adsabs/AstroCLIMB huggingface dataset:
Paper: Distributions and Physical Properties of Molecular Clouds in the Third Galactic Quadrant: l = [219.°75, 229.°75] and b = [−5.°25, 5.°25]
Authors: Yiwei Dong, Yan Sun, Ye Xu, Zehao Lin, Shuaibo Bian, Chaojie Hao, Dejian Liu, Yingjie Li, Ji Yang, Yang Su, Xin Zhou, Shaobo Zhang, Qing-Zeng Yan, Zhiwei Chen
Figure caption: Histograms of the excitation temperatures (left) and H2 column densities (right). Top to bottom: histograms of the Local, Perseus, and Outer arms. The mask “B,” “G,” and “R” regions are colored in blue, green, and red, respectively. The vertical dashed lines in the corresponding colors indicate the median values.
Paper: Distributions and Physical Properties of Molecular Clouds in the Third Galactic Quadrant: l = [219.°75, 229.°75] and b = [−5.°25, 5.°25]
Authors: Yiwei Dong, Yan Sun, Ye Xu, Zehao Lin, Shuaibo Bian, Chaojie Hao, Dejian Liu, Yingjie Li, Ji Yang, Yang Su, Xin Zhou, Shaobo Zhang, Qing-Zeng Yan, Zhiwei Chen
Figure caption: Longitude–velocity (left) and latitude–velocity (right) maps of the “cleaned” CO emission, integrated over a Galactic latitude range from −5.°25 to 5.°25 and a Galactic longitude range from 219.°75 to 229.°75, respectively. The maps only contain emission from the samples in our catalog. Masks “B,” “G,” and “R” indicate the regions where 12CO, 13CO, and C18O emission exists, respectively. The three contaminated MCs are marked as the red circles. The dashed lines sketch out the boundaries of each velocity layer.
Paper: Distributions and Physical Properties of Molecular Clouds in the Third Galactic Quadrant: l = [219.°75, 229.°75] and b = [−5.°25, 5.°25]
Authors: Yiwei Dong, Yan Sun, Ye Xu, Zehao Lin, Shuaibo Bian, Chaojie Hao, Dejian Liu, Yingjie Li, Ji Yang, Yang Su, Xin Zhou, Shaobo Zhang, Qing-Zeng Yan, Zhiwei Chen
Figure caption: Left: histograms of the rms noise levels (σ) for 12CO (blue), 13CO (green), and C18O (red). The median values of σ and the total number of pixels are marked in the top right corner. Right: cumulative distributions of σ.
Paper: The New Swift/UVOT+MaNGA (SwiM) Value-added Catalog
Authors: Mallory Molina, Laura Duffy, Michael Eracleous, Mary Ogborn, Mary E. Kaldor, Renbin Yan, Caryl Gronwall, Robin Ciardullo, Nikhil Ajgaonkar
Figure caption: Top left: same as Figure 1, but for stellar mass. SwiM_v4.1 is slightly overdense in low-mass galaxies as compared to MaNGA. Top right: same as Figure 1, but for the SFR as measured by the total Hα luminosity within one effective radius (R e). The L(Hα) measurements are corrected for both foreground extinction and internal attenuation, assuming the O’Donnell (1994) law, R V  = 3.1, and an intrinsic Balmer ratio of 2.86. SwiM has a significant overabundance in low-SFR objects. Bottom: SFR(Hα) within 1 R e versus stellar mass for the SwiM_v4.1 catalog (green filled circles) as compared to the MaNGA MPL-11 catalog (black and gray contours). The SFRs are corrected for reddening as described above. While SwiM_v4.1 generally recovers both the star-forming and passive galaxy sequences, the catalog is slightly overpopulated at the lower-mass, low-SFR end of the diagram and underpopulated in the transition region between red and blue galaxies, compared to the MaNGA sample. See Sections 6.1 and 6.2 for details.
Paper: The New Swift/UVOT+MaNGA (SwiM) Value-added Catalog
Authors: Mallory Molina, Laura Duffy, Michael Eracleous, Mary Ogborn, Mary E. Kaldor, Renbin Yan, Caryl Gronwall, Robin Ciardullo, Nikhil Ajgaonkar
Figure caption: 2D histograms of the number distribution of the MPL-11 MaNGA main sample (top left), SwiM_v4.1 (top right), and the ratio between the two (bottom center), in g − r versus stellar mass. The two sample distributions on the top show high density as yellow, and low density as shades of purple, denoted by the color bar. The MaNGA main sample has a strong peak in the high-mass portion of the red sequence. While the SwiM_v4.1 catalog appears to have a qualitatively similar distribution, the difference between the two samples is clear in the ratio of the number densities (﹩{n}_{\mathrm{SwiM}}﹩ and n MaNGA, respectively) in the bottom panel. Both number densities are calculated by normalizing to the total number of objects in each sample. If the number densities are equal, the bin color is white, while overdensities in SwiM_v4.1 catalog are represented by shades of red and underdensities by shades of blue, as denoted by the color bar. The inner region red sequence is slightly undersampled in SwiM_v4.1, while the lower-mass, red-end of the distribution is oversampled.
Paper: The New Swift/UVOT+MaNGA (SwiM) Value-added Catalog
Authors: Mallory Molina, Laura Duffy, Michael Eracleous, Mary Ogborn, Mary E. Kaldor, Renbin Yan, Caryl Gronwall, Robin Ciardullo, Nikhil Ajgaonkar
Figure caption: The [O III]/Hβ versus [N II]/Hα, [S II]/Hα, and [O I]/Hα diagrams for the nuclear resolution element of the AGN candidate galaxies. The extreme starburst, Seyfert, and LINER lines from Kewley et al. (2006) are shown as solid black lines, while the composite line, representing galaxies where emission is dominated neither by star formation nor by AGN activity, from Kauffmann et al. (2003) is shown as a dashed line. The different regions within the three diagrams are labeled, with “SF” and “C” corresponding to the star-forming and composite loci, respectively. The characteristic error bar for each diagram is shown in the upper left corner. Galaxies outside of the star-forming locus on all three diagrams are shown as black circles, those outside of the locus in two of the three diagrams are shown as red squares, those outside in just one are shown as green triangles, and those in the star-forming locus in all three diagrams are shown as blue stars. There are 67 galaxies that fall outside the star-forming locus in all three diagrams.
Paper: The New Swift/UVOT+MaNGA (SwiM) Value-added Catalog
Authors: Mallory Molina, Laura Duffy, Michael Eracleous, Mary Ogborn, Mary E. Kaldor, Renbin Yan, Caryl Gronwall, Robin Ciardullo, Nikhil Ajgaonkar
Figure caption: Distributions of redshift (top left), g − r color (top right), Petrosian half-light radius (derived using r-band photometry, bottom left), and the r-band axis ratio (b/a, bottom right) of the galaxies in the new SwiM catalog, SwiM_v4.1, as compared to the MaNGA MPL-11 catalog. All the histograms are normalized by the total number of galaxies in each data set. For each panel, the red solid outline denotes the SwiM_v4.1 distribution, while the gray shaded region represents the MaNGA sample. All the data presented here are from the NSA. The SwiM_v4.1 catalog has a similar distribution to the MaNGA sample for each of these properties. Please see Sections 6.1 and 6.2 for details.
Paper: The New Swift/UVOT+MaNGA (SwiM) Value-added Catalog
Authors: Mallory Molina, Laura Duffy, Michael Eracleous, Mary Ogborn, Mary E. Kaldor, Renbin Yan, Caryl Gronwall, Robin Ciardullo, Nikhil Ajgaonkar
Figure caption: Left: the distribution of exposure times for each Swift/UVOT filter in seconds, with uvw2 shown as a gray filled histogram, uvw1 as a solid red line, and the intermediate-bandpass uvm2 filter displayed as a dashed blue line. Right: the S/N distribution for the integrated Swift/UVOT NUV fluxes, with a same color scheme as the left panel. We note that ∼20% of galaxies in all three filters have an integrated flux with an S/N < 10. However, we purposely make no cuts on S/N, so as not to bias the data set toward particular science questions. A more in-depth discussion on these statistics is provided in Section 6.3.
Paper: The New Swift/UVOT+MaNGA (SwiM) Value-added Catalog
Authors: Mallory Molina, Laura Duffy, Michael Eracleous, Mary Ogborn, Mary E. Kaldor, Renbin Yan, Caryl Gronwall, Robin Ciardullo, Nikhil Ajgaonkar
Figure caption: Histogram of the K-S test statistic for 1000 random samples drawn from the MaNGA main sample. The test statistic for the SwiM_v4.1 catalog is denoted by the red vertical line. SwiM_v4.1 lies at the 13.6th percentile of the distribution, and thus there is only a small statistical probability that a random sample pulled from the MaNGA main sample would have properties similar to the catalog.
Paper: Linear Mode Decomposition in Magnetohydrodynamics Revisited
Authors: G. P. Zank, L.-L. Zhao, L. Adhikari, M. Nakanotani, A. Pitňa, D. Telloni, H. Che
Figure caption: The black curves denote the reconstruction of the normalized (left column, top to bottom) total density δ ρ, and fluctuating velocity components δ u  z,y,x  respectively, from the summed mode decomposition, over which are plotted (orange curves) the corresponding measured values δ ρ  m  and ﹩\delta {u}_{z,y,x}^{m};﹩ (right column, top to bottom), total pressure δ p, and fluctuating magnetic field components δ B  z,y,x , respectively, over which are plotted (black curves) the corresponding normalized measured values δ p  m  and ﹩\delta {B}_{z,y,x}^{m}﹩. All fluctuating quantities are normalized to the appropriate mean value as labeled.
Paper: Linear Mode Decomposition in Magnetohydrodynamics Revisited
Authors: G. P. Zank, L.-L. Zhao, L. Adhikari, M. Nakanotani, A. Pitňa, D. Telloni, H. Che
Figure caption: PSD plots of the fluctuating magnetic field. Top row: the frequency spectra of the magnetic island and forward Alfvén, fast, and slow magnetosonic modes (left); and the spectra of the magnetic island and backward Alfvén, fast, and slow magnetosonic modes (right). The dashed line in each plot is a reference f −5/3 spectrum. Middle row: the parallel wavenumber spectra of the magnetic island and forward and backward Alfvén mode magnetic field fluctuations (left); the parallel wavenumber spectra of the parallel and perpendicular components, as well as the total magnetic field fluctuations of the fast magnetosonic modes (middle); and the parallel wavenumber spectra of the parallel and perpendicular components, as well as the total magnetic field fluctuations of the slow magnetosonic modes (right). Bottom row: the perpendicular wavenumber spectra of the magnetic island and forward and backward Alfvén mode magnetic field fluctuations (left); the perpendicular wavenumber spectra of the parallel and perpendicular components, as well as the total magnetic field fluctuations of the fast magnetosonic modes (middle); and the perpendicular wavenumber spectra of the parallel and perpendicular components, as well as the total magnetic field fluctuations of the slow magnetosonic modes (right).
Paper: Linear Mode Decomposition in Magnetohydrodynamics Revisited
Authors: G. P. Zank, L.-L. Zhao, L. Adhikari, M. Nakanotani, A. Pitňa, D. Telloni, H. Che
Figure caption: Mode decomposition over the highly aligned 30 minute interval showing the density fluctuations. Top row, left to right: the frequency spectra of the entropy, forward fast and slow, and backward fast and slow magnetosonic modes, δ ρ  e , δ ρ  f±, and δ ρ  s±; Bottom left: from top to bottom the entropy mode and the forward and backward fast and slow magnetosonic modes. Bottom right: PSDs in isotropic wavenumber k of the entropy the and forward- (top) and backward-propagating magnetosonic modes (bottom). All fluctuating quantities are normalized to the mean density as labeled.
Paper: Linear Mode Decomposition in Magnetohydrodynamics Revisited
Authors: G. P. Zank, L.-L. Zhao, L. Adhikari, M. Nakanotani, A. Pitňa, D. Telloni, H. Che
Figure caption: The orange curves denote the normalized measured data for the full 30 minute interval showing (left column, top to bottom) the normalized fluctuating total pressure δ p and the fluctuating magnetic field components δ B  z,y,x , as well as (right column, top to bottom) the density δ ρ and the fluctuating velocity components δ u  z,y,x , respectively, over which are plotted (black curves) the reconstructed values derived from the connected six 5 minute intervals. All fluctuating quantities are normalized to the appropriate mean value as labeled.
Paper: Linear Mode Decomposition in Magnetohydrodynamics Revisited
Authors: G. P. Zank, L.-L. Zhao, L. Adhikari, M. Nakanotani, A. Pitňa, D. Telloni, H. Che
Figure caption: PSD plots of the fluctuating velocity field showing (left) frequency spectra of the forward Alfvén, fast, and slow magnetosonic modes (left); and spectra of the backward Alfvén, fast, and slow magnetosonic modes (right). The dashed line in each plot is a reference f −5/3 spectrum. Middle row: the parallel wavenumber spectra of the forward and backward Alfvén mode magnetic field fluctuations (left); the parallel wavenumber spectra of the parallel and perpendicular components, as well as the total velocity field fluctuations of the fast magnetosonic modes (middle); and the parallel wavenumber spectra of the parallel and perpendicular components, as well as the total velocity field fluctuations of the slow magnetosonic modes (right). Bottom row: the perpendicular wavenumber spectra of the forward and backward Alfvén mode magnetic field fluctuations (left); the perpendicular wavenumber spectra of the parallel and perpendicular components, as well as the total velocity field fluctuations of the fast magnetosonic modes (middle); and the perpendicular wavenumber spectra of the parallel and perpendicular components, as well as the total velocity field fluctuations of the slow magnetosonic modes (right).
Paper: Linear Mode Decomposition in Magnetohydrodynamics Revisited
Authors: G. P. Zank, L.-L. Zhao, L. Adhikari, M. Nakanotani, A. Pitňa, D. Telloni, H. Che
Figure caption: Overview of a 30 minute slow solar wind interval observed by the Solar Orbiter spacecraft on 2020 August 12. From top to bottom, we plot the magnitude of the magnetic field ∣B∣, the components of the magnetic field (left axis and black curves) and velocity field (right axis and blue curves) in the RTN coordinate system, the angle θ  BV  between the magnetic and flow velocity vectors, the proton number density, and the proton plasma beta β  p .
Paper: Linear Mode Decomposition in Magnetohydrodynamics Revisited
Authors: G. P. Zank, L.-L. Zhao, L. Adhikari, M. Nakanotani, A. Pitňa, D. Telloni, H. Che
Figure caption: PSD plots for the fluctuating density showing the frequency spectra of the entropy and the forward fast and slow magnetosonic modes (left), the frequency spectra of the entropy and the backward fast and slow magnetosonic modes (middle), and the wavenumber spectra of the entropy and forward fast and slow magnetosonic modes (right). The dashed lines in the left and middle plots are reference f −5/3 curves, and that in the right plot is a k −5/3 curve.
Paper: Linear Mode Decomposition in Magnetohydrodynamics Revisited
Authors: G. P. Zank, L.-L. Zhao, L. Adhikari, M. Nakanotani, A. Pitňa, D. Telloni, H. Che
Figure caption: The orange curve shows the fully nonlinear FFT-derived PSD for the transverse magnetic field fluctuations drawn from the original data in the 30 minute interval shown in Figure 2. The black curve is a reconstructed spectrum for the transverse fluctuations derived by summing the transverse contributions from each mode that admits transverse fluctuations, i.e., the separate transverse contributions from each of the Alfvén, magnetic island, forward fast, backward fast, forward slow, and backward slow modes. The dashed line represents f −5/3.
Paper: Linear Mode Decomposition in Magnetohydrodynamics Revisited
Authors: G. P. Zank, L.-L. Zhao, L. Adhikari, M. Nakanotani, A. Pitňa, D. Telloni, H. Che
Figure caption: PSD plots for the fluctuating pressure showing wavenumber spectra of the forward fast and slow magnetosonic modes.
Paper: The Multiwavelength Environment of Second Bologna Catalog Sources
Authors: A. Paggi, F. Massaro, H. Penã-Herazo, V. Missaglia, A. Jimenez-Gallardo, F. Ricci, S. Ettori, G. Giovannini, F. Govoni, R. D. Baldi, B. Mingo, M. Murgia, E. Liuzzo, F. Galati
Figure caption: Surface flux profiles for the sources that show evidence of extended X-ray emission in the soft 0.3–3 keV band (see Section 3.1). For each source we present with black dots the surface flux profiles from the source itself, and with red dots the profiles from the simulated PSF.
Paper: The Multiwavelength Environment of Second Bologna Catalog Sources
Authors: A. Paggi, F. Massaro, H. Penã-Herazo, V. Missaglia, A. Jimenez-Gallardo, F. Ricci, S. Ettori, G. Giovannini, F. Govoni, R. D. Baldi, B. Mingo, M. Murgia, E. Liuzzo, F. Galati
Figure caption: Spectral fits of the extended X-ray emission (excluding the regions connected with extended radio structures) presented in Table 5 with a model including a thermal plasma plus Galactic absorption. For each source, in the upper part of the panel we show the extracted spectrum with blue crosses and the best-fit model with a blue line, while in the lower part of the panel we show the residuals.
Paper: The Multiwavelength Environment of Second Bologna Catalog Sources
Authors: A. Paggi, F. Massaro, H. Penã-Herazo, V. Missaglia, A. Jimenez-Gallardo, F. Ricci, S. Ettori, G. Giovannini, F. Govoni, R. D. Baldi, B. Mingo, M. Murgia, E. Liuzzo, F. Galati
Figure caption: Spectral fits of the extended X-ray emission presented in Table 4 with a model including a thermal plasma plus Galactic absorption. For each source, in the upper part of the panel we show the extracted spectrum with blue crosses and the best-fit model with a blue line, while in the lower part of the panel we show the residuals.
Paper: The Multiwavelength Environment of Second Bologna Catalog Sources
Authors: A. Paggi, F. Massaro, H. Penã-Herazo, V. Missaglia, A. Jimenez-Gallardo, F. Ricci, S. Ettori, G. Giovannini, F. Govoni, R. D. Baldi, B. Mingo, M. Murgia, E. Liuzzo, F. Galati
Figure caption: Nuclear spectral fits presented in Table 2 with a power law plus Galactic absorption model. For each source, in the upper part of the panel, we show the extracted spectrum with blue crosses and the best-fit model with a blue line, while in the lower part of the panel we show the residuals.
Paper: The Multiwavelength Environment of Second Bologna Catalog Sources
Authors: A. Paggi, F. Massaro, H. Penã-Herazo, V. Missaglia, A. Jimenez-Gallardo, F. Ricci, S. Ettori, G. Giovannini, F. Govoni, R. D. Baldi, B. Mingo, M. Murgia, E. Liuzzo, F. Galati
Figure caption: Nuclear spectral fits presented in Table 3 with a power-law model with slope fixed to 1.8 plus Galactic absorption, and an additional absorption component. For each source, in the upper part of the panel we show the extracted spectrum with blue crosses and the best-fit model with a blue line, while in the lower part of the panel we show the residuals.
Paper: The Multiwavelength Environment of Second Bologna Catalog Sources
Authors: A. Paggi, F. Massaro, H. Penã-Herazo, V. Missaglia, A. Jimenez-Gallardo, F. Ricci, S. Ettori, G. Giovannini, F. Govoni, R. D. Baldi, B. Mingo, M. Murgia, E. Liuzzo, F. Galati
Figure caption: X-ray 0.3–3 keV extended emission fluxes vs. 145 MHz specific fluxes of the extended radio structures (see Section 3.1). Upper limits on X-ray fluxes are represented with triangles pointing down. The blue line indicates the linear regression to the logarithmic data, while the light blue shaded area represents the 1σ uncertainty around the best-fit relation.
Paper: Noise Reduction Methods for Large-scale Intensity-mapping Measurements with Infrared Detector Arrays
Authors: Grigory Heaton, Walter Cook, James Bock, Jill Burnham, Sam Condon, Viktor Hristov, Howard Hui, Branislav Kecman, Phillip Korngut, Hiromasa Miyasaka, Chi Nguyen, Stephen Padin, Marco Viero
Figure caption: Spatial power spectrum of a 32-channel N = 74 image pair difference obtained with a physical H2RG array and the readout electronics, before and after r = 32 reference correction with distributed rows. S = 24 row chopping is applied during readout. The range of ﹩\theta =5^{\prime} \mbox{--}20^{\prime} ﹩ is shown in red, corresponding to 0.03 < k < 0.13 pix−1. An estimate of the photon noise spectra due to the expected zodiacal light incident photocurrents in the first 4 SPHEREx bands (spanning 0.75–3.8μm) for the SPHEREx deep fields at the ecliptic poles is also included. Reference correction and row chopping provide a significant noise reduction at large spatial scales on measured images, with spatial noise brought near the level of the ZL photocurrent photon noise.
Paper: Noise Reduction Methods for Large-scale Intensity-mapping Measurements with Infrared Detector Arrays
Authors: Grigory Heaton, Walter Cook, James Bock, Jill Burnham, Sam Condon, Viktor Hristov, Howard Hui, Branislav Kecman, Phillip Korngut, Hiromasa Miyasaka, Chi Nguyen, Stephen Padin, Marco Viero
Figure caption: (a) Pixel standard deviation σ as a function of frame count N, after σ clipping, for measured and simulated images produced using a single Video8 (8 channels) with r = 32 ACN reference correction and (b) spatial power spectra for uncorrected 32-channel image pairs at N = 74, showing an offset between output spectra, particularly at high k. For (a), measured channels are processed by subtracting a low-noise N = 386 ACN reference-corrected long exposure. Unmodeled per-pixel noise increases the deviation between measured and simulated channels at large N, even after accounting for dark current variation (see Section 3.3).
Paper: Noise Reduction Methods for Large-scale Intensity-mapping Measurements with Infrared Detector Arrays
Authors: Grigory Heaton, Walter Cook, James Bock, Jill Burnham, Sam Condon, Viktor Hristov, Howard Hui, Branislav Kecman, Phillip Korngut, Hiromasa Miyasaka, Chi Nguyen, Stephen Padin, Marco Viero
Figure caption: Spatial power spectrum from a 32-channel N = 74 simulated image realization with S = 24 row chopping and r = 32 reference correction. We obtain a significant improvement at low k compared with the uncorrected image.
Paper: Noise Reduction Methods for Large-scale Intensity-mapping Measurements with Infrared Detector Arrays
Authors: Grigory Heaton, Walter Cook, James Bock, Jill Burnham, Sam Condon, Viktor Hristov, Howard Hui, Branislav Kecman, Phillip Korngut, Hiromasa Miyasaka, Chi Nguyen, Stephen Padin, Marco Viero
Figure caption: Average noise power on ﹩\theta =5^{\prime} \mbox{--}20^{\prime} ﹩ scales (0.03 < k < 0.13 pix−1) with varying skip parameter S for a 32-channel N = 74 simulated reference-corrected image with all noise sources active. Here, we calculate noise after excluding the horizontal axis in Fourier space (see Figure 7) to isolate the effect of row chopping from reference correction limitations.
Paper: Noise Reduction Methods for Large-scale Intensity-mapping Measurements with Infrared Detector Arrays
Authors: Grigory Heaton, Walter Cook, James Bock, Jill Burnham, Sam Condon, Viktor Hristov, Howard Hui, Branislav Kecman, Phillip Korngut, Hiromasa Miyasaka, Chi Nguyen, Stephen Padin, Marco Viero
Figure caption: 2D Fourier transform magnitudes in arbitrary units of a 32-channel simulated image before and after S = 24 row chopping, cropped to show the region near the origin. Noise power is transferred from the horizontal axis to discrete packets above and below. Significant power remains on the horizontal axis, demonstrating the need for reference correction. We excluded the horizontal axis in Figure 6 to optimize the choice of skip parameter.
Paper: Noise Reduction Methods for Large-scale Intensity-mapping Measurements with Infrared Detector Arrays
Authors: Grigory Heaton, Walter Cook, James Bock, Jill Burnham, Sam Condon, Viktor Hristov, Howard Hui, Branislav Kecman, Phillip Korngut, Hiromasa Miyasaka, Chi Nguyen, Stephen Padin, Marco Viero
Figure caption: Average noise power on ﹩\theta =5^{\prime} \mbox{--}20^{\prime} ﹩ scales as a function of the number of row samples r for both reference correction methods with S = 24 row chopping, averaged over five simulated 32-channel images. The distributed method provides an improvement over repeated sampling of the default reference rows, at little cost to readout time from row shifts.