adsabs/AstroCLIMB huggingface dataset:
Paper: Shooting for the Stars: Jet-mode Feedback and AGN Jet Deceleration from Stellar Mass Loading
Authors: Talia M. O'Shea, Sebastian Heinz, Melinda Soares-Furtado, Zsofi Igo, Andrea Merloni
Figure caption: Feedback power in decelerated jets. The top panel shows the mean kinetic power decelerated per stellar mass (i.e., specific feedback power) as a function of stellar population age, for selected stellar masses. The bottom panel shows the fraction of kinetic power in jets that is affected (i.e., the top panel divided by the total mean jet power for a given stellar mass). Throughout we use our fiducial model of θ = 3° and Γj = 3.
Paper: Shooting for the Stars: Jet-mode Feedback and AGN Jet Deceleration from Stellar Mass Loading
Authors: Talia M. O'Shea, Sebastian Heinz, Melinda Soares-Furtado, Zsofi Igo, Andrea Merloni
Figure caption: Fraction of jets not decelerated by mass loading. The top panel shows the escape fraction of jets above the Z. Igo et al. (2024) jet Eddington fraction range, for a range of opening angles. The horizontal dashed lines represent the FR-II fraction found in Z. Igo et al. (2024) for varying stellar mass bins, though note that these measurements have large errors (see Table 2 in Z. Igo et al. 2024). In the bottom panel, we use the extrapolated sample for a ∼2 dex range of stellar masses. The bottom panel assumes θ = 3°, and both panels adopt Γj = 3.
Paper: Shooting for the Stars: Jet-mode Feedback and AGN Jet Deceleration from Stellar Mass Loading
Authors: Talia M. O'Shea, Sebastian Heinz, Melinda Soares-Furtado, Zsofi Igo, Andrea Merloni
Figure caption: Top panel: number of AGB stars, NAGB, as a function of stellar population age, scaled by stellar mass. The right-hand axis shows the expected number of AGB stars in a bidirectional jet with a 3° opening angle and stellar mass of 109 M⊙. The bottom panel shows the critical stellar mass necessary to expect one AGB star within a jet of opening angle 3°, enclosed in the jet.
Paper: Shooting for the Stars: Jet-mode Feedback and AGN Jet Deceleration from Stellar Mass Loading
Authors: Talia M. O'Shea, Sebastian Heinz, Melinda Soares-Furtado, Zsofi Igo, Andrea Merloni
Figure caption: Fraction of power in the decelerated jet population for different opening angles, calculated for the extrapolated radio AGN incidence. We adopt Γj = 3 and M* = 1011.3 M⊙ (though fP is roughly mass independent).
Paper: Shooting for the Stars: Jet-mode Feedback and AGN Jet Deceleration from Stellar Mass Loading
Authors: Talia M. O'Shea, Sebastian Heinz, Melinda Soares-Furtado, Zsofi Igo, Andrea Merloni
Figure caption: Critical jet power stopped by stellar populations of mass Mcrit from the bottom panel of Figure 7. The light purple line shows the critical jet power if only mass loss from low-mass MS stellar populations is considered. The dark blue line shows the addition of one AGB star (i.e., using the total MLR with M* = Mcrit from the bottom panel of Figure 7.)
Paper: Shooting for the Stars: Jet-mode Feedback and AGN Jet Deceleration from Stellar Mass Loading
Authors: Talia M. O'Shea, Sebastian Heinz, Melinda Soares-Furtado, Zsofi Igo, Andrea Merloni
Figure caption: Edge-on view of our planar fit (dashed line) to log incidence η (normalized per dex in jet Eddington ratio) of radio AGN, as a function of log(λ) and stellar mass.
Paper: Long-term Monitoring of Scintillation in the Pulsar J0332+5434
Authors: Grayce C. Brown, Sofia Z. Sheikh, Luigi F. Cruz, Wael Farah, Vishal Gajjar, Christian Gilbertson, Brandon Grimaldo, Michael T. Lam, Sofia L. Marquez, Maura McLaughlin, Alexander W. Pollak, Andrew Siemion, Gurmehar Singh
Figure caption: Lomb–Scargle model for the scintillation bandwidth, showing a periodicity of ∼204 days for both Band 1 (left panels) and Band 2 (right panels). Top panels show the Lomb–Scargle periodogram, middle panels show the sinusoid model fit to the data, and the bottom panels show the residuals of the sinusoid model fit. Due to this period approaching the length of our observing period, these fits are inconclusive.
Paper: Long-term Monitoring of Scintillation in the Pulsar J0332+5434
Authors: Grayce C. Brown, Sofia Z. Sheikh, Luigi F. Cruz, Wael Farah, Vishal Gajjar, Christian Gilbertson, Brandon Grimaldo, Michael T. Lam, Sofia L. Marquez, Maura McLaughlin, Alexander W. Pollak, Andrew Siemion, Gurmehar Singh
Figure caption: An example scaling index measurement of one observation taken on MJD 60010 made with the novel cross-subband method described in Section 5.4.
Paper: Long-term Monitoring of Scintillation in the Pulsar J0332+5434
Authors: Grayce C. Brown, Sofia Z. Sheikh, Luigi F. Cruz, Wael Farah, Vishal Gajjar, Christian Gilbertson, Brandon Grimaldo, Michael T. Lam, Sofia L. Marquez, Maura McLaughlin, Alexander W. Pollak, Andrew Siemion, Gurmehar Singh
Figure caption: The unscaled daily average bandwidths (black) compared to a log-normal distribution (red).
Paper: Long-term Monitoring of Scintillation in the Pulsar J0332+5434
Authors: Grayce C. Brown, Sofia Z. Sheikh, Luigi F. Cruz, Wael Farah, Vishal Gajjar, Christian Gilbertson, Brandon Grimaldo, Michael T. Lam, Sofia L. Marquez, Maura McLaughlin, Alexander W. Pollak, Andrew Siemion, Gurmehar Singh
Figure caption: Time series of scaling index measurements over time using the established subband method (top panel) and the novel cross-subband method (bottom panel). The black line indicates the 10 day average with the rms error represented in the gray shaded area.
Paper: Long-term Monitoring of Scintillation in the Pulsar J0332+5434
Authors: Grayce C. Brown, Sofia Z. Sheikh, Luigi F. Cruz, Wael Farah, Vishal Gajjar, Christian Gilbertson, Brandon Grimaldo, Michael T. Lam, Sofia L. Marquez, Maura McLaughlin, Alexander W. Pollak, Andrew Siemion, Gurmehar Singh
Figure caption: A comparison of measured scintillation bandwidth values from the literature for PSR J0332+5434. Measurements from Section 4.1 are included in red. The scaling index measured from these data points is shown as the orange line.
Paper: Long-term Monitoring of Scintillation in the Pulsar J0332+5434
Authors: Grayce C. Brown, Sofia Z. Sheikh, Luigi F. Cruz, Wael Farah, Vishal Gajjar, Christian Gilbertson, Brandon Grimaldo, Michael T. Lam, Sofia L. Marquez, Maura McLaughlin, Alexander W. Pollak, Andrew Siemion, Gurmehar Singh
Figure caption: Daily averages of Band 1 (purple) and Band 2 (green) measurements of scintillation bandwidth Δνd. Band 2 has been scaled to Band 1’s reference frequency with a scaling index of α = 4.25.
Paper: Long-term Monitoring of Scintillation in the Pulsar J0332+5434
Authors: Grayce C. Brown, Sofia Z. Sheikh, Luigi F. Cruz, Wael Farah, Vishal Gajjar, Christian Gilbertson, Brandon Grimaldo, Michael T. Lam, Sofia L. Marquez, Maura McLaughlin, Alexander W. Pollak, Andrew Siemion, Gurmehar Singh
Figure caption: Example fit of the scaling index of a single observation on MJD 60010, in semilog space.
Paper: Long-term Monitoring of Scintillation in the Pulsar J0332+5434
Authors: Grayce C. Brown, Sofia Z. Sheikh, Luigi F. Cruz, Wael Farah, Vishal Gajjar, Christian Gilbertson, Brandon Grimaldo, Michael T. Lam, Sofia L. Marquez, Maura McLaughlin, Alexander W. Pollak, Andrew Siemion, Gurmehar Singh
Figure caption: Daily average time series, Band 1 (1139 MHz) and Band 2 (1668 MHz), with the scaling index fit in semilog space. The scaling index was measured to be 3.624  ±  0.006.
Paper: A Detailed Chemical Analysis of the Red Giant Orbiting Gaia BH3: From Lithium to Thorium 
Authors: Zoe Hackshaw, Keith Hawkins, Catherine Manea
Figure caption: Similar to Figure 3 from Gaia Collaboration et al. (2024), the radial velocity evolution of Gaia BH3. The blue line is the radial velocity evolution predicted by the Gaia combined binary model and the Gaia RVS epoch data are shown in black. We combine our RV points spanning 11 nights into three epochs (purple stars).
Paper: Measuring Star Formation Histories from Asymptotic Giant Branch Stars. I. A Demonstration in M31
Authors: Abigail J. Lee, Daniel R. Weisz, Yi Ren, Alessandro Savino, Andrew E. Dolphin
Figure caption: An example of recovering an SFH back to the oldest epochs of star formation, ≳13 Gyr ago, using only AGB stars in the NIR. (Left) Density maps for the observed, best-fit, and residual CMDs, expressed in units of Poisson standard deviations. (Middle) Cumulative stellar mass formed as a function of time. (Right) Total star formation rate as a function of time. The excellent agreement indicates that resolved AGB stars in the NIR, in principle, can be used to measure SFHs across all cosmic time.
Paper: Measuring Star Formation Histories from Asymptotic Giant Branch Stars. I. A Demonstration in M31
Authors: Abigail J. Lee, Daniel R. Weisz, Yi Ren, Alessandro Savino, Andrew E. Dolphin
Figure caption: Accuracy and precision of AGB star SFH and SFR fits as a function of the number of randomly sampled AGB stars from the full sample of ∼7700 AGB stars used in Figure 7.
Paper: Measuring Star Formation Histories from Asymptotic Giant Branch Stars. I. A Demonstration in M31
Authors: Abigail J. Lee, Daniel R. Weisz, Yi Ren, Alessandro Savino, Andrew E. Dolphin
Figure caption: Same as the previous figure and test, only for the JWST filter combination F115W − F277W, which is recommended for precision TRGB distances (e.g., M. J. B. Newman et al. 2024).
Paper: Measuring Star Formation Histories from Asymptotic Giant Branch Stars. I. A Demonstration in M31
Authors: Abigail J. Lee, Daniel R. Weisz, Yi Ren, Alessandro Savino, Andrew E. Dolphin
Figure caption: Number of stars recovered per age bin versus age for our full t < 14 Gyr fits. We recover a negligible number of stars in the t = 11.2 Gyr age bin, as expected.
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: The precision of each category of galaxies in the parameter space of the validation set (red: SPH, blue: ETD, yellow: LTD, green: IRR, and gray: UNC). Panels (a), (b), (c), (d), (e), and (f) represent the precision of galaxies on parameters such as Sérsic index (n), radius (re), Gini(G), M20, and NUV–r and r–J colors. We define the parameter range to encompass all galaxy types and calculate the median precision of each parameter interval within a metric for its classification precision. The parameter range includes all galaxy types, and the median precision within each parameter interval is calculated as a metric for its classification precision. The label gives the median precision of this type of galaxy within the entire parameter range. The precision of the model for classifying various categories of galaxies is independent of galaxy morphology and physical parameters. We find no significant difference or trend in the precision of each category in the parameter space, indicating that the False Positives do not rely on galaxy morphological and physical parameters.
Paper: Abundance Pattern Fitting with Bayesian Inference: Constraining First Stars’ Properties and Their Explosion Mechanism with Extremely Metal-poor Stars
Authors: Ruizheng Jiang, Haining Li, Gang Zhao, Qianfan Xing, Wenyu Xin
Figure caption: The abundances of EMP stars collected from FS, MMP, and VMP 400 samples, which are represented as blue circles, orange squares, and green triangles, respectively. For FS samples, stars cataloged in different publications are distinguished by different brightnesses. The carbon abundance is corrected according to stellar evolution, while the sodium, magnesium, and aluminum abundances are corrected for the one-dimensional NLTE effect. The typical observational uncertainties are on the order of 0.1 dex. The dotted horizontal line in the carbon panel represents the division of CEMP of [C/Fe] > 0.7.
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: Panels (a) and (b) show the distribution of galaxies in rest-frame NUV–r versus r–J color space and in the G–M20 parameter space, respectively. The contours enclose 70% of the galaxies in each subclass. The scattered points represent 500 galaxies randomly selected from each subclass. Colored diamonds indicate the median values of the distributions, and the associated error bars represent the standard deviations. Panels (c) and (d) display the distributions of Sérsic index (n) and effective radius (re), respectively. In the box plots, the boxes span the interquartile range (IQR) from the first to the third quartile, the central black line marks the median, and the whiskers extend to the minimum and maximum values.
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: Same as Figure 11, but for the recall metric. Similar to the results of precision, we find no significant difference or trend in the recall of each category in the parameter space, indicating the False Negatives do not rely on galaxy morphological and physical parameters. The recall of each category of galaxies in the parameter space of the validation set. The sequence and symbols are the same as Figure 11. The model’s recall across different galaxy categories is independent of morphology and physical parameters, indicating that False Negatives show no significant dependence on these factors.
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: Panels (a), (b), and (c) show the t-SNE diagrams of galaxies in the samples obtained using UML, SML, and the combined method, respectively. Panels (d), (e), and (f) present the corresponding class-wise contours for each of the three diagrams, enclosing 20%, 50%, and 70% of the respective samples. The clear boundaries between different galaxy types in the t-SNE maps indicate that the classification algorithms (UML, SML, and the combined model) exhibit strong robustness.
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: The distribution of training (red) and validation (blue) set data across various physical parameters. The consistent distribution between the training and validation sets illustrates the reliability of our methodology.
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: The distribution ratio of different types of galaxies in the training and validation sets remains consistent. This consistency ensures the reliability and generalization ability of the model evaluation results.
Paper: Robustness Analysis of USmorph. I. Generalization Efficiency of Unsupervised Strategies and Supervised Learning in Galaxy Morphological Classification
Authors: Shiwei Zhu, Guanwen Fang, Yao Dai, Chichun Zhou, Yirui Zheng, Jie Song, Shiying Lu, Xu Kong
Figure caption: An overview of the UML dataset. Left: cutouts of galaxies selected from different categories, i.e., SPH, ETD, LTD, IRR, and UNC galaxies, are shown from left to right. Right: the UML dataset illustrates the statistical distribution features of 50 galaxy groups (panel (a)) and the corresponding five-class merger label distributions (panel (b)).
Paper: PROJECT-J: The Shocking H2 Outflow from HH 46
Authors: Maria Gabriela Navarro, Brunella Nisini, Teresa Giannini, Patrick J. Kavanagh, Alessio Caratti o Garatti, Simone Antoniucci, Hector G. Arce, Francesca Bacciotti, Sylvie Cabrit, Deirdre Coffey, Catherine Dougados, Jochen Eislöffel, Patrick Hartigan, Alberto Noriega- Crespo, Linda Podio, Ewine F. van Dishoeck, Emma T. Whelan
Figure caption: Top left: temperature map of the warm H2 component, derived from the 0–0 S(1)–S(4) transitions. Top right: temperature map of the hot H2 component, obtained from the 0–0 S(5)–S(8) transitions. Bottom left: H2 column density map of the warm component. Bottom right: visual extinction (AV) map. White stars indicate the source position. Magenta contours correspond to the [Fe II] 5.34 μm line tracing the atomic jet (levels from 0.4 to 17.0 MJy sr−1), while black contours represent the H2 0–0 S(7) 5.51 μm line (levels from 0.4 to 4.0 MJy sr−1). Only lines with SNR > 5 were included in the analysis; pixels with fewer than three detected lines per temperature regime were excluded. The maps were convolved to match the spatial resolution of MIRI-MRS at 17 μm, corresponding to an FWHM of ∼0﹩\mathop{.}\limits^{^{\prime\prime} }﹩6 and a spectral resolving power of R ∼ 1600–1800 (Δv ≈ 170 km s−1; I. Argyriou et al. 2023; M. Wells et al. 2015; JWST Documentation). This wavelength provides the lowest spatial and spectral resolution among the H2 lines used to construct the rotational diagrams.
Paper: PROJECT-J: The Shocking H2 Outflow from HH 46
Authors: Maria Gabriela Navarro, Brunella Nisini, Teresa Giannini, Patrick J. Kavanagh, Alessio Caratti o Garatti, Simone Antoniucci, Hector G. Arce, Francesca Bacciotti, Sylvie Cabrit, Deirdre Coffey, Catherine Dougados, Jochen Eislöffel, Patrick Hartigan, Alberto Noriega- Crespo, Linda Podio, Ewine F. van Dishoeck, Emma T. Whelan
Figure caption: Schematic representation of the observed H2 structures based on the emission morphology, analogous to Figures 1 and 4. Sources a⋆ and b⋆ are marked as black filled circles. The collimated atomic jet is illustrated in blue and red, while the H2 emission is shown in cyan and violet. Regions of enhanced H2 emission are indicated with more intense colors and are spatially connected to each component of the binary system. The figure is an artistic rendering by A. Spazzoli, designed specifically for this work.
Paper: PROJECT-J: The Shocking H2 Outflow from HH 46
Authors: Maria Gabriela Navarro, Brunella Nisini, Teresa Giannini, Patrick J. Kavanagh, Alessio Caratti o Garatti, Simone Antoniucci, Hector G. Arce, Francesca Bacciotti, Sylvie Cabrit, Deirdre Coffey, Catherine Dougados, Jochen Eislöffel, Patrick Hartigan, Alberto Noriega- Crespo, Linda Podio, Ewine F. van Dishoeck, Emma T. Whelan
Figure caption: Rotational diagrams with extinction-corrected column densities for regions in the blueshifted outflow lobe covered by both MIRI and NIRSpec observations. Red and blue symbols correspond to MIRI and NIRSpec data, respectively. Symbols denote transitions from different vibrational levels: v = 0 (squares), v = 1 (triangles), v = 2 (circles), and v > 2 (stars). Straight lines indicate the two-component linear fits performed for each region.
Paper: PROJECT-J: The Shocking H2 Outflow from HH 46
Authors: Maria Gabriela Navarro, Brunella Nisini, Teresa Giannini, Patrick J. Kavanagh, Alessio Caratti o Garatti, Simone Antoniucci, Hector G. Arce, Francesca Bacciotti, Sylvie Cabrit, Deirdre Coffey, Catherine Dougados, Jochen Eislöffel, Patrick Hartigan, Alberto Noriega- Crespo, Linda Podio, Ewine F. van Dishoeck, Emma T. Whelan
Figure caption: Left: radial velocity map of the H2 1–0 S(1) line at 2.12 μm obtained with NIRSpec. Right: FWHM map in velocity space derived from the same line. Velocities are given in the rest frame of the ambient CO cloud. Black stars indicate the positions of the binary sources. Magenta contours trace the stacked H2 emission (levels from 0.085 to 2.0 MJy sr−1), while black contours correspond to the [Fe II] 1.81 μm line delineating the collimated atomic jet (levels from 0.028 to 0.4 MJy sr−1).
Paper: PROJECT-J: The Shocking H2 Outflow from HH 46
Authors: Maria Gabriela Navarro, Brunella Nisini, Teresa Giannini, Patrick J. Kavanagh, Alessio Caratti o Garatti, Simone Antoniucci, Hector G. Arce, Francesca Bacciotti, Sylvie Cabrit, Deirdre Coffey, Catherine Dougados, Jochen Eislöffel, Patrick Hartigan, Alberto Noriega- Crespo, Linda Podio, Ewine F. van Dishoeck, Emma T. Whelan
Figure caption: Top panel: rotational diagram of the pure rotational v = 0 lines for knot A1, assuming a temperature stratification. Red and blue squares represent MIRI and NIRSpec data, respectively, while black open circles denote the best-fit model. The corresponding fitted parameters are listed in the inset. Bottom panel: rotational diagrams of the pure rotational v = 0 lines for all regions covered by both NIRSpec and MIRI. Colored squares represent the observed data for each region, and open circles show the corresponding best-fit models.
Paper: PROJECT-J: The Shocking H2 Outflow from HH 46
Authors: Maria Gabriela Navarro, Brunella Nisini, Teresa Giannini, Patrick J. Kavanagh, Alessio Caratti o Garatti, Simone Antoniucci, Hector G. Arce, Francesca Bacciotti, Sylvie Cabrit, Deirdre Coffey, Catherine Dougados, Jochen Eislöffel, Patrick Hartigan, Alberto Noriega- Crespo, Linda Podio, Ewine F. van Dishoeck, Emma T. Whelan
Figure caption: Rotational diagrams of the pure rotational v = 0 H2 lines observed with MIRI in representative regions of the redshifted (A5 and A6) and blueshifted (Cav3 and Bow2) outflows. Filled squares represent the MIRI data, while black open circles denote the best-fit models.
Paper: PROJECT-J: The Shocking H2 Outflow from HH 46
Authors: Maria Gabriela Navarro, Brunella Nisini, Teresa Giannini, Patrick J. Kavanagh, Alessio Caratti o Garatti, Simone Antoniucci, Hector G. Arce, Francesca Bacciotti, Sylvie Cabrit, Deirdre Coffey, Catherine Dougados, Jochen Eislöffel, Patrick Hartigan, Alberto Noriega- Crespo, Linda Podio, Ewine F. van Dishoeck, Emma T. Whelan
Figure caption: Absolute value for the radial velocity vs. the energy of the level for knot A1. Red and blue symbols indicate MIRI and NIRSpec measurements, respectively. Different vibrational levels are indicated with squares (v = 0), triangles (v = 1), and circles (v = 2). The combined errors include those from Gaussian fits and instrumental uncertainties.
Paper: PROJECT-J: The Shocking H2 Outflow from HH 46
Authors: Maria Gabriela Navarro, Brunella Nisini, Teresa Giannini, Patrick J. Kavanagh, Alessio Caratti o Garatti, Simone Antoniucci, Hector G. Arce, Francesca Bacciotti, Sylvie Cabrit, Deirdre Coffey, Catherine Dougados, Jochen Eislöffel, Patrick Hartigan, Alberto Noriega- Crespo, Linda Podio, Ewine F. van Dishoeck, Emma T. Whelan
Figure caption: H2 radial velocity map obtained with the MIRI 0–0 S(4) line at 8.08 μm. Velocities are in the rest frame of the ambient CO cloud. Black stars mark the source position. Yellow and black contours correspond to the H2 emission traced by the S(4) line at 8.03 μm (levels from 0.4 to 4.0 MJy sr−1) and collimated atomic jet emission traced by the [Fe II] at 1.81 μm (levels from 0.4 to 17.0 MJy sr−1), respectively.
Paper: PROJECT-J: The Shocking H2 Outflow from HH 46
Authors: Maria Gabriela Navarro, Brunella Nisini, Teresa Giannini, Patrick J. Kavanagh, Alessio Caratti o Garatti, Simone Antoniucci, Hector G. Arce, Francesca Bacciotti, Sylvie Cabrit, Deirdre Coffey, Catherine Dougados, Jochen Eislöffel, Patrick Hartigan, Alberto Noriega- Crespo, Linda Podio, Ewine F. van Dishoeck, Emma T. Whelan
Figure caption: Best-fit shock models (black open circles) for knot A1. The left and right panels correspond to the best J-type and C-type shock models, respectively, while the top and bottom panels show models with and without an external UV radiation field (G0), respectively. Red and blue symbols represent MIRI and NIRSpec data, respectively, with different markers (squares, triangles, circles, and stars) denoting vibrational levels from v = 0 to v > 2.