adsabs/AstroCLIMB huggingface dataset:
Paper: exoALMA. VIII. Probabilistic Moment Maps and Data Products Using Nonparametric Linear Models
Authors: Thomas Hilder, Andrew R. Casey, Daniel J. Price, Christophe Pinte, Andrés F. Izquierdo, Caitlyn Hardiman, Jaehan Bae, Marcelo Barraza-Alfaro, Myriam Benisty, Gianni Cataldi, Pietro Curone, Ian Czekala, Stefano Facchini, Daniele Fasano, Mario Flock, Misato Fukagawa, Maria Galloway-Sprietsma, Himanshi Garg, Cassandra Hall, Iain Hammond, Jane Huang, John D. Ilee, Kazuhiro Kanagawa, Geoffroy Lesur, Cristiano Longarini, Ryan Loomis, Ryuta Orihara, Giovanni Rosotti, Jochen Stadler, Richard Teague, Hsi-Wei Yen, Gaylor Wafflard, Andrew J. Winter, Lisa Wölfer, Tomohiro C. Yoshida, Brianna Zawadzki
Figure caption: Schematic overview of the methodology for generating probabilistic data products using the nonparametric cube model. The cube graphic represents data cubes, with the orange and blue cubes illustrating posterior model cube samples before and after beam convolution, respectively. The Pi values indicate sample data products (DPs) calculated from the corresponding cube samples, color-coded accordingly. The numbered steps in the bottom left correspond directly to those in Section 2.4.
Paper: exoALMA. VIII. Probabilistic Moment Maps and Data Products Using Nonparametric Linear Models
Authors: Thomas Hilder, Andrew R. Casey, Daniel J. Price, Christophe Pinte, Andrés F. Izquierdo, Caitlyn Hardiman, Jaehan Bae, Marcelo Barraza-Alfaro, Myriam Benisty, Gianni Cataldi, Pietro Curone, Ian Czekala, Stefano Facchini, Daniele Fasano, Mario Flock, Misato Fukagawa, Maria Galloway-Sprietsma, Himanshi Garg, Cassandra Hall, Iain Hammond, Jane Huang, John D. Ilee, Kazuhiro Kanagawa, Geoffroy Lesur, Cristiano Longarini, Ryan Loomis, Ryuta Orihara, Giovanni Rosotti, Jochen Stadler, Richard Teague, Hsi-Wei Yen, Gaylor Wafflard, Andrew J. Winter, Lisa Wölfer, Tomohiro C. Yoshida, Brianna Zawadzki
Figure caption: The same as Figure 3 except showing recovered line width maps w0.
Paper: exoALMA. VIII. Probabilistic Moment Maps and Data Products Using Nonparametric Linear Models
Authors: Thomas Hilder, Andrew R. Casey, Daniel J. Price, Christophe Pinte, Andrés F. Izquierdo, Caitlyn Hardiman, Jaehan Bae, Marcelo Barraza-Alfaro, Myriam Benisty, Gianni Cataldi, Pietro Curone, Ian Czekala, Stefano Facchini, Daniele Fasano, Mario Flock, Misato Fukagawa, Maria Galloway-Sprietsma, Himanshi Garg, Cassandra Hall, Iain Hammond, Jane Huang, John D. Ilee, Kazuhiro Kanagawa, Geoffroy Lesur, Cristiano Longarini, Ryan Loomis, Ryuta Orihara, Giovanni Rosotti, Jochen Stadler, Richard Teague, Hsi-Wei Yen, Gaylor Wafflard, Andrew J. Winter, Lisa Wölfer, Tomohiro C. Yoshida, Brianna Zawadzki
Figure caption: Best-fitting nonparametric (NP) model cube for HD 135344B. The top row shows the data. The second row shows the best fit after beam convolution. The third row shows the best fit prior to beam convolution. The fourth row shows the residual between the data and the convolved model.
Paper: exoALMA. VIII. Probabilistic Moment Maps and Data Products Using Nonparametric Linear Models
Authors: Thomas Hilder, Andrew R. Casey, Daniel J. Price, Christophe Pinte, Andrés F. Izquierdo, Caitlyn Hardiman, Jaehan Bae, Marcelo Barraza-Alfaro, Myriam Benisty, Gianni Cataldi, Pietro Curone, Ian Czekala, Stefano Facchini, Daniele Fasano, Mario Flock, Misato Fukagawa, Maria Galloway-Sprietsma, Himanshi Garg, Cassandra Hall, Iain Hammond, Jane Huang, John D. Ilee, Kazuhiro Kanagawa, Geoffroy Lesur, Cristiano Longarini, Ryan Loomis, Ryuta Orihara, Giovanni Rosotti, Jochen Stadler, Richard Teague, Hsi-Wei Yen, Gaylor Wafflard, Andrew J. Winter, Lisa Wölfer, Tomohiro C. Yoshida, Brianna Zawadzki
Figure caption: Posterior distributions for a subset of the J1842 DISCMINER model. Posteriors are plotted in each panel, with the corresponding median and 1σ quantiles indicated by the points and lines above the distributions. Fits from individual cube samples are shown in the blue–green color map, and the combined distribution is shown in black. Red shows the posterior from fitting the data directly. Pink is taken from the production exoALMA model. The y-scale of the red and black curves has been scaled for easier comparison. The DISCMINER model parameters shown are stellar mass M⋆, systemic velocity vLSRK, inclination i, position angle PA, model origin (xc, yc), reference height z0, height power-law index p, taper radius Rb, and taper index q (see A. F. Izquierdo et al. 2025).
Paper: exoALMA. VIII. Probabilistic Moment Maps and Data Products Using Nonparametric Linear Models
Authors: Thomas Hilder, Andrew R. Casey, Daniel J. Price, Christophe Pinte, Andrés F. Izquierdo, Caitlyn Hardiman, Jaehan Bae, Marcelo Barraza-Alfaro, Myriam Benisty, Gianni Cataldi, Pietro Curone, Ian Czekala, Stefano Facchini, Daniele Fasano, Mario Flock, Misato Fukagawa, Maria Galloway-Sprietsma, Himanshi Garg, Cassandra Hall, Iain Hammond, Jane Huang, John D. Ilee, Kazuhiro Kanagawa, Geoffroy Lesur, Cristiano Longarini, Ryan Loomis, Ryuta Orihara, Giovanni Rosotti, Jochen Stadler, Richard Teague, Hsi-Wei Yen, Gaylor Wafflard, Andrew J. Winter, Lisa Wölfer, Tomohiro C. Yoshida, Brianna Zawadzki
Figure caption: Peak velocity, peak intensity, and line width maps for HD 135344B (top) and CQ Tau (bottom). The left column shows the results using the conventional method. The second column shows the results using our new method. The third column shows the difference of these. The fourth column shows the 1σ uncertainty on the results from the new method. As in the benchmark, the new method better resolves the velocity perturbations associated with substructures.
Paper: exoALMA. VIII. Probabilistic Moment Maps and Data Products Using Nonparametric Linear Models
Authors: Thomas Hilder, Andrew R. Casey, Daniel J. Price, Christophe Pinte, Andrés F. Izquierdo, Caitlyn Hardiman, Jaehan Bae, Marcelo Barraza-Alfaro, Myriam Benisty, Gianni Cataldi, Pietro Curone, Ian Czekala, Stefano Facchini, Daniele Fasano, Mario Flock, Misato Fukagawa, Maria Galloway-Sprietsma, Himanshi Garg, Cassandra Hall, Iain Hammond, Jane Huang, John D. Ilee, Kazuhiro Kanagawa, Geoffroy Lesur, Cristiano Longarini, Ryan Loomis, Ryuta Orihara, Giovanni Rosotti, Jochen Stadler, Richard Teague, Hsi-Wei Yen, Gaylor Wafflard, Andrew J. Winter, Lisa Wölfer, Tomohiro C. Yoshida, Brianna Zawadzki
Figure caption: Uncertainty in model prediction as a function of regularization strength λ for the model before (orange) and after (blue) convolution with the beam. The green region indicates the value of λ used in our results. The red region indicates the region where the model is clearly overregularized.
Paper: exoALMA. VIII. Probabilistic Moment Maps and Data Products Using Nonparametric Linear Models
Authors: Thomas Hilder, Andrew R. Casey, Daniel J. Price, Christophe Pinte, Andrés F. Izquierdo, Caitlyn Hardiman, Jaehan Bae, Marcelo Barraza-Alfaro, Myriam Benisty, Gianni Cataldi, Pietro Curone, Ian Czekala, Stefano Facchini, Daniele Fasano, Mario Flock, Misato Fukagawa, Maria Galloway-Sprietsma, Himanshi Garg, Cassandra Hall, Iain Hammond, Jane Huang, John D. Ilee, Kazuhiro Kanagawa, Geoffroy Lesur, Cristiano Longarini, Ryan Loomis, Ryuta Orihara, Giovanni Rosotti, Jochen Stadler, Richard Teague, Hsi-Wei Yen, Gaylor Wafflard, Andrew J. Winter, Lisa Wölfer, Tomohiro C. Yoshida, Brianna Zawadzki
Figure caption: Single channel for the best-fitting nonparametric (NP) model and posterior samples for J1842. The top left panel shows the data and beam. The top middle panel shows the best-fitting model convolved with the beam. The top right panel shows the residual between the data and best fit. The bottom row shows three posterior model channel samples convolved with the beam.
Paper: exoALMA. VIII. Probabilistic Moment Maps and Data Products Using Nonparametric Linear Models
Authors: Thomas Hilder, Andrew R. Casey, Daniel J. Price, Christophe Pinte, Andrés F. Izquierdo, Caitlyn Hardiman, Jaehan Bae, Marcelo Barraza-Alfaro, Myriam Benisty, Gianni Cataldi, Pietro Curone, Ian Czekala, Stefano Facchini, Daniele Fasano, Mario Flock, Misato Fukagawa, Maria Galloway-Sprietsma, Himanshi Garg, Cassandra Hall, Iain Hammond, Jane Huang, John D. Ilee, Kazuhiro Kanagawa, Geoffroy Lesur, Cristiano Longarini, Ryan Loomis, Ryuta Orihara, Giovanni Rosotti, Jochen Stadler, Richard Teague, Hsi-Wei Yen, Gaylor Wafflard, Andrew J. Winter, Lisa Wölfer, Tomohiro C. Yoshida, Brianna Zawadzki
Figure caption: The same as Figure 6 except for MWC 758.
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Mid-infrared spectral line variability observed with Spitzer-IRS (A. Banzatti et al. 2012) and JWST-MIRI (this work) in the T Tauri disk of EX Lup over ∼20 yr (from 2005 with the SP1 epoch to 2023 with the JW2 epoch). The two MIRI epochs are plotted in gray (JW1) and black (JW2) without offset to demonstrate their similarity. The individual molecular models obtained for the JW2 epoch (Table 2) are shown in different colors, with their sum in gray. The same models are shown as downgraded to the resolving power of Spitzer-IRS for comparison to the SP1 and SP2 data, with multiplication factors as labeled for each molecule; additional models for water and OH are shown on top of the SP2 epoch to explain the more complex structure observed (see text for details). The vertical dashed lines show the range where the line flux of organic molecules is measured for Figure 6. The lowest-energy lines covered by MIRI (Eu = 878–1448 K), which are more sensitive to the snowline region at T < 180 K, are marked with a star (see also Figure 5).
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Water diagnostic diagrams from A. Banzatti et al. (2025), with the JDISCS sample from that work shown for reference in light green. The position of the JW2 spectrum of EX Lup (large blue data point) in these diagrams shows (1) a moderate slab radius (≈0.3 au) for the hot water component (left plot), (2) optically thick emission (N ≈ 1018 cm−2) in the warm water component (middle plot), and (3) a temperature gradient with negative slope ≈0.45–0.55 and strong cold water enrichment (right plot; see also Figure 5). These estimates are confirmed by the slab fit results both with discrete components and with the radial gradient (Sections 3.1 and 3.2). The line ratios from the outburst SP2 spectrum are more uncertain due to line blending (see Appendix C) but indicate a larger and colder water reservoir (see also Figure 5).
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Coldest water detected in EX Lup, in comparison to the JDISCS sample from A. Banzatti et al. (2025). The 23 μm line flux asymmetry diagnostic (the 1448/1615 K flux ratio) shows one of the largest values ever measured before, consistent with ice sublimation in the inner disk (the temperatures associated with specific 1448/1615 K values assume a column density of N = 1017 cm−2; see A. Banzatti et al. 2025). The other object near EX Lup (JW2) is the young disk of IRAS 04385–2550.
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Light curve of EX Lupi during the period containing the four epochs of analysis (SP1 and SP2 from Spitzer-IRS, JW1 and JW2 from JWST-MIRI). V-band data (y-axis to the left) are taken from AAVSO (www.aavso.org), the ASAS-3 catalog (G. Pojmanski 2002), and ASAS-SN (B. J. Shappee et al. 2014; C. S. Kochanek et al. 2017). Accretion luminosity estimates (y-axis to the right) are reported with red bars where available from previous work, and large dots show the values adopted in this work (see Table 1 and Section 2.1 for details), color-coded to distinguish them in all figures in this Letter.
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Cold water measured from the 1500/6000 K line ratio in the MIRI spectra of EX Lup in comparison to the larger sample from the JDISC Survey (gray data points from A. Banzatti et al. 2025). The dashed line in the right plot shows the anticorrelation between the line ratio diagnostic of cold water and the dust disk radius, attributed to pebble drift (A. Banzatti et al. 2023b, 2025). The large cold water excess measured in EX Lup is suggestive of the role of accretion outbursts in triggering ice sublimation at the snowline (Figure 8), enriching the inner disk surface with ∼170 K water vapor (Figure 5).
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Changes measured in EX Lup in the four epochs included in this work (colored data points, using line fluxes from Table 3) as compared to molecular luminosities measured in T Tauri disks of similar age from A. Banzatti et al. (2020).
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: MIRI epochs of EX Lup analyzed in this work, zooming in on two regions that illustrate organic and water emission (insets). The 2022 spectrum has been published before in Á. Kóspál et al. (2023), and here we provide the new reduction, where the improved spectral response function removes spurious broad features previously attributed to dust emission (compare to Figures 1 and 2 in Á. Kóspál et al. 2023). The 2022 epoch also had higher residual fringes (see inset) due to a large pointing offset. The new reduction of both spectra is available on SpExoDisks.com (C. I. Wheeler et al. 2024).
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Left panel: stellar spectrum (dashed colored lines) and predicted SED (solid colored lines) during the quiescent (in blue) and outburst (in red) phases for the representative EX Lup model. The colored symbols with black borders show photometry measurements from the literature (A. Juhász et al. 2012). The observed Spitzer spectrum (outburst) and JWST spectrum (quiescent), as used in this work, are shown in gray with stretched error bars for better visibility. Middle and right panels: water gas-phase abundance (relative to the total hydrogen number density) at the end of the outburst and in the quiescent phase. The blue and red contours show Tdust = 150 K in the quiescent and outburst phase, respectively. The water abundance between these two contours slowly decreases after the end of the burst until it reaches the initial (quiescent) level as shown in Figure 10.
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Time evolution measured in the cold water lines tracing the surface snowline. Both the cold water area relative to the inner hot water (diagnostic to the left) and the cold water temperature (diagnostic to the right) evolve significantly over 10–30 yr after accretion outbursts. Two additional systems with evidence for recent accretion bursts are included in this figure: AS 209 and Sz 98 (see Section 4.3 for details).
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Diagnostic water lines defined in A. Banzatti et al. (2025) as observed in the spectra of EX Lup. Left plots: JW2 spectrum observed with MIRI at the resolving power of R ∼ 3000, which resolves these lines from nearby transitions. Right plots: the same lines as observed in the SP2 spectrum with IRS (R ∼ 700); line deblending is performed with iSLAT and shown with colored dashed lines, with a thicker red line showing the total fit (see Appendix C for details).
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Water emission in EX Lup as compared to that observed with MIRI in other representative disks, following Figure 8 in A. Banzatti et al. (2025). A portion of the short wavelengths (top) and long wavelengths (bottom) illustrates that the spectrum in EX Lup is dominated by lower-energy lines that get excited at intermediate-to-low temperatures down to ice sublimation, while the spectra of GQ Lup and CI Tau include increasing flux from hotter emission. Individual slab models and the unblended transitions (marked with stars) presented in A. Banzatti et al. (2025) are shown at the bottom in each plot. The diagnostic lines introduced in A. Banzatti et al. (2025) and used in Figures 4 and 5 in this Letter are marked in red and included in Table 4.
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Illustration of the proposed interpretation for the water emission variability observed in EX Lup during and after accretion outbursts. The increased irradiation and heating of the inner disk during outburst are proposed to push the snowline to larger radii, triggering a burst of cold water vapor from ice sublimation. A remnant layer of cold water vapor is left behind due to the long freeze-out timescales in the disk surface after outburst to explain the increased cold water excess in the MIRI epochs analyzed in this work.
Paper: JWST’s Sharper View of EX Lup: Cold Water from Ice Sublimation during Accretion Outbursts
Authors: Sarah A. Smith, Carlos E. Romero-Mirza, Andrea Banzatti, Christian Rab, Péter Ábrahám, Ágnes Kóspál, Rik Claes, Carlo F. Manara, Karin I. Öberg, Jeroen Bouwman, Fernando Cruz-Sáenz de Miera, Joel D. Green
Figure caption: Postoutburst freeze-out of cold water vapor produced during an accretion outburst. The modeling framework is based on C. Rab et al. (2017) and described in Appendix D. The red solid line shows the water column density at the end of the outburst, in reference to the quiescent phase in blue. The solid gray-scale lines show the evolution at different times after the outburst, indicating >3 yr freeze-out timescales for cold water after an outburst. The vertical dotted lines show the midplane water snowline in quiescence (blue) and outburst (red).
Paper: Transfer of Entropy between the Magnetic Field and Solar Energetic Particles during an Interplanetary Coronal Mass Ejection
Authors: M. E. Cuesta, G. Livadiotis, D. J. McComas, L. Y. Khoo, H. A. Farooki, R. Bandyopadhyay, S. D. Bale
Figure caption: Left panel: the probability density function of unsigned radial magnetic increments with the best-fit (Equation (5a)) yielding ﹩{\kappa }_{{\rm{\Delta }}{B}_{{\rm{R}}}}^{{\rm{(fit)}}}=1.96\pm 0.20﹩. Right panel: the analytic expression expected for possible ratios of the moments as a function of κ0, yielding ﹩{\kappa }_{{\rm{\Delta }}{B}_{{\rm{R}}}}^{{\rm{(m)}}}=1.91\pm 0.02﹩ when compared to the empirically computed ratio from the data (Equation (9)). These values of κΔBR correspond to the 3 hr interval centered about 2022 February 16 02:00:00.
Paper: Transfer of Entropy between the Magnetic Field and Solar Energetic Particles during an Interplanetary Coronal Mass Ejection
Authors: M. E. Cuesta, G. Livadiotis, D. J. McComas, L. Y. Khoo, H. A. Farooki, R. Bandyopadhyay, S. D. Bale
Figure caption: The distributions of the solar wind (SW), suprathermal (ST), and energetic particle (EP) populations as a function of energy. This illustration was taken from M. E. Cuesta et al. (2024a).
Paper: Transfer of Entropy between the Magnetic Field and Solar Energetic Particles during an Interplanetary Coronal Mass Ejection
Authors: M. E. Cuesta, G. Livadiotis, D. J. McComas, L. Y. Khoo, H. A. Farooki, R. Bandyopadhyay, S. D. Bale
Figure caption: Top panel: the time series of κEP (red triangles) and ﹩{\kappa }_{{\rm{\Delta }}B}^{{\rm{(m)}}}﹩ (blue circles) for the 2022 February 15 SEP event. Bottom left panel: the time series from the top panel collapsed over time, showing the exchange of correlation between the magnetic field and energetic protons. Bottom right panel: the block entropy as a function of the thermodynamic κ0 = κEP − 3/2, which is related to the thermodynamic entropy for the energetic protons. The numbers within their respective markers represent the portion number of the ICME, which is marked in Figure 3.
Paper: MeerKAT H I Observations of Low Surface Brightness/Ultradiffuse Galaxy Candidates Projected around Two Southern Loose Groups
Authors: Chandreyee Sengupta, Tom C. Scott, Hao Chen, Hyein Yoon, Yogesh Chandola, Mengtian Li, Gyula I. G. Józsa, O. Ivy Wong, Yin-Zhe Ma, Patricio Lagos, Ruta Kale, Denis Tramonte
Figure caption: 1° FWHP primary beams for the MeerKAT pointings are shown with the large green circles and marked P1 and P2 for NGC 1200 (left) and NGC 7396 (right). The projected positions of the LSBG and UDG candidates and their DES g − z colors are indicated by the symbols in the legend. Candidates with an H I detection are shown with midsized circles and the candidate’s ID number. The circle’s color indicates the H I detection’s velocity relative to its group per the legend. Note: two LSBGs in the NGC 1200 group, both candidate “blue UDGs,” have very similar coordinates (46.25, −12.47) and thus appear as one galaxy in Figure 1. The group center coordinates are the following: NGC 1200 45.97, −11.99 and NGC 7396 343.09, +1.09