adsabs/AstroCLIMB huggingface dataset:
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: Top panel: average cross-power spectrum between the cleaned CMB maps from Pipelines B (empty circles) and C (filled squares) and the lensing template. Different colors represent the results for the three foreground suites. The spectra are normalized to the input lensed BB power spectrum, and the error bars are divided by ﹩\sqrt{{N}_{{\rm{sims}}}}﹩. Bottom panel: lensing template noise power spectrum, calculated using Equation (29), with the same color coding as in the top panel. The black dashed line represents the fiducial lensing B-mode power. The auto-spectrum of the lensing template and the cross-spectrum between the lensing template and the cleaned CMB maps form part of the input data vector for the likelihood. This illustrates the high degree of recovery in the lensing B modes, consistent with S. Belkner et al. (2023), and highlights the agreement in cross-power and uncertainties between Pipelines B and C across different foreground models.
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: Comparison of the recovered mean cleaned CMB BB power spectrum across the two component-separation methods (B and C) and across foreground suites (0/1/2), normalized with respect to the input theory. In each panel, the empty circle points show the results from Pipeline B, while the filled squares refer to Pipeline C. We show results obtained for foreground suites 0, 1, and 2 in blue, orange, and green, respectively. The left panel shows results for ΛCDM-only simulations (r = 0), while the right panel presents the case with PGW power (r = 0.003). Note that the error bars are divided by ﹩\sqrt{250}﹩. The shaded gray bands denote modes at ℓ < 30 and ℓ > 200, which are not used in the likelihood analysis. As in Figure 3, Model 2 shows a notable excess of residual power at large angular scales, whereas Models 0 and 1 exhibit minimal to negligible residuals.
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: Scatter plots and histograms displaying best-fit tensor-to-scalar ratio values from different component-separation pipelines for three foreground models in the r = 0 scenario. Each panel provides pairwise comparisons of the pipelines. The scatter plots in the off-diagonal panels show correlations of the r values between the pipelines, with Pearson correlation coefficients indicated by ρ. The histograms on the diagonal display the distribution of maximum-likelihood estimates of r values for each pipeline, with smooth lines representing kernel density estimates of the histograms. Colors orange, green, and blue represent foreground models 1, 2, and 3, respectively. The faint-blue line in the histograms illustrates the case of extended foreground marginalization applied when considering foreground model 2.
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: Summary of the biases and uncertainties on the inferred tensor-to-scalar ratios across component-separation pipelines and foreground models. Each point shows the mean ﹩\bar{r}﹩ and standard deviation σ(r) (in units of 10−3). Results are shown for foreground models 0, 1, and 2 from left to right, while the blue diamond/red circle/orange square markers indicate pipelines A, B, and C, respectively. Empty markers show results from the extended cleaning pipelines (only for the high-complexity Model 2). Points at the bottom correspond to input r = 0, while those at the top are for r = 0.003.
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: Lensing template noise bias for foreground models 3–5 (see Section 4.2.4). We show the difference between the idealistic estimate of the noise bias including full knowledge of the respective foreground template (NLT,PySM) and the more realistic estimate of a fully Gaussian foreground simulation with matching two-point power (NLT,Gauss). In a realistic analysis, only the latter could be used and the potential bias due to the non-Gaussian/higher-order correlations are not captured in these simulations as shown in the dashed lines.
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: Flowchart of the simulation generation and foreground-cleaning process. The simulation generation is described in Section 4 and includes simulations of the CMB, CMB-S4 noise at each frequency as well as multifrequency simulations of various foreground models. These simulated maps are fed into three different component separation pipelines (labeled A, B, and C) as well as a realistic lensing B-mode reconstruction pipeline. The outputs of these pipelines are passed to a likelihood to estimate the bias and uncertainty on r.
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: Normalized hit pattern on the sky for the South Pole small aperture telescopes’ (SATs') ultra-deep survey. The gray background shows the Galactic dust map from Planck Commander in intensity plotted on a logarithmic scale.
Paper: The Slow Brightening of WNTR23bzdiq/WTP19aalzlk: Possible Onset of Common Envelope Evolution in an Asymptotic Giant Branch Star?
Authors: Viraj R. Karambelkar, Mansi M. Kasliwal, Kishalay De, Danielle Frostig, Robert Stein, Geoffrey Mo, Nathan P. Lourie, Robert A. Simcoe, Nadejda Blagorodnova
Figure caption: The r-band lightcurve (red points) shows evidence for periodicity at the end of the first eruption in 2023, with two successive bumps of ≈0.2 mag amplitude (open dashed square). The inset shows a phase-folded lightcurve of these two bumps, where the flux has been normalized by a smooth GP fit (black line) and phase folded at the derived period of 84 days.
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: Mean set of auto and cross-BB spectra from the CMB-S4 South Pole deep patch across different frequencies and foreground models. The three different models are Model 0 (Gaussian simulations, shown in blue), Model 1 (amplitude-modulated simulations, shown in orange), and Model 2 (Vansyngel simulations, shown in green). The auto-spectra are not noise debiased. The dotted black line represents the lensed CMB spectrum, while the dashed black line represents the combination of the lensed CMB, foreground components (from Model 0), and instrumental noise (for auto-spectra). The blue lines completely overlap with the black dashed lines in all cases. The Model 2 curves (green) show noticeably suppressed power in certain multipole bins, reflecting the loss of dust coherence (decorrelation) between widely separated frequency channels due to spatial variations in the dust spectral index.
Paper: A Unified Three-dimensional Magnetohydrodynamic Model of the Solar Corona, Solar Wind, and Global Heliosphere with Turbulence Transport
Authors: Arcadi V. Usmanov, Rohit Chhiber, William H. Matthaeus, Sohom Roy, Melvyn L. Goldstein
Figure caption: Color maps of the plasma, magnetic field and turbulence parameters in region 1 (1–30 R⊙) in the meridional plane ﹩\phi =0\mathop{.}\limits^{\unicode{x000b0}}75﹩: (a) radial velocity ur, (b) proton density NS, (c) magnetic field magnitude B, (d) twice the turbulence energy per unit mass Z2, (e) normalized cross helicity σc, (f) correlation length scale λ, (g) proton temperature TS, (h) electron temperature TE, and (i) normalized energy difference σD. The heliocentric distance is in solar radii.
Paper: A Unified Three-dimensional Magnetohydrodynamic Model of the Solar Corona, Solar Wind, and Global Heliosphere with Turbulence Transport
Authors: Arcadi V. Usmanov, Rohit Chhiber, William H. Matthaeus, Sohom Roy, Melvyn L. Goldstein
Figure caption: Ulysses daily averages of plasma and magnetic field parameters (blue) as a function of heliographic latitude, measured during Ulysses’ first fast latitude transit from 1994 September 13 to 1995 July 31, compared with simulated profiles (red) for a solar dipole tilted by 10∘. The parameters shown are (a) radial velocity ur, (b) number density of thermal protons NS, and (c) thermal proton temperature TS, (d) radial magnetic field component Br, (e) azimuthal magnetic field component Bϕ, and (f) electron temperature TE. Two estimates of the proton temperature, “T-large” and “T-small”, measured by Ulysses (B. E. Goldstein 2003), are shown by the blue solid and dotted lines, respectively.
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: Scatter plots displaying the inferred foreground parameters βd (dust spectral index, top row) and βs (synchrotron spectral index, bottom row) from two component-separation methods: map-based maximum likelihood (Pipeline C) and cross-spectral likelihood (Pipeline A). Each column corresponds to a different foreground suite: Gaussian (Model 0), amplitude modulated (Model 1), and Vansyngel (Model 2), from left to right. Points are color-coded to represent different tensor-to-scalar ratio scenarios, with blue representing r = 0 and orange representing r = 0.003. The black cross in each panel marks the input values used in the simulations, where applicable. In all cases, except for βd in Model 2, Pipelines A and C yield consistent dust parameter measurements.
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: Mean foreground spectra recovered by the parametric map-based maximum-likelihood Pipeline C. The left panel shows the mean Galactic dust spectra, while the right panel displays the mean synchrotron spectra. Different colors (orange, red, and blue) in each panel represent results from the various foreground suites (0, 1, and 2). The error bars correspond to a single realization. The uncertainties for Model 2 appear smaller compared to other models, as only one full-sky realization of the foreground power is available. The spectra have been debiased for instrumental noise.
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: Correlation matrices for the three foreground simulation models. Each matrix evaluates the Pearson correlation coefficients calculated from the inferred tensor-to-scalar ratios r using the three distinct foreground-cleaning methods on 250 simulations. In each panel, the upper triangle matrix shows results for r = 0.003 while the elements in the lower triangle matrix correspond to r = 0. The matrices are color-coded from 0 to 1. For foreground model 2, effects of extending the nominal pipelines to marginalize over residual foreground contamination are noted in parentheses.
Paper: A Unified Three-dimensional Magnetohydrodynamic Model of the Solar Corona, Solar Wind, and Global Heliosphere with Turbulence Transport
Authors: Arcadi V. Usmanov, Rohit Chhiber, William H. Matthaeus, Sohom Roy, Melvyn L. Goldstein
Figure caption: Same as in Figure 2, but in region 2 (30 R⊙–5 au). The heliocentric distance is in astronomical units.
Paper: CMB-S4: Foreground-cleaning Pipeline Comparison for Measuring Primordial Gravitational Waves
Authors: Federico Bianchini, Dominic Beck, W. L. Kimmy Wu, Zeeshan Ahmed, Sebastian Belkner, Julien Carron, Brandon S. Hensley, Clement L. Pryke, Caterina Umiltá
Figure caption: The same figure as Figure 11, but predicting the correlation coefficients from the spread of the distributions of r summarized in Table 2 for each foreground model.
Paper: A Unified Three-dimensional Magnetohydrodynamic Model of the Solar Corona, Solar Wind, and Global Heliosphere with Turbulence Transport
Authors: Arcadi V. Usmanov, Rohit Chhiber, William H. Matthaeus, Sohom Roy, Melvyn L. Goldstein
Figure caption: Color maps of the computed quantities in the meridional plane containing the interstellar upwind direction, from 40 to 600 au. The simulation is based on a solar magnetic dipole aligned with the solar rotation axis. The parameters shown are (a) radial velocity ur, (b) number density of thermal protons NS, (c) magnetic field magnitude B, (d) thermal proton temperature TS, (e) electron temperature TE, (f) number density of atomic hydrogen NH (g) pickup proton pressure PI, (h) number density of pickup protons NI, (i) twice the turbulence energy per unit mass Z2, (j) normalized cross helicity σc, (k) normalized energy difference σD, and (l) correlation length scale λ.
Paper: A Unified Three-dimensional Magnetohydrodynamic Model of the Solar Corona, Solar Wind, and Global Heliosphere with Turbulence Transport
Authors: Arcadi V. Usmanov, Rohit Chhiber, William H. Matthaeus, Sohom Roy, Melvyn L. Goldstein
Figure caption: Radial profiles of the flow, magnetic field, and turbulence parameters in the upstream direction from 40 to 1200 au for the simulation with the solar dipole aligned with the solar rotation axis: (a) radial velocity ur and magnetic field strength B; (b) thermal proton NS, pickup proton NI, interstellar hydrogen NH, and total proton NS + NI densities; (c) proton TS, electron TE, pickup proton TI, interstellar hydrogen TH, and mean plasma ﹩\bar{T}﹩ temperatures, where ﹩\bar{T}=({T}_{S}{N}_{S}+{T}_{E}{N}_{E}+{T}_{I}{N}_{I})/({N}_{S}+{N}_{E}+{N}_{I})﹩; (d) proton PS, electron PE, pickup proton PI, interstellar hydrogen PH, and magnetic PM pressures; (e) turbulent energy density Z2 and correlation length scale λ; (f) cross helicity σc and energy difference σD. The vertical lines mark the approximate locations of the termination shock, heliopause, and bow shock (TS/HP/BS).
Paper: A Unified Three-dimensional Magnetohydrodynamic Model of the Solar Corona, Solar Wind, and Global Heliosphere with Turbulence Transport
Authors: Arcadi V. Usmanov, Rohit Chhiber, William H. Matthaeus, Sohom Roy, Melvyn L. Goldstein
Figure caption: Results of the simulation along the Parker Solar Probe’s (PSP) sixth orbit, from 2020 August 28 to October 27, in comparison with PSP observations. Solar wind, magnetic field, and turbulence parameters observed by PSP are shown by blue crosses: (a) radial velocity ur, (b) number density of solar wind protons NS, (c) radial magnetic field Br, (d) temperature of solar wind protons TS, (e) azimuthal magnetic field Bϕ, (f) the correlation length scale λ, (g) twice the mean turbulent energy Z2, (h) normalized cross helicity σc, and (i) normalized energy difference σD. All observed quantities are 1 hr averages, except for λ, which is calculated from PSP data every 24 hr. Red lines denote the corresponding simulated values. The first realization (of 12) of the ADAPT map with a central meridian time of 2020 September 27 at 12:00 UTC was used as the inner boundary condition. The vertical dotted line indicates PSP’s sixth perihelion. Shaded regions in panels (a), (c), and (e) represent envelopes formed by adding and subtracting the local turbulence amplitude from the simulated mean values.
Paper: The Galaxy–Active Galactic Nucleus Scaling Relations over 13 Billion Years in SHARK v2.0. I. Supermassive Black Hole Masses
Authors: Matías Bravo, Claudia del P. Lagos, Katy L. Proctor, Ángel Chandro-Gómez, Chris Power
Figure caption: Comparison of the BHMF predicted by SHARK v2.0 from z = 9 to z = 0 to observational results from the literature. Each panel corresponds to the SMBH mass function at the redshift indicated at the top right corner. The lines show the results from SHARK v2.0, the total BHMF with the thick black line, the total BHMF with a 0.5 dex scatter applied to M• with the thin (solid) black line, and the contribution of central and satellites in teal and orange, respectively. The z = 0 BHMF is repeated in the other panels with the dotted black line to highlight the time evolution of the BHMF. Observational data shown are from F. Shankar et al. (2009) with gray bands, J. Wu et al. (2022) with a solid dark gray line and shaded area at z = 6, single Schechter fit from E. R. Liepold & C.-P. Ma (2024) with a hatched reddish gray at z = 0, C. J. Burke et al. (2025) with solid dark gray line and shaded area at z = 0, the lower limits from Y. Shen & B. C. Kelly (2012) with light gray arrows, and the lower limits from T. T. Ananna et al. (2022), W. He et al. (2024), and J. Matthee et al. (2024) with dark gray arrows, three-pointed stars, and triangles, respectively.
Paper: A Unified Three-dimensional Magnetohydrodynamic Model of the Solar Corona, Solar Wind, and Global Heliosphere with Turbulence Transport
Authors: Arcadi V. Usmanov, Rohit Chhiber, William H. Matthaeus, Sohom Roy, Melvyn L. Goldstein
Figure caption: Radial profiles of the angular momentum flux integral ﹩{\dot{J}}_{\odot }﹩ (Equation (32)), labeled “total,” and its individual components from 5 to 40 au (region 3): the plasma component ﹩{\dot{J}}_{P}={\int }_{0}^{\pi }{\int }_{0}^{2\pi }{r}^{3}{\sin }^{2}\theta \rho {u}_{r}{u}_{\phi }d\theta d\phi ﹩, the magnetic component ﹩{\dot{J}}_{M}=-{\int }_{0}^{\pi }{\int }_{0}^{2\pi }{r}^{3}{\sin }^{2}\theta ({B}_{r}{B}_{\phi }/4\pi )d\theta d\phi ﹩, the turbulent component ﹩{\dot{J}}_{T}={\int }_{0}^{\pi }{\int }_{0}^{2\pi }{r}^{3}{\sin }^{2}\theta {{ \mathcal R }}_{r\phi }d\theta d\phi ﹩, which is plotted with the opposite sign, and the component due to pickup protons, ﹩{\dot{J}}_{{pp}}={\int }_{0}^{\pi }{\int }_{0}^{2\pi }{r}^{3}{\sin }^{2}\theta {m}_{p}{N}_{I}{u}_{r}{u}_{\phi }d\theta d\phi ﹩.
Paper: A Unified Three-dimensional Magnetohydrodynamic Model of the Solar Corona, Solar Wind, and Global Heliosphere with Turbulence Transport
Authors: Arcadi V. Usmanov, Rohit Chhiber, William H. Matthaeus, Sohom Roy, Melvyn L. Goldstein
Figure caption: Simulation results (red lines) for a solar dipole aligned with the Sun’s rotation axis, compared with New Horizons spacecraft observations (blue crosses) reported by D. J. McComas et al. (2023), along the spacecraft’s trajectory between 11.26 and 46.40 au from 2008 October 10 to 2020 January 26. The 25 days averaged solar wind plasma parameters shown are (a) number density of thermal protons NS, (b) radial velocity ur, (c) temperature of thermal protons TS, (d) number density of pickup protons NI, and (e) temperature of pickup protons TI.
Paper: A Unified Three-dimensional Magnetohydrodynamic Model of the Solar Corona, Solar Wind, and Global Heliosphere with Turbulence Transport
Authors: Arcadi V. Usmanov, Rohit Chhiber, William H. Matthaeus, Sohom Roy, Melvyn L. Goldstein
Figure caption: Results of the simulation at 1 au from 2020 August 28 to October 27 (red lines), in comparison with WIND observations (blue “+” symbols). The simulation uses the ADAPT map with a central meridian time 2020 September 27 at 12:00 UTC as the boundary condition. The same parameters as in Figure 4 are shown. Observed plasma and magnetic field values in panels (a)–(e) are hourly averages from the OMNI2 data set. The turbulence quantities in panels (f)–(i) are six-hour averages, computed from the 5 minutes of OMNI data. Red lines represent the simulated values.
Paper: A Unified Three-dimensional Magnetohydrodynamic Model of the Solar Corona, Solar Wind, and Global Heliosphere with Turbulence Transport
Authors: Arcadi V. Usmanov, Rohit Chhiber, William H. Matthaeus, Sohom Roy, Melvyn L. Goldstein
Figure caption: Same as in Figure 7, but for the boundary conditions in the interstellar medium specified by Set 2 in Table 2.
Paper: The Galaxy–Active Galactic Nucleus Scaling Relations over 13 Billion Years in SHARK v2.0. I. Supermassive Black Hole Masses
Authors: Matías Bravo, Claudia del P. Lagos, Katy L. Proctor, Ángel Chandro-Gómez, Chris Power
Figure caption: Comparison of the predicted M⋆,bulge–M• distribution in SHARK v2.0 from z = 9 to z = 0 to observational results from the literature. Each panel corresponds to the M⋆,bulge–M• distribution at the redshift indicated at the bottom right corner. The colored histograms in the background show the overall distribution of SHARK v2.0 galaxies at each redshift, linearly colored and with the scale adjusted for maximum contrast in each panel (i.e., the exact value of a given shade changes from panel to panel), with higher-density regions in darker shades. The solid and dotted lines showing the running medians and 16th and 84th running percentiles, respectively. Literature measurements from observations are shown in the panel with the closest redshift. Observational data shown are from V. N. Bennert et al. (2011) with pentagons, N. J. McConnell & C.-P. Ma (2013) with squares, A. W. Graham & N. Sahu (2023a) with circles (including the G. Chabrier 2003 initial mass function (IMF) correction from A. W. Graham & N. Sahu 2024), and J. I. H. Li et al. (2023) with diamonds.
Paper: The Galaxy–Active Galactic Nucleus Scaling Relations over 13 Billion Years in SHARK v2.0. I. Supermassive Black Hole Masses
Authors: Matías Bravo, Claudia del P. Lagos, Katy L. Proctor, Ángel Chandro-Gómez, Chris Power
Figure caption: Similar to Figure 3, showing a comparison of the predicted M⋆–M• distribution in SHARK v2.0 from z = 9 to z = 0 to observational results from the literature. Observational data shown are from R. Decarli et al. (2010a, 2010b) with crosses, A. Merloni et al. (2010) with downward triangles, V. N. Bennert et al. (2011) with squares, T. A. Targett et al. (2012) with octagons, A. E. Reines & M. Volonteri (2015) with pentagons, V. F. Baldassare et al. (2020) with upward triangles, H. Suh et al. (2020) with thin crosses, X. Ding et al. (2023) with circles, A. W. Graham & N. Sahu (2023a) with three-pointed stars, Y. Harikane et al. (2023) with hexagons, J. I. H. Li et al. (2023) with diamonds, I. E. López et al. (2023) with inverted three-pointed stars, R. Maiolino et al. (2024) with thick crosses, and R. Poitevineau et al. (2023) with stars.