adsabs/AstroCLIMB huggingface dataset:
Paper: ALMA Survey of Orion Planck Galactic Cold Clumps (ALMASOP): Molecular Jets and Episodic Accretion in Protostars
Authors: Somnath Dutta, Chin-Fei Lee, Doug Johnstone, Jeong-Eun Lee, Naomi Hirano, James Di Francesco, Anthony Moraghan, Tie Liu, Dipen Sahu, Sheng-Yuan Liu, Ken'ichi Tatematsu, Paul F. Goldsmith, Chang Won Lee, Shanghuo Li, David Eden, Mika Juvela, Leonardo Bronfman, Shih-Ying Hsu, Kee-Tae Kim, Woojin Kwon, Patricio Sanhueza, Xunchuan Liu, Jesús Alejandro López-Vázquez, Qiuyi Luo, Hee-Weon Yi
Figure caption: G206.12-15.76. (a) 1.3 mm continuum map at ACA resolution with sensitivity ∼6.0 mJy beam−1. The symbols and contour levels are the same as in Figure 1. (b) The C18O spectra are extracted from high-resolution maps, and V sys = 8 km s−1. All symbols are the same as in Figure 3. (c) CO emission integrated over −4 to +8 km s−1 with sensitivity σ ∼ 4.63 K km s−1, with similar symbols to those in Figure 4(a). (d) CO PV diagram with sensitivity 0.16 K ,with similar symbols and contours to those in Figure 4(b). (e) SiO emission integrated over −52 to +42 km s−1 with sensitivity 4.6 K km s−1, with similar symbols and contours to those in Figure 5(a). (f) SiO PV diagram emission with sensitivity 0.14 K, with similar symbols and contours to those in Figure 5(b).
Paper: ALMA Survey of Orion Planck Galactic Cold Clumps (ALMASOP): Molecular Jets and Episodic Accretion in Protostars
Authors: Somnath Dutta, Chin-Fei Lee, Doug Johnstone, Jeong-Eun Lee, Naomi Hirano, James Di Francesco, Anthony Moraghan, Tie Liu, Dipen Sahu, Sheng-Yuan Liu, Ken'ichi Tatematsu, Paul F. Goldsmith, Chang Won Lee, Shanghuo Li, David Eden, Mika Juvela, Leonardo Bronfman, Shih-Ying Hsu, Kee-Tae Kim, Woojin Kwon, Patricio Sanhueza, Xunchuan Liu, Jesús Alejandro López-Vázquez, Qiuyi Luo, Hee-Weon Yi
Figure caption: G208.68-19.20N1. (a) 1.3 mm continuum map at ACA resolution with sensitivity ∼18 mJy beam−1. The symbols and contour levels are the same as in Figure 1. (b) The C18O spectra are extracted from high-resolution maps, and V sys = 11 km s−1. All symbols are the same as in Figure 3. (c) Integrated CO emission with sensitivity 31.6 K km s−1, with similar symbols to those in Figure 4(a). The contours are at (3, 5) × 31.6 K. (d) CO PV diagram with sensitivity 0.16 K, with similar symbols and contours to those in Figure 4(b). (e) SiO emission integrated over −50 to +50 km s−1 with sensitivity 4.6 K km s−1, with similar symbols and contours to those in Figure 5(a). (f) SiO PV diagram emission with sensitivity 0.14 K, with similar symbols and contours to those in Figure 5(b).
Paper: Librating Kozai–Lidov Cycles with a Precessing Quadrupole Potential Are Analytically Approximately Solved
Authors: Ygal Y. Klein, Boaz Katz
Figure caption: Amplitude of the change in j  z  vs. initial C  K  (equal to the global constant in Equation (5) with ﹩{j}_{z}^{0}=0﹩ up to first order in α) for librating KLCs. Left panels: constant α = 1° and different values of β (written explicitly above each panel). Right panels: constant β = 2.4 and different values of α (logarithmically spaced). Results from a full numerical solution of Equations (2)–(3) are marked using black crosses. Green circles denote the prediction of the analytic solution using Equations (19), (22), and (23) (see Section 3). The number N marked above each plot is the number of initial conditions shown. This number is the number of initial conditions that are librating KLCs among a random sample of 1000 realizations of initial conditions.
Paper: Librating Kozai–Lidov Cycles with a Precessing Quadrupole Potential Are Analytically Approximately Solved
Authors: Ygal Y. Klein, Boaz Katz
Figure caption: Amplitude of the change in j  z  vs. initial C  K  in the numerical integrations (same as the black crosses in Figure 1) color-coded by the analytically specified nature of the pair ﹩\left(V,E\right)﹩ as defined in Section 3.4: red—Class 1 (no ﹩{V}_{\max }﹩); blue—Class 2 (﹩E\gt {V}_{\max }﹩); magenta—Class 3 (﹩E\lt {V}_{\max }﹩ and ﹩\delta \lt {\delta }_{{V}_{\max }}﹩); cyan—Class 4 (﹩E\lt {V}_{\max }﹩ and ﹩\delta \gt {\delta }_{{V}_{\max }}﹩). Panels are the same as in Figure 1.
Paper: Librating Kozai–Lidov Cycles with a Precessing Quadrupole Potential Are Analytically Approximately Solved
Authors: Ygal Y. Klein, Boaz Katz
Figure caption: The maximal amplitude of change in j  z  vs. β for α = 1°. Shown are results from full numerical solutions in librating KLCs (black crosses) and as predicted from initial conditions by the analytic solution (green circles). The results for β = 1.2, 1.8, and 2.4 and β 0 ≈ 2.9 and 3.5 are the highest values attained by Δj  z  in the corresponding panels of Figures 1.
Paper: Librating Kozai–Lidov Cycles with a Precessing Quadrupole Potential Are Analytically Approximately Solved
Authors: Ygal Y. Klein, Boaz Katz
Figure caption: The potential V (Equation (23)) in blue and the constant energy E (Equation (22)) in black for β = 2.4 showing the four distinct classes of ﹩\left(V,E\right)﹩ pairs. Top left panel: Class 1—no ﹩{V}_{\max }﹩; top right panel: Class 2—﹩E\gt {V}_{\max }﹩; bottom left panel: Class 3—﹩E\lt {V}_{\max }﹩ and ﹩\delta \lt {\delta }_{{V}_{\max }}﹩; bottom right panel: Class 4—﹩E\lt {V}_{\max }﹩ and ﹩\delta \gt {\delta }_{{V}_{\max }}﹩.
Paper: Korg: Fitting, Model Atmosphere Interpolation, and Brackett Lines
Authors: Adam J. Wheeler, Andrew R. Casey, Matthew W. Abruzzo
Figure caption: Predicted lines of  Br-η  and  Br-λ  (n = 4 to n = 11 and n = 15, respectively), two lines in the APOGEE wavelength range. Agreement between synthesis codes is poor because models do not properly account for line formation in the infrared and because of differing treatments of level dissolution. Each row represents a different set of stellar parameters (T eff and  ﹩\mathrm{log}\,g﹩ are indicated in the first column, and all models are computed with [M/H]  =   −1.5). The third column shows the probability that the n = 11 and n = 15 orbitals survive (are not dissolved into the continuum) as a function of optical depth at 5000 Å,  τ 5000. The vertical gray band marks the approximate depth of formation of the Brackett lines. These spectra were synthesized using the APOGEE DR 17 linelist and convolved to the instrument resolution (R  =  22, 500).
Paper: Korg: Fitting, Model Atmosphere Interpolation, and Brackett Lines
Authors: Adam J. Wheeler, Andrew R. Casey, Matthew W. Abruzzo
Figure caption: Top: the Rosseland mean optical depth of formation of  H-α and  Br-η  as a function of wavelength. Lines in the infrared form much deeper in the stellar atmosphere, where different broadening mechanisms dominate. Bottom: The characteristic profile widths of line broadening mechanisms as a function of depth. The dashed lines in each panel mark the Rosseland mean optical depth at which the core of each line forms. For line cores in the visible, which form high in the atmosphere, Doppler broadening dominates, but for line cores in the infrared, which form deep in the atmosphere, Stark broadening dominates. These calculations were done using a model atmosphere with T eff  =  6000 K, ﹩\mathrm{log}\,g\,=\,3.5﹩.
Paper: Korg: Fitting, Model Atmosphere Interpolation, and Brackett Lines
Authors: Adam J. Wheeler, Andrew R. Casey, Matthew W. Abruzzo
Figure caption: Fractional correction to the hydrogen partition function,  U H, deep in the stellar atmosphere according to the MHD formalism across the Kiel diagram. Stellar atmospheres are produced using  Korg's interpolation of the SDSS model atmosphere grid for solar-composition stars. Corrections are less than 4 × 10−3 for all stars and much smaller than that at higher layers.
Paper: Korg: Fitting, Model Atmosphere Interpolation, and Brackett Lines
Authors: Adam J. Wheeler, Andrew R. Casey, Matthew W. Abruzzo
Figure caption: Br-η  in Gaia FGK benchmark stars with T eff  >  5500 K compared to  Korg  spectra using the legacy and corrected Brackett line profiles with level dissolution included and neglected. The updated profiles are a much closer match to the spectra in nearly all cases.
Paper: Korg: Fitting, Model Atmosphere Interpolation, and Brackett Lines
Authors: Adam J. Wheeler, Andrew R. Casey, Matthew W. Abruzzo
Figure caption: Comparisons of synthesized Br–η  profiles for four representative Gaia FGK benchmark stars. The fit is much improved using the corrected profiles, though the effect of the MHD dissolution formalism is to subtle to constrain using these data.
Paper: Korg: Fitting, Model Atmosphere Interpolation, and Brackett Lines
Authors: Adam J. Wheeler, Andrew R. Casey, Matthew W. Abruzzo
Figure caption: The same as Figure 10 for stars with T eff  <  5500 K.
Paper: Using AI for Wave-front Estimation with the Rubin Observatory Active Optics System
Authors: John Franklin Crenshaw, Andrew J. Connolly, Joshua E. Meyers, J. Bryce Kalmbach, Guillem Megias Homar, Tiago Ribeiro, Krzysztof Suberlak, Sandrine Thomas, Te-Wei Tsai
Figure caption: Distribution of wave-front estimation errors for the DL and TIE methods in ideal conditions (no camera vignetting and no bright blends). The distribution in gray is the expected distribution of wave-front estimation errors due to the phase variance of the atmosphere. The vertical black line is the AOS wave-front estimation error requirement of 0.″079.
Paper: Using AI for Wave-front Estimation with the Rubin Observatory Active Optics System
Authors: John Franklin Crenshaw, Andrew J. Connolly, Joshua E. Meyers, J. Bryce Kalmbach, Guillem Megias Homar, Tiago Ribeiro, Krzysztof Suberlak, Sandrine Thomas, Te-Wei Tsai
Figure caption: Example of an intra- and extra-focal donut fed into the AOS pipeline, with the DL and TIE wave-front estimates compared to the truth from the simulation. The plotted amplitudes are the quantities s  i  α  i  and ﹩{s}_{i}{\hat{\alpha }}_{i}﹩, i.e., the contribution of each Zernike mode to the PSF FWHM. The error bars on the truth are the expected median 1σ errors due to the atmosphere.
Paper: Using AI for Wave-front Estimation with the Rubin Observatory Active Optics System
Authors: John Franklin Crenshaw, Andrew J. Connolly, Joshua E. Meyers, J. Bryce Kalmbach, Guillem Megias Homar, Tiago Ribeiro, Krzysztof Suberlak, Sandrine Thomas, Te-Wei Tsai
Figure caption: Left: a bright blend where the blending donut is at a distance of 82 pixels. Right: wave-front estimation error for donuts with a single bright blend, as a function of the centroid-to-centroid distance of the central and blending donut. The red cross denotes the distance and TIE error corresponding to the blend depicted on the left. The data set plotted excludes donuts vignetted by the camera.
Paper: Using AI for Wave-front Estimation with the Rubin Observatory Active Optics System
Authors: John Franklin Crenshaw, Andrew J. Connolly, Joshua E. Meyers, J. Bryce Kalmbach, Guillem Megias Homar, Tiago Ribeiro, Krzysztof Suberlak, Sandrine Thomas, Te-Wei Tsai
Figure caption: The PSF FWHM and PSSN as a function of closed-loop iteration, when using the DL and TIE methods for wave-front estimation. The AOS requirements are marked by the horizontal dashed lines. The PSF FWHM must be below this limit, and the PSSN must be above this limit. For both metrics there is an inset that zooms in to the last two iterations, where it can be seen the DL method slightly outperforms the TIE.
Paper: Using AI for Wave-front Estimation with the Rubin Observatory Active Optics System
Authors: John Franklin Crenshaw, Andrew J. Connolly, Joshua E. Meyers, J. Bryce Kalmbach, Guillem Megias Homar, Tiago Ribeiro, Krzysztof Suberlak, Sandrine Thomas, Te-Wei Tsai
Figure caption: Median wave-front estimation error as a function of the donut S/N in the r band. The x-axis below the plot shows the total S/N, while the x-axis above the plot shows the corresponding r-band source magnitude, assuming the median r-band sky brightness of 21.20 AB mag arcsec−2. The vertical gray line marks the current minimum S/N specified by the Rubin AOS pipeline.
Paper: Using AI for Wave-front Estimation with the Rubin Observatory Active Optics System
Authors: John Franklin Crenshaw, Andrew J. Connolly, Joshua E. Meyers, J. Bryce Kalmbach, Guillem Megias Homar, Tiago Ribeiro, Krzysztof Suberlak, Sandrine Thomas, Te-Wei Tsai
Figure caption: Median wave-front estimation error as a function of the number of faint blends. The faint blends are divided into two groups: those where the faint blends are at most 1 mag beyond the bright blend cut (2 < Δm < 3), and those where the faint blends are more than 1 mag beyond the bright blend cut (Δm > 3). The data set plotted excludes donuts vignetted by the camera, and donuts with bright blends.
Paper: Using AI for Wave-front Estimation with the Rubin Observatory Active Optics System
Authors: John Franklin Crenshaw, Andrew J. Connolly, Joshua E. Meyers, J. Bryce Kalmbach, Guillem Megias Homar, Tiago Ribeiro, Krzysztof Suberlak, Sandrine Thomas, Te-Wei Tsai
Figure caption: Left: distribution of errors for the TIE solver for different numbers of bright blends. Right: same for the DL model. The data set plotted excludes donuts vignetted by the camera, and blends for which the centroid-to-centroid distance is less than 88 pixels.
Paper: Using AI for Wave-front Estimation with the Rubin Observatory Active Optics System
Authors: John Franklin Crenshaw, Andrew J. Connolly, Joshua E. Meyers, J. Bryce Kalmbach, Guillem Megias Homar, Tiago Ribeiro, Krzysztof Suberlak, Sandrine Thomas, Te-Wei Tsai
Figure caption: Wave-front estimation error as a function of intra-focal field angle. Above the scatter plot are donut stamps representative of the given field angle. Sharp vignetting from the camera body impacts field angles greater than about 1.74°. The data set plotted excludes donuts with bright blends.
Paper: Using AI for Wave-front Estimation with the Rubin Observatory Active Optics System
Authors: John Franklin Crenshaw, Andrew J. Connolly, Joshua E. Meyers, J. Bryce Kalmbach, Guillem Megias Homar, Tiago Ribeiro, Krzysztof Suberlak, Sandrine Thomas, Te-Wei Tsai
Figure caption: Left: distribution of errors for the TIE solver, in the presence of mirror and camera vignetting. Right: same for the DL model. The data set plotted excludes donuts with bright blends.
Paper: Deconvolution of JWST/MIRI Images: Applications to an Active Galactic Nucleus Model and GATOS Observations of NGC 5728
Authors: M. T. Leist, C. Packham, D. J. V. Rosario, D. A. Hope, A. Alonso-Herrero, E. K. S. Hicks, S. Hönig, L. Zhang, R. Davies, T. Díaz-Santos, O. González-Martín, E. Bellocchi, P. G. Boorman, F. Combes, I. García-Bernete, S. García-Burillo, B. García-Lorenzo, H. Haidar, K. Ichikawa, M. Imanishi, S. M. Jefferies, Á. Labiano, N. A. Levenson, R. Nikutta, M. Pereira-Santaella, C. Ramos Almeida, C. Ricci, D. Rigopoulou, W. Schaefer, M. Stalevski, M. J. Ward, L. Fuller, T. Izumi, D. Rouan, T. Shimizu
Figure caption: Toy AGN model image grid comparisons between the MIRISim and deconvolved images as a function of filter. Each image shows the central 150 × 150 MIRIM pixels in the x- and y-coordinate plane, is log scaled, and photometrically scaled to the IWFT F2100W image. (Top row) MIRISim, (second row) Kraken, (third row) Richardson–Lucy, (fourth row) AIDA, (fifth row) SCV, and (sixth row) IWFT. The number of deconvolution iterations the image converged to is noted in each image panel.
Paper: Deconvolution of JWST/MIRI Images: Applications to an Active Galactic Nucleus Model and GATOS Observations of NGC 5728
Authors: M. T. Leist, C. Packham, D. J. V. Rosario, D. A. Hope, A. Alonso-Herrero, E. K. S. Hicks, S. Hönig, L. Zhang, R. Davies, T. Díaz-Santos, O. González-Martín, E. Bellocchi, P. G. Boorman, F. Combes, I. García-Bernete, S. García-Burillo, B. García-Lorenzo, H. Haidar, K. Ichikawa, M. Imanishi, S. M. Jefferies, Á. Labiano, N. A. Levenson, R. Nikutta, M. Pereira-Santaella, C. Ramos Almeida, C. Ricci, D. Rigopoulou, W. Schaefer, M. Stalevski, M. J. Ward, L. Fuller, T. Izumi, D. Rouan, T. Shimizu
Figure caption: Toy AGN model components, from left to right: the central region (dominantly the obscuring torus illuminated by the accretion disk of the central engine), the polar dust component, the ionization bicone, and the host galaxy. Each figure is log scaled (except for the central region, which is linear scaled), scaled to the central region component. The x- and y-axes are given in pixels, and the size of the field of view (FOV) for each region is given at parsec scales below each frame (1 pixel = 20.8 pc).
Paper: Deconvolution of JWST/MIRI Images: Applications to an Active Galactic Nucleus Model and GATOS Observations of NGC 5728
Authors: M. T. Leist, C. Packham, D. J. V. Rosario, D. A. Hope, A. Alonso-Herrero, E. K. S. Hicks, S. Hönig, L. Zhang, R. Davies, T. Díaz-Santos, O. González-Martín, E. Bellocchi, P. G. Boorman, F. Combes, I. García-Bernete, S. García-Burillo, B. García-Lorenzo, H. Haidar, K. Ichikawa, M. Imanishi, S. M. Jefferies, Á. Labiano, N. A. Levenson, R. Nikutta, M. Pereira-Santaella, C. Ramos Almeida, C. Ricci, D. Rigopoulou, W. Schaefer, M. Stalevski, M. J. Ward, L. Fuller, T. Izumi, D. Rouan, T. Shimizu
Figure caption: JWST/MIRIM (row 1) and Kraken deconvolved (row 2) images for each filter. Each image is normalized, displayed log scaled, scaled to the corresponding deconvolved image peak for each filter, rotated to the N through E orientation, and ∼4″ × 4″. Rows 3 and 4 display the normalized flux distribution of the central ∼4″ × 4″ for the JWST/MIRIM and Kraken deconvolved images, respectively.
Paper: Deconvolution of JWST/MIRI Images: Applications to an Active Galactic Nucleus Model and GATOS Observations of NGC 5728
Authors: M. T. Leist, C. Packham, D. J. V. Rosario, D. A. Hope, A. Alonso-Herrero, E. K. S. Hicks, S. Hönig, L. Zhang, R. Davies, T. Díaz-Santos, O. González-Martín, E. Bellocchi, P. G. Boorman, F. Combes, I. García-Bernete, S. García-Burillo, B. García-Lorenzo, H. Haidar, K. Ichikawa, M. Imanishi, S. M. Jefferies, Á. Labiano, N. A. Levenson, R. Nikutta, M. Pereira-Santaella, C. Ramos Almeida, C. Ricci, D. Rigopoulou, W. Schaefer, M. Stalevski, M. J. Ward, L. Fuller, T. Izumi, D. Rouan, T. Shimizu
Figure caption: Merit function results for simulated MIRIM observations of the toy AGN model. Left: FWHM results as a function of deconvolution iteration. The iteration number where the measured FWHM value dropped below the theoretical diffraction limit for that image is marked with a dotted line. The iteration number where the regularization convergence criteria were met is listed in the legend and marked by an “X” for each plot. Right: normalized flux in the aperture as a function of deconvolution iteration. The aperture flux for each deconvolved image was normalized to the MIRISim image in the same wave band. Note the increase in normalized aperture flux after the first few iterations for each algorithm caused by the initial concentration of flux within the aperture.
Paper: Deconvolution of JWST/MIRI Images: Applications to an Active Galactic Nucleus Model and GATOS Observations of NGC 5728
Authors: M. T. Leist, C. Packham, D. J. V. Rosario, D. A. Hope, A. Alonso-Herrero, E. K. S. Hicks, S. Hönig, L. Zhang, R. Davies, T. Díaz-Santos, O. González-Martín, E. Bellocchi, P. G. Boorman, F. Combes, I. García-Bernete, S. García-Burillo, B. García-Lorenzo, H. Haidar, K. Ichikawa, M. Imanishi, S. M. Jefferies, Á. Labiano, N. A. Levenson, R. Nikutta, M. Pereira-Santaella, C. Ramos Almeida, C. Ricci, D. Rigopoulou, W. Schaefer, M. Stalevski, M. J. Ward, L. Fuller, T. Izumi, D. Rouan, T. Shimizu
Figure caption: FWHM and aperture flux comparisons between MIRISim and the deconvolved images as a function of simulated central wavelength. Each point is plotted at the central wavelength for the respective filter. Left: measured FWHMs, where the dotted line shows the theoretical PSF FWHM at the center of the respective filter, and the length of the dotted line represents the filter width. Right: log-scaled comparative SEDs generated for the MIRISim and deconvolved images.
Paper: Deconvolution of JWST/MIRI Images: Applications to an Active Galactic Nucleus Model and GATOS Observations of NGC 5728
Authors: M. T. Leist, C. Packham, D. J. V. Rosario, D. A. Hope, A. Alonso-Herrero, E. K. S. Hicks, S. Hönig, L. Zhang, R. Davies, T. Díaz-Santos, O. González-Martín, E. Bellocchi, P. G. Boorman, F. Combes, I. García-Bernete, S. García-Burillo, B. García-Lorenzo, H. Haidar, K. Ichikawa, M. Imanishi, S. M. Jefferies, Á. Labiano, N. A. Levenson, R. Nikutta, M. Pereira-Santaella, C. Ramos Almeida, C. Ricci, D. Rigopoulou, W. Schaefer, M. Stalevski, M. J. Ward, L. Fuller, T. Izumi, D. Rouan, T. Shimizu
Figure caption: Kraken deconvolved toy AGN D AGN (top row), Kraken deconvolved central region combined with ionization bicone D MS (middle row), and residual images (bottom row). The top two rows are displayed log scaled and the bottom row is displayed in linear scale. Each image is photometrically scaled to the F2100W image in each row and shows the central 50 × 50 MIRIM pixels.
Paper: Deconvolution of JWST/MIRI Images: Applications to an Active Galactic Nucleus Model and GATOS Observations of NGC 5728
Authors: M. T. Leist, C. Packham, D. J. V. Rosario, D. A. Hope, A. Alonso-Herrero, E. K. S. Hicks, S. Hönig, L. Zhang, R. Davies, T. Díaz-Santos, O. González-Martín, E. Bellocchi, P. G. Boorman, F. Combes, I. García-Bernete, S. García-Burillo, B. García-Lorenzo, H. Haidar, K. Ichikawa, M. Imanishi, S. M. Jefferies, Á. Labiano, N. A. Levenson, R. Nikutta, M. Pereira-Santaella, C. Ramos Almeida, C. Ricci, D. Rigopoulou, W. Schaefer, M. Stalevski, M. J. Ward, L. Fuller, T. Izumi, D. Rouan, T. Shimizu
Figure caption: Three-component model contour map (left). Contour levels correspond to counts ranging from 102–105 counts per pixel. Three-component model (right). Image is displayed log scaled, showing the central 200 × 200 pixels (∼22.″2, ∼4.2 kpc). Note the central region component is excluded from this model.
Paper: Deconvolution of JWST/MIRI Images: Applications to an Active Galactic Nucleus Model and GATOS Observations of NGC 5728
Authors: M. T. Leist, C. Packham, D. J. V. Rosario, D. A. Hope, A. Alonso-Herrero, E. K. S. Hicks, S. Hönig, L. Zhang, R. Davies, T. Díaz-Santos, O. González-Martín, E. Bellocchi, P. G. Boorman, F. Combes, I. García-Bernete, S. García-Burillo, B. García-Lorenzo, H. Haidar, K. Ichikawa, M. Imanishi, S. M. Jefferies, Á. Labiano, N. A. Levenson, R. Nikutta, M. Pereira-Santaella, C. Ramos Almeida, C. Ricci, D. Rigopoulou, W. Schaefer, M. Stalevski, M. J. Ward, L. Fuller, T. Izumi, D. Rouan, T. Shimizu
Figure caption: Toy AGN model generation flow chart for the F2100W image. Note that this procedure was followed for all five filter images.
Paper: Deconvolution of JWST/MIRI Images: Applications to an Active Galactic Nucleus Model and GATOS Observations of NGC 5728
Authors: M. T. Leist, C. Packham, D. J. V. Rosario, D. A. Hope, A. Alonso-Herrero, E. K. S. Hicks, S. Hönig, L. Zhang, R. Davies, T. Díaz-Santos, O. González-Martín, E. Bellocchi, P. G. Boorman, F. Combes, I. García-Bernete, S. García-Burillo, B. García-Lorenzo, H. Haidar, K. Ichikawa, M. Imanishi, S. M. Jefferies, Á. Labiano, N. A. Levenson, R. Nikutta, M. Pereira-Santaella, C. Ramos Almeida, C. Ricci, D. Rigopoulou, W. Schaefer, M. Stalevski, M. J. Ward, L. Fuller, T. Izumi, D. Rouan, T. Shimizu
Figure caption: Ratio between the MIRISim and final deconvolved toy AGN model images for each deconvolution algorithm as a function of simulated central wavelength. Each point is plotted at the central wavelength for the respective filter. Left: FWHM ratios. Right: aperture flux ratios.