adsabs/AstroCLIMB huggingface dataset:
Paper: CIBER Fourth-flight Fluctuation Analysis: Measurements of Near-infrared Auto and Cross Power Spectra on Arcminute to Subdegree Scales
Authors: Richard M. Feder, James J. Bock, Yun-Ting Cheng, Asantha Cooray, Phillip M. Korngut, Shuji Matsuura, Jordan Mirocha, Chi H. Nguyen, Kohji Takimoto, Kohji Tsumura, Ryan Wills, Michael Zemcov
Figure caption: Fractional response of half-exposure cross power spectra to integer pixel shifts between maps, evaluated on mocks with instrument noise only (dashed–dotted lines), point sources only (dotted), and their combination (solid). The same is then done for the observed data (crosses). The agreement between observed and mock responses supports the conclusion that the observed small-scale power is consistent with unmasked sources.
Paper: CIBER Fourth-flight Fluctuation Analysis: Measurements of Near-infrared Auto and Cross Power Spectra on Arcminute to Subdegree Scales
Authors: Richard M. Feder, James J. Bock, Yun-Ting Cheng, Asantha Cooray, Phillip M. Korngut, Shuji Matsuura, Jordan Mirocha, Chi H. Nguyen, Kohji Takimoto, Kohji Tsumura, Ryan Wills, Michael Zemcov
Figure caption: Comparison of auto power spectrum measurements using the fiducial method (red) and the method of half-exposure cross correlations (black). We use the same field weights for both sets of power spectra when calculating the field average. In the bottom panels we plot the ratio of the half-exposure cross power spectra and the fiducial, field-averaged power spectrum.
Paper: CIBER Fourth-flight Fluctuation Analysis: Measurements of Near-infrared Auto and Cross Power Spectra on Arcminute to Subdegree Scales
Authors: Richard M. Feder, James J. Bock, Yun-Ting Cheng, Asantha Cooray, Phillip M. Korngut, Shuji Matsuura, Jordan Mirocha, Chi H. Nguyen, Kohji Takimoto, Kohji Tsumura, Ryan Wills, Michael Zemcov
Figure caption: Wavelength dependence of surface brightness fluctuations from CIBER and Spitzer autospectra and cross spectra for multipoles 875 < ℓ < 1930. The central wavelengths of the plotted cross-spectrum measurements (crosses) are the means of the pairs of wavelengths from each cross correlation. We also show the IGL+ISL auto power spectrum based predictions (dashed blue), calculated over the same multipole range.
Paper: CIBER Fourth-flight Fluctuation Analysis: Measurements of Near-infrared Auto and Cross Power Spectra on Arcminute to Subdegree Scales
Authors: Richard M. Feder, James J. Bock, Yun-Ting Cheng, Asantha Cooray, Phillip M. Korngut, Shuji Matsuura, Jordan Mirocha, Chi H. Nguyen, Kohji Takimoto, Kohji Tsumura, Ryan Wills, Michael Zemcov
Figure caption: Comparison of auto power spectrum measurements for the two Boötes fields using our fiducial method (red) and the method of field differences (black), for which FF errors are mitigated. We find broad consistency between methods on large and small angular scales, validating our treatment of FF errors.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: Similar to Figure 8, a visualization of our posterior distributions for the enclosed dark matter mass MDM and NFW halo scale radius rs for fitting streams with various inclination angles (along the line of sight) in ΦDM and ΦGal. Key takeaways: for σtrack = 1 kpc, rs constraints improve with higher inclinations in ΦGal with and without RVs, while enclosed DM mass measurements become more precise for streams with higher inclinations and a RV included in the fit in ΦDM.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: Similar to Figure 8, a visualization of our posterior distributions for the enclosed dark matter mass MDM and scale radius rs in ΦDM and ΦGal for fitting streams with varying apocenters. Note that this figure differs from the others in that the top two panels showing the enclosed mass prior (gray shaded region) and true enclosed mass (dashed gray line) now vary as distance changes. Key takeaway: with current stream-track uncertainties, both MDM and rs are better measured for streams with apocenters larger than the scale radius of the halo.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: MCMC results for fitting mock stream-track observations of the stream with two wraps with σtrack = 1 kpc in ΦPL. The corner plot shows the MCMC samples for the initial stream parameters x, z, vx, vy, vz,  and ΦPL parameters vc and γ using only the mock observations of the stream track. The true values are indicated by the blue dots. Key takeaway: while the velocities still remain mostly unconstrained, both the stream’s initial position and γ are well recovered in this case.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: Left: a 2D histogram of γ samples vs. the inclination angle ϕ of the fiducial stream fit without a RV. Right: the same histogram of γ samples as a function of inclination angle for the stream with two wraps and no RV. The true values of γ and ϕ are denoted by dashed gray lines, while the darker colors correspond to a higher volume of samples. This visualizes the trade-off between γ and ϕ in the case where the stream does not have multiple loops and how the degeneracy is broken when the stream is long enough.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: The constraint on the radial profile of a stream in ΦPL as a function of the length of the stream. The gray dashed line denotes the true value of γ, while the colored circles and error bars correspond to the best-fit γ value and its 1σ (darker) and 2σ (lighter) uncertainties. The blue points correspond to fits done using only stream-track measurements, while the purple ones denote track fits including a RV measurement. Key takeaways: radial profile measurements improve with stream length, and γ can be tightly constrained with and without a RV for an track with two wraps around the host.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: Same as Figure 8, visualizing our posterior distributions for the enclosed dark matter mass MDM and scale radius rs in ΦDM and ΦGal for fitting streams with varying eccentricities. Key takeaways: with current track uncertainties, both the enclosed dark matter mass and scale radius measurements improve for orbits with lower eccentricities. MDM is best measured for the low-eccentricity (e = 0.2) case with a RV.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: Similar to Figure 9, the radial profile dependence on the inclination angle of an observed stream in ΦPL. Key takeaways: the radial profile is best recovered for observed streams with little inclination along the line of sight. Including a RV in the fit to constrain γ makes the most difference for the least inclined case.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: The dependence of radial profile constraints on the eccentricity of an observed stream in ΦPL. Key takeaway: while it is a weak trend, measuring the radial profile improves as the eccentricity increases, and adding a RV to the fit improves the measurement the most for the high-eccentricity (e = 0.7) case.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: The dependence of radial profile constraints on the distance of the apocenter from the host galaxy of an observed stream in ΦPL. Key takeaway: the precision of γ improves as distance increases for fits with a RV, but no constraints can be made for any of the cases.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: Similar in style to Figure 8, visualizes the dependence of how well MDM and rs are constrained as a function of the number of RV measurements included when fitting the fiducial stream in ΦDM (left side) and ΦGal (right side). The blue points correspond to the fits without any radial velocities included, the purple points include one RV in the fit, green points include two, and pink points include three. Key takeaway: more than one RV measurement does not improve the ability to recover MDM and rs significantly. For both potentials, additional RV measurements yield similar constraints for rs, while a second and third RV measurement slightly improves on the MDM constraint.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: Left: normalized histograms displaying the enclosed dark matter mass posterior distributions within 15 kpc for the stream case with two wraps and no RV in ΦDM (blue) and ΦGal (purple), with medians indicated by the dashed vertical lines of the corresponding color. The truth is denoted by a dashed black line. Right: a zoomed-in version of the left panel showing the lower mass range (≤20 × 1010 M⊙) of both distributions. Key takeaway: the MDM posterior hits a lower bound in ΦGal instead of going to zero, demonstrating the ability of the stream with two wraps to limit the range of possible enclosed DM masses.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: Normalized histograms displaying the enclosed mass prior, posterior, and mixed (prior informed by rs posterior) distributions for the e = 0.2 stream case with one RV in ΦGal. The colors and labels denote the same aspects of the plot as in Figure 20. Key takeaway: the MDM posterior in this case seems to be the least affected by the bias induced by a rs constraint.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: Normalized histograms displaying the enclosed mass prior (gray), posterior (purple), and mixed (prior informed by rs posterior in blue) distributions for the stream case with two wraps and no RV in ΦDM. Each histogram has a dashed line of the corresponding color denoting the median of the distribution. The true enclosed dark matter mass is denoted by the black dashed line. Key takeaway: this demonstrates how the tight constraint on rs in this case influences the enclosed DM mass posterior.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: Initial stream velocity and circular velocity vc MCMC results for fitting mock stream-track observations with a RV measurement of the stream with two wraps with σtrack = 1 kpc in ΦPL. Key takeaway: this illustrates how the velocity degeneracies seen in Figure 17 are broken once a RV is added to the fit.
Paper: Probing the Dark Matter Halos of External Galaxies with Stellar Streams
Authors: Madison Walder, Denis Erkal, Michelle Collins, David Martínez-Delgado
Figure caption: The dependence of a γ constraint on the number of RV measurements included when fitting the fiducial stream in ΦPL. Key takeaway: the addition of a second RV significantly boosts the accuracy of the γ measurement, while a third RV yields similar results.
Paper: Prestellar Cores in Turbulent Clouds: Observational Perspectives on Structure, Kinematics, and Lifetime
Authors: Sanghyuk Moon, Eve C. Ostriker
Figure caption: (a) Similar to Figure 3(b), but using Gaussian-convolved NH,c to calculate ﹩{n}_{{\rm{H}},c}^{{\rm{obs}}}﹩ (see text for the context and beam size choice). (b) Similar to Figure 5(c), but using this “beam-smoothed” version of ﹩{n}_{{\rm{H}},c}^{{\rm{obs}}}﹩ in the abscissa. The black line with symbols plot the average Δtbin,cum at each bin measured for simulated cores, which can be compared to the observational lifetime based on the relative number count (Equation (42)). The thick blue solid line plots the lifetime derived from the aggregated core counts from nine HGBS clouds relative to the number of Class II objects, assuming the nominal Class II lifetime of ΔtII = 2 Myr and constant star formation rate. To facilitate the shape comparison, we plot the same curve scaled down arbitrarily by a factor of 6.7, as the thin blue line.
Paper: Prestellar Cores in Turbulent Clouds: Observational Perspectives on Structure, Kinematics, and Lifetime
Authors: Sanghyuk Moon, Eve C. Ostriker
Figure caption: (a) Radial profiles of the three-dimensional rms velocity dispersion (Equation (39)) for all critical cores. Circles mark each core’s critical radius. (b) Projected radial profiles of the line-of-sight velocity dispersion (see Equations (24)–(26) for the relevant definitions), using the threshold density ﹩{n}_{{\rm{\min }}}=2\times 1{0}^{4}\,{{\rm{cm}}}^{-3}﹩. Thin lines represent individual cores projected along x-, y-, and z-axes. Panels (c) and (d) shows the similar projected profiles using ﹩{n}_{{\rm{\min }}}=6\times 1{0}^{3}\,{{\rm{cm}}}^{-3}﹩ and 2 × 103 cm−3, respectively. In all panels, the thick line with error bars plots the median and ± 34.1th percentiles. In panels (b)–(d), the individual curves extend to the radius touching the Nd contour at 10% of the central value.
Paper: Prestellar Cores in Turbulent Clouds: Observational Perspectives on Structure, Kinematics, and Lifetime
Authors: Sanghyuk Moon, Eve C. Ostriker
Figure caption: (a) Time evolution of the observational central volume density, with each line representing an individual core. The x-axis is shifted with respect to the critical time of each core. For comparison, we also plot the theoretical trajectory of freefall collapse starting from a central density of 105 cm−3 by the red line. (b) Histogram of the time spent in each density bin (Equation (32)). (c) Cumulative histogram of the time spent above each density bin (Equation (33)). For reference, we plot tff and 2tff as a function of the central density in panels (b) and (c) using dotted lines.
Paper: Prestellar Cores in Turbulent Clouds: Observational Perspectives on Structure, Kinematics, and Lifetime
Authors: Sanghyuk Moon, Eve C. Ostriker
Figure caption: The line-of-sight velocity dispersion averaged within a circular aperture Rap = RFWHM,d, vs. the plane-of-sky core radius RFWHM,d. Both quantities are computed after applying the density selection function Θthr to the data, where panels (a) and (b) show the results using a top-hat and a step function, respectively. For comparison, we plot the best-fit intrinsic line width–size relation shown in Figure 7(a) as solid lines in both panels. In panel (a), we additionally show our best-fit relation ﹩{\sigma }_{{\rm{los}}}={c}_{s}{({R}_{{\rm{FWHM}},d}/0.24\,{\rm{pc}})}^{0.44}﹩ as a dashed line, together with observed σlos and RFWHM,d for six starless cores from G. A. Fuller & P. C. Myers (1992). Circles, triangles, and squares represent NH3, CS, and C18O observations, respectively.
Paper: Prestellar Cores in Turbulent Clouds: Observational Perspectives on Structure, Kinematics, and Lifetime
Authors: Sanghyuk Moon, Eve C. Ostriker
Figure caption: The line-of-sight velocity dispersion σlos (Equation (41)) vs. the effective line-of-sight path length leff (Equation (40)), for all critical cores seen in x-, y-, and z-projections. Both quantities are obtained by taking average over a pencil beam with fixed aperture Rap = 0.05 pc around each core center. Red, orange, and blue points correspond to the results with ﹩{n}_{{\rm{\min }}}=2\times 1{0}^{4}\,{{\rm{cm}}}^{-3}﹩, 6 × 103 cm−3, and 2 × 103 cm−3. The dashed line is the least-square fit over the data range leff ∈ [0.02, 1] pc, and the solid line represents the best-fit intrinsic relation (i.e., the fit to the median curve shown in Figure 7(a); see text for the fit parameters).
Paper: Prestellar Cores in Turbulent Clouds: Observational Perspectives on Structure, Kinematics, and Lifetime
Authors: Sanghyuk Moon, Eve C. Ostriker
Figure caption: Distribution of the sonic radius (relative to cloud-scale LJ,0) and the average density (relative to mean cloud density ρ0) of cores measured at their individual tcrit. Red and blue circles correspond to individual cores formed in Mach 5 and Mach 10 models, respectively, with a hue representing the ratio rcrit/rs. The red and blue horizontal lines show rs,box for Mach 5 and Mach 10 models, respectively. The three diagonal dashed lines plot the loci of rcrit/rs = 0.1, 1, and 10 (from top to bottom) for the TESs with p = 0.5.
Paper: Prestellar Cores in Turbulent Clouds: Observational Perspectives on Structure, Kinematics, and Lifetime
Authors: Sanghyuk Moon, Eve C. Ostriker
Figure caption: Similar to Figure 8, but using the observational proxy leff,obs (see Equation (43)) instead of the true leff (see Equation (40)). We repeat our calculation of σlos and leff,obs using two different Θthr (top-hat vs. step function) and two alternative Rap (RFWHM,d vs. fixed 0.05 pc). The results for each of four combinations are shown in panels (a)–(d), with the choices for Θthr and Rap annotated on top. In each panel, solid lines show the intrinsic line width–size relation (i.e., the best-fit line in Figure 7(a)), and dashed lines show the least-square fits to the measured σobs/cs and leff,obs (results denoted in bottom right corners).
Paper: Prestellar Cores in Turbulent Clouds: Observational Perspectives on Structure, Kinematics, and Lifetime
Authors: Sanghyuk Moon, Eve C. Ostriker
Figure caption: Selected trajectories of the “remaining lifetime” (Equation (31)) as a function of ﹩{n}_{{\rm{H}},c}^{{\rm{obs}}}﹩. Plus symbols mark the loci of t = tcrit (at this point, the hue changes from blue to red) for the entire core sample, with those corresponding to the selected trajectories bold-faced. Dotted diagonal lines indicate tff and 2tff.
Paper: Prestellar Cores in Turbulent Clouds: Observational Perspectives on Structure, Kinematics, and Lifetime
Authors: Sanghyuk Moon, Eve C. Ostriker
Figure caption: The ratio of the average starless (i.e., prior to introduction of a sink particle) duration above each central density bin to the average infall time measured for simulated cores (black line with markers). Here, similar to Figure 9, we use the beam-smoothed version of ﹩{n}_{{\rm{H}},c}^{{\rm{obs}}}﹩ for comparison with observation. Blue line plots the cumulative histogram of the prestellar core counts (i.e., total number above each ﹩{n}_{{\rm{H}},c}^{{\rm{obs}}}﹩ bin), normalized by the number of Class 0+I sources. The observed core sample is taken from nine HGBS clouds for which both the prestellar core and YSO catalogs are available.
Paper: Characterizing the Star Cluster Populations in Stephan’s Quintet Using HST and JWST Observations
Authors: P. Aromal, S. C. Gallagher, K. Fedotov, N. Bastian, U. Lisenfeld, J. C. Charlton, P. N. Appleton, J. Braine, K. E. Johnson, P. Tzanavaris, B. H. C. Emonts, A. Togi, C. K. Xu, P. Guillard, L. Barcos-Muñoz, L. J. Smith, I. S. Konstantopoulos
Figure caption: The cluster age vs cluster mass relation as obtained from CIGALE SED fitting for different regions of interest as described in Section 3.3. The star formation rate estimated for the regions based on derived age and mass as explained in Section 3.4 is shown in each panel.
Paper: Characterizing the Star Cluster Populations in Stephan’s Quintet Using HST and JWST Observations
Authors: P. Aromal, S. C. Gallagher, K. Fedotov, N. Bastian, U. Lisenfeld, J. C. Charlton, P. N. Appleton, J. Braine, K. E. Johnson, P. Tzanavaris, B. H. C. Emonts, A. Togi, C. K. Xu, P. Guillard, L. Barcos-Muñoz, L. J. Smith, I. S. Konstantopoulos
Figure caption: The figure shows the spatial distribution of SCCs around the merging galaxies 7318a/b in different cluster age bins as derived from the CIGALE SED fits (color coded with respect to the cluster age). The different regions of interest, as shown in Figure 6, are marked in white: 1 - SQA, 2 - Ridge (Left arc), 3 - Southern arm (Left arc), 4 - Right arc, 5 - USDR, and 6 - SDR. It can be seen that the very young SCCs (∼a few megayears) are predominantly clustered along shock regions near the merging galaxies, while older globular clusters are more widely scattered.
Paper: Characterizing the Star Cluster Populations in Stephan’s Quintet Using HST and JWST Observations
Authors: P. Aromal, S. C. Gallagher, K. Fedotov, N. Bastian, U. Lisenfeld, J. C. Charlton, P. N. Appleton, J. Braine, K. E. Johnson, P. Tzanavaris, B. H. C. Emonts, A. Togi, C. K. Xu, P. Guillard, L. Barcos-Muñoz, L. J. Smith, I. S. Konstantopoulos
Figure caption: The histogram of the distribution of SCC properties (1588 SCCs) such as cluster age (top), AV (middle), and cluster mass (bottom) as derived from CIGALE fits using only HST photometry (blue dashed lines) and HST+JWST photometry (orange solid lines).
Paper: Characterizing the Star Cluster Populations in Stephan’s Quintet Using HST and JWST Observations
Authors: P. Aromal, S. C. Gallagher, K. Fedotov, N. Bastian, U. Lisenfeld, J. C. Charlton, P. N. Appleton, J. Braine, K. E. Johnson, P. Tzanavaris, B. H. C. Emonts, A. Togi, C. K. Xu, P. Guillard, L. Barcos-Muñoz, L. J. Smith, I. S. Konstantopoulos
Figure caption: Top panel: the histogram of best-fit μ values (﹩\mu =\frac{{A}_{V,{\rm{ISM}}}}{{A}_{V,{\rm{BC}}}+{A}_{V,{\rm{ISM}}}}﹩) after keeping it as a free parameter in CIGALE runs as discussed in 3.2.1. Note that we exclude sources with AV,total = AV,ISM + AV,BC = 0 (334 SCCs) for which μ values have no physical significance. Middle and bottom panels: comparison of CIGALE parameters such as cluster age (top) and cluster mass (bottom) using fiducial model parameters and after varying input parameters such as μ.
Paper: Characterizing the Star Cluster Populations in Stephan’s Quintet Using HST and JWST Observations
Authors: P. Aromal, S. C. Gallagher, K. Fedotov, N. Bastian, U. Lisenfeld, J. C. Charlton, P. N. Appleton, J. Braine, K. E. Johnson, P. Tzanavaris, B. H. C. Emonts, A. Togi, C. K. Xu, P. Guillard, L. Barcos-Muñoz, L. J. Smith, I. S. Konstantopoulos
Figure caption: This figure shows three examples of comparison between CIGALE SED fits and the output parameters based on HST + JWST photometry and HST photometry only for (1) top panel: an SCC with a consistent young age of ∼4 Myr; (2) middle panel: an SCC with consistent older age of ∼2 × 108 yr; (3) bottom panel: an SCC (R.A. = 339.0255, decl. = 33.9636) that shows large changes in age and extinction (Δ ∼ 1 dex) values after the inclusion of NIR photometry. This is a clear example how NIRCam photometry affects the age–extinction degeneracy.
Paper: Characterizing the Star Cluster Populations in Stephan’s Quintet Using HST and JWST Observations
Authors: P. Aromal, S. C. Gallagher, K. Fedotov, N. Bastian, U. Lisenfeld, J. C. Charlton, P. N. Appleton, J. Braine, K. E. Johnson, P. Tzanavaris, B. H. C. Emonts, A. Togi, C. K. Xu, P. Guillard, L. Barcos-Muñoz, L. J. Smith, I. S. Konstantopoulos
Figure caption: The zoom-in of the JWST NIRCam false-color image, focusing on a region of interest that is mostly covered by U336 and V547 HST bands, which have the smallest field of view. The different regions of interest in the SQ field as mentioned in 3.3 are marked here for clarity.