adsabs/AstroCLIMB huggingface dataset:
Paper: The Molecular Composition of Shadowed Proto-solar Disk Midplanes Beyond the Water Snowline
Authors: Shota Notsu, Kazumasa Ohno, Takahiro Ueda, Catherine Walsh, Christian Eistrup, Hideko Nomura
Figure caption: Same as Figure 3, but for the total reservoir of larger (complex) organic molecules. The left panel (“All”) shows the sums of all of larger organic molecules for which we show the results in Section 3.2 (Figures 4–8). The right panel (“Reduced”) shows the sums of all of larger organic molecules after we subtract dominant unsaturated hydrocarbon molecules for which we show the results in Figure 6.
Paper: The Molecular Composition of Shadowed Proto-solar Disk Midplanes Beyond the Water Snowline
Authors: Shota Notsu, Kazumasa Ohno, Takahiro Ueda, Catherine Walsh, Christian Eistrup, Hideko Nomura
Figure caption: Same as Figure 3, but for CH3NH2 (﹩{n}_{{\mathrm{CH}}_{3}{\mathrm{NH}}_{2}}﹩/n H, top-left panel), CH2NH (﹩{n}_{{\mathrm{CH}}_{2}\mathrm{NH}}﹩/n H, top-right panel), CH3CN (﹩{n}_{{\mathrm{CH}}_{3}\mathrm{CN}}﹩/n H, middle-left panel), HC3N (﹩{n}_{{\mathrm{HC}}_{3}{\rm{N}}}﹩/n H, middle-right panel), NH2OH (﹩{n}_{{\mathrm{NH}}_{2}\mathrm{OH}}﹩/n H, bottom-left panel), and HNCO (n HNCO/n H, bottom-right panel).
Paper: The Molecular Composition of Shadowed Proto-solar Disk Midplanes Beyond the Water Snowline
Authors: Shota Notsu, Kazumasa Ohno, Takahiro Ueda, Catherine Walsh, Christian Eistrup, Hideko Nomura
Figure caption: Same as Figure 3, but for CH4 (﹩{n}_{{\mathrm{CH}}_{4}}﹩/n H, top-left panel), C2H6 (﹩{n}_{{{\rm{C}}}_{2}{{\rm{H}}}_{6}}﹩/n H, top-right panel), H2CO (﹩{n}_{{{\rm{H}}}_{2}\mathrm{CO}}﹩/n H, bottom-left panel), and CH3OH (﹩{n}_{{\mathrm{CH}}_{3}\mathrm{OH}}﹩/n H, bottom-right panel).
Paper: The Mass Scale of High-redshift Galaxies: Virial Mass Estimates Calibrated with Stellar Dynamical Models from LEGA-C
Authors: Arjen van der Wel, Josha van Houdt, Rachel Bezanson, Marijn Franx, Francesco D'Eugenio, Caroline Straatman, Eric F. Bell, Adam Muzzin, David Sobral, Michael V. Maseda, Anna de Graaff, Bradford P. Holden
Figure caption: The ratio between homology-corrected virial mass and Jeans mass for three different definitions of the virial mass (as indicated in the panels) vs. the projected axis ratio. Left: M vir with R sma and ﹩\sigma {{\prime} }_{\star ,\mathrm{int}}﹩. The black line in the left-hand panel is a fit to the axis ratio trend and functions as the structural homology correction K(q) (Equation (6)). This correction is applied to M vir in the middle panel. Right: M vir with R circ instead of R sma and without K(q).
Paper: The Mass Scale of High-redshift Galaxies: Virial Mass Estimates Calibrated with Stellar Dynamical Models from LEGA-C
Authors: Arjen van der Wel, Josha van Houdt, Rachel Bezanson, Marijn Franx, Francesco D'Eugenio, Caroline Straatman, Eric F. Bell, Adam Muzzin, David Sobral, Michael V. Maseda, Anna de Graaff, Bradford P. Holden
Figure caption: Ratio of M JAM and M 5 (see Figure 1) vs. Sérsic index n, color-coded with the projected axis ratio b/a. The black line represents the proportionality factor K(n) = 8.87 − 0.831n + 0.0241n 2 from Cappellari et al. (2006) divided by a factor 5 (from M 5), which describes the n dependence well. But a strong residual correlation with the projected axis ratio is readily apparent, implying that a viewing angle correction is required to properly scale the virial mass estimator.
Paper: The Mass Scale of High-redshift Galaxies: Virial Mass Estimates Calibrated with Stellar Dynamical Models from LEGA-C
Authors: Arjen van der Wel, Josha van Houdt, Rachel Bezanson, Marijn Franx, Francesco D'Eugenio, Caroline Straatman, Eric F. Bell, Adam Muzzin, David Sobral, Michael V. Maseda, Anna de Graaff, Bradford P. Holden
Figure caption: Comparison of MGE-based virial M/L with JAM M/L for ATLAS3D from C13 as a function of the projected axis ratio. Galaxies with quality flag 0 (see C13) are removed from the sample. Left: M vir/L as defined by C13 for MGE parameters; Right: a revised M vir/L for MGE parameters using the inclination correction velocity estimator ﹩\langle {V}_{\mathrm{rms}}^{2}{\rangle }_{e}﹩ from C13. See the text for details.
Paper: The Mass Scale of High-redshift Galaxies: Virial Mass Estimates Calibrated with Stellar Dynamical Models from LEGA-C
Authors: Arjen van der Wel, Josha van Houdt, Rachel Bezanson, Marijn Franx, Francesco D'Eugenio, Caroline Straatman, Eric F. Bell, Adam Muzzin, David Sobral, Michael V. Maseda, Anna de Graaff, Bradford P. Holden
Figure caption: Virial mass vs. JAM mass, separately for quiescent and star-forming galaxies. Our newly constructed virial mass agrees very well with the JAM mass, without systematic bias. The random uncertainty (as indicated by the scatter) is larger for star-forming galaxies than for quiescent galaxies.
Paper: The Mass Scale of High-redshift Galaxies: Virial Mass Estimates Calibrated with Stellar Dynamical Models from LEGA-C
Authors: Arjen van der Wel, Josha van Houdt, Rachel Bezanson, Marijn Franx, Francesco D'Eugenio, Caroline Straatman, Eric F. Bell, Adam Muzzin, David Sobral, Michael V. Maseda, Anna de Graaff, Bradford P. Holden
Figure caption:  M vir/M JAM vs. rotation parameter κ calculated from the Jeans dynamical model, color-coded with projected axis ratio. κ ranges from ∼0 for nonrotating galaxies to ∼1 for galaxies that are rotationally supported. Note that the dynamical model distinguishes between galaxies that are round in projection (color-coded with blue) that are face-on disks and and galaxies that are intrinsically round and nonrotating. There is no bias in our M vir estimates that depends on the orbital structure of the galaxy; our inclination correction K(q) serves to account for any such dependence.
Paper: The Mass Scale of High-redshift Galaxies: Virial Mass Estimates Calibrated with Stellar Dynamical Models from LEGA-C
Authors: Arjen van der Wel, Josha van Houdt, Rachel Bezanson, Marijn Franx, Francesco D'Eugenio, Caroline Straatman, Eric F. Bell, Adam Muzzin, David Sobral, Michael V. Maseda, Anna de Graaff, Bradford P. Holden
Figure caption: The simplest virial mass estimator, M 5, vs. M JAM, color-coded with Sérsic index n. For low-n galaxies M JAM is systematically larger than M 5, implying that a nonhomology correction is required to properly scale the virial mass estimator.
Paper: The Mass Scale of High-redshift Galaxies: Virial Mass Estimates Calibrated with Stellar Dynamical Models from LEGA-C
Authors: Arjen van der Wel, Josha van Houdt, Rachel Bezanson, Marijn Franx, Francesco D'Eugenio, Caroline Straatman, Eric F. Bell, Adam Muzzin, David Sobral, Michael V. Maseda, Anna de Graaff, Bradford P. Holden
Figure caption: Comparison of JAM (M/L) from ATLAS3D (left) and LEGA-C (right) with the Sérsic profile-based virial M/L estimates as defined for ATLAS3D by C13 (﹩{M}_{\mathrm{vir},{\rm{n}}}=K(n){\sigma }_{\mathrm{Re}}^{2}{R}_{\mathrm{Sersic},\mathrm{circ}}/G﹩). For LEGA-C only quiescent galaxies are included to create a more direct comparison with the early-type ATLAS3D sample. For LEGA-C we show two flavors of JAM M/L. In red the M/L from the default model with a dark matter component (calculated within R  e ) and in black, for direct comparison with ATLAS3D, the model without dark matter.
Paper: An Improved Method for Coupling Hydrodynamics with Astrophysical Reaction Networks
Authors: M. Zingale, M. P. Katz, A. Nonaka, M. Rasmussen
Figure caption: Flowchart of the operator split (Strang) time integration. We first react for Δt/2, then advect for Δt, and finally react for Δt/2. Each process uses the state left behind from the previous process.
Paper: On the Nature of the Mass-gap Object in the GW190814 Event
Authors: Luiz L. Lopes, Debora P. Menezes
Figure caption: (Color online) Strangeness fraction as a function of α.
Paper: On the Nature of the Mass-gap Object in the GW190814 Event
Authors: Luiz L. Lopes, Debora P. Menezes
Figure caption: (Color online) Particle population for the SU(6) group and different values of α.
Paper: The Effects of a Magnetar Engine on the Gamma-Ray Burst-associated Supernovae: Application to Double-peaked SN 2006aj
Authors: Zhen-Dong Zhang, Yun-Wei Yu, Liang-Duan Liu
Figure caption: The bolometric light curves of the SBO and supernova emission in comparison with the luminosity evolution of the heating powers. The parameter values are the same as Figure 3. The zero time in this figure is t mag,0.
Paper: The Effects of a Magnetar Engine on the Gamma-Ray Burst-associated Supernovae: Application to Double-peaked SN 2006aj
Authors: Zhen-Dong Zhang, Yun-Wei Yu, Liang-Duan Liu
Figure caption: The temporal evolution of the spin-down luminosity of the mangetar, which is required by the consistency of the nonthermal PWN emission with the observational data of SN 2006aj. The zero time in this figure is t mag,0.
Paper: The Effects of a Magnetar Engine on the Gamma-Ray Burst-associated Supernovae: Application to Double-peaked SN 2006aj
Authors: Zhen-Dong Zhang, Yun-Wei Yu, Liang-Duan Liu
Figure caption: The same as Figure 3 but with an extra nonthermal PWN emission component shown in dashed lines; the thermal component is shown in dotted lines.
Paper: The Effects of a Magnetar Engine on the Gamma-Ray Burst-associated Supernovae: Application to Double-peaked SN 2006aj
Authors: Zhen-Dong Zhang, Yun-Wei Yu, Liang-Duan Liu
Figure caption: Posterior distributions of parameters for the fittings of SN 2006aj with the model in Section 4.
Paper: Velocity-resolved Reverberation Mapping of Changing-look Active Galactic Nucleus NGC 4151 during Outburst Stage: Evidence for Kinematics Evolution of Broad-line Region
Authors: Sha-Sha Li, Hai-Cheng Feng, H. T. Liu, J. M. Bai, Rui Li, Kai-Xing Lu, Jian-Guo Wang, Ying-Ke Huang, Zhi-Xiang Zhang
Figure caption: The left panels show photometry, Hα, Hβ, Hγ, He I, and He II light curves. Panel (a) is the intercalibrated result of B (Lijiang) and g (ZTF). The blue and orange shaded regions represent light curves reconstructed by MICA and JAVELIN. The right panels show time-lag distributions. Panel (g) shows the photometric autocorrelation function (ACF). Furthermore, in panels (h)–(l), the black and green lines correspond to the interpolated cross-correlation function (ICCF) and cross-correlation centroid distribution (CCCD), respectively, and the blue dotted and orange dashed lines represent time-lag probability distributions of MICA and JAVELIN, respectively. The vertical dashed lines represent a time lag of 0 days.
Paper: Velocity-resolved Reverberation Mapping of Changing-look Active Galactic Nucleus NGC 4151 during Outburst Stage: Evidence for Kinematics Evolution of Broad-line Region
Authors: Sha-Sha Li, Hai-Cheng Feng, H. T. Liu, J. M. Bai, Rui Li, Kai-Xing Lu, Jian-Guo Wang, Ying-Ke Huang, Zhi-Xiang Zhang
Figure caption: The upper-left panel shows the fit of the mean spectrum, where the broad Balmer lines (Hα, Hβ, Hγ) are shown in magenta, the broad He I and He II are shown in cyan, and orange lines represent narrow emission lines. The blue, green, and gray lines correspond to an AGN power law, Fe II template, and host galaxy template, respectively. Additionally, the red line symbolizes the best-fit model, and the original spectrum is shown in black. The lower-left panel is fitting residuals. The right panels are the same as the left panels but for an individual spectrum.
Paper: Velocity-resolved Reverberation Mapping of Changing-look Active Galactic Nucleus NGC 4151 during Outburst Stage: Evidence for Kinematics Evolution of Broad-line Region
Authors: Sha-Sha Li, Hai-Cheng Feng, H. T. Liu, J. M. Bai, Rui Li, Kai-Xing Lu, Jian-Guo Wang, Ying-Ke Huang, Zhi-Xiang Zhang
Figure caption: This is the long-term light curve of NGC 4151, which was generated by combing the collected continuum and photometry with the B band of Lijiang. Details about the intercalibrated data can be seen in Section 3.3. The horizontal dashed line represents the latest peak.
Paper: Velocity-resolved Reverberation Mapping of Changing-look Active Galactic Nucleus NGC 4151 during Outburst Stage: Evidence for Kinematics Evolution of Broad-line Region
Authors: Sha-Sha Li, Hai-Cheng Feng, H. T. Liu, J. M. Bai, Rui Li, Kai-Xing Lu, Jian-Guo Wang, Ying-Ke Huang, Zhi-Xiang Zhang
Figure caption: The photometric light curves of Johnson B filter of NGC 4151 (upper) and comparison star (lower).
Paper: Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches for Supermassive Black Hole Binaries in Time-domain Surveys
Authors: Caitlin A. Witt, Maria Charisi, Stephen R. Taylor, Sarah Burke-Spolaor
Figure caption: True-positive rates (red) and false-positive rates (blue) for LSST-like (solid lines) and CRTS-like (dashed lines) simulations, shown as a function of the input values of each parameter in the simulations. Note that false-positive rates are only shown as a function of the two DRW parameters, as there are no input sinusoids present in the false positives. The rates in each parameter bin are shown with associated uncertainties.
Paper: Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches for Supermassive Black Hole Binaries in Time-domain Surveys
Authors: Caitlin A. Witt, Maria Charisi, Stephen R. Taylor, Sarah Burke-Spolaor
Figure caption: ROC curves for CRTS-like (orange-lined diamonds) and LSST-like (blue-lined circles) light curves. Overall, LSST can be seen to perform better than CRTS at selecting the correct model. For comparison, with our standard ΔBIC = −2, the true-positive rate is 64% and the false-positive rate is 3.8%. Stars in the curves represent the point where ΔBIC = −2. Additionally, the model selection is significantly improved when white noise (small points) is present instead of a DRW process (large points), indicating that red processes are indeed a significant hindrance.
Paper: Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches for Supermassive Black Hole Binaries in Time-domain Surveys
Authors: Caitlin A. Witt, Maria Charisi, Stephen R. Taylor, Sarah Burke-Spolaor
Figure caption: Recovery capabilities for the three sinusoid parameters (P, A, and ϕ 0) and two DRW parameters (σ and τ), as demonstrated by our LSST-like light-curve simulations. The color axis represents the S/N of the input signal, with red points being strong signals (S/N > 5). The sinusoids in these simulations were able to be recovered extremely accurately, and the DRW parameters were recovered to the extent we expect from noise-only simulations.
Paper: Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches for Supermassive Black Hole Binaries in Time-domain Surveys
Authors: Caitlin A. Witt, Maria Charisi, Stephen R. Taylor, Sarah Burke-Spolaor
Figure caption: True-positive (red) and false-negative (blue) signals tend to lie in particular areas of parameter space in idealized LSST-like searches, when quantified by the ratios of A/σ and P/τ. The net true-positive rates integrated over A/σ and P/τ are shown in the upper and right panels, respectively, with associated uncertainties.
Paper: Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches for Supermassive Black Hole Binaries in Time-domain Surveys
Authors: Caitlin A. Witt, Maria Charisi, Stephen R. Taylor, Sarah Burke-Spolaor
Figure caption: Simulations of DRW light curves, with (red) and without (blue) a sinusoid, lie in regular regions of parameter space when parametrized by the ratio of A/σ and P/τ. This makes apparent the cause of the location of false negatives in Figure 6. It is also clear that more signals will become detectable in future surveys as cadences and baselines improve.
Paper: Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches for Supermassive Black Hole Binaries in Time-domain Surveys
Authors: Caitlin A. Witt, Maria Charisi, Stephen R. Taylor, Sarah Burke-Spolaor
Figure caption: An example of simulated light curves containing a DRW process (top panel) and a DRW process plus a sinusoid (bottom panel). The sinusoid is shown in the solid black curve, while the simulated data for a CRTS-like and LSST-like survey are shown as red ×’s and blue points, respectively. Depending on the DRW and sinusoid parameters, it is possible for these two models to produce deceptively similar results.
Paper: Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches for Supermassive Black Hole Binaries in Time-domain Surveys
Authors: Caitlin A. Witt, Maria Charisi, Stephen R. Taylor, Sarah Burke-Spolaor
Figure caption: ROC curves for variations on our nominal LSST simulations (solid curve), including increased observation baseline (dashed curve) and increased observation cadence (dotted curve).
Paper: Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches for Supermassive Black Hole Binaries in Time-domain Surveys
Authors: Caitlin A. Witt, Maria Charisi, Stephen R. Taylor, Sarah Burke-Spolaor
Figure caption: If a light curve is simulated to contain both a sinusoid and a DRW process, but is modeled with only noise, significant confusion can occur. The periods of recoverable sinusoids (red) can be confused for the DRW timescale τ if only noise is modeled.
Paper: Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches for Supermassive Black Hole Binaries in Time-domain Surveys
Authors: Caitlin A. Witt, Maria Charisi, Stephen R. Taylor, Sarah Burke-Spolaor
Figure caption: Parameter estimation capability of our methods for LSST-like light curves with a DRW process, colorized by the simulated value of τ. For low values of τ, both parameters are recoverable as expected. However, for very high values of τ, both are unlikely to be constrained accurately.
Paper: Merger Effects on the Spin and Shape Alignments of Galaxy Stellar, Cold Gas, Hot Gas, and Dark Matter Components
Authors: Jounghun Lee, Jun-Sung Moon
Figure caption: Mean values of the dot products between the spin and shape vectors of the galaxy stellar, cold gas, hot gas, and DM components (top, second from the top, third from the top, and bottom panels, respectively), averaged over each of the four controlled a(z  m )-selected samples. In the top and bottom panels, the errorbars are invisible due to their tiny sizes. The earlier the latest mergers occur, the stronger (the weaker) the alignments between the galaxy stellar (DM) spin and shape vectors become.
Paper: Merger Effects on the Spin and Shape Alignments of Galaxy Stellar, Cold Gas, Hot Gas, and Dark Matter Components
Authors: Jounghun Lee, Jun-Sung Moon
Figure caption: Mean absolute values of the cosines of the angles of the galaxy DM spin vectors from the major, intermediate, and minor principal directions of the local tidal tensors (top, middle, and bottom panels, respectively) averaged over each of the four controlled a(z  m )-selected samples. No strong dependence of the alignment strength between the galaxy DM spins and the principal axes of the local tidal fields on the latest merger epochs.
Paper: Merger Effects on the Spin and Shape Alignments of Galaxy Stellar, Cold Gas, Hot Gas, and Dark Matter Components
Authors: Jounghun Lee, Jun-Sung Moon
Figure caption: Mean absolute values of the cosines of the angles of the galaxy stellar, cold gas, and hot gas spin vectors of the galaxies from the major principal directions of the local tidal tensors (top, middle, and bottom panels, respectively) averaged over each of the four controlled a(z  m )-selected samples. The earlier the galaxies experience their latest mergers, the stronger the peculiar tidal connections of their stellar components become.
Paper: Merger Effects on the Spin and Shape Alignments of Galaxy Stellar, Cold Gas, Hot Gas, and Dark Matter Components
Authors: Jounghun Lee, Jun-Sung Moon
Figure caption: Same as Figure 3 but for four different cases of the particle number cuts: n  s  ≥ 300 (top panel); n  cg  ≥ 300 (second panel from the top); n  hg  ≥ 300 (third panel from the top); n  d  ≥ 300 (bottom panel).
Paper: Merger Effects on the Spin and Shape Alignments of Galaxy Stellar, Cold Gas, Hot Gas, and Dark Matter Components
Authors: Jounghun Lee, Jun-Sung Moon
Figure caption: Same as Figure 2 but for four different cases of the particle number cuts: n  s  ≥ 300 (top panel); n  cg  ≥ 300 (second panel from the top); n  hg  ≥ 300 (third panel from the top); n  d  ≥ 300 (bottom panel).
Paper: Merger Effects on the Spin and Shape Alignments of Galaxy Stellar, Cold Gas, Hot Gas, and Dark Matter Components
Authors: Jounghun Lee, Jun-Sung Moon
Figure caption: Mean absolute values of the dot products of the galaxy stellar, cold gas, hot gas, DM shape vectors from the major principal directions of the local tidal tensors (top, second from the top, third from the top, and bottom panels, respectively), averaged over each of the four controlled a(z  m )-selected samples. The earlier the latest mergers occur, the stronger alignments the galaxies exhibit between their spin and shape vectors.
Paper: Merger Effects on the Spin and Shape Alignments of Galaxy Stellar, Cold Gas, Hot Gas, and Dark Matter Components
Authors: Jounghun Lee, Jun-Sung Moon
Figure caption: Mean values of the triaxiality of the galaxy stellar, cold gas, hot gas, and DM components averaged over the four controlled a(z  m )-selected samples. The errorbars in the top two panels are invisible due to their tiny sizes. The earlier the latest mergers occur, the less triaxial shapes the galaxies have.
Paper: Merger Effects on the Spin and Shape Alignments of Galaxy Stellar, Cold Gas, Hot Gas, and Dark Matter Components
Authors: Jounghun Lee, Jun-Sung Moon
Figure caption: Same as Figure 10 but of the sphericity. The errorbars in the second panel from the top are invisible due to their tiny sizes. The earlier the latest mergers occur, the more spherical shapes the galaxies have.
Paper: Nature and Scalings of Density Fluctuations of Compressible Magnetohydrodynamic Turbulence with Applications to the Solar Wind
Authors: Xiangrong Fu, Hui Li, 晖 李, Zhaoming Gan, Senbei Du, John Steinberg
Figure caption: (a) Contours of the Fourier power of density fluctuations in the ω– k  space using 4D FFT analysis for Run 1, with 50 < t < 80. For visualization purposes, the 4D FFT data has been reduced to 3D by projecting  k  vector into k ⊥–k ∥ plane. Gray surfaces represent the dispersion surface of the slow mode (lower) and the fast mode (upper). The majority of the power resides in oblique directions where k ⊥ ≫ k ∥ (c.f. Figure 4). The fractions of the power carried by the nonlinear structures, slow mode, and fast mode are 91%, 8%, and < 1%, respectively. (b) A 2D cut of the power in the ω–k ⊥ plane with k ∥ = 0. The white line is the dispersion relation of the fast mode. (c) A 2D cut of the power in the ω–k ∥ plane with k ⊥ = 5. The upper white line is the dispersion relation curve of the fast mode, and the lower white line is the dispersion relation curve of the slow mode. Most of the wave power is in the slow mode. (d) Fourier power of fluctuations in the k ⊥–k ∥ plane, showing strong anisotropy in the perpendicular direction.
Paper: Nature and Scalings of Density Fluctuations of Compressible Magnetohydrodynamic Turbulence with Applications to the Solar Wind
Authors: Xiangrong Fu, Hui Li, 晖 李, Zhaoming Gan, Senbei Du, John Steinberg
Figure caption: Power spectra of (a) total velocity field, magnetic field, and density field fluctuations and (b) magnetic and velocity field components at t = 80 for Run 1. In the inertial range (3 < k < 40), both the magnetic field and velocity field power spectra follow approximately the Kolmogorov law with ﹩{k}_{\perp }^{-5/3}﹩ in the perpendicular direction.