adsabs/AstroCLIMB huggingface dataset:
Paper: Insights into the X-Ray Burst Pulse Morphology from SGR J1935+2154
Authors: Jiao-Jiao Yang, Shuo Xiao, Yue Wang, Shao-Lin Xiong, Lin Lin, Zheng-Huo Jiang, Tong-Lei Liao, Xiao-Bo Li, Cheng-Kui Li, Shu-Xu Yi, Zhen Zhang, Shuang-Nan Zhang
Figure caption: Correlations among pulse parameters (amplitude, peakedness, width, skewness, and rise/decay time) of MXBs from SGR J1935+2154 detected by HXMT. The power-law fits (black) characterize these relationships as y = bxa, where a represents the power-law index and b denotes the proportionality constant.
Paper: The Extended Atlas of Low-resolution Spectra from the Infrared Astronomical Satellite
Authors: G. C. Sloan, Kathleen E. Kraemer, K. Volk
Figure caption: A layered histogram showing the distribution of sources in the original LRS Atlas and the supplemental sources as a function of Galactic latitude close to the Galactic plane. The bin closest to the plane has 205 original sources and 707 supplemental and extra sources, for a total of 912 sources.
Paper: The Extended Atlas of Low-resolution Spectra from the Infrared Astronomical Satellite
Authors: G. C. Sloan, Kathleen E. Kraemer, K. Volk
Figure caption: The resolution element (Δλ) as a function of wavelength for the blue and red segments of the LRS at each wavelength in the standard LRS wavelength grid.
Paper: The Extended Atlas of Low-resolution Spectra from the Infrared Astronomical Satellite
Authors: G. C. Sloan, Kathleen E. Kraemer, K. Volk
Figure caption: The results of applying the new spectral correction, which is derived from both red giants and warmer stars. The new correction reproduces the SiO band in a late K giant well, and it reduces the degradation of the A dwarf at the blue end.
Paper: The Extended Atlas of Low-resolution Spectra from the Infrared Astronomical Satellite
Authors: G. C. Sloan, Kathleen E. Kraemer, K. Volk
Figure caption: Assembling the spectral correction for the red giants. Top: the ratios of the LRS spectrum divided by the template spectrum for the same star. Bottom: the same ratios, after normalization to the flux-weighted mean at 10.6–13.4 μm, along with the preliminary spectral correction derived from the individual ratios (in black).
Paper: The Extended Atlas of Low-resolution Spectra from the Infrared Astronomical Satellite
Authors: G. C. Sloan, Kathleen E. Kraemer, K. Volk
Figure caption: Combining the spectral corrections from the red giants and warm stars. Top: the new correction is the average of the corrections for the red giants and warm stars determined in the bottom two panels, and the Cohen correction is included for comparison. Middle and bottom: determining the final corrections for the red giants and warm stars, respectively. The orange and light-blue curves give the preliminary corrections, and the dark-red and dark-blue curves give the final corrections. The error bars in the Cohen correction are as reported by M. Cohen et al. (1992a); all other error bars are the uncertainty in the mean.
Paper: The Extended Atlas of Low-resolution Spectra from the Infrared Astronomical Satellite
Authors: G. C. Sloan, Kathleen E. Kraemer, K. Volk
Figure caption: Assembling the spectral correction for the warm stars. As in Figure 8, the top and bottom panels show the ratios of LRS to spectral template before and after normalization at 10.6–13.4 μm. The plotting range in the top panel is much wider than in Figure 8 to accommodate the greater spread in the ratios of spectrum to template.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The angular stacking signal from H I only mocks (no foregrounds and thermal noise), averaged over 100 realizations. The stacked image is calculated according to Equation (19) and averaged into a 1D profile according to Equation (21). The upper-left panel shows the stacked image without any PCA cleaning effects, and the upper-right panel shows the case with PCA cleaning of 10 modes. The excess signal at the center corresponds to the primary beam. The apparent ellipticity and orientation of the excess signal around the center are due to projection, as explained in Figure 3. Note that the pixels away from the center region also have a nonzero emission in the left panel. In the H I only case, the first 10 eigenmodes contain much more H I signal, as there is no foreground to be removed, and therefore, the signal loss is more severe. The lower panel shows the 1D polar average of the stacked image for the PCA cleaned case (“With PCA effects”). The error bars are the standard deviations of the stacked profile among the realizations. For illustration, the primary beam profile matching the amplitude of the first Δθ bin is plotted in black dashed line (“Beam”).
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: Upper panel: the frequency-averaged flux density map of mock H I signal for one realization. The flux density is shown in the unit of Jy pixel−1, where the pixel area is 0.3 × 0.3 deg2. Lower panel: the mock galaxy positions in one realization. Blue dots show galaxies that are generated in the comoving box that are outside the MeerKLASS survey area (“Buffer”). They are included in the H I signal simulation as required by the beam smoothing. Orange dots show galaxies that are inside the MeerKLASS survey area but outside the GAMA region (“Outside GAMA”). Green dots show the galaxies inside the GAMA region that have relatively small H I mass and are not included in the subsample for stacking (“Unselected”). The red dots show the galaxies selected for stacking (“GAMA-like sample”). Note the high number density of galaxies results in pixelated clumps seen in the panel. They correspond to the resolution over which the galaxy overdensity is generated, which is much smaller than the resolution of the 21 cm maps.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The spectral stacking signal from H I only mocks, averaged over 100 realizations. The stacked spectrum is calculated according to Equation (22). The stacked H I signal without any PCA cleaning (“Without PCA effects”), with PCA cleaning of 10 modes (“With PCA effects”), and the average of the input H I profiles of the GAMA-like galaxies (“Input profile”) are shown. The zoomed-in panel shows the stacked spectrum after PCA for ∣Δv∣< 1600 km s−1, compared against the average of the input H I galaxies. The stacked spectrum is much larger than the input profile due to the beam smoothing, which causes double counting of H I sources. The black dashed lines show the ∣Δv∣ = 1000 km s−1 boundary within which the stacked angular image is produced. In the H I only case with no foreground and noise, the first 10 eigenmodes of PCA contain much more H I signal, as there is no foreground to be removed, and therefore, the signal loss is more severe compared to the full mock case shown later in Figure 9.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: Top panel: the frequency-averaged intensity map from the MeerKLASS L-band deep-field data reported in MK25. The maps are trimmed so that only pixels within 334° < R.A. < 357° and −35° < decl. < −26﹩\mathop{.}\limits^{\unicode{x000b0}}﹩5 are kept. The green dots denote the positions of the overlapping GAMA galaxies within the redshift bin of the intensity mapping data. Bottom panel: the time-stamp counts of each pixel in the intensity map.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The EIDOS primary beam model (K. M. B. Asad et al. 2021) for the MeerKAT telescope. For the visualization, the beam is pointed toward the center of the survey area ﹩(\mathrm{R.A.,\; decl.})=(345\mathop{.}\limits^{^\circ }4,-31\mathop{.}\limits^{^\circ }4)﹩ at the center of the frequency sub-band ν = 997.38 MHz. Note that the apparent ellipticity and orientation of the beam are due to projecting the sky coordinates onto the Cartesian grids. The angular grid lines are shown as black dotted lines to further illustrate the projection.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The redshift distribution of the GAMA G23 catalog. The blue solid line denotes the distribution for the entire catalog, whereas the orange filled region denotes the distribution of the subsample that overlaps with the intensity mapping data. The top-right corner shows the zoom-in of the overlapping redshift bin. Note that the values are different in the zoomed-in plot due to different choices of binning width in redshift.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The frequency-averaged brightness temperature map for the mock foreground signal.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: Upper-left panel: the measurement of the stacked spectrum of the MeerKLASS L-band deep-field data over the GAMA galaxies (“Stacked spectrum”). The orange dashed line shows the average of the reference spectrum over the random shuffles (“Reference spectrum”). The green dotted line shows the standard deviation of the reference spectrum among the random shuffles (“Reference spectrum rms”). The shaded region shows the estimated measurement error (“Measurement error”), which is also the square root of the diagonal elements of the estimated covariance matrix. The vertical dashed lines show the ∣v∣ < 6500 km s−1 boundary within which we use to calculate the detection significance. Upper-right panel: the estimated correlation matrix. Lower-left panel: the same as the upper-left panel, but the stacked spectrum is symmetrized. The vertical dashed lines show the 0 < v < 6500 km s−1 boundary within which we use to perform model inference. Lower-right panel: the estimated correlation matrix for the symmetrized spectrum.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The angular stacking signal from full mocks (including foreground and noise simulation), averaged over 100 realizations. The top panel shows the average of the stacked images across the realizations, and the central panel shows the standard deviation of the realizations. The dashed circle in the top panel denotes the 1.2° boundary within which the signal is summed into the stacked spectrum. Note the differences in the color scale in the two panels. The lower panel shows the 1D polar average of the stacked image for the full mock (“Stacked mock signal”). The error bars are the standard deviations of the stacked profile among the realizations. For illustration, the primary beam profile matching the amplitude of the first Δθ bin is plotted in black dashed line (“Beam”).
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The spectral stacking signal from full mocks, averaged over 100 realizations. The H I only signal without any PCA cleaning is shown in the blue solid line, with the plateau from double counting subtracted (“HI only—plateau”). The averaged spectrum of the full mocks with PCA cleaning of 10 modes is shown in the yellow dashed line. The shaded region corresponds to the standard deviation among the realizations. The average of the input H I profiles of the GAMA-like galaxies (“Input profile”) is also shown for reference.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: Left panel: the measured angular stacked image. The dashed circle shows the 1.2° boundary within which we use to calculate the stacked spectrum. Center-left panel: the average of the reference image across all random shuffles. Center panel: the reference image standard deviation among the random shuffles. Center-right panel: the measurement error at each pixel in the stacked image, which is also the square root of the diagonal elements of the estimated covariance matrix. Note that the color scale for the center and center-right panels are different from the color scale for the left- and center-left panels. Right panel: the estimated correlation matrix from mock covariance. The indexing of the array iterates from left to right, and then bottom to top of the stacked image.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: Left panel: the standard deviation of the angular stacked image across the mock realizations, which is also the square root of the diagonal elements of the mock covariance matrix ﹩{{\boldsymbol{C}}}_{\mathrm{angular}}^{\mathrm{mock}}﹩. Center-left panel: the reference image standard deviation among the random shuffles, averaged across all mock realizations, which is also the square root of the diagonal elements of the estimated covariance from shuffling ﹩{\bar{{\boldsymbol{C}}}}_{\mathrm{angular}}^{\mathrm{shuffle}}﹩. Center-right panel: the correlation matrix from mock covariance. The indexing of the array iterates from left to right, and then bottom to top of the stacked image. Right panel: the correlation matrix from covariance estimation using shuffling.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: Left panel: the blue solid line shows the standard deviation of the spectral stacked spectrum across the mock realizations (“Mock standard deviation”), which is also the square root of the diagonal elements of the mock covariance matrix ﹩{{\boldsymbol{C}}}_{\mathrm{spectral}}^{\mathrm{mock}}﹩. The orange dashed line shows the average of the standard deviation of the randomly shuffled reference spectrum across the realizations (“Reference spectrum rms”). Center-right panel: The correlation matrix from mock covariance. Right panel: the correlation matrix from covariance estimation using random shuffling.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The comparison between the correlation matrix of the symmetrized stacked spectrum using the true mock covariance and the shuffling estimate. The upper triangle of the matrix shows values from the true mock covariance, and the lower triangle shows values from the shuffling.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The stacked spectrum of the H I signal from simplified assumption (“Simplified assumption”), compared against the true H I signal (“Full mock”). The results shown are averaged across 100 realizations. The shaded region around the dashed line shows the standard deviation for the simplified assumption case among the realizations.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The 1D polar average of the stacked image (“Stacked signal”). The error bars are the standard deviations of the stacked profile among the realizations. For illustration, the primary beam profile matching the amplitude of the first Δθ bin is plotted in black dashed line (“Beam”).
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The posterior distribution of the parameter fitting results of this work. The histogram plots show the posterior distribution of each model parameter when marginalizing over all other parameters. The contour plots show the marginalized 2D posterior distribution of each parameter pair. The outer contour denotes the 2σ confidence region, whereas the inner contour denotes the 1σ confidence region. Three scenarios are shown, with the shape of systematics fixed (“[﹩{\bar{M}}_{\mathrm{HI}}﹩,Asys] ”), varying the amplitude and the oscillation frequency (“[﹩{\bar{M}}_{\mathrm{HI}}﹩,Asys,νsys]” ), and varying the full shape of the systematics ([﹩{\bar{M}}_{\mathrm{HI}}﹩,Asys,νsys,στ]). The title of each histogram plot shows the median and the 68% interval. From top to bottom, the results shown are for the two-parameter, three-parameter, and four-parameter cases, respectively.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The 2D posterior distribution between the inferred H I density ΩH I and the amplitude of the systematics, for the cases with corrected covariance and shuffling covariance of the four-parameter model. The outer, middle, and inner contours denote the 3σ, 2σ, and 1σ regions. From top to bottom, the titles shown are for the shuffling covariance and the corrected covariance, respectively. The dotted line in the 2D posterior shows an illustrative direction of parameter degeneracy. The red star denotes ΩH I = 0.5 × 10−3,  Asys = 0.0.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: Upper panel: the blue solid line shows the FWHM of the MeerKAT primary beam across the frequency sub-band from the EIDOS model (“Eidos beam”). The orange dashed line shows a linear best fit of the FWHM (“Linear fit”). Lower panel: the green solid line shows the differences between the FWHM and its linear fit (“Unsymmetrized”), which represents the ripple in the primary beam. The red dashed line shows the symmetrized beam ripple (“Symmetrized”) according to Equation (42), which is used for forward modeling.
Paper: Emission-line Stacking of 21 cm Intensity Maps with MeerKLASS: Inference Pipeline and Application to the L-band Deep-field Data
Authors: Zhaoting Chen, 兆庭 陈, Steven Cunnington, Alkistis Pourtsidou, Laura Wolz, Marta Spinelli, José Luis Bernal, Matilde Barberi-Squarotti, Stefano Camera, Isabella P. Carucci, José Fonseca, Keith Grainge, Melis O. Irfan, Mario G. Santos, Jingying Wang, 婧颖 王
Figure caption: The posterior distribution of the fitted spectrum. The orange solid line denotes the median values of the model spectrum (“Median”). The dark shaded region shows the 68% interval of the fitted spectrum, and the light shaded region shows the 95th percentile. The orange dotted line shows the model spectrum of the highest log-likelihood (“Best fit”). The stacked spectrum is shown as the blue solid line for reference (“Data”).