adsabs/AstroCLIMB huggingface dataset:
Paper: ALMA Measurement of 10 kpc Scale Lensing-power Spectra toward the Lensed Quasar MG J0414+0534
Authors: Kaiki Taro Inoue, Takeo Minezaki, Satoki Matsushita, Kouichiro Nakanishi
Figure caption: Result of visibility fitting in which object Y is modeled by a Gaussian source. The blue line shows the best-fitted flux of object Y. δ θ is the angular separation between the centers of adjacent grids. We used a perturbed Type A model with the magnification weighting and L = 3.″6. In the fitting, only the line-free visibility data were used.
Paper: ALMA Measurement of 10 kpc Scale Lensing-power Spectra toward the Lensed Quasar MG J0414+0534
Authors: Kaiki Taro Inoue, Takeo Minezaki, Satoki Matsushita, Kouichiro Nakanishi
Figure caption: Comparison between perturbed and unperturbed Type A models. The red boxes and the blue stars show the reduced χ 2 for the perturbed and unperturbed background Type A models, respectively. The green filled circles show the reduced χ 2 for the perturbed Type A model in which the point-source flux ratios of A1–A2 are artificially fixed to be unity. δ θ is the angular separation between the centers of adjacent grids.
Paper: ALMA Measurement of 10 kpc Scale Lensing-power Spectra toward the Lensed Quasar MG J0414+0534
Authors: Kaiki Taro Inoue, Takeo Minezaki, Satoki Matsushita, Kouichiro Nakanishi
Figure caption: Distribution of grid centers. Each blue dot shows the center of a grid that contains sampled ALMA visibility data at 335.3 GHz. The radial and azimuthal angular separations of centers of adjacent grids are δ r = 100 m and δ θ = 10°, respectively.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: The redshift distributions of various LGRB samples normalized such that the distributions have a value of approximately 60 at a redshift of 2.5. The scaling factors applied are given in Table A2 of Appendix A. Deviations between the sample distributions allow selection effects within the samples to be identified. A gap is seen in the X-shooter metallicity sample (both the total sample, blue line, and its high-metallicity subsamples, purple and dark green lines) from 1.7 < z < 2.1 due to observational difficulties in obtaining all the lines needed for a metallicity measurement (see the text). As measuring a redshift does not require observing specific lines this gap is not seen in the Krühler et al. (2015) redshift sample. Note that the Krühler et al. (2015) super-solar metallicity LGRB sample (purple) follows the same distribution as the general Krühler et al. (2015) metallicity sample (blue), which suggests both that (i) the metallicity of the LGRB hosts does not bias the likelihood of being able to measure this metallicity (i.e., low-metallicity galaxies have metallicity measurements at the same rate as high-metallicity ones), and (ii) the distribution of metallicities measured in LGRB host galaxies does not notably evolve out to z ∼ 2, which is consistent with the results of Section 3.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: Cumulative distribution of measured LGRB host metallicities binned by redshift. The sample is selected from Graham & Fruchter (2013) and Krühler et al. (2015; see Section 2.1), and all metallicities have been computed using the R23 diagnostic and KK04 scale and code. Surprisingly, the data show no evidence for statistically significant evolution in the LGRB host metallicity distribution with redshift.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: Metallicity as a function of redshift for the 55 LGRB host galaxies in our sample. The oxygen abundance is computed using the KK04 R23 diagnostic described in Section 2.3. The average R23 metallicity in bins of Δz = 0.5 is plotted in red and given in Table B3 to illustrate the lack of evolution in metallicity with redshift.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: Normalized number of objects of each type in Figure 1. The upper chart is normalized to the total number of z < 4 objects and uses regular binning. The lower chart is normalized to the total number of z < 2.5 objects (dropping the two samples which do not approach this redshift) and the binning has been adjusted around the redshift–metallicity gaps. The comoving volume of the universe has been added for reference. The legend applies to the lower chart as well, and the colors of the populations are matched to Figure 1.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: Left: cumulative distribution of objects for which we have measured metallicities with errors (see Table B1) with the error range of each value overplotted. Right: the 1000 metallicity cumulative distribution for the 55 LGRBs in our sample produced by the 1000 Monte Carlo iterations described in Section 2.3.1. For reference, the black line in the left plot is overplotted in red in the right plot. Note that both the errors for the individual objects and the cumulative distribution errors are not symmetric.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: Cumulative distribution of the mass-based metallicity estimates from the Perley et al. (2016b) SHOALS mass and redshift values (see Section 3.3) binned by redshift. The estimated metallicity upper limits are shown as dashed lines, whereas the estimated metallicity values (i.e., not limits) are shown as solid lines. As in Figure 8, a shaded regions indicate where the true distribution must lie. If the color fades out to the left, the distribution could, in principle, extend to an arbitrarily low metallicity. Where the shaded region is bounded by lines (dotted or solid) the true distribution goes between the bounds. Due to the limited number of objects in the SHOALS z < 0.5 bin we omit plotting this bin and instead replot the combined Perley et al. (2016b) and Svensson et al. (2010) z < 0.5 bin. For reference and comparison with the full estimated metallicity sample, we also plot the combined metallicities across the entire z < 2.5 redshift range (dotted black line). Fortunately, all the upper limits are contained in the lower half of the distributions and thus do not disrupt this analysis.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: Cumulative distribution similar figure to Figure 4 (left pane) and a similar figure to Figure 5 (right pane), but with the measured LGRB host metallicities now derived using the metallicity diagnostic calibrations from CCM+17 and the method described in Curti et al. (2020). In the right pane the KK04 diagnostic results have been overplotted. The average R23 and CCM+17 optimal metallicities in bins of Δz = 0.5 are also plotted as larger, open, circle, and square symbols, respectively, which illustrate the lack of evolution in metallicity with redshift for both metallicity diagnostics. We have offset the average metallicity values by 0.01 dex for clarity. Many of the data points at z < 1 correspond to LGRB host galaxies taken from Graham & Fruchter (2013), which have no reported line-flux measurements, and we therefore report no uncertainty on the derived metallicities. Note that since the metallicity method of Curti et al. (2020) includes multiple metallicity diagnostics, with each using a different set of emission-line ratios, this method provides metallicities for a larger sample of LGRB host galaxies (79) than when applying the R23 diagnostic alone, which requires the detection of O II, O III, and Hβ. The Curti et al. (2020) metallicities for those GRBs not listed in Table B1 are given in Table B2.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: Cumulative distribution of the Perley et al. (2016b) SHOALS LGRB host masses binned by redshift. Mass upper limits are shown as dashed lines and mass measurements are shown as solid lines. When normalizing the cumulative distributions, we include the number of sources with just limits on their stellar mass, which is why the solid lines (corresponding to constrained stellar mass measurements) do not extend down to zero. These two approaches define the maximum and minimum range possible for the distributions. The shaded region between them indicates where, due to the upper limits, the true distribution must lie. Where the shaded region is bounded by lines (dotted or solid) the true distribution is constrained between those bounds. If the color fades out to the left, the distribution could, in principle, extend to an arbitrarily low mass.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: Measured (black) and estimated (gray) metallicities from Figure 4 and Figure C1 right, respectively (where both lines show metallicities across the entire z < 2.5 redshift range). The estimated metallicities (gray line) are determined from the LGRB host mass and redshift data using the MZR relation shown in Figure 7. A green box with a width of 0.25 dex is overplotted; this corresponds to a difference factor of 1.8 in linear scale. This resolves much of the difference between the LGRB formation metallicity cutoff of about a third solar in Graham & Fruchter (2017) with the cutoff value of approximately solar claimed in Perley et al. (2016b), in favor of the former.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: Cumulative distribution plots comparing the host metallicity (left), mass (center), and SFR (right) of the LGRB host metallicity sample compiled here with the subset of LGRB host galaxies taken from the Salvaterra et al. (2012) BAT6, Perley et al. (2016b) SHOALS, and Hjorth et al. (2012) TOUGH samples. All samples are limited to the same redshift ranges as our LGRB host galaxy sample (z < 1.7 and 2.1 < z < 2.5). We find quite good agreement between the metallicity and mass distributions of the various samples, and reasonable agreement in SFR. See Section 3.1 for a more detailed discussion of the comparisons used and their results. K-S test results for the left, center, and right plots are given in Table C1.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: Left: cumulative distribution of the Perley et al. (2016a) SHOALS measured LGRB host masses binned by redshift. Similar to Figure 8 but no stellar mass upper limits are included in this case. Right: cumulative distribution of the estimated metallicities, based on the SHOALS stellar mass sample (plotted in the left panel), which is converted to a metallicity sample using a redshift-dependent MZR relation from Zahid et al. (2013; see Section 3). The data are again binned by redshift, using the same color scheme as in the left panel. This figure is comparable to Figure 9, but metallicity upper limits are not included. The results from the K-S statistic analysis between the distributions shown in both panels are summarized in Table C2 and C3.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: The mass–metallicity relation fits for the different redshifts of Zahid et al. (2013) Figure 1 (thick dashed lines) with our estimated metallicity results for a continuous range of galaxy masses and matching redshift bins (thin continuous lines) overplotted. The fitting is deliberately kept approximate to avoid over-fitting.
Paper: A Surprising Lack of Metallicity Evolution with Redshift in the Long Gamma-Ray Burst Host Galaxy Population
Authors: J. F. Graham, P. Schady, A. S. Fruchter
Figure caption: Metallicity vs. mass for objects with both measured and estimated metallicity values (i.e., those given in Table C4) with our fitting of the mass–metallicity relation curves of Zahid et al. (2013) shown for comparison. The redshifts of the different objects and comparison curves are indicated by color. Metallicity errors are shown for objects with errors in Table B1. Objects without metallicity errors do not have line fluxes with error measurement suitable to estimate errors. Mass errors are not given in the samples from which the mass values are compiled nor are errors given in the raw photometry from which they were determined.
Paper: Wave Generation and Energetic Electron Scattering in Solar Flares
Authors: Hanqing Ma, J. F. Drake, M. Swisdak
Figure caption: For the case with v  d /v Ae = 1.06 two-dimensional plots of the out-of-plane magnetic field B  z  at (a) tΩ e  = 15, (b) tΩ e  = 30, (c) tΩ e  = 500, and (d) tΩ e  = 1200. Shown in (e) is the spacetime diagram (t–y) of B  z . The black line in (a) is where the data for the spacetime plot shown in panel (e) are taken.
Paper: Wave Generation and Energetic Electron Scattering in Solar Flares
Authors: Hanqing Ma, J. F. Drake, M. Swisdak
Figure caption: The evolution of the box-averaged out-of-plane magnetic field fluctuations for different cases of v  d /v Ae, where v  d  is the mean parallel drift speed of the heat flux and v Ae is the electron Alfvén speed.
Paper: Wave Generation and Energetic Electron Scattering in Solar Flares
Authors: Hanqing Ma, J. F. Drake, M. Swisdak
Figure caption: Ratio of the parallel electron temperature T eyy  to the perpendicular temperature (T exx  + T ezz )/2 of the total distribution at the end of the simulation for different values of v  d /v Ae, where v  d  is the mean parallel drift speed of the heat flux and v Ae is the electron Alfvén speed.
Paper: Wave Generation and Energetic Electron Scattering in Solar Flares
Authors: Hanqing Ma, J. F. Drake, M. Swisdak
Figure caption: Electron distribution functions in v  x –v  y  phase space at the end of the simulation of Figure 4 at different y positions in the box. The sampling area of each position is the entire x range and 1% of the total y range. Shown in panels (a)–(c) are the electron velocity distribution functions on a logarithmic scale near the bottom, middle, and top of the box, corresponding to positions at 0%, 80%, and 99% of the total y range, respectively. Panels (d)–(f) are comparisons to the initial distribution, ﹩\mathrm{log}\left(\left|{f}_{\mathrm{end}}-{f}_{\mathrm{ini}}\right|\right)\ \mathrm{sgn}\left({f}_{\mathrm{end}}-{f}_{\mathrm{ini}}\right)﹩, at the same positions, where sgn is the sign function.
Paper: Wave Generation and Energetic Electron Scattering in Solar Flares
Authors: Hanqing Ma, J. F. Drake, M. Swisdak
Figure caption: Power spectrum of the out-of-plane magnetic field B  z  from the simulation in Figure 4 at (a) tΩ e  = 30 (see Figure 4(b)) and (b) tΩ e  = 1200 (see Figure 4(d)).
Paper: Wave Generation and Energetic Electron Scattering in Solar Flares
Authors: Hanqing Ma, J. F. Drake, M. Swisdak
Figure caption: Ratio of final to initial y-directed average heat flux for different values of v  d /v Ae, where v  d  is the mean parallel drift speed of the heat flux and v Ae is the electron Alfvén speed. The red point corresponds to a case in which 25% of electrons, rather than 50%, are found in the kappa distribution (Equation (4)) at t = 0, while the remaining 75% are in the drifting Maxwellian distribution (Equation (6)).
Paper: Wave Generation and Energetic Electron Scattering in Solar Flares
Authors: Hanqing Ma, J. F. Drake, M. Swisdak
Figure caption: The averaged wave–electron scattering rate at late time for the four runs in Figure 1 as a function of v  d /v Ae, the ratio of mean parallel drift speed of heat flux to electron Alfvén speed. The scattering rate is calculated from Equation (11) and is averaged over the ranges 0 ≲ y ≲ 80d  e , 0 ≲ y ≲ 60d  e , 0 ≲ y ≲ 10d  e , and 0 ≲ y ≲ 4d  e  for the drift speeds v  d /v Ae = 0.75, 1.06, 1.50, and 2.12, respectively. The red dashed line shows a linear fit to the data above the threshold v  d /v Ae ≈ 1.
Paper: Wave Generation and Energetic Electron Scattering in Solar Flares
Authors: Hanqing Ma, J. F. Drake, M. Swisdak
Figure caption: (a) Electron trajectories in the x–y plane for the case of strong drift with v  d /v Ae = 2.12. Three electron trajectories are shown, with red dots indicating the starting positions and blue dots the end positions. The trajectories are from the middle of the simulation (around tΩ e  = 900). (b) Electron velocity trajectories corresponding to the three cases in panel (a) in v ∥–v ⊥ space. Red dots indicate the starting positions and blue dots are the ends of the trajectories. θ 0 gives the initial pitch angle.
Paper: Wave Generation and Energetic Electron Scattering in Solar Flares
Authors: Hanqing Ma, J. F. Drake, M. Swisdak
Figure caption: Two-dimensional plots of the out-of-plane magnetic field B  z  at tΩ e  = 1280. (a) The normal setup with v  d /v Ae = 1.50 (as shown in Figures 1 and 2); (b) the case with the reduced number density carrying the heat flux.
Paper: Wave Generation and Energetic Electron Scattering in Solar Flares
Authors: Hanqing Ma, J. F. Drake, M. Swisdak
Figure caption: Box-averaged out-of-plane magnetic fluctuation amplitude ﹩{B}_{z}^{2}﹩ as a function of time for the simulation with the reduced number density of electrons carrying the heat flux (dashed curve) and the corresponding base case (solid curve). Both have v  d /v Ae = 1.50.
Paper: Metallicity Dependence of Molecular Cloud Hierarchical Structure at Early Evolutionary Stages
Authors: Masato I. N. Kobayashi, Kazunari Iwasaki, Kengo Tomida, Tsuyoshi Inoue, Kazuyuki Omukai, Kazuki Tokuda
Figure caption: Three-dimensional view of the density and magnetic fields. Panels (a), (b), and (c) are at t = 3 Myr from 1.0 Z ⊙, 0.5 Z ⊙, and 0.2 Z ⊙. Panels (d) and (e) are at t = 3t cool from 0.5 Z ⊙ and 0.2 Z ⊙, which therefore correspond to t = 6.0 Myr and 15.0 Myr, respectively. We show the slices of the density field on the three boundaries at x = 10 pc, y = − 5 pc, and z = − 5 pc. The density is colored with n [cm−3] from blue (0.1 cm−3) to yellow (103 cm−3). The magnetic field lines are integrated from the two x-boundaries, whose strength ﹩\left|B\right|﹩ is colored in orange.
Paper: Metallicity Dependence of Molecular Cloud Hierarchical Structure at Early Evolutionary Stages
Authors: Masato I. N. Kobayashi, Kazunari Iwasaki, Kengo Tomida, Tsuyoshi Inoue, Kazuyuki Omukai, Kazuki Tokuda
Figure caption: The t cool-normalized time evolution of the volume-weighted velocity dispersion ﹩\sqrt{\langle \delta {v}^{2}\rangle }﹩ and the density-weighted velocity dispersion ﹩\sqrt{\langle \delta {v}^{2}{\rangle }_{\rho }}﹩ (panel (a)), the volume-weighted mean density 〈n〉 (panel (b)), and the averaged turbulent pressure 〈P turb〉 (panel (c)), where 〈P turb〉 = 〈ρ〉〈δ v 2〉 ρ . The black, red, and blue colors represent 1.0, 0.5, and 0.2 Z ⊙, respectively.
Paper: Metallicity Dependence of Molecular Cloud Hierarchical Structure at Early Evolutionary Stages
Authors: Masato I. N. Kobayashi, Kazunari Iwasaki, Kengo Tomida, Tsuyoshi Inoue, Kazuyuki Omukai, Kazuki Tokuda
Figure caption: The phase diagram of the shock-compressed layer. The upper (lower) panels compare the thermal states at t = 3 Myr (at t = 3t cool). The color represents the number of cells. The red circle at the lower left shows the initial state of the injected WNM, and the gray solid line emanating from that red point shows the isothermal line (i.e., P ∝ n). The black horizontal line shows the flow ram pressure.
Paper: Metallicity Dependence of Molecular Cloud Hierarchical Structure at Early Evolutionary Stages
Authors: Masato I. N. Kobayashi, Kazunari Iwasaki, Kengo Tomida, Tsuyoshi Inoue, Kazuyuki Omukai, Kazuki Tokuda
Figure caption: The phase histogram on the plane of the magnetic field strength and the number density. The color represents the number of the numerical cells. The black small circle shows the initial condition of the injected WNM flow, and the translucent dashed gray line emanating from this black circle shows the relation of B ∝ n 1. The horizontal black dashed line shows the typical maximum field strength by assuming the balance between the magnetic pressure and the inflow ram pressure is that of Equation (7). The black solid curve shows the volume-weighted mean field strength 〈B〉 as a function of density in the range of n ≥ 1 cm−3. The gray straight line at the top shows the relation of 〈B〉 ∝ n 1/5.
Paper: Metallicity Dependence of Molecular Cloud Hierarchical Structure at Early Evolutionary Stages
Authors: Masato I. N. Kobayashi, Kazunari Iwasaki, Kengo Tomida, Tsuyoshi Inoue, Kazuyuki Omukai, Kazuki Tokuda
Figure caption: The thermal equilibrium states as a function of pressure (P), density (n), and the metallicity (from 1.0–0.2 Z ⊙, shown with differently colored lines). The black circle at the bottom left shows the initial condition at 1.0 Z ⊙.
Paper: Metallicity Dependence of Molecular Cloud Hierarchical Structure at Early Evolutionary Stages
Authors: Masato I. N. Kobayashi, Kazunari Iwasaki, Kengo Tomida, Tsuyoshi Inoue, Kazuyuki Omukai, Kazuki Tokuda
Figure caption: The initial condition. The color shows n [cm−3]. The white lines represent the initial uniform magnetic fields with 1 μG strength. The two supersonic flows are injected through the two x-boundaries at x = − 10 and 10 pc, where the origin of the coordinate is at the box center.
Paper: Metallicity Dependence of Molecular Cloud Hierarchical Structure at Early Evolutionary Stages
Authors: Masato I. N. Kobayashi, Kazunari Iwasaki, Kengo Tomida, Tsuyoshi Inoue, Kazuyuki Omukai, Kazuki Tokuda
Figure caption: The one-dimensional averaged turbulent power spectrum of the shock-compressed layer at t = 3t cool. The cyan, blue, and red curves correspond to the total power, the solenoidal mode power, and the compressive mode power, respectively. Their width represents the Poisson noise at each frequency k. It is difficult to visually recognize the cyan curve because the solenoidal mode dominates the total power so that they almost overlap in this presentation. The two vertical gray lines show the lowest frequency of the shock-compressed layer and the Nyquist frequency. The thin gray dotted line shows one-tenth of the Nyquist frequency, above which the numerical diffusion impacts the Fourier power. We employ the powers between the left gray line (k/2π = 0.1 pc−1) and the thin dotted line (k/2π = 2.56 pc−1) to measure the total fraction of the solenoidal and compressive modes in the subsequent analyses and figures. The black dashed line shows the one-dimensional Kolmogorov spectrum of k 2 P  v (k) ∝ k −5/3.
Paper: Type W and Type 15bn Subgroups of Hydrogen-poor Superluminous Supernovae: Premaximum Diversity, Postmaximum Homogeneity?
Authors: Réka Könyves-Tóth, Bálint Seli
Figure caption: Left panel: continuum-normalized early-phase (between +1 and ∼+10 days) postmaximum spectra of the studied SLSNe-I corrected for redshift and Milky Way extinction. The orange color denotes Type W SLSNe-I, while Type 15bn objects are plotted in green. Right panel: continuum-normalized “later-phase” (between +10 and +35 days) postmaximum spectra of the studied SLSNe-I plotted with the same methodology and color coding as in the left panel.