adsabs/AstroCLIMB huggingface dataset:
Paper: The Curious Case of Twin Fast Radio Bursts: Evidence for Neutron Star Origin?
Authors: Apurba Bera, Clancy W. James, Adam T. Deller, Keith W. Bannister, Ryan M. Shannon, Danica R. Scott, Kelly Gourdji, Lachlan Marnoch, Marcin Glowacki, Ronald D. Ekers, Stuart D. Ryder, Tyson Dial
Figure caption: RM of FRB 20181112A estimated using the RM synthesis method, in sub-burst A. The frequency-averaged Stokes I profile of the FRB is shown in red at a time resolution of 3.8 μs (in normalized flux density units not shown in the plots). The horizontal error bars represent the time range for the corresponding measurements. The bottom panel shows the corresponding PA at infinite frequency, assuming that PA has a linear dependence on λ 2. See Appendix B for details.
Paper: The Curious Case of Twin Fast Radio Bursts: Evidence for Neutron Star Origin?
Authors: Apurba Bera, Clancy W. James, Adam T. Deller, Keith W. Bannister, Ryan M. Shannon, Danica R. Scott, Kelly Gourdji, Lachlan Marnoch, Marcin Glowacki, Ronald D. Ekers, Stuart D. Ryder, Tyson Dial
Figure caption: Time-resolved polarization spectra of FRB 20181112A in sub-burst A before correcting for the average RM. The time ranges for averaging and the slope of the V/I vs. λ 2 curve, κ, are mentioned in each panel. See Appendix B for details. Data points are plotted after averaging two adjacent channels of the 64-channel spectra on which the fits were performed.
Paper: The Curious Case of Twin Fast Radio Bursts: Evidence for Neutron Star Origin?
Authors: Apurba Bera, Clancy W. James, Adam T. Deller, Keith W. Bannister, Ryan M. Shannon, Danica R. Scott, Kelly Gourdji, Lachlan Marnoch, Marcin Glowacki, Ronald D. Ekers, Stuart D. Ryder, Tyson Dial
Figure caption: PA swing in sub-bursts A (left) and B (right) of FRB 20210912A. The dashed black lines show the best-fit Gaussians to the rate of change of PA. See text for details.
Paper: The Curious Case of Twin Fast Radio Bursts: Evidence for Neutron Star Origin?
Authors: Apurba Bera, Clancy W. James, Adam T. Deller, Keith W. Bannister, Ryan M. Shannon, Danica R. Scott, Kelly Gourdji, Lachlan Marnoch, Marcin Glowacki, Ronald D. Ekers, Stuart D. Ryder, Tyson Dial
Figure caption: PA swing in sub-burst A of FRB 20181112A. The dashed black lines show the best-fit Gaussian to the rate of change of PA.
Paper: Carrington Maps in H I Lyα and Their Relationships with Extreme-ultraviolet and Magnetic-field Maps
Authors: Shuting Li, Li Feng, Beili Ying, Lei Lu, Kaifan Ji, Ying Li, Guanglu Shi, Hui Li, Yu Huang, Weiqun Gan
Figure caption: Top row: examples of the ASO-S/LST/SDI images in log scale. (a) The image with good quality that can be used to construct the Carrington map. (b) The SDI image identified by the keyword QUALITY with a block of missing data. (c) The SDI image identified by the keyword DATAMEAN due to the Earth eclipse with poor signal-to-noise. Middle row: (d) The disk image shown in panel (a) remapped to Carrington heliographic coordinates; the vertical dashed lines indicate the 6° width strip at the Carrington longitude of the central meridian. (e) The example of the weighting function (dashed lines) for successive strips 14 to 17. Each strip is denoted by the border with different colors: blue for strip 14, red for strip 15, yellow for strip 16, and green for strip 17. Bottom row: two versions of the SDI Carrington map. (f) A complete Carrington map for CR 2271; the x-axis indicates Carrington longitudes, and the y-axis indicates the sine of latitudes. (g) An example of the daily updated SDI Carrington map updated at 00:00 UT on 2023 June 10; the red arrow indicates the given time.
Paper: Carrington Maps in H I Lyα and Their Relationships with Extreme-ultraviolet and Magnetic-field Maps
Authors: Shuting Li, Li Feng, Beili Ying, Lei Lu, Kaifan Ji, Ying Li, Guanglu Shi, Hui Li, Yu Huang, Weiqun Gan
Figure caption: (a) The illustration of the CME apex in heliocentric coordinates that is acquired from GCS 3D reconstruction. The Sun is denoted by the black ball, and the red curve corresponds to the disk-area boundary inside the subtended solid angle at the CME apex. (b) The corrected SDI Carrington map for CR 2271 in log scale. The white dashed line corresponds to the region where it should be replaced. The standard SDI Carrington map for CR 2271 is shown in Figure 5(b).
Paper: A NIRCam-dark Galaxy Detected with the MIRI/F1000W Filter in the MIDIS/JADES Hubble Ultra Deep Field
Authors: Pablo G. Pérez-González, Pierluigi Rinaldi, Karina I. Caputi, Javier Álvarez-Márquez, Marianna Annunziatella, Danial Langeroodi, Thibaud Moutard, Leindert Boogaard, Edoardo Iani, Jens Melinder, Luca Costantin, Göran Östlin, Luis Colina, Thomas R. Greve, Gillian Wright, Almudena Alonso-Herrero, Arjan Bik, Sarah E. I. Bosman, Alejandro Crespo Gómez, Daniel Dicken, Andreas Eckart, Macarena García-Marín, Steven Gillman, Manuel Güdel, Thomas Henning, Jens Hjorth, Iris Jermann, Álvaro Labiano, Romain A. Meyer, Florian Peiβker, John P. Pye, Thomas P. Ray, Tuomo Tikkanen, Fabian Walter, Paul P. van der Werf
Figure caption: In the center of the figure, we show an RGB composition of the MIDIS F1000W field. The color images have been built with JADES data in two NIRCam filters, F277W and F356W, and the MIDIS MIRI F1000W filter (all images convolved to the same PSF of MIRI/F1000W). In the background, we show the HUDF JADES data in grayscale. We provide a series of zoomed-in RGB frames that lead to the NIRCam-dark MIRI source, Cerberus, whose image is located in the lower right corner. The NIRCam-dark MIRI source Cerberus is highlighted with a square in that RGB frame. Additionally, we provide postage stamp images (2″ × 2″) of Cerberus in MIRI/F1000W, MIRI/F560W, and NIRCam/F444W (left column), showcasing that Cerberus (marked with an r = 0.″25 green circle) is clearly detected only at 10 μm.
Paper: A NIRCam-dark Galaxy Detected with the MIRI/F1000W Filter in the MIDIS/JADES Hubble Ultra Deep Field
Authors: Pablo G. Pérez-González, Pierluigi Rinaldi, Karina I. Caputi, Javier Álvarez-Márquez, Marianna Annunziatella, Danial Langeroodi, Thibaud Moutard, Leindert Boogaard, Edoardo Iani, Jens Melinder, Luca Costantin, Göran Östlin, Luis Colina, Thomas R. Greve, Gillian Wright, Almudena Alonso-Herrero, Arjan Bik, Sarah E. I. Bosman, Alejandro Crespo Gómez, Daniel Dicken, Andreas Eckart, Macarena García-Marín, Steven Gillman, Manuel Güdel, Thomas Henning, Jens Hjorth, Iris Jermann, Álvaro Labiano, Romain A. Meyer, Florian Peiβker, John P. Pye, Thomas P. Ray, Tuomo Tikkanen, Fabian Walter, Paul P. van der Werf
Figure caption: Detailed analysis of the SED of Cerberus for the main redshift solutions. The symbols are the same as described in Figure 3. We provide best-fitting models provided by different codes that include both stellar and AGN emission. The top left panel shows the best-fitting brown dwarf template from the ATMO2020++ models, for a Y-type dwarf with an effective temperature of ∼300 K at a distance of ∼300 pc. The rest of the panels show results for z = 0.4 (top right), z = 3.5 (bottom left), and z = 15 (bottom right).
Paper: A NIRCam-dark Galaxy Detected with the MIRI/F1000W Filter in the MIDIS/JADES Hubble Ultra Deep Field
Authors: Pablo G. Pérez-González, Pierluigi Rinaldi, Karina I. Caputi, Javier Álvarez-Márquez, Marianna Annunziatella, Danial Langeroodi, Thibaud Moutard, Leindert Boogaard, Edoardo Iani, Jens Melinder, Luca Costantin, Göran Östlin, Luis Colina, Thomas R. Greve, Gillian Wright, Almudena Alonso-Herrero, Arjan Bik, Sarah E. I. Bosman, Alejandro Crespo Gómez, Daniel Dicken, Andreas Eckart, Macarena García-Marín, Steven Gillman, Manuel Güdel, Thomas Henning, Jens Hjorth, Iris Jermann, Álvaro Labiano, Romain A. Meyer, Florian Peiβker, John P. Pye, Thomas P. Ray, Tuomo Tikkanen, Fabian Walter, Paul P. van der Werf
Figure caption: Stacked NIRCam (left panel) and MIRI/F1000W (right panel) images of the region around Cerberus. The stacked NIRCam image was produced from individually PSF-matched LW images. Note that the spurious pixels in the F460M image (see text for details) are removed in the median-stacking procedure. The angular sizes of the images and zoomed-in inset are 3″ × 3″ and 0.″6 × 0.″6, respectively. The red (blue) circle shows the location of the detected source in the NIRCAM stack (F1000W) and has a radius of 0.″2. The green filled circle shows the resolution of the F1000W image (with a diameter of 0.″328). In the zoomed insets, we also show the centroid positions with the blue and red crosses, corresponding to the F1000W image and the NIRCam stack, respectively.
Paper: A NIRCam-dark Galaxy Detected with the MIRI/F1000W Filter in the MIDIS/JADES Hubble Ultra Deep Field
Authors: Pablo G. Pérez-González, Pierluigi Rinaldi, Karina I. Caputi, Javier Álvarez-Márquez, Marianna Annunziatella, Danial Langeroodi, Thibaud Moutard, Leindert Boogaard, Edoardo Iani, Jens Melinder, Luca Costantin, Göran Östlin, Luis Colina, Thomas R. Greve, Gillian Wright, Almudena Alonso-Herrero, Arjan Bik, Sarah E. I. Bosman, Alejandro Crespo Gómez, Daniel Dicken, Andreas Eckart, Macarena García-Marín, Steven Gillman, Manuel Güdel, Thomas Henning, Jens Hjorth, Iris Jermann, Álvaro Labiano, Romain A. Meyer, Florian Peiβker, John P. Pye, Thomas P. Ray, Tuomo Tikkanen, Fabian Walter, Paul P. van der Werf
Figure caption: Photometric redshift probability distribution functions of Cerberus. All distributions are normalized to unity at the peak. We show the main solutions and also secondary solutions at z < 10 and z > 10. Different codes were used in the SED analysis, described in Appendix.
Paper: Class Symbolic Regression: Gotta Fit ’Em All
Authors: Wassim Tenachi, Rodrigo Ibata, Thibaut L. François, Foivos I. Diakogiannis
Figure caption: Comparison of exact symbolic recovery rates and rate of accurate expressions (having R 2 > 0.999) between Class SR and standard SR on our Class SR challenges using an SRBench-style benchmarking pipeline (La Cava et al. 2021). This figure demonstrates the enhanced effectiveness of Class SR in identifying common underlying functions across multiple data sets with varying scale parameters, resulting in a higher success rate compared to the traditional SR method exploiting only one data set at a time—especially in the presence of noise.
Paper: Class Symbolic Regression: Gotta Fit ’Em All
Authors: Wassim Tenachi, Rodrigo Ibata, Thibaut L. François, Foivos I. Diakogiannis
Figure caption: Class symbolic regression framework sketch: searching for a unique functional form simultaneously fitting multiple data sets. The process starts at the left-hand side; a batch of trial class analytical expressions are generated using our Φ-SO framework (Tenachi et al. 2023a). The free parameters appearing in those expressions are then optimized in a data set–specific manner i.e., allowing each data set to have its own unique associated values for each parameter. The neural network used to generate the trial expressions is then reinforced based on the fit quality of the trial symbolic functions. This process is repeated until convergence.
Paper: Class Symbolic Regression: Gotta Fit ’Em All
Authors: Wassim Tenachi, Rodrigo Ibata, Thibaut L. François, Foivos I. Diakogiannis
Figure caption: This figure presents the exact symbolic recovery rate and median R 2 achieved by our Class SR algorithm in the task of recovering an NFW dark matter halo model (Navarro et al. 1997) from synthetic data sets of stellar stream positions and velocities. The performance metrics are displayed as functions of noise levels and the number of realizations exploited. The edge case, in which a single realization is used, corresponds to the conditions of traditional SR. The results distinctly demonstrate that Class SR substantially outperforms traditional SR, particularly in noisy environments.
Paper: Class Symbolic Regression: Gotta Fit ’Em All
Authors: Wassim Tenachi, Rodrigo Ibata, Thibaut L. François, Foivos I. Diakogiannis
Figure caption: Synthetic stellar stream data utilized by our algorithm to recover the Galactic potential. The left and middle panels display the spatial positions of stream members relative to the Milky Way, while the right panel illustrates the kinetic energy of these members as a function of their radial distance from the Galactic center.
Paper: Carrington Maps in H I Lyα and Their Relationships with Extreme-ultraviolet and Magnetic-field Maps
Authors: Shuting Li, Li Feng, Beili Ying, Lei Lu, Kaifan Ji, Ying Li, Guanglu Shi, Hui Li, Yu Huang, Weiqun Gan
Figure caption: Full-disk images and the scatterplot of our data set with fitting results. (a) The radiometrically calibrated image of the pure He II line at 30.378 nm. (b) The original image from SDI observation. (c) The resampled SDI image coaligned with AIA data. The colored contours denote different regions on the solar disk, the cyan contours correspond to filaments, the red contour indicates the flare region, the yellow lines are the active regions, and the dark purple lines denote the off-limb prominences. (d) The 2D scatterplot of the SDI 121.6 nm and AIA 30.4 nm intensities for different features. The color codes are the same as in panel (c). The gray filled circles correspond to the quiet-Sun data points. The solid line represents the fitting to the data points with C 1 = 1041.95, C 2 = 0.9443, and C 3 = 0.00359. The dashed line shows the fit from Gordino et al. (2022), and the dotted–dashed line indicates the fit from Auchère (2005).
Paper: Carrington Maps in H I Lyα and Their Relationships with Extreme-ultraviolet and Magnetic-field Maps
Authors: Shuting Li, Li Feng, Beili Ying, Lei Lu, Kaifan Ji, Ying Li, Guanglu Shi, Hui Li, Yu Huang, Weiqun Gan
Figure caption: (a) The magnetic field synoptic map from GONG. The black contours are overlapped to show the magnetic field strength of 100, 150, and 200 Gauss; the red contours are the same magnitude but have a negative value. (b) The SDI Carrington map in units of erg per second per centimeter square per steradian in log scale; the overlapped contours indicate the locations of the positive and negative magnetic fluxes on the disk shown in (a).
Paper: Carrington Maps in H I Lyα and Their Relationships with Extreme-ultraviolet and Magnetic-field Maps
Authors: Shuting Li, Li Feng, Beili Ying, Lei Lu, Kaifan Ji, Ying Li, Guanglu Shi, Hui Li, Yu Huang, Weiqun Gan
Figure caption: (a) AIA Carrington map in 30.4 nm for CR 2271. (b) SDI Carrington map in Lyα for CR 2271. (c) Synthetic Lyα Carrington map from the AIA Carrington map by using the relationship given in Section 4.1. (d) The difference distribution between the synthetic Carrington map and the SDI Carrington map, in linear scale. The Carrington maps (a)–(c) are in units of erg per second per centimeter square per steradian and in log scale.
Paper: From Seeds to Supermassive Black Holes: Capture, Growth, Migration, and Pairing in Dense Protobulge Environments
Authors: Yanlong Shi, Kyle Kremer, Philip F. Hopkins
Figure caption: BH capture, migration, and growth as subclusters merge. Left: trajectories of the centers of mass of the two subclusters (1, 2; solid), which capture the two BHs (1, 2; dashed) from Figure 1. The BHs are “captured” (become bound to the subcluster) at the times labeled, well before they reach the center, and are carried to the center by the merging subclusters. Minor subclusters merged into these two massive clusters are tracked with gray lines. Top right: mass evolution of the subclusters and BHs. Clusters acquire mass initially through star formation and then hierarchical merging, which completes (and the system relaxes) by ∼1 Myr. The BHs grow in early “jumps” as they accrete clumps near their subcluster centers and then at a steady rate ∼1–5 M ⊙ yr−1 after ∼0.7 Myr from the nuclear disk. Bottom right: boundedness/sinking of each BH in its subcluster. We show the spatial (∣ r  rel∣; solid) and velocity (∣ v  rel∣; dashed) separation between the BH and its subcluster center of mass, normalized by the subcluster half-mass radius r h or escape velocity ﹩\sqrt{-2{{\rm{\Phi }}}_{{\rm{c}}}({{\boldsymbol{r}}}_{\mathrm{rel}})}﹩. The BHs sink and become more confined as their subclusters grow and merge.
Paper: From Seeds to Supermassive Black Holes: Capture, Growth, Migration, and Pairing in Dense Protobulge Environments
Authors: Yanlong Shi, Kyle Kremer, Philip F. Hopkins
Figure caption: Dynamics and magnetic field of the disk. Upper left: surface/column density, mass accretion rate, and magnetic Toomre Q mag profiles of the disk (measured in cylindrical annuli). We also plot the predicted surface density Σ(R) for the analytic hypermagnetized disk models in Hopkins et al. (2024c), assuming an accretion rate ﹩\dot{M}/{\varpi }_{\nu }=30\,{M}_{\odot }\,{\mathrm{yr}}^{-1}﹩. Lower left: mean rotation velocity v  ϕ  of the gas measured from the simulation (with the gray band representing the standard deviation), and the total circular velocity ﹩\equiv \sqrt{G\,{M}_{\mathrm{tot}}(\lt R)/R}﹩ with the contribution ﹩\equiv \sqrt{G\,{M}_{i}(\lt R)/R}﹩ the mass of stars, BHs, and gas. Upper right: average radial and azimuthal velocities (dashed if negative) of the gas in the disk and Alfvén speed (v A), thermal sound speed (c s), and rms turbulent velocities (v turb). Lower right: strength of the mean radial, toroidal, and poloidal magnetic field (dashed if negative). The overall magnetic field strength is in agreement with the flux-freezing assumption (∣ B ∣ ∝ ρ 2/3; dotted).
Paper: From Seeds to Supermassive Black Holes: Capture, Growth, Migration, and Pairing in Dense Protobulge Environments
Authors: Yanlong Shi, Kyle Kremer, Philip F. Hopkins
Figure caption: Visualization of the simulation. We show the gas morphology (column density in logarithmic scales) and positions of star particles (colored dots; only a subset is displayed for esthetic purposes) and two selected BHs (black stars) at different stages of the simulation. Panel (a): early star formation (t ≪ t ff), where seed BHs wander in the GMC. Panel (b): hierarchical cluster assembly and mergers (t ∼ t ff), where bursty star formation happens but the GMC is bound due to strong self-gravity. Massive subclusters form, and one of the BHs is “captured” by (gravitationally bound to) a cluster (red dots in the inserted zoom-in panel, where the radius of the red circle equals five half-mass radii of the cluster). Panel (c): protobulge formation and steady BH accretion (t ≳ 2 t ff), where subclusters merge into the final massive cluster, and the seed BH captured by the subcluster is migrated to the center. The inserted zoom-in panel shows the gas morphology around the BHs, which suggests convergent inflow and disk structure.
Paper: From Seeds to Supermassive Black Holes: Capture, Growth, Migration, and Pairing in Dense Protobulge Environments
Authors: Yanlong Shi, Kyle Kremer, Philip F. Hopkins
Figure caption: Illustration of the scenario of seed BH capture, growth, migration, and pairing in the star-forming GMC complex. The evolution of the star-forming complex is largely determined by the surface density, while low-surface-density clouds are expelled by stellar feedback, halting possible seed BH accretion (upper left → lower left). In high-surface-density clouds, seed BHs may undergo steps (a)–(e), corresponding to the qualitative trend of star formation and BH mass growth (lower middle panel; also see Figure 2). Image credits—M42 (upper left panel): NASA, ESA, M. Robberto (Space Telescope Science Institute/ESA) and the Hubble Space Telescope Orion Treasury Project Team; M60-UCD1 (panel (e)): NASA, ESA, and the Hubble Heritage (STScI/AURA).
Paper: From Seeds to Supermassive Black Holes: Capture, Growth, Migration, and Pairing in Dense Protobulge Environments
Authors: Yanlong Shi, Kyle Kremer, Philip F. Hopkins
Figure caption: Magnetic field lines (near the midplane of each box) and gas morphology (logarithm of the column density) at the late stage of the simulation. The main panel suggests that the large-scale magnetic field is advected to smaller scales due to gravitational collapse throughout the simulation. The inserted zoom-in panels focus on the disk structure, adapted to face-on (left panel) and edge-on (right panel) views. The face-on view shows a dominant toroidal magnetic field spiraling inward counterclockwise, while the edge-on view shows the (weaker) poloidal magnetic field lines threading through the disk structure.
Paper: A Larger Sample Confirms Small Planets around Hot Stars Are Misaligned 
Authors: Emma M. Louden, Songhu Wang, Joshua N. Winn, Erik A. Petigura, Howard Isaacson, Luke Handley, Samuel W. Yee, Corey Beard, Joseph M. Akana Murphy, Gregory Laughlin
Figure caption: Projected rotation velocity vs. effective temperature. The planet hosts (magenta) have slightly higher mean ﹩v\sin i﹩ than the control stars (navy) below 6250 K, in agreement with Louden et al. (2021) and indicating a tendency for spin–orbit alignment. The stars are binned in 50 K intervals, and the diamonds mark the binned values of ﹩v\sin i﹩. The bottom panel shows the ratio of ﹩v\sin i﹩ of the planet hosts to the control stars for each bin with the requisite uncertainties. The dashed line shows the mean value of the ratio for stars below 6300 K. Every bin hotter than 6350 K is considerably below the value for cool stars, except for the hottest bin, which has a large error bar due to high scatter. The error bar for the final bin is calculated by using the typical scatter in neighboring bins due to limited points in this bin.
Paper: A Larger Sample Confirms Small Planets around Hot Stars Are Misaligned 
Authors: Emma M. Louden, Songhu Wang, Joshua N. Winn, Erik A. Petigura, Howard Isaacson, Luke Handley, Samuel W. Yee, Corey Beard, Joseph M. Akana Murphy, Gregory Laughlin
Figure caption: Histogram of the summed deviation statistic (S) over 100,000 simulated trials. The vertical line represents the observed value S obs = 10.41 in the real data. The histogram illustrates the distribution of S values across the simulated data sets, comparing planet-hosting and control stars below 6250 K. The extremely low occurrence of simulations exceeding the observed S obs value (35 in this case) indicates a statistically significant difference between the two groups, with a calculated p-value of 0.00035. This result strongly suggests that the observed differences in ﹩v\sin i﹩ distributions are not due to random chance. S is similar to a χ 2 statistic; see Equation (1).
Paper: A Larger Sample Confirms Small Planets around Hot Stars Are Misaligned 
Authors: Emma M. Louden, Songhu Wang, Joshua N. Winn, Erik A. Petigura, Howard Isaacson, Luke Handley, Samuel W. Yee, Corey Beard, Joseph M. Akana Murphy, Gregory Laughlin
Figure caption: Planetary properties for the combined sample used for analysis and probability density distribution split by planet radius or period. Left: planetary radius and orbital period for all the known transiting planets associated with the 153 planet hosts in Louden et al. (2021) and the 20 planet hosts in the 2022 sample are shown on top of the full KOI sample. The planets outlined in black have hosts with T eff > 6250 K. Right: we divided the planets into subsets based on radius and period and fit the subsamples. The dashed lines on the left panel show the locations of the cuts over the planet sample in period–radius space. After performing each of the two cuts, the resulting distributions of ﹩\langle \sin i\rangle ﹩ are labeled according to the half they represent.
Paper: A Larger Sample Confirms Small Planets around Hot Stars Are Misaligned 
Authors: Emma M. Louden, Songhu Wang, Joshua N. Winn, Erik A. Petigura, Howard Isaacson, Luke Handley, Samuel W. Yee, Corey Beard, Joseph M. Akana Murphy, Gregory Laughlin
Figure caption: Sources of the obliquity distribution and observational trends. We reproduce selected columns of Table 3 of Albrecht et al. (2022). Blue coloring indicates that the prediction is tentatively consistent with our data. Red coloring indicates that the observational data do not support that prediction.