the Dynamics of Dense Cores in Cluster-forming Clumps: A 3D Magnetohydrodynamics Simulation Study of Angular Momentum and Magnetic Field Properties
Authors: Shinichi. W. Kinoshita, Fumitaka Nakamura
Figure caption: Time evolution of column density along the x-axis for the Rot-M5-B10P (top) and Rot-M5-B10D (bottom) model. Snapshots at 0.0, 0.2, and 0.4 Myr are shown. Mass-weighted magnetic field direction projected on the corresponding plane are shown as black lines. Ω 0 is indicated by green arrows. In both models, the gas forms a roughly perpendicular, disk-like structure with respect to the rotation axis. Other Rotation setup models also undergo similar temporal evolution, forming elongated structures that extend perpendicular to the rotation axis.
Paper: Unveiling the Dynamics of Dense Cores in Cluster-forming Clumps: A 3D Magnetohydrodynamics Simulation Study of Angular Momentum and Magnetic Field Properties
Authors: Shinichi. W. Kinoshita, Fumitaka Nakamura
Figure caption: Time evolution of column density along the x-axis for the Col-M5-B10P (top) and Col-M5-B10D (bottom) model. Snapshots at 0.0, 0.1, and 0.2 Myr are shown. Mass-weighted magnetic field direction projected on the corresponding plane are shown as black lines. Ω col is indicated by blue arrows. White arrows indicate the collision axis.
Paper: Identifying Acoustic Wave Sources on the Sun. II. Improved Filter Techniques for Source Wavefield Seismology
Authors: Shah Mohammad Bahauddin, Mark Peter Rast
Figure caption: Azimuthally averaged photospheric line-of-sight velocity (normalized by its mean and offset vertically with time) as a function of radial distance from the source site (r 0), illustrating the acoustic response of the atmosphere to a strong, isolated source in the intergranular lane. The plots are stacked vertically with time stamps starting from t = 1596 s (lowest plot) and ending at t = 1656 s (uppermost plot), with Δt = 2 s between them. Inset: region over which the azimuthal average was computed, showing the granule at t = 1614 s with colors corresponding to those in the main figure and indicating their radial distance from the source site. The cross indicates the photospheric position of the source assuming an approximately circular wave front. The annular region delineated by the inner and outer boundaries between the radial spokes is the region over which source wavefield seismology is conducted in Section 3.3.
Paper: Identifying Acoustic Wave Sources on the Sun. II. Improved Filter Techniques for Source Wavefield Seismology
Authors: Shah Mohammad Bahauddin, Mark Peter Rast
Figure caption: Power (integrated amplitude squared) of the three-difference signal amplitude for a varying signal velocity and temporal sampling period in a MURaM grid (16 km spatial pixel). The dashed white curve represents the criterion Δt = Δx/v ph, where optimal sampling is achieved and the amplitude of the difference signal is maximum. The dashed horizontal black line indicates the approximate sound speed at the surface of the MURaM photosphere and intersects the dashed white curve at the optimal Δt sampling of 2 s for a photospheric source. The phase speed of the wave fronts generated by deeper sources are higher and therefore must be sampled at a higher cadence for optimal sampling. Inset:  power of the three-difference signal amplitude vs. temporal sampling period for v = 8 km s−1. For clarity, the relation is arbitrarily fit by a third-order polynomial (dashed line).
Paper: Identifying Acoustic Wave Sources on the Sun. II. Improved Filter Techniques for Source Wavefield Seismology
Authors: Shah Mohammad Bahauddin, Mark Peter Rast
Figure caption: A narrow Gaussian perturbation moving with velocity v is sampled with different temporal sampling intervals at a fix spatial grid point (left column). Time t = 0 corresponds to the time the peak signal crosses that sampling location. The spatial σ of the perturbation is 16 km (the signal is spatially sampled at the Nyquist limit of the MURaM spatial frequency), and the velocity of the perturbation is 8 km s−1 (photospheric sound speed). When the perturbation is oversampled (first and second rows), application of three differences yields a low amplitude at all times (right column). For undersampled perturbation (fourth row), the three-difference operation fails to produce a usable n-difference signal (see text). When the perturbation is critically sampled (third row), satisfying the relationship Δt = Δx/v ph, the three-difference operation produces the strongest response.
Paper: Identifying Acoustic Wave Sources on the Sun. II. Improved Filter Techniques for Source Wavefield Seismology
Authors: Shah Mohammad Bahauddin, Mark Peter Rast
Figure caption: Comparison between the original MURaM atmosphere and the line-of-sight velocity u  z  in panel (a), horizontal velocity magnitude u  h  in panel (b), and sound speed c  s  in panel (c) as deduced from inversions of the source wavefield at five heights between the source depth (−192 km) and photosphere (0 km). For each, the simulation values are shown in the top row, values obtained by inversion are shown in the middle row, and the pointwise correlation between them is plotted in the bottom row.
Paper: Identifying Acoustic Wave Sources on the Sun. II. Improved Filter Techniques for Source Wavefield Seismology
Authors: Shah Mohammad Bahauddin, Mark Peter Rast
Figure caption: Ratio of the amplitude of a propagating wave to the standard deviation of the granular fluctuations (S/N) after application of an n-difference filter as a function of n. In the upflow regions of granulation, the S/N quickly rises for n ≤ 3 and plateaus near its maximum, n ≥ 5–6. These are similar values to those deduced from a convolutional neural network (Bahauddin & Rast 2021).
Paper: Identifying Acoustic Wave Sources on the Sun. II. Improved Filter Techniques for Source Wavefield Seismology
Authors: Shah Mohammad Bahauddin, Mark Peter Rast
Figure caption: Top: change of amplitude A (normalized by the source amplitude) at the photosphere as a function of horizontal distance from the source position for various source depths. Bottom: change in photospheric wave-front phase velocity v ph with distance. As the wave front passes through the surface, wave fronts from shallower sources undergo faster changes in phase velocity and saturate at a lower phase speed (the mean sound speed at the source depth) with distance.
Paper: Identifying Acoustic Wave Sources on the Sun. II. Improved Filter Techniques for Source Wavefield Seismology
Authors: Shah Mohammad Bahauddin, Mark Peter Rast
Figure caption: Coefficient of determination (R 2) between the MURaM atmospheric parameters and the inverted parameters calculated as a measure of strength of the model. The correlation rapidly decreases with depth below d ≈ −80 km of the photosphere.
Paper: Crossing the Rubicon of Reionization with z ∼ 5 QSOs
Authors: Andrea Grazian, Konstantina Boutsia, Emanuele Giallongo, Stefano Cristiani, Fabio Fontanot, Manuela Bischetti, Angela Bongiorno, Giorgio Calderone, Guido Cupani, Valentina D'Odorico, Chiara Feruglio, Fabrizio Fiore, Francesco Guarneri, Matteo Porru, Ivano Saccheo
Figure caption: The QSO luminosity function at z ∼ 5 from the HSC-Udeep and HSC-Wide surveys. The filled green pentagon shows the space density of z ∼ 5 QSOs in the HSC-Udeep area, while the open green pentagon shows the space density in the HSC-Wide area, considering only confirmed QSOs with available spectroscopic redshifts. These values are a factor of ∼2–3 larger than previous determinations available in the literature, highlighted by small symbols. The magenta line is model 4 of Pan et al. (2022).
Paper: Crossing the Rubicon of Reionization with z ∼ 5 QSOs
Authors: Andrea Grazian, Konstantina Boutsia, Emanuele Giallongo, Stefano Cristiani, Fabio Fontanot, Manuela Bischetti, Angela Bongiorno, Giorgio Calderone, Guido Cupani, Valentina D'Odorico, Chiara Feruglio, Fabrizio Fiore, Francesco Guarneri, Matteo Porru, Ivano Saccheo
Figure caption: The completeness of the HSC-Udeep and HSC-Wide surveys at different z-band magnitudes (18.5, 19.0, 19.5, and 20.0) as a function of redshift. The completeness is derived through simulations, as described in Section 4.1.
Paper: Crossing the Rubicon of Reionization with z ∼ 5 QSOs
Authors: Andrea Grazian, Konstantina Boutsia, Emanuele Giallongo, Stefano Cristiani, Fabio Fontanot, Manuela Bischetti, Angela Bongiorno, Giorgio Calderone, Guido Cupani, Valentina D'Odorico, Chiara Feruglio, Fabrizio Fiore, Francesco Guarneri, Matteo Porru, Ivano Saccheo
Figure caption: The G − R vs. I − Z color selection criterion for z ∼ 5 QSO candidates in the HSC-Wide survey. The legend of symbols is the same as that of Figure 1.
Paper: Crossing the Rubicon of Reionization with z ∼ 5 QSOs
Authors: Andrea Grazian, Konstantina Boutsia, Emanuele Giallongo, Stefano Cristiani, Fabio Fontanot, Manuela Bischetti, Angela Bongiorno, Giorgio Calderone, Guido Cupani, Valentina D'Odorico, Chiara Feruglio, Fabrizio Fiore, Francesco Guarneri, Matteo Porru, Ivano Saccheo
Figure caption: The photoionization rate of the IGM measured by Lyman forest fitting (Bolton & Haehnelt 2007; Wyithe & Bolton 2011; Becker & Bolton 2013; Davies et al. 2018; Faucher-Giguère 2020; Gallego et al. 2021; Gaikwad et al. 2023) and with the proximity effect (Calverley et al. 2011). The ionizing background produced by bright QSOs and faint AGN at z ∼ 5 is shown by the blue square, assuming a LyC escape fraction of 70%.
Paper: Crossing the Rubicon of Reionization with z ∼ 5 QSOs
Authors: Andrea Grazian, Konstantina Boutsia, Emanuele Giallongo, Stefano Cristiani, Fabio Fontanot, Manuela Bischetti, Angela Bongiorno, Giorgio Calderone, Guido Cupani, Valentina D'Odorico, Chiara Feruglio, Fabrizio Fiore, Francesco Guarneri, Matteo Porru, Ivano Saccheo
Figure caption: The optical spectrum of the newly discovered QSO ID = 124850 in the HSC-Wide area. This object has been confirmed as a QSO at z spec = 5.021, based on the identification of broad Lyα, N V, Si IV, and C IV emission lines. The red line marks the zero level of the continuum.(The data used to create this figure are available.)
Paper: Crossing the Rubicon of Reionization with z ∼ 5 QSOs
Authors: Andrea Grazian, Konstantina Boutsia, Emanuele Giallongo, Stefano Cristiani, Fabio Fontanot, Manuela Bischetti, Angela Bongiorno, Giorgio Calderone, Guido Cupani, Valentina D'Odorico, Chiara Feruglio, Fabrizio Fiore, Francesco Guarneri, Matteo Porru, Ivano Saccheo
Figure caption: The best-fit SED (left) and the χ 2(z phot) at different redshifts (right) for color-selected QSO candidates in the HSC-Udeep survey.
Paper: Crossing the Rubicon of Reionization with z ∼ 5 QSOs
Authors: Andrea Grazian, Konstantina Boutsia, Emanuele Giallongo, Stefano Cristiani, Fabio Fontanot, Manuela Bischetti, Angela Bongiorno, Giorgio Calderone, Guido Cupani, Valentina D'Odorico, Chiara Feruglio, Fabrizio Fiore, Francesco Guarneri, Matteo Porru, Ivano Saccheo
Figure caption: The best-fit SED (left) and the χ 2(z phot) at different redshifts (right) for spectroscopically confirmed QSOs at z ∼ 5 in the HSC-Wide survey.
Paper: Crossing the Rubicon of Reionization with z ∼ 5 QSOs
Authors: Andrea Grazian, Konstantina Boutsia, Emanuele Giallongo, Stefano Cristiani, Fabio Fontanot, Manuela Bischetti, Angela Bongiorno, Giorgio Calderone, Guido Cupani, Valentina D'Odorico, Chiara Feruglio, Fabrizio Fiore, Francesco Guarneri, Matteo Porru, Ivano Saccheo
Figure caption: The best-fit SED (left) and the χ 2(z phot) at different redshifts (right) for color-selected QSO candidates in the HSC-Wide survey.
Paper: Effects of Barnett Magnetic Dipole–Dipole Interaction on Grain Growth and Destruction
Authors: Thiem Hoang, Bao Truong
Figure caption: Enhanced collision rate of SPM grains by Barnett dipole–dipole interaction assuming grains having Brownian motion in the gas and dust of temperature T gas = T dust = 100 K, calculated for different iron inclusions, N cl. Dashed colored lines represent the variation of disruption sizes a disr by RATs, assuming different tensile strength of grains ﹩{S}_{\max }={10}^{9}\mbox{--}{10}^{11}\,\mathrm{erg}\,{\mathrm{cm}}^{-3}﹩. The Barnett dipole–dipole interaction is more effective with increasing γ U/n 1. However, the effect of RAT-D could disrupt large grains into smaller fragments and constrain grain collisions by dipole–dipole interaction, particularly in environments of a strong radiation field or lower gas density (γ U/n 1 > 1). The effect of Barnett dipole–dipole interaction on grain collisions is then more important for SPM grains having high N cl > 102.
Paper: Effects of Barnett Magnetic Dipole–Dipole Interaction on Grain Growth and Destruction
Authors: Thiem Hoang, Bao Truong
Figure caption: Same as Figure 2 but with T gas = T dust = 500 K. The cross section ﹩{({b}_{\max }/a)}^{2}﹩ tends to decrease due to the efficient gas collision damping and strong thermal fluctuation of electron spins inside grains in environments with higher gas and dust temperature.
Paper: Effects of Barnett Magnetic Dipole–Dipole Interaction on Grain Growth and Destruction
Authors: Thiem Hoang, Bao Truong
Figure caption: Schematic illustrations of the magnetic dipole–dipole interaction between two grains of equal size (a) with magnetic moments μ and ﹩\mu ^{\prime} ﹩ induced by the Barnett effect in two optimal scenarios: (a)  μ  parallel to ﹩{\boldsymbol{\mu }}^{\prime} ﹩ and the grain moves along the magnetic field, and (b)  μ  antiparallel to ﹩{\boldsymbol{\mu }}^{\prime} ﹩ and the grain moves perpendicular to the magnetic field. We consider the projectile grain moving with an initial velocity v gg relative to the target grain at rest with the impact parameter ﹩{b}_{\max }﹩.
Paper: Modeling of the High-velocity Jet Powered by the Massive Star MWC 349A
Authors: Antonio Martínez-Henares, Izaskun Jiménez-Serra, Jesús Martín-Pintado, Nuria Huélamo, Sirina Prasad, Qizhou Zhang, James Moran, Yue Cao, Alejandro Báez-Rubio
Figure caption: Four different jet orientations (upper panels) and the resulting H30α centroid maps from the model (lower panels). The jet panels represent those points where the jet velocity is v ≥ 0.5v jet for a collimation ψ 0 = 0.4. This corresponds to a semi-opening angle of 24° by substituting in Equation (3). Blue points are those where z < 0, i.e., where the emission is blueshifted as seen by the observer; red points, conversely, represent redshifted emission. The jet orientation (θ jet, φ jet) for each case is indicated at the top of the upper panels. The leftmost model corresponds to the final model presented in Figure 4.
Paper: Modeling of the High-velocity Jet Powered by the Massive Star MWC 349A
Authors: Antonio Martínez-Henares, Izaskun Jiménez-Serra, Jesús Martín-Pintado, Nuria Huélamo, Sirina Prasad, Qizhou Zhang, James Moran, Yue Cao, Alejandro Báez-Rubio
Figure caption: Centroid maps for the H30α (left) and H26α (right) lines from the model with an extended radial velocity range of (−120, 135) km s−1 to show the behavior of the second turnaround of the jet branch at the most extreme radial velocities. The shift toward the disk seen in the observations is predicted by our best-fit model, but at a larger velocity than observed with ALMA as shown here.
Paper: Modeling of the High-velocity Jet Powered by the Massive Star MWC 349A
Authors: Antonio Martínez-Henares, Izaskun Jiménez-Serra, Jesús Martín-Pintado, Nuria Huélamo, Sirina Prasad, Qizhou Zhang, James Moran, Yue Cao, Alejandro Báez-Rubio
Figure caption: Centroid maps for the H30α emission from observations (colored points with errors) and from the model (colored line) with an extended radial velocity range of (−120, 135) km s−1 to show the effect of the symmetrical orientation of the jet vs. a slight asymmetry. The three leftmost panels represent a symmetrical jet, where θ jet represents the orientation of the northern jet facing the observer (φ jet = 0°). The rightmost panel corresponds to the final model presented in Figure 4 consisting of a slightly asymmetrical jet, where the southern cone is more inclined than the northern one. In the four models, φ jet,north = 0°, φ jet,south = 180°.
Paper: Modeling of the High-velocity Jet Powered by the Massive Star MWC 349A
Authors: Antonio Martínez-Henares, Izaskun Jiménez-Serra, Jesús Martín-Pintado, Nuria Huélamo, Sirina Prasad, Qizhou Zhang, James Moran, Yue Cao, Alejandro Báez-Rubio
Figure caption: Centroid maps of the H30α line from the same model with full Keplerian rotation of the outflow (left), no rotation (center), and half of the rotation (right), which is the final model. The more rotation included in the model, the further away the jet branches get from the rotation axis.
Paper: Modeling of the High-velocity Jet Powered by the Massive Star MWC 349A
Authors: Antonio Martínez-Henares, Izaskun Jiménez-Serra, Jesús Martín-Pintado, Nuria Huélamo, Sirina Prasad, Qizhou Zhang, James Moran, Yue Cao, Alejandro Báez-Rubio
Figure caption: H30α line profile from observations (blue) and a model (red) where only the ionized wind expanding at 60 km s−1 is included. We show a zoom-in at the lower intensity values to highlight the behavior of the wing humps.
Paper: Variability of Magnetic Hot Stars from the TESS Observations
Authors: Dong-Xiang Shen, Gang Li, Iskandar Abdusamatjan, Jian-Ning Fu, Chun-Hua Zhu, Jin-Long Yu, Yu Zhang, Guo-Liang Lü, Nan-Nan Zhai, Jin-Zhong Liu
Figure caption: The SLF variability analysis results of Ap/Bp stars in our sample. The pair-wise relationships between the fitting parameters, α 0, ν char, and γ in Equation (2) are presented in the top row. Each star is color-coded by the luminosity. The arrows extending from the single colored circle indicate the direction of variation in the fitting parameters of the SLF variabilities, revealing trends in the fitting parameters across the different sectors. Location of the stars within our sample in the HR diagram are presented in bottom row. Each star is color-coded by the fitting parameters α 0 (left panel) and ν char (right panel). The symbol sizes are proportional to the γ-values. Evolutionary tracks are plotted as gray lines. A typical error bar is shown in the top-left corner.
Paper: Variability of Magnetic Hot Stars from the TESS Observations
Authors: Dong-Xiang Shen, Gang Li, Iskandar Abdusamatjan, Jian-Ning Fu, Chun-Hua Zhu, Jin-Long Yu, Yu Zhang, Guo-Liang Lü, Nan-Nan Zhai, Jin-Zhong Liu
Figure caption: The SLF variability analysis results of upper-main-sequence stars in our sample. The pair-wise relationships between the fitting parameters, α 0, ν char and γ in Equation (2) are presented in the top row. Each star is color-coded by the luminosity. The arrows extending from the single colored circle indicate the direction of variation in the fitting parameters of the SLF variabilities, revealing trends in the fitting parameters across the different sectors. The locations of the stars within our sample in the HR diagram are presented in the bottom row. Each star is color-coded by the fitting parameters α 0 (left panel) and ν char (right panel). The symbol sizes are proportional to the γ-values. Evolutionary tracks are plotted as gray lines.
Paper: Variability of Magnetic Hot Stars from the TESS Observations
Authors: Dong-Xiang Shen, Gang Li, Iskandar Abdusamatjan, Jian-Ning Fu, Chun-Hua Zhu, Jin-Long Yu, Yu Zhang, Guo-Liang Lü, Nan-Nan Zhai, Jin-Zhong Liu
Figure caption: The relationship between the fitting parameters (α 0,  ν char,  and γ) and the polar strength (B p) of the surface dipole magnetic fields is presented in the top panels. Each star is color-coded by luminosity. The Spearman’s rank correlation coefficient, R, and the corresponding p-value are also provided. The HR diagrams of 37 magnetic hot stars are shown in bottom panels. Each star is represented by a circle, which is also color-coded by the polar strength of the surface dipole magnetic fields (B p). The symbol sizes of the points are proportional to the fitting parameter log α 0 (bottom-left panel) and ν char (bottom-right panel), respectively.
Paper: Machine-learning Cosmology from Void Properties
Authors: Bonny Y. Wang, 玥 汪, Alice Pisani, Francisco Villaescusa-Navarro, Benjamin D. Wandelt
Figure caption: Void density contrast and ellipticity as a function of radii from all the simulations in the high-resolution QUIJOTE Latin hypercube simulations at z = 0.0. The blue dots and error bars represent the mean and the standard deviation in the mean of each bin. Void radii are binned from 10.5 to 61.5 Mpc h−1.
Paper: Variability of Magnetic Hot Stars from the TESS Observations
Authors: Dong-Xiang Shen, Gang Li, Iskandar Abdusamatjan, Jian-Ning Fu, Chun-Hua Zhu, Jin-Long Yu, Yu Zhang, Guo-Liang Lü, Nan-Nan Zhai, Jin-Zhong Liu
Figure caption: The pair-wise relationships between the luminosities and fitting parameters (log α 0, ν char, and γ) for our sample of more massive magnetic hot stars. The Spearman rank-order correlation coefficients and p-values are provided in the figures accordingly.
Paper: Variability of Magnetic Hot Stars from the TESS Observations
Authors: Dong-Xiang Shen, Gang Li, Iskandar Abdusamatjan, Jian-Ning Fu, Chun-Hua Zhu, Jin-Long Yu, Yu Zhang, Guo-Liang Lü, Nan-Nan Zhai, Jin-Zhong Liu
Figure caption: The pair-wise relationships between the luminosities and fitting parameters (log α 0, ν char, and γ) for our sample of Ap/Bp stars. The Spearman rank-order correlation coefficients and p-values are provided in the figures accordingly.
Paper: Variability of Magnetic Hot Stars from the TESS Observations
Authors: Dong-Xiang Shen, Gang Li, Iskandar Abdusamatjan, Jian-Ning Fu, Chun-Hua Zhu, Jin-Long Yu, Yu Zhang, Guo-Liang Lü, Nan-Nan Zhai, Jin-Zhong Liu
Figure caption: The light curves (left panels) and amplitude spectra (right panels) of binary stars. The markers in the amplitude spectra have the same meaning as in Figure 7.