adsabs/AstroCLIMB huggingface dataset:
Paper: The Thermonuclear X-Ray Bursts of 4U 1730–22
Authors: Peter Bult, Giulio C. Mancuso, Tod E. Strohmayer, Arianna C. Albayati, Diego Altamirano, Douglas J. K. Buisson, Jérôme Chenevez, Sebastien Guillot, Tolga Güver, Wataru Iwakiri, Gaurava K. Jaisawal, Mason Ng, Andrea Sanna, Jean H. Swank
Figure caption: Histogram of the flux fraction contributed by the blackbody component. Each histogram bar is color coded according to the average blackbody normalization in that bin.
Paper: Binary Evolution and Blue Stragglers in Different Regions of the Color–Magnitude Diagrams of Globular Clusters with Different Ages
Authors: Dengkai Jiang
Figure caption: Locations of the unresolved BS binaries, the BS components, and the companions in the CMD at 10 Gyr. The upper and lower panels are for the MT and post-MT BS binaries, respectively, while the left, middle, and right panels show the locations of the unresolved BS binaries, the BS components, and the companions, respectively. The color bars represent the formation times of the BS components (t BS, the time when the secondaries appear in the BS region of the cluster). Black dashed–dotted, black dotted, and gray solid lines show the ZAMS, ZAMS+0.75, and 10 Gyr isochrone, respectively. For comparison, the locations of the two kinds of unresolved BS binaries are also shown in these panels as gray points.
Paper: Binary Evolution and Blue Stragglers in Different Regions of the Color–Magnitude Diagrams of Globular Clusters with Different Ages
Authors: Dengkai Jiang
Figure caption: Locations of the two kinds of unresolved BS binaries in the CMDs at 10, 11, 12, 13, 14, and 15 Gyr. Red and blue points show the locations of the MT and post-MT BS binaries, respectively. Black dashed–dotted, black dotted, and gray solid lines show the ZAMS, ZAMS+0.75, and isochrones, respectively.
Paper: Physical Correlations Lead to Kappa Distributions
Authors: G. Livadiotis, D. J. McComas
Figure caption: Analogy between mass defect M D and entropy defect S D, and their equivalence to a change in energy level (per c 2 and temperature, respectively) during the composition of a system. (a) The mass defect M D constitutes the missing mass between the mass of a composite particle system and the sum of the masses of its constituents A and B; it is caused by the release of the binding energy (mass). (b) The entropy defect S D constitutes the missing entropy between the entropy of a composite particle system and the sum of the entropies of its constituents A and B; it is caused by the order induced by the existence of particle correlations and represents the release of a “binding entropy.”
Paper: Physical Correlations Lead to Kappa Distributions
Authors: G. Livadiotis, D. J. McComas
Figure caption: The scheme demonstrates the contribution of this paper in understanding the role and importance of the kappa distribution function in space plasma physics. Earlier studies have shown the correlations in particle velocities induced by the specific formulation of kappa distributions (Abe 1999; Livadiotis & McComas 2011a; Livadiotis 2015b; Livadiotis et al. 2021). Here, we showed for the first time the reverse result: the presence of correlations among particles residing in stationary states cannot be the outcome of any non-Maxwellian distribution but it is only connected to kappa distributions.
Paper: Physical Correlations Lead to Kappa Distributions
Authors: G. Livadiotis, D. J. McComas
Figure caption: The scheme demonstrates the method used in this paper to derived the entropic function.
Paper: Implicit Large-eddy Simulations of Global Solar Convection: Effects of Numerical Resolution in Nonrotating and Rotating Cases
Authors: G. Guerrero, A. M. Stejko, A. G. Kosovichev, P. K. Smolarkiewicz, A. Strugarek
Figure caption: Radial profiles of the effective viscosity, ν eff (panel a), and the thermal conductivity κ eff for the nonrotating simulations represented with different colors. The shadows show the standard deviation for the highest wavenumbers resolved in each simulation. The average value over the convection zone as a function of the longitudinal resolution N  ϕ  is presented in panel (c). The thin continuous line shows the corresponding scaling laws.
Paper: Implicit Large-eddy Simulations of Global Solar Convection: Effects of Numerical Resolution in Nonrotating and Rotating Cases
Authors: G. Guerrero, A. M. Stejko, A. G. Kosovichev, P. K. Smolarkiewicz, A. Strugarek
Figure caption: Reynolds stresses resulting from simulations (a) R1x24, (b) R2x24, and (c) R4x24.
Paper: Implicit Large-eddy Simulations of Global Solar Convection: Effects of Numerical Resolution in Nonrotating and Rotating Cases
Authors: G. Guerrero, A. M. Stejko, A. G. Kosovichev, P. K. Smolarkiewicz, A. Strugarek
Figure caption: Same as Figure 18 but for the rotating simulations R1x24 (blue line in panels (a) and (b)), R2x24 (red), and R4x24 (green).
Paper: Forecasting Pulsar Timing Array Sensitivity to Anisotropy in the Stochastic Gravitational Wave Background
Authors: Nihan Pol, Stephen R. Taylor, Joseph D. Romano
Figure caption: The evolution of detection statistics with the sensitivity FOM, N psr/σ, defined in Section 4.3 for an ideal PTA with an isotropic injected GWB. The points represent the medians, while the error bars represent the 95% confidence intervals across 104 noise realizations. Top: Evolution of the total S/N as a function of the sensitivity FOM. This scaling relation implies that PTAs with either a large number of pulsars or small cross-correlation uncertainties (or both) will return a larger total S/N value than a PTA with fewer pulsars and/or larger cross-correlation uncertainty. Bottom: The evolution of the decision threshold as a function of the sensitivity FOM. This implies that PTAs with fewer pulsars or larger cross-correlation uncertainties will have higher decision thresholds, while PTAs with more pulsars and smaller cross-correlation uncertainties will have lower decision thresholds.
Paper: Forecasting Pulsar Timing Array Sensitivity to Anisotropy in the Stochastic Gravitational Wave Background
Authors: Nihan Pol, Stephen R. Taylor, Joseph D. Romano
Figure caption: The evolution of the total, isotropic, and anisotropic S/N values over 104 noise realizations as a function of cross-correlation uncertainty for an ideal PTA with 100 pulsars and an isotropic GWB injection. The points represent the median, while the error bars represent the 95% confidence intervals on the distribution of the S/N values. A black dashed line corresponding to the scaling relation in Section 4.2 is shown for reference. For low cross-correlation uncertainties, the total and isotropic S/N values have identically large values relative to the anisotropic S/N, implying strong evidence for an isotropic GWB in the data. These S/N values decrease as the cross-correlation uncertainty increases, implying loss of confidence in the detection of a GWB as well as loss of ability to distinguish isotropy from anisotropy. The anisotropic S/N shows little evolution across uncertainties, though the better fit provided by the additional degrees of freedom in an anisotropic model prevents this S/N from being consistent with zero for small cross-correlation uncertainties.
Paper: Forecasting Pulsar Timing Array Sensitivity to Anisotropy in the Stochastic Gravitational Wave Background
Authors: Nihan Pol, Stephen R. Taylor, Joseph D. Romano
Figure caption: The evolution of the cross-correlation uncertainty across all pulsars and 100 noise realizations of the realistic PTA data set simulations described in Section 5. The evolution of the median cross-correlation uncertainty can be approximately described by σ ∝ T −7/2, which is shallower than the scaling law prediction of σ ∝ T −13/3 for the weak-signal regime in Section 4.2, but steeper than the strong-signal regime prediction of σ ∝ T −1/2. This implies that the NANOGrav PTA is in the intermediate-signal regime, which is corroborated by the fact that the lowest frequencies of the PTA are now dominated by a common-spectrum process (interpreted as the GWB) as shown in Arzoumanian et al. (2020).
Paper: Forecasting Pulsar Timing Array Sensitivity to Anisotropy in the Stochastic Gravitational Wave Background
Authors: Nihan Pol, Stephen R. Taylor, Joseph D. Romano
Figure caption: Example recovery of an anisotropic GWB using the square-root spherical harmonic basis described in Section 2. These simulations are based on an ideal PTA consisting of 100 pulsars, with a cross-correlation uncertainty of 0.01 across all pulsar pairs, while the anisotropy is based on a realistic population of inspiraling SMBHBs (Taylor et al. 2020). Top: The true and recovered angular power spectra, as well as the percent difference between them, where both are normalized such that the power in the l = 0 mode is C 0 = 4π. Bottom: The sky map of the GWB power corresponding to the recovered angular power spectrum. The contours represent the true distribution of the GWB power on the sky for the anisotropic GWB, while the stars represent the positions of the simulated pulsars on the sky.
Paper: Forecasting Pulsar Timing Array Sensitivity to Anisotropy in the Stochastic Gravitational Wave Background
Authors: Nihan Pol, Stephen R. Taylor, Joseph D. Romano
Figure caption: The evolution of the total S/N values for an ideal PTA with 100 pulsars and an isotropic injected GWB. The points represent the median values across 104 noise realizations, while the errors represent 95% confidence intervals. Left: Evolution of the total S/N as a function of number of pulsars in the PTA for different values of cross-correlation uncertainty. A black dashed line corresponding to the scaling relation in Section 4.2 is shown for reference. Right: Evolution of the total S/N as a function of the cross-correlation uncertainty for different numbers of pulsars in the PTA. A black dashed line corresponding to the scaling relation in Section 4.2 is shown for reference. Together, these results show that the total S/N is higher for a PTA with small cross-correlation uncertainties and a large number of pulsars.
Paper: Forecasting Pulsar Timing Array Sensitivity to Anisotropy in the Stochastic Gravitational Wave Background
Authors: Nihan Pol, Stephen R. Taylor, Joseph D. Romano
Figure caption: The evolution of the decision threshold, C  l  th, for an ideal PTA with an isotropic injected GWB. The points represent the median values while the errors represent the 95% confidence interval values across 104 noise realizations. Top: Evolution of the decision threshold per mode for different numbers of pulsars in the PTA. Bottom: Evolution of the decision threshold for different cross-correlation uncertainties. These values are generated for an ideal PTA with 100 pulsars and a cross-correlation uncertainty of 0.1. These results show that the decision threshold is lower for PTAs that have a larger number of pulsars and smaller cross-correlation uncertainties.
Paper: Forecasting Pulsar Timing Array Sensitivity to Anisotropy in the Stochastic Gravitational Wave Background
Authors: Nihan Pol, Stephen R. Taylor, Joseph D. Romano
Figure caption: Evolution of the S/N values for the realistic simulations described in Section 5. The total, isotropic, and anisotropic S/N are shown by the blue, green, and orange histograms, respectively. Since the injected GWB is isotropic, we see the total and isotropic S/N values increase as a function of the timing baseline, while the anisotropic S/N stays consistent with zero for all baselines.
Paper: Forecasting Pulsar Timing Array Sensitivity to Anisotropy in the Stochastic Gravitational Wave Background
Authors: Nihan Pol, Stephen R. Taylor, Joseph D. Romano
Figure caption: Evolution of decision threshold for realistic simulations described in Section 5. Left: Evolution of the decision threshold as a function of timing baseline for all spherical harmonic multipoles. The decision threshold decreases with an increase in the timing baseline, and higher spherical harmonic multipoles have a higher decision threshold than lower multipoles. Right: Evolution of the decision threshold across spherical harmonic multipoles for different timing baselines. We also plot the Bayesian 95% upper limits on anisotropy derived in Taylor et al. (2015) from EPTA Data Release 1. As these realistic simulations have 45 pulsars with different noise properties resulting in different cross-correlation uncertainties per pulsar pair, we see the sensitivity of the PTA saturate at higher multipoles.
Paper: A Global Simulation of the Dynamo, Zonal Jets, and Vortices on Saturn
Authors: Rakesh Kumar Yadav, Hao Cao, Jeremy Bloxham
Figure caption: Panel (a) shows the variation of the electrical conductivity as a function of the radius. The light-shaded region (from radius 0.62 to 0.8) is the SSL and the dark-shaded region (radius 0.9 to 1) has zero electrical conductivity. Panel (b) shows the axisymmetric zonal flow on the surface of the simulation and on Saturn’s cloud deck, given in terms of the Rossby number u/(Ωr  o ) on the left axis and in meters per second on the right axis. We use the Cassini data set (from the “CB” filter) covering a period from year 2004 to year 2009 presented by Garcia-Melendo et al. (2011). The data has been rescaled to a recent estimate of Saturn’s rotation period of 10h33m38s (Mankovich et al. 2019). We assume a mean radius of 5.8232 × 107 m for Saturn to convert the observed wind speeds to a radius-based Rossby number. The top half of panel (c) shows the instantaneous axisymmetric zonal flow on a meridional plane, given in terms of the Reynolds number Re = u d/ν; the lower half of the panel shows 5 times the magnetic Reynolds number Rm defined by u d/λ, where λ is the local magnetic diffusivity. The factor of 5 is applied for the Rm half-panel to share the same color map with the Re half-panel.
Paper: A Global Simulation of the Dynamo, Zonal Jets, and Vortices on Saturn
Authors: Rakesh Kumar Yadav, Hao Cao, Jeremy Bloxham
Figure caption: Panel (a) shows the magnitude of the radial magnetic field at various representative depths. The field magnitude is given in Elsässer number units; see the method section for its definition. The range of the color map is shown at the lower left side of each subpanel. The intersection of the tangent cylinder created by the inner core at r  i  and a given spherical surface at various radii is shown using a yellow circle. Panel (b) shows the axisymmetric zonal magnetic field as a color map and the axisymmetric poloidal magnetic field as contour lines; solid (dashed) lines represent clockwise (counterclockwise) field lines. A zoomed-in section, showing the dense field lines in the northern hemisphere of the dynamo region, is shown in panel (c).
Paper: A Global Simulation of the Dynamo, Zonal Jets, and Vortices on Saturn
Authors: Rakesh Kumar Yadav, Hao Cao, Jeremy Bloxham
Figure caption: Variation of the logarithmic poloidal magnetic energy, normalized by its overall maximum value, contained in different spherical harmonic degrees as we go from the innermost radius to the outermost radius. The boundaries of the SSL are shown using dashed vertical lines.
Paper: A Global Simulation of the Dynamo, Zonal Jets, and Vortices on Saturn
Authors: Rakesh Kumar Yadav, Hao Cao, Jeremy Bloxham
Figure caption: Radial velocity (given in Reynolds number) on the equator and at various depths; the color map is saturated at ±5000 and the red (blue) shades correspond to +ve (−ve) values.
Paper: The Turndown of the Baryonic Tully–Fisher Relation and Changing Baryon Fraction at Low Galaxy Masses
Authors: Kristen. B. W. McQuinn, Elizabeth A. K. Adams, John M. Cannon, Jackson Fuson, Evan D. Skillman, Alyson Brooks, Katherine L. Rhode, Martha P. Haynes, John L. Inoue, Joshua Marine, John. J. Salzer, Anjana K. Talluri
Figure caption: Theoretical rotation curves for the SHIELD galaxies AGC110482, AGC111164, and AGC229053 with the measured velocities corrected for asymmetric drift overplotted at the radii at which the velocity was measured. See Figure 6 caption and Section 5.3.
Paper: The Turndown of the Baryonic Tully–Fisher Relation and Changing Baryon Fraction at Low Galaxy Masses
Authors: Kristen. B. W. McQuinn, Elizabeth A. K. Adams, John M. Cannon, Jackson Fuson, Evan D. Skillman, Alyson Brooks, Katherine L. Rhode, Martha P. Haynes, John L. Inoue, Joshua Marine, John. J. Salzer, Anjana K. Talluri
Figure caption: Theoretical rotation curves for the LITTLE THINGS galaxies F564v3, HoII, and WLM with the measured velocities corrected for asymmetric drift overplotted at the radii at which the velocity was measured. See Figure 6 caption and Section 5.3.
Paper: The Turndown of the Baryonic Tully–Fisher Relation and Changing Baryon Fraction at Low Galaxy Masses
Authors: Kristen. B. W. McQuinn, Elizabeth A. K. Adams, John M. Cannon, Jackson Fuson, Evan D. Skillman, Alyson Brooks, Katherine L. Rhode, Martha P. Haynes, John L. Inoue, Joshua Marine, John. J. Salzer, Anjana K. Talluri
Figure caption: Theoretical rotation curves for the SHIELD galaxies AGC7393005, AGC742601, and AGC 749237 with the measured velocities corrected for asymmetric drift overplotted at the radii at which the velocity was measured. See Figure 6 caption and Section 5.3.
Paper: The Turndown of the Baryonic Tully–Fisher Relation and Changing Baryon Fraction at Low Galaxy Masses
Authors: Kristen. B. W. McQuinn, Elizabeth A. K. Adams, John M. Cannon, Jackson Fuson, Evan D. Skillman, Alyson Brooks, Katherine L. Rhode, Martha P. Haynes, John L. Inoue, Joshua Marine, John. J. Salzer, Anjana K. Talluri
Figure caption: Theoretical rotation curves for the VLA-ANGST galaxies Sextans A, Sextans B, and UGC04483 with the measured velocities corrected for asymmetric drift overplotted at the radii at which the velocity was measured. See Figure 6 caption and Section 5.3.
Paper: The Turndown of the Baryonic Tully–Fisher Relation and Changing Baryon Fraction at Low Galaxy Masses
Authors: Kristen. B. W. McQuinn, Elizabeth A. K. Adams, John M. Cannon, Jackson Fuson, Evan D. Skillman, Alyson Brooks, Katherine L. Rhode, Martha P. Haynes, John L. Inoue, Joshua Marine, John. J. Salzer, Anjana K. Talluri
Figure caption: Theoretical rotation curves for the VLA-ANGST galaxies UGC08508, UGC08833, and UGCA292 with the measured velocities corrected for asymmetric drift overplotted at the radii at which the velocity was measured. See Figure 6 caption and Section 5.3.
Paper: The Turndown of the Baryonic Tully–Fisher Relation and Changing Baryon Fraction at Low Galaxy Masses
Authors: Kristen. B. W. McQuinn, Elizabeth A. K. Adams, John M. Cannon, Jackson Fuson, Evan D. Skillman, Alyson Brooks, Katherine L. Rhode, Martha P. Haynes, John L. Inoue, Joshua Marine, John. J. Salzer, Anjana K. Talluri
Figure caption: Theoretical rotation curves for the LITTLE THINGS galaxies DDO53, DDO126, and DDO154 with the measured velocities corrected for asymmetric drift overplotted at the radii at which the velocity was measured. See Figure 6 caption and Section 5.3.
Paper: The Turndown of the Baryonic Tully–Fisher Relation and Changing Baryon Fraction at Low Galaxy Masses
Authors: Kristen. B. W. McQuinn, Elizabeth A. K. Adams, John M. Cannon, Jackson Fuson, Evan D. Skillman, Alyson Brooks, Katherine L. Rhode, Martha P. Haynes, John L. Inoue, Joshua Marine, John. J. Salzer, Anjana K. Talluri
Figure caption: Theoretical rotation curves for the VLA-ANGST galaxies DDO183, NGC3109, and NGC3741 with the measured velocities corrected for asymmetric drift overplotted at the radii at which the velocity was measured. See Figure 6 caption and Section 5.3.
Paper: The Turndown of the Baryonic Tully–Fisher Relation and Changing Baryon Fraction at Low Galaxy Masses
Authors: Kristen. B. W. McQuinn, Elizabeth A. K. Adams, John M. Cannon, Jackson Fuson, Evan D. Skillman, Alyson Brooks, Katherine L. Rhode, Martha P. Haynes, John L. Inoue, Joshua Marine, John. J. Salzer, Anjana K. Talluri
Figure caption: Theoretical rotation curves for the VLA-ANGST galaxies DDO99, DDO125, and DDO181 with the measured velocities corrected for asymmetric drift overplotted at the radii at which the velocity was measured. See Figure 6 caption and Section 5.3.
Paper: Tracking Halo Orbits and Their Mass Evolution around Large-scale Filaments
Authors: Hannah Jhee, Hyunmi Song, Rory Smith, Jihye Shin, Inkyu Park, Clotilde Laigle
Figure caption: Left: the current mass normalized by the mass at first crossing, M now/M FC, as a function of time since first crossing (t FC). The color represents the three-dimensional acceleration (km s−1 Gyr−1) at the first crossing moment. M now/M FC is well correlated with the acceleration at first crossing. We further divide our sample according to t FC and the mass ratio M now/M FC as shown by the boxes numbered from one to five for further analyses; the divisions are made at t FC = 3 and 6 Gyr and M now/M FC = 1. Right: the histogram of the mass ratio M now/M FC. For most halos, their current mass has not evolved much compared to the mass at first crossing.
Paper: Tracking Halo Orbits and Their Mass Evolution around Large-scale Filaments
Authors: Hannah Jhee, Hyunmi Song, Rory Smith, Jihye Shin, Inkyu Park, Clotilde Laigle
Figure caption: Top: the stacked phase-space trajectories of all central halos. Middle: three representative cases of phase-space trajectories of halos around large-scale filaments. The starting point is marked as “formation,” and the pericenter is marked as “crossing.” The x- and y-axes are normalized by r 0 and v peak of each case, respectively, but note that this normalization is purely for representation, rather than by any physical meaning. The cases of “going for another orbit” and “escaping from potentional” are later called “bound” and “fly-by” objects. Bottom: the fraction (black dashed line) and number (blue solid line) of crossers (those denoted in green in the middle panel) that have passed the pericenter at least once at z = 0 as a function of distance to filaments at z = 0.
Paper: Tracking Halo Orbits and Their Mass Evolution around Large-scale Filaments
Authors: Hannah Jhee, Hyunmi Song, Rory Smith, Jihye Shin, Inkyu Park, Clotilde Laigle
Figure caption: The mass distribution of halos in one of the N-Cluster Run simulations. We track the evolution of halos with 4 × 1010  M ⊙ h −1 ≤ M < 1013  M ⊙ h −1 (red) around filaments that are extracted from the region within 10 virial radii of massive halos of > 1014 M ⊙ h −1 (blue). The additional red dotted line at M = 1012  M ⊙ h −1 splits our halo sample into massive and less massive ones.
Paper: Tracking Halo Orbits and Their Mass Evolution around Large-scale Filaments
Authors: Hannah Jhee, Hyunmi Song, Rory Smith, Jihye Shin, Inkyu Park, Clotilde Laigle
Figure caption: The distributions of current halo mass with respect to the mass at first crossing (M now/M FC), initial distance (r 0), initial velocity (v 0), maximum velocity (﹩{v}_{\max }﹩), time since first crossing (t FC), and filament density (n fil) of 335 bound (blue) and 121 fly-by (red) halos. The y-axis represents a probability density. The errors are statistical errors.
Paper: Tracking Halo Orbits and Their Mass Evolution around Large-scale Filaments
Authors: Hannah Jhee, Hyunmi Song, Rory Smith, Jihye Shin, Inkyu Park, Clotilde Laigle
Figure caption: Phase-space distributions of halos at z = 0 that have crossed their pericenters more than 6 Gyr ago, subsampled by the density of filaments. The inset plot shows the filament density (n fil) distribution; high and low densities correspond to n fil/(h 3/Mpc3) > 8 and < 0.8, respectively. Each data point corresponds to one halo.
Paper: Tracking Halo Orbits and Their Mass Evolution around Large-scale Filaments
Authors: Hannah Jhee, Hyunmi Song, Rory Smith, Jihye Shin, Inkyu Park, Clotilde Laigle
Figure caption: Binned distribution of r 0 and ﹩{v}_{\max }﹩ of crossers color-coded by the current (z = 0) mass of halos (top) and time since formation t formed (bottom). For a given r 0, more massive halos tend to have lower ﹩{v}_{\max }﹩, and to form earlier.