adsabs/AstroCLIMB huggingface dataset:
Paper: CEERS Key Paper. IX. Identifying Galaxy Mergers in CEERS NIRCam Images Using Random Forests and Convolutional Neural Networks
Authors: Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Marc Huertas-Company, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Laura Bisigello, Antonello Calabrò, Nikko J. Cleri, Mark Dickinson, Henry C. Ferguson, Steven L. Finkelstein, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Benne W. Holwerda, Kartheik G. Iyer, Lisa J. Kewley, Allison Kirkpatrick, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Ray A. Lucas, Lorenzo Napolitano, Casey Papovich, Laura Pentericci, Pablo G. Pérez-González, Nor Pirzkal, Swara Ravindranath, Rachel S. Somerville, Amber N. Straughn, Jonathan R. Trump, Stephen M. Wilkins, Guang Yang
Figure caption: F277W G−M 20 space for observed CEERS galaxies from 3 < z < 5. In the left panel, observed galaxies are color-coded by visual classifications as defined in Section 4.1 (group 1/G1: at least two out of three volunteer classifiers assigned an interaction class; group 2/G2: at least two out of three classifiers assigned the Irregular morphology class; group 4/G4: one of out three classifiers assigned an interaction class). In the middle and right panels, galaxies are color-coded by the merger probability output by the random forest or neural network, respectively.
Paper: CEERS Key Paper. IX. Identifying Galaxy Mergers in CEERS NIRCam Images Using Random Forests and Convolutional Neural Networks
Authors: Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Marc Huertas-Company, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Laura Bisigello, Antonello Calabrò, Nikko J. Cleri, Mark Dickinson, Henry C. Ferguson, Steven L. Finkelstein, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Benne W. Holwerda, Kartheik G. Iyer, Lisa J. Kewley, Allison Kirkpatrick, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Ray A. Lucas, Lorenzo Napolitano, Casey Papovich, Laura Pentericci, Pablo G. Pérez-González, Nor Pirzkal, Swara Ravindranath, Rachel S. Somerville, Amber N. Straughn, Jonathan R. Trump, Stephen M. Wilkins, Guang Yang
Figure caption: Examples of TP, FP, TN, and FP (as defined in Section 4.4) simulated CEERS galaxies in the F356W filter from the 3.5 < z < 4 redshift bin. Each stamp is 3″ × 3″. Within each stamp, the merger probability output by the DeepMerge network is in the upper left, and the timescale since or until the most recent merger (major or minor) is in the bottom left. The outlines show the segmentation map, color-coded by major (magenta) and minor (green) mergers.
Paper: CEERS Key Paper. IX. Identifying Galaxy Mergers in CEERS NIRCam Images Using Random Forests and Convolutional Neural Networks
Authors: Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Marc Huertas-Company, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Laura Bisigello, Antonello Calabrò, Nikko J. Cleri, Mark Dickinson, Henry C. Ferguson, Steven L. Finkelstein, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Benne W. Holwerda, Kartheik G. Iyer, Lisa J. Kewley, Allison Kirkpatrick, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Ray A. Lucas, Lorenzo Napolitano, Casey Papovich, Laura Pentericci, Pablo G. Pérez-González, Nor Pirzkal, Swara Ravindranath, Rachel S. Somerville, Amber N. Straughn, Jonathan R. Trump, Stephen M. Wilkins, Guang Yang
Figure caption: Examples of simulated CEERS galaxies and their corresponding Grad-CAMs from the single-filter DeepMerge test using F356W images. The bottom left corner of the F356W image stamps shows the categorization (e.g., TP, FP, etc.) of this object and the DeepMerge merger probability. “True Positive” indicates that the galaxy was correctly classified as a merger by DeepMerge. “False Positive” indicates that the galaxy was incorrectly classified as a merger by DeepMerge and is actually a nonmerger according to our merger definition from Section 3.3. The red plus signs show the location of the center of each image.
Paper: CEERS Key Paper. IX. Identifying Galaxy Mergers in CEERS NIRCam Images Using Random Forests and Convolutional Neural Networks
Authors: Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Marc Huertas-Company, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Laura Bisigello, Antonello Calabrò, Nikko J. Cleri, Mark Dickinson, Henry C. Ferguson, Steven L. Finkelstein, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Benne W. Holwerda, Kartheik G. Iyer, Lisa J. Kewley, Allison Kirkpatrick, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Ray A. Lucas, Lorenzo Napolitano, Casey Papovich, Laura Pentericci, Pablo G. Pérez-González, Nor Pirzkal, Swara Ravindranath, Rachel S. Somerville, Amber N. Straughn, Jonathan R. Trump, Stephen M. Wilkins, Guang Yang
Figure caption: Examples of TP, FP, TN, and FP observed CEERS galaxies (from group 1) in the F356W filter from the 3.5 < z < 4 redshift bin categorized by the random forest (top) or the DeepMerge network (bottom). Each stamp is 3″ × 3″. Within each stamp, the merger probability output by the respective algorithm is in the upper left. The white outlines are segmentation map outlines.
Paper: CEERS Key Paper. IX. Identifying Galaxy Mergers in CEERS NIRCam Images Using Random Forests and Convolutional Neural Networks
Authors: Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Marc Huertas-Company, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Laura Bisigello, Antonello Calabrò, Nikko J. Cleri, Mark Dickinson, Henry C. Ferguson, Steven L. Finkelstein, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Benne W. Holwerda, Kartheik G. Iyer, Lisa J. Kewley, Allison Kirkpatrick, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Ray A. Lucas, Lorenzo Napolitano, Casey Papovich, Laura Pentericci, Pablo G. Pérez-González, Nor Pirzkal, Swara Ravindranath, Rachel S. Somerville, Amber N. Straughn, Jonathan R. Trump, Stephen M. Wilkins, Guang Yang
Figure caption: Top: DeepMerge confusion matrices for the simulated CEERS test set for each redshift bin. Bottom: corresponding ROC curves for the simulated CEERS test set for each redshift bin. The training set (green) and test set (purple) curves lie in the region of “good” classifiers between the perfect (black) and no skill (red) classifiers.
Paper: CEERS Key Paper. IX. Identifying Galaxy Mergers in CEERS NIRCam Images Using Random Forests and Convolutional Neural Networks
Authors: Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Marc Huertas-Company, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Laura Bisigello, Antonello Calabrò, Nikko J. Cleri, Mark Dickinson, Henry C. Ferguson, Steven L. Finkelstein, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Benne W. Holwerda, Kartheik G. Iyer, Lisa J. Kewley, Allison Kirkpatrick, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Ray A. Lucas, Lorenzo Napolitano, Casey Papovich, Laura Pentericci, Pablo G. Pérez-González, Nor Pirzkal, Swara Ravindranath, Rachel S. Somerville, Amber N. Straughn, Jonathan R. Trump, Stephen M. Wilkins, Guang Yang
Figure caption: Left: random forest confusion matrix for 4 < z < 5 objects from the test set. The diagonal shows the fraction of objects correctly classified for each class. Right: ROC curve for the 4 < z < 5 random forest. The training set (green) and test set (purple) curves lie in the region of “good” classifiers between the perfect (black) and no skill (red) classifiers.
Paper: CEERS Key Paper. IX. Identifying Galaxy Mergers in CEERS NIRCam Images Using Random Forests and Convolutional Neural Networks
Authors: Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Marc Huertas-Company, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Laura Bisigello, Antonello Calabrò, Nikko J. Cleri, Mark Dickinson, Henry C. Ferguson, Steven L. Finkelstein, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Benne W. Holwerda, Kartheik G. Iyer, Lisa J. Kewley, Allison Kirkpatrick, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Ray A. Lucas, Lorenzo Napolitano, Casey Papovich, Laura Pentericci, Pablo G. Pérez-González, Nor Pirzkal, Swara Ravindranath, Rachel S. Somerville, Amber N. Straughn, Jonathan R. Trump, Stephen M. Wilkins, Guang Yang
Figure caption: Random forest confusion matrix for observed CEERS galaxies at 3 < z < 3.5.
Paper: CEERS Key Paper. IX. Identifying Galaxy Mergers in CEERS NIRCam Images Using Random Forests and Convolutional Neural Networks
Authors: Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Marc Huertas-Company, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Laura Bisigello, Antonello Calabrò, Nikko J. Cleri, Mark Dickinson, Henry C. Ferguson, Steven L. Finkelstein, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Benne W. Holwerda, Kartheik G. Iyer, Lisa J. Kewley, Allison Kirkpatrick, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Ray A. Lucas, Lorenzo Napolitano, Casey Papovich, Laura Pentericci, Pablo G. Pérez-González, Nor Pirzkal, Swara Ravindranath, Rachel S. Somerville, Amber N. Straughn, Jonathan R. Trump, Stephen M. Wilkins, Guang Yang
Figure caption: DeepMerge neural network confusion matrix for observed CEERS galaxies at 3 < z < 3.5.
Paper: CEERS Key Paper. IX. Identifying Galaxy Mergers in CEERS NIRCam Images Using Random Forests and Convolutional Neural Networks
Authors: Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Marc Huertas-Company, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Laura Bisigello, Antonello Calabrò, Nikko J. Cleri, Mark Dickinson, Henry C. Ferguson, Steven L. Finkelstein, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Benne W. Holwerda, Kartheik G. Iyer, Lisa J. Kewley, Allison Kirkpatrick, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Ray A. Lucas, Lorenzo Napolitano, Casey Papovich, Laura Pentericci, Pablo G. Pérez-González, Nor Pirzkal, Swara Ravindranath, Rachel S. Somerville, Amber N. Straughn, Jonathan R. Trump, Stephen M. Wilkins, Guang Yang
Figure caption: Random forest confusion matrices for observed CEERS galaxies at 3 < z < 3.5 (top row), 3.5 < z < 4 (middle row), and 4 < z < 5 (bottom row).
Paper: CEERS Key Paper. IX. Identifying Galaxy Mergers in CEERS NIRCam Images Using Random Forests and Convolutional Neural Networks
Authors: Caitlin Rose, Jeyhan S. Kartaltepe, Gregory F. Snyder, Marc Huertas-Company, L. Y. Aaron Yung, Pablo Arrabal Haro, Micaela B. Bagley, Laura Bisigello, Antonello Calabrò, Nikko J. Cleri, Mark Dickinson, Henry C. Ferguson, Steven L. Finkelstein, Adriano Fontana, Andrea Grazian, Norman A. Grogin, Benne W. Holwerda, Kartheik G. Iyer, Lisa J. Kewley, Allison Kirkpatrick, Dale D. Kocevski, Anton M. Koekemoer, Jennifer M. Lotz, Ray A. Lucas, Lorenzo Napolitano, Casey Papovich, Laura Pentericci, Pablo G. Pérez-González, Nor Pirzkal, Swara Ravindranath, Rachel S. Somerville, Amber N. Straughn, Jonathan R. Trump, Stephen M. Wilkins, Guang Yang
Figure caption: DeepMerge neural network confusion matrices for observed CEERS galaxies at 3 < z < 3.5 (top row), 3.5 < z < 4 (middle row), and 4 < z < 5 (bottom row).
Paper: The Extreme Low-mass End of the Mass–Metallicity Relation at z ∼ 7
Authors: Iryna Chemerynska, Hakim Atek, Pratika Dayal, Lukas J. Furtak, Robert Feldmann, Jenny E. Greene, Michael V. Maseda, Themiya Nanayakkara, Pascal A. Oesch, Seiji Fujimoto, Ivo Labbé, Rachel Bezanson, Gabriel Brammer, Sam E. Cutler, Joel Leja, Richard Pan, Sedona H. Price, Bingjie Wang, John R. Weaver, Katherine E. Whitaker
Figure caption: The relationship between stellar mass (M ⋆) and SFR for our JWST sample (red stars), including the literature sample compiled from K. Nakajima et al. (2023; violet dots; CEERS) and M. Curti et al. (2024; gold dots; EROs). Left: comparison between our best-fit galaxy and the main sequence of star-forming galaxies determined from the literature at z ∼ 0 and z ∼ 6.5 (P. Popesso et al. 2023; solid blue and dark red lines, respectively), at 6 < z ≲ 7 (L. Clarke et al. 2024; dotted–dashed dark red line), at 0.2 < z < 0.7 (K. G. Noeske et al. 2007; dotted–dashed blue line), and a starburst cloud at high redshift (P. Rinaldi et al. 2022; dashed red line). The extrapolation for lower masses is depicted in lighter shades. Literature results are color-coded depending on the redshift. Right: we also provided recent results from the SPHINX simulation for SFMS for 10 Myr at z = 7 (H. Katz et al. 2023; green solid line), the FLARES simulation at z = 6–8 (A. P. Vijayan et al. 2024; gray shaded region) with SFR timescale 100 Myr, ASTRAEUS at z = 6 with an evolving IMF (E. R. Cueto et al. 2024; green shaded region), the FIRE-2 simulations at redshift z = 6 with SFR averaged over 10 Myr (X. Ma et al. 2018; teal dashed line), and the NEWHORIZON simulation for SFR for 10 Myr at the same redshift (Y. Dubois et al. 2021; gray shaded region). The red shaded area in both figures indicates uncertainties in the fitting.
Paper: The Extreme Low-mass End of the Mass–Metallicity Relation at z ∼ 7
Authors: Iryna Chemerynska, Hakim Atek, Pratika Dayal, Lukas J. Furtak, Robert Feldmann, Jenny E. Greene, Michael V. Maseda, Themiya Nanayakkara, Pascal A. Oesch, Seiji Fujimoto, Ivo Labbé, Rachel Bezanson, Gabriel Brammer, Sam E. Cutler, Joel Leja, Richard Pan, Sedona H. Price, Bingjie Wang, John R. Weaver, Katherine E. Whitaker
Figure caption: Extending the MZR at z = 6–8 to the lowest-mass galaxies. The red stars represent measurements of the present sample (the best-fit relation is the red shaded region) based on R. L. Sanders et al. (2024) calibration compared to literature results at similar redshifts: the JADES survey (M. Curti et al. 2024; blue squares) and JWST public surveys (K. Nakajima et al. 2023; violet circles). We also show for reference a lower-redshift determination at z = 0 from the SDSS (R. L. Sanders et al. 2021; gray dashed line) and at z = 3.3 from MOSDEF (R. L. Sanders et al. 2021; blue shaded region and line). A comparison to theoretical predictions of the MZR is also provided: the FIRE simulations over the redshift range z = 6 (X. Ma et al. 2016; teal dashed line), the FIRE-2 simulations at redshift 7 (A. Marszewski et al. 2024; purple dotted–dashed line), the ASTRAEUS determination at z = 6 (G. Ucci et al. 2023; green shaded region) assuming SFR = [0.1–0.5] M ⊙ yr−1, ASTRAEUS at z = 6 assuming an evolving IMF (E. R. Cueto et al. 2024; green dotted line), and the NEWHORIZON simulation at the redshift z = 7 (Y. Dubois et al. 2021; gray shaded region).
Paper: The Extreme Low-mass End of the Mass–Metallicity Relation at z ∼ 7
Authors: Iryna Chemerynska, Hakim Atek, Pratika Dayal, Lukas J. Furtak, Robert Feldmann, Jenny E. Greene, Michael V. Maseda, Themiya Nanayakkara, Pascal A. Oesch, Seiji Fujimoto, Ivo Labbé, Rachel Bezanson, Gabriel Brammer, Sam E. Cutler, Joel Leja, Richard Pan, Sedona H. Price, Bingjie Wang, John R. Weaver, Katherine E. Whitaker
Figure caption: The impact of SFR on the MZR. The stars represent measurements of the present sample, which are color-coded according to their sSFR. The rest of the legend is identical to Figure 1.
Paper: The Extreme Low-mass End of the Mass–Metallicity Relation at z ∼ 7
Authors: Iryna Chemerynska, Hakim Atek, Pratika Dayal, Lukas J. Furtak, Robert Feldmann, Jenny E. Greene, Michael V. Maseda, Themiya Nanayakkara, Pascal A. Oesch, Seiji Fujimoto, Ivo Labbé, Rachel Bezanson, Gabriel Brammer, Sam E. Cutler, Joel Leja, Richard Pan, Sedona H. Price, Bingjie Wang, John R. Weaver, Katherine E. Whitaker
Figure caption: Identical to Figure 1. The MZR at z = 6–8 for the lowest-mass galaxies using a single power-law fit. The pink stars represent the metallicities derived by using calibrations from K. Nakajima et al. (2022), I. H. Laseter et al. (2024), and M. Hirschmann et al. (2023; panels from left to right, respectively), along with metallicities derived by the R. L. Sanders et al. (2024; red stars). The fitted MZR is shown in pink.
Paper: The Extreme Low-mass End of the Mass–Metallicity Relation at z ∼ 7
Authors: Iryna Chemerynska, Hakim Atek, Pratika Dayal, Lukas J. Furtak, Robert Feldmann, Jenny E. Greene, Michael V. Maseda, Themiya Nanayakkara, Pascal A. Oesch, Seiji Fujimoto, Ivo Labbé, Rachel Bezanson, Gabriel Brammer, Sam E. Cutler, Joel Leja, Richard Pan, Sedona H. Price, Bingjie Wang, John R. Weaver, Katherine E. Whitaker
Figure caption: Relationships between metallicity and the strong line ratios of R3 and ﹩\hat{R}﹩ (from left to right).
Paper: Solar System Migration Points to a Renewed Concept: Galactic Habitable Orbits
Authors: Junichi Baba, Takuji Tsujimoto, Takayuki R. Saitoh
Figure caption: Estimations of the solar birth radius (Rbirth,⊙) and the probability density functions of the eventual guiding radius (Rg). Panel (a): recent estimates of Rbirth from Galactic chemical evolution models (GCE; blue squares; M. F. Nieva & N. Przybilla 2012; M. Haywood et al. 2019; T. Tsujimoto & J. Baba 2020; J. Baba et al. 2023; N. Prantzos et al. 2023), the stellar age–metallicity relation (AMR; red dots; R. Wielen et al. 1996; B. Ratcliffe et al. 2023; L. Lu et al. 2024), and a chemodynamical model using an orbital diffusion approximation (CDY; orange triangle; N. Frankel et al. 2020), overlaid for comparison. In cases where the references did not specify the range of Rbirth,⊙ estimates, an uncertainty of ±1 kpc was applied. The mode value of these recent estimations is indicated by a vertical solid line. The green shaded region around 5 kpc denotes the adopted range of the Sun's birth radius for this study, while the blue shaded region around 8.5 kpc indicates the present-day guiding radius of the Sun (Rg,⊙). The vertical dashed line marks the present-day CR radius of the Galactic bar at 6.43 kpc. Panel (b): eventual Rg probability density distributions of stars for different scenarios. The dotted–dashed line represents the “steady model” with a constant rotational speed for the bar and spiral arms (Ωs/Ω0 = 1.0), with a spiral amplitude ratio of Σs/Σdisk = 25%. The red solid line depicts the “evolving model,” which includes a decelerating bar and dynamic spiral arms, also at a spiral amplitude of Σs/Σdisk = 25%. Details on variations in the pattern speed and amplitude of the spiral arms are further examined in Figure 2.
Paper: Solar System Migration Points to a Renewed Concept: Galactic Habitable Orbits
Authors: Junichi Baba, Takuji Tsujimoto, Takayuki R. Saitoh
Figure caption: Eventual Rg ≡ Lz/V0 distributions of stars with orbital eccentricity with e < 0.1, which are initially set at 4.5 kpc < Rg < 5.5 kpc (highlighted by the green shaded zone). Panel (a): cases with a rigid bar + SDW model. The spiral amplitudes are varied as Σs/Σdisk = 20% (dotted–dashed line), 25% (solid line), and 30% (dashed line). The vertical dashed line represents the radius of CR of the rigid bar at 6.43 kpc. Panel (b) examines the effects of different pattern speed ratios (Ωs/Ω0) in SDW models on the guiding radii distribution of stars. It presents cases with ratios of 0.63, 0.84, and 1.26, translating to Ωs values of 18, 24, and 36 km s−1 kpc−1, respectively. Panel (c) investigates how combining a rigid bar with DYN arms influences stellar migration, with arm amplitudes of 20% (dotted–dashed line), 25% (solid line), and 30% (dashed line) showcasing varying migration efficiencies. Panels (d), (e), and (f) illustrate the migration outcomes with a slowing bar replacing the rigid bar, using the same spiral arm models as in panels (a)–(c), to compare how the bar's dynamics influence the Sun's migration.
Paper: Solar System Migration Points to a Renewed Concept: Galactic Habitable Orbits
Authors: Junichi Baba, Takuji Tsujimoto, Takayuki R. Saitoh
Figure caption: Histories of surrounding environmental changes along the Sun’s potential orbits. The environmental changes along the Sun’s potential orbits are distinctly illustrated for “trapped migrators” (depicted in orange colors) and “untrapped migrators” (depicted in green colors). Panel (a) shows SFR densities, panel (b) details lethal GRB event rates, panel (c) depicts comet flux due to Galactic tides, and panel (d) presents frequencies of stellar encounters. The error bars represent the estimated values in the current solar neighborhood taken from the literature (B. C. Thomas et al. 2005; H. Rickman et al. 2008; C. A. L. Bailer-Jones 2018; J. D. Soler et al. 2023). The vertical shaded regions in each panel indicate the geological eras of the Earth (Hadean, Archean, Proterozoic, and Phanerozoic).
Paper: Solar System Migration Points to a Renewed Concept: Galactic Habitable Orbits
Authors: Junichi Baba, Takuji Tsujimoto, Takayuki R. Saitoh
Figure caption: Trajectory of the Sun on the R–tbk plane for the evolving model. The orange lines show the trajectories of “trapped migrators,” while the green lines depict “untrapped migrators.” Thick lines represent the trajectories of Sun-like particles, while thin lines show orbits similar to those indicated by the thick lines. The background colors with contours indicate (a) the SFR density (ΣSFR) and (b) lethal GRB event rates (NGBR), based on the Galactic chemical evolution model (J. Baba et al. 2023). The black dashed lines indicate the locations of the bar's CR and OLR radii.
Paper: Solar System Migration Points to a Renewed Concept: Galactic Habitable Orbits
Authors: Junichi Baba, Takuji Tsujimoto, Takayuki R. Saitoh
Figure caption: Panel (a): circular velocity (Vc) and contributions of individual components as a function of the galactocentric radius, R. The green shaded region around 5 kpc denotes the adopted range of the Sun's birth radius (Rbirth,⊙) for this study, while the blue shaded region around 8.5 kpc indicates the present-day guiding radius of the Sun (Rg,⊙). The vertical dashed line marks the present-day CR radius of the Galactic bar at 6.43 kpc. Panel (b): the radial profiles of the effective potentials along the bar's major axis, Φeff,b, for these slowdown bar models are shown for look-back times tbk = 0, 3.0, and 4.6 Gyr ago. At each of these times, the peak of the profile corresponds to the CR radius of the bar, with respective values of 6.43 kpc, 6.1 kpc, and 4.1 kpc. The horizontal red line indicates the current value of the Sun's Jacobi energy.
Paper: Solar System Migration Points to a Renewed Concept: Galactic Habitable Orbits
Authors: Junichi Baba, Takuji Tsujimoto, Takayuki R. Saitoh
Figure caption: Panel (a): normalized luminosity functions at z = 0. Panel (b): cosmic GRB rates. Panel (c): cosmic SFR density.
Paper: Detection of Hidden Emissions in Two Rotating Radio Transients with High Surface Magnetic Fields
Authors: S. B. Zhang, X. Yang, J. J. Geng, Y. P. Yang, X. F. Wu
Figure caption: Left: isotropic-equivalent spectral luminosity vs. the product of observing frequency and pulse width for various pulsars. The brightest strong RRAT pulses from RRATs with relatively high Bs (J1846-0257 and 1854+0306), detected in this study, are represented by large red-filled stars, while their weak emissions are denoted by small red-filled triangles. The brightest strong RRAT pulses from RRATs with regular Bs (J1839-0141 and J1913+1330), detected in this study, are shown as large black-filled stars, with their weak emissions constraints indicated by small black unfilled triangles. The brightest giant pulses burst from J0534+2200 (A. Bera & J. N. Chengalur 2019) and J0540-6919 (M. Geyer et al. 2021), are denoted by large green-filled squares, with their normal emissions (R. N. Manchester et al. 2005) marked by small green-filled circles. Pulsar (R. N. Manchester et al. 2005) and RRAT populations (RRATalog) are indicated in thistle and blue, respectively. Gray dashed lines represent constant isotropic-equivalent energy release, and gray dotted lines indicate constant brightness temperature. Right: the energy release contribution fraction of strong pulse emissions versus the rate of strong pulse emissions occurring in one rotation period. RRATs with relatively high Bs (J1846-0257 and 1854+0306) are shown as red-filled stars, while RRATs with regular Bs (J1839-0141 and J1913+1330) are depicted as black-filled stars. Pulsars with giant pulses (J0534+2200; M. V. Popov et al. 2006) and J0540-6919 (M. Geyer et al. 2021) are represented by green-filled circles.