adsabs/AstroCLIMB huggingface dataset:
Paper: Near-Sun In Situ and Remote-sensing Observations of a Coronal Mass Ejection and its Effect on the Heliospheric Current Sheet
Authors: O. M. Romeo, C. R. Braga, S. T. Badman, D. E. Larson, M. L. Stevens, J. Huang, T. Phan, A. Rahmati, R. Livi, S. T. Alnussirat, P. L. Whittlesey, A. Szabo, K. G. Klein, T. Niembro-Hernandez, K. Paulson, J. L. Verniero, D. Lario, N. E. Raouafi, T. Ervin, J. Kasper, M. Pulupa, S. D. Bale, M. G. Linton
Figure caption: ADAPT-GONG magnetograms observed on (a) 2022 September 1, prior to the CME eruption, and (b) 2022 September 15, after the CME and rotation of the source active region into view. The red and blue map shadings indicate positive and negative radial photospheric magnetic fields, respectively. The black curve represents the nominal HCS obtained through a potential field source surface extrapolation for a given magnetogram. The trajectories of PSP and SOLO are ballistically mapped down to the same altitude as the HCS and colorized according to the measured polarity in space. The black and white squares indicate the initial and final positions of each orbit, respectively, with arrows depicting the orbital direction. The in situ data in panel (a) show a two-sector structure of the magnetic field over the course of the Carrington rotation prior to the CME. Four polarity sectors emerge after the CME, where one of the positive sectors is aligned with the location of the source active region (AR 13102) near ﹩({\sin }({\theta }_{\mathrm{Carr}}),{\phi }_{\mathrm{Carr}})\cong (-0\buildrel{\circ}\over{.} 5,300^\circ )﹩, indicating a large-scale reconfiguration of the HCS.
Paper: Near-Sun In Situ and Remote-sensing Observations of a Coronal Mass Ejection and its Effect on the Heliospheric Current Sheet
Authors: O. M. Romeo, C. R. Braga, S. T. Badman, D. E. Larson, M. L. Stevens, J. Huang, T. Phan, A. Rahmati, R. Livi, S. T. Alnussirat, P. L. Whittlesey, A. Szabo, K. G. Klein, T. Niembro-Hernandez, K. Paulson, J. L. Verniero, D. Lario, N. E. Raouafi, T. Ervin, J. Kasper, M. Pulupa, S. D. Bale, M. G. Linton
Figure caption: Remote-sensing observations of the CME on 2022 September 5 near time t 1 when PSP encountered a fast-forward shock. (a) Running difference COR2 image from STA at 17:26 UT, where the location of PSP is represented by the white asterisk. An expanding front observed by COR2 is outlined by a red dashed curve. (b) Combined FOV of WISPR-I (left) and WISPR-O (right) at 17:30 UT, processed using the L3 algorithm and overlaid on a grid of heliocentric longitude and latitude. The Sun is shown to scale at the origin, with an overlaid Carrington map from the Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI). The orbital plane of PSP is represented by the blue line. The corresponding spacecraft speed, distance from the Sun, Carrington longitude, and FOV range at 0° latitude for this time are reported near the bottom left.
Paper: Near-Sun In Situ and Remote-sensing Observations of a Coronal Mass Ejection and its Effect on the Heliospheric Current Sheet
Authors: O. M. Romeo, C. R. Braga, S. T. Badman, D. E. Larson, M. L. Stevens, J. Huang, T. Phan, A. Rahmati, R. Livi, S. T. Alnussirat, P. L. Whittlesey, A. Szabo, K. G. Klein, T. Niembro-Hernandez, K. Paulson, J. L. Verniero, D. Lario, N. E. Raouafi, T. Ervin, J. Kasper, M. Pulupa, S. D. Bale, M. G. Linton
Figure caption: Time series from 22-09-05/19:52 to 22-09-06/05:00 UTC as observed by PSP. (a) QTN (black) and core (red) electron density, (b) RTN proton velocity with magnitude (black), (c) proton (blue), alpha particle (green), core electron (red), and expected proton (magenta) temperature, (d) Alfvén Mach number, (e) proton (blue) and electron (red) plasma β, (f) magnetic field elevation angle, (g) magnetic field azimuthal angle, (h) RTN magnetic field with magnitude (black), and (i) normalized ePADs at 433 eV. The magnetic field angles have been smoothed using a moving average of 5.5 minutes. The heliocentric distance of PSP in R  S  is shown at the bottom along the time axis. The vertical dashed lines represent different time intervals, corresponding to the intervals in Table 1, from t 4a  to t 5b .
Paper: Near-Sun In Situ and Remote-sensing Observations of a Coronal Mass Ejection and its Effect on the Heliospheric Current Sheet
Authors: O. M. Romeo, C. R. Braga, S. T. Badman, D. E. Larson, M. L. Stevens, J. Huang, T. Phan, A. Rahmati, R. Livi, S. T. Alnussirat, P. L. Whittlesey, A. Szabo, K. G. Klein, T. Niembro-Hernandez, K. Paulson, J. L. Verniero, D. Lario, N. E. Raouafi, T. Ervin, J. Kasper, M. Pulupa, S. D. Bale, M. G. Linton
Figure caption: Time series from 22-09-06/17:20 to 22-09-06/17:50 UTC as observed by PSP during the second magnetic inversion line crossing. (a) QTN (black) and core (red) electron density, (b) RTN proton velocity with magnitude (black), (c) proton (blue), alpha particle (green), core electron (red), and expected proton (magenta) temperature, (d) alpha particle to proton number density ratio, (e) Alfvén Mach number, (f) proton (blue) and electron (red) plasma β, (g) RTN magnetic field with magnitude (black), and (i) normalized ePADs at 433 eV. The heliocentric distance of PSP in R  S  is shown at the bottom along the time axis. The vertical dashed lines represent the t 7a  and t 7b  time intervals, corresponding to Table 1.
Paper: Near-Sun In Situ and Remote-sensing Observations of a Coronal Mass Ejection and its Effect on the Heliospheric Current Sheet
Authors: O. M. Romeo, C. R. Braga, S. T. Badman, D. E. Larson, M. L. Stevens, J. Huang, T. Phan, A. Rahmati, R. Livi, S. T. Alnussirat, P. L. Whittlesey, A. Szabo, K. G. Klein, T. Niembro-Hernandez, K. Paulson, J. L. Verniero, D. Lario, N. E. Raouafi, T. Ervin, J. Kasper, M. Pulupa, S. D. Bale, M. G. Linton
Figure caption: Time series from 22-09-06/08:00 to 22-09-07/15:00 UTC as observed by PSP. (a) QTN (black) and core (red) electron density, (b) RTN proton velocity with magnitude (black), (c) proton (blue), alpha particle (green), core electron (red), and expected proton (magenta) temperature, (d) alpha particle to proton number density ratio, (e) Alfvén Mach number, (f) proton (blue) and electron (red) plasma β, (g) RTN magnetic field with magnitude (black), and (i) normalized ePADs at 433 eV. The heliocentric distance of PSP in R  S  is shown at the bottom along the time axis. The vertical dashed lines represent different time intervals, corresponding to the intervals in Table 1, from t 6 to t 9.
Paper: Near-Sun In Situ and Remote-sensing Observations of a Coronal Mass Ejection and its Effect on the Heliospheric Current Sheet
Authors: O. M. Romeo, C. R. Braga, S. T. Badman, D. E. Larson, M. L. Stevens, J. Huang, T. Phan, A. Rahmati, R. Livi, S. T. Alnussirat, P. L. Whittlesey, A. Szabo, K. G. Klein, T. Niembro-Hernandez, K. Paulson, J. L. Verniero, D. Lario, N. E. Raouafi, T. Ervin, J. Kasper, M. Pulupa, S. D. Bale, M. G. Linton
Figure caption: Time series from 17:25 to 17:45 UTC on 2022 September 5, showing the (a) RTN magnetic field vector with magnitude (black). The normalized ePADs are shown for energies (b) 2072 eV, (c) 1401 eV, (d) 947 eV, (e) 779 eV, (f) 640 eV, (g) 526 eV, (h) 433 eV, and (i) 241 eV. The time intervals t 1 and t 2a  are designated by the vertical dashed lines. The ePADs above 750 eV exhibit a strong peak near 90°, while electrons below 300 eV show a distinct strahl flowing antiparallel to the magnetic field.
Paper: Constraining Cosmology with Machine Learning and Galaxy Clustering: The CAMELS-SAM Suite
Authors: Lucia A. Perez, Shy Genel, Francisco Villaescusa-Navarro, Rachel S. Somerville, Austen Gabrielpillai, Daniel Anglés-Alcázar, Benjamin D. Wandelt, L. Y. Aaron Yung
Figure caption: Verification of our fiducial model and setup of the SC-SAM at z = 0. The five CAMELS-SAM “cosmic variance” (CV) galaxy catalogs (red dotted lines) are compared against relevant z ∼ 0 observations (light green shapes) and the default SC-SAM run through IllustrisTNG300-1 (dark gray solid line; N = 25003) and IllustrisTNG300-2 (light gray solid line; N = 12503) dark-matter-only volumes. Top row: stellar mass function (left), stellar mass–halo mass relationship (right). Bottom row: cold gas fraction vs. stellar mass for disk-dominated galaxies (left), stellar metallicity vs. stellar mass (middle), and black hole mass vs. bulge mass (right). The observational data (green) used for the calibration of the SC-SAM are detailed in Somerville et al. (2015) and Yung et al. (2019a). The CV simulations were each generated with a different random initial seed, and all other parameters were set to the fiducial values of {ΩM, σ 8, ﹩{A}_{\mathrm{SN}1}﹩, ﹩{A}_{\mathrm{SN}2}﹩, A AGN} = {0.3, 0.8, 1, 0, 1,}.
Paper: Constraining Cosmology with Machine Learning and Galaxy Clustering: The CAMELS-SAM Suite
Authors: Lucia A. Perez, Shy Genel, Francisco Villaescusa-Navarro, Rachel S. Somerville, Austen Gabrielpillai, Daniel Anglés-Alcázar, Benjamin D. Wandelt, L. Y. Aaron Yung
Figure caption: Our best cosmological constraints using a stellar-mass-selected sample and the LFI loss function. Here, we selected SAM galaxies with stellar mass greater than 109 M ⊙, downsampled to a density of 0.005 h 3 cMpc−3 at z = {0.0, 0.1, 0.5, 1.0}.
Paper: Constraining Cosmology with Machine Learning and Galaxy Clustering: The CAMELS-SAM Suite
Authors: Lucia A. Perez, Shy Genel, Francisco Villaescusa-Navarro, Rachel S. Somerville, Austen Gabrielpillai, Daniel Anglés-Alcázar, Benjamin D. Wandelt, L. Y. Aaron Yung
Figure caption: Key galaxy relationships for the 1P pair of A AGN = 0.25 × κ radio (cyan) and A AGN = 4.0 × κ radio (magenta). See Figure 9 for explanation of plotted quantities.
Paper: Constraining Cosmology with Machine Learning and Galaxy Clustering: The CAMELS-SAM Suite
Authors: Lucia A. Perez, Shy Genel, Francisco Villaescusa-Navarro, Rachel S. Somerville, Austen Gabrielpillai, Daniel Anglés-Alcázar, Benjamin D. Wandelt, L. Y. Aaron Yung
Figure caption: Comparing how well a neural network trained on the clustering of a dark matter halo mass-selected sample can predict cosmological parameters for a stellar-mass-selected sample. This network was trained with “all” clustering at z = {0.0, 0.1, 0.5, 1.0} for dark matter halos with dark matter halo mass greater than 2 × 1011 M ⊙, downsampled to a density of 0.005 h 3 cMpc−3. Blue circles show the results of giving the network the test set for the same type of clustering with which it was trained and validated. Red stars show the results from instead evaluating the best-performing model on the test set of simulations using the clustering of SAM galaxies of stellar mass greater than 1 × 109 M ⊙, downsampled to the same density of 0.005 h 3 cMpc−3.
Paper: Constraining Cosmology with Machine Learning and Galaxy Clustering: The CAMELS-SAM Suite
Authors: Lucia A. Perez, Shy Genel, Francisco Villaescusa-Navarro, Rachel S. Somerville, Austen Gabrielpillai, Daniel Anglés-Alcázar, Benjamin D. Wandelt, L. Y. Aaron Yung
Figure caption: The χ  i  distribution across the test set for the top five best-performing networks (each in a unique color). The dotted gray curve is a Gaussian whose center is at zero (black vertical line) and has a variance of one.
Paper: Constraining Cosmology with Machine Learning and Galaxy Clustering: The CAMELS-SAM Suite
Authors: Lucia A. Perez, Shy Genel, Francisco Villaescusa-Navarro, Rachel S. Somerville, Austen Gabrielpillai, Daniel Anglés-Alcázar, Benjamin D. Wandelt, L. Y. Aaron Yung
Figure caption: Similar to Figures 3 and 7, but instead showing the constraints obtained when different clustering statistics are used separately (see Section 6, Tables 8 and 9, and Appendix D). Dotted lines connect the same galaxy selection scenarios for ease of comparison. The dashed–dotted lines indicate the mean of the prior, where constraints are not informative.
Paper: Constraining Cosmology with Machine Learning and Galaxy Clustering: The CAMELS-SAM Suite
Authors: Lucia A. Perez, Shy Genel, Francisco Villaescusa-Navarro, Rachel S. Somerville, Austen Gabrielpillai, Daniel Anglés-Alcázar, Benjamin D. Wandelt, L. Y. Aaron Yung
Figure caption: Similar to Figure 3, but instead summarizing the constraints of Section 4.3, Table 6, and Appendix D, illustrating the effects of using clustering constraints at a single redshift vs. four redshifts combined (All).
Paper: Constraining Cosmology with Machine Learning and Galaxy Clustering: The CAMELS-SAM Suite
Authors: Lucia A. Perez, Shy Genel, Francisco Villaescusa-Navarro, Rachel S. Somerville, Austen Gabrielpillai, Daniel Anglés-Alcázar, Benjamin D. Wandelt, L. Y. Aaron Yung
Figure caption: Key galaxy relationships for the 1P pair of ﹩{A}_{\mathrm{SN}1}=0.25\times {\epsilon }_{\mathrm{SN}0}﹩ (cyan) and ﹩{A}_{\mathrm{SN}1}=4.0\times {\epsilon }_{\mathrm{SN}0}﹩ (magenta). See Figure 9 for explanation of plotted quantities.
Paper: Constraining Cosmology with Machine Learning and Galaxy Clustering: The CAMELS-SAM Suite
Authors: Lucia A. Perez, Shy Genel, Francisco Villaescusa-Navarro, Rachel S. Somerville, Austen Gabrielpillai, Daniel Anglés-Alcázar, Benjamin D. Wandelt, L. Y. Aaron Yung
Figure caption: Key galaxy relationships for the 1P pair of ﹩{A}_{\mathrm{SN}2}=-2+{\alpha }_{\mathrm{rh}}﹩ (cyan) and ﹩{A}_{\mathrm{SN}2}=+2+{\alpha }_{\mathrm{rh}}﹩ (magenta). See Figure 9 for explanation of plotted quantities.
Paper: Rocky Planet or Water World? Observability of Low-density Lava World Atmospheres
Authors: Anjali A. A. Piette, Peter Gao, Kara Brugman, Anat Shahar, Tim Lichtenberg, Francesca Miozzi, Peter Driscoll
Figure caption: Left: a mass–radius (M–R) diagram showing exoplanets with masses and radii known to within 25%. Planets in the blue shaded region are less dense than an Earth-like interior composition but do not require a hydrogen-rich atmosphere to explain their radii (low-density super-Earths). The upper boundary of this region is blurred to represent the temperature dependence of mass–radius curves for water-rich planets. Lines show M–R relations for an Earth-like (solid gray), 100% MgSiO3 (solid purple), and 100% H2O composition (∼300 K, dashed blue) from Madhusudhan et al. (2020). The color scale shows the substellar temperature for each planet. Larger points with error bars show planets with substellar temperatures >1700 K. For clarity, error bars are not shown for the smaller points (substellar temperature <1700 K). Notable targets with high emission spectroscopy metrics (Kempton et al. 2018) are labeled. Mass and radius data are from the NASA Exoplanet Archive. Right: the atmospheric scenarios considered in this work for low-density lava worlds.
Paper: On the Likely Dynamical Origin of GW191109 and Binary Black Hole Mergers with Negative Effective Spin
Authors: Rachel C. Zhang, Giacomo Fragione, Chase Kimball, Vicky Kalogera
Figure caption: Posterior distributions of the effective spin of GW191109 and GW200225_060421 derived from the PEsummary package by Hoy & Raymond (Hoy 2021) using the open data from the LIGO Scientific Collaboration et al. (2023). The probability of a negative effective spin is about 90.6% and 86.7% for GW191109 and GW200225_060421, respectively.
Paper: On the Likely Dynamical Origin of GW191109 and Binary Black Hole Mergers with Negative Effective Spin
Authors: Rachel C. Zhang, Giacomo Fragione, Chase Kimball, Vicky Kalogera
Figure caption: In solid blue, we plot the posterior over the rate of GW191109-like mergers assuming one Poisson-distributed count from a population drawn from the public parameter estimation samples. The dashed blue lines indicate the 90% confidence interval. The dotted green line marks the combined 1G–2G and 2G–2G merger rate, assuming ρ GC = 0.77 Mpc−3, and the shaded green region marks the range of rates bounded by assuming ρ GC = 0.32 and 2.31 Mpc−3.
Paper: On the Likely Dynamical Origin of GW191109 and Binary Black Hole Mergers with Negative Effective Spin
Authors: Rachel C. Zhang, Giacomo Fragione, Chase Kimball, Vicky Kalogera
Figure caption: Cumulative distribution of the final tilts for binaries with the following initial conditions: the mass-loss distribution is simulated by SSE with initial metallicities of 0.01 (see Figure A2), the initial semimajor axis distribution is log-uniform with a range of 10−2–10−1 au, and the initial eccentricity distribution is uniform. Different colors show different kick velocity distributions: σ = 50 (blue), 100 (black), 265 (purple), and 265 km s−1 scaled by momentum conservation (red). The dotted yellow line marks π/2, the tilt angle at which the spin of the post-SN mass would be antialigned with the orbital angular momentum, possibly producing a negative χ eff.
Paper: On the Likely Dynamical Origin of GW191109 and Binary Black Hole Mergers with Negative Effective Spin
Authors: Rachel C. Zhang, Giacomo Fragione, Chase Kimball, Vicky Kalogera
Figure caption: Primary and secondary mass of 1G–2G and 2G–2G BBHs from 148 simulated globular clusters in the models of Kremer et al. (2020). For 1G–2G mergers, we distinguish between 1G BHs born as a result of the collapse of massive stars (blue points) and 1G BHs formed via star collisions (yellow points). We label GW191109's median component masses with a black star, with the contour corresponding to its 90% confidence region in mass space.
Paper: On the Likely Dynamical Origin of GW191109 and Binary Black Hole Mergers with Negative Effective Spin
Authors: Rachel C. Zhang, Giacomo Fragione, Chase Kimball, Vicky Kalogera
Figure caption: Relative mass-loss distribution for an SSE-simulated population of single stars with initial metallicities of 0.01 and final masses within the error bar range of the GW191109 secondary mass.
Paper: On the Likely Dynamical Origin of GW191109 and Binary Black Hole Mergers with Negative Effective Spin
Authors: Rachel C. Zhang, Giacomo Fragione, Chase Kimball, Vicky Kalogera
Figure caption: Distribution of effective spin for 1G–2G and 2G–2G BBHs for component masses consistent with GW191109 and assuming nonspinning 1G BHs. Both distributions are symmetric around zero, with a nonnegligible likelihood of reproducing negative χ eff values.
Paper: On the Likely Dynamical Origin of GW191109 and Binary Black Hole Mergers with Negative Effective Spin
Authors: Rachel C. Zhang, Giacomo Fragione, Chase Kimball, Vicky Kalogera
Figure caption: Relative mass-loss distribution for an SSE-simulated population of single stars with initial metallicities of 0.001 and final masses within the error bar range of the GW191109 secondary mass.
Paper: SN 2020bio: A Double-peaked, H-poor Type IIb Supernova with Evidence of Circumstellar Interaction
Authors: C. Pellegrino, D. Hiramatsu, I. Arcavi, D. A. Howell, K. A. Bostroem, P. J. Brown, J. Burke, N. Elias-Rosa, K. Itagaki, H. Kaneda, C. McCully, M. Modjaz, E. Padilla Gonzalez, T. A. Pritchard, N. Yesmin
Figure caption: Same as Figure 7, but assuming a H-poor envelope composition (κ = 0.20 cm2 g−1). The fits are of comparable quality to those assuming a H-rich composition, but the best-fit parameters are quantitatively different (Table A1).
Paper: SN 2020bio: A Double-peaked, H-poor Type IIb Supernova with Evidence of Circumstellar Interaction
Authors: C. Pellegrino, D. Hiramatsu, I. Arcavi, D. A. Howell, K. A. Bostroem, P. J. Brown, J. Burke, N. Elias-Rosa, K. Itagaki, H. Kaneda, C. McCully, M. Modjaz, E. Padilla Gonzalez, T. A. Pritchard, N. Yesmin
Figure caption: Same as Figure A1, but for the SW17 (n = 3/2) model.
Paper: SN 2020bio: A Double-peaked, H-poor Type IIb Supernova with Evidence of Circumstellar Interaction
Authors: C. Pellegrino, D. Hiramatsu, I. Arcavi, D. A. Howell, K. A. Bostroem, P. J. Brown, J. Burke, N. Elias-Rosa, K. Itagaki, H. Kaneda, C. McCully, M. Modjaz, E. Padilla Gonzalez, T. A. Pritchard, N. Yesmin
Figure caption: Same as Figure A1, but for the SW17 (n = 3) model.
Paper: SN 2020bio: A Double-peaked, H-poor Type IIb Supernova with Evidence of Circumstellar Interaction
Authors: C. Pellegrino, D. Hiramatsu, I. Arcavi, D. A. Howell, K. A. Bostroem, P. J. Brown, J. Burke, N. Elias-Rosa, K. Itagaki, H. Kaneda, C. McCully, M. Modjaz, E. Padilla Gonzalez, T. A. Pritchard, N. Yesmin
Figure caption: Corner plots showing the fitted parameter distributions for the P15 model.
Paper: SN 2020bio: A Double-peaked, H-poor Type IIb Supernova with Evidence of Circumstellar Interaction
Authors: C. Pellegrino, D. Hiramatsu, I. Arcavi, D. A. Howell, K. A. Bostroem, P. J. Brown, J. Burke, N. Elias-Rosa, K. Itagaki, H. Kaneda, C. McCully, M. Modjaz, E. Padilla Gonzalez, T. A. Pritchard, N. Yesmin
Figure caption: Same as Figure A1, but for the P21 model.
Paper: Identification of Galaxy–Galaxy Strong Lens Candidates in the DECam Local Volume Exploration Survey Using Machine Learning
Authors: E. A. Zaborowski, A. Drlica-Wagner, F. Ashmead, J. F. Wu, R. Morgan, C. R. Bom, A. J. Shajib, S. Birrer, W. Cerny, E. J. Buckley-Geer, B. Mutlu-Pakdil, P. S. Ferguson, K. Glazebrook, S. J. Gonzalez Lozano, Y. Gordon, M. Martinez, V. Manwadkar, J. O'Donnell, J. Poh, A. Riley, J. D. Sakowska, L. Santana-Silva, B. X. Santiago, D. Sluse, C. Y. Tan, E. J. Tollerud, A. Verma, J. A. Carballo-Bello, Y. Choi, D. J. James, N. Kuropatkin, C. E. Martínez-Vázquez, D. L. Nidever, J. L. Nilo Castellon, N. E. D. Noël, K. A. G. Olsen, A. B. Pace, S. Mau, B. Yanny, A. Zenteno, T. M. C. Abbott, M. Aguena, O. Alves, F. Andrade-Oliveira, S. Bocquet, D. Brooks, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, F. J. Castander, C. J. Conselice, M. Costanzi, M. E. S. Pereira, J. De Vicente, S. Desai, J. P. Dietrich, P. Doel, S. Everett, I. Ferrero, B. Flaugher, D. Friedel, J. Frieman, J. García-Bellido, D. Gruen, R. A. Gruendl, G. Gutierrez, S. R. Hinton, D. L. Hollowood, K. Honscheid, K. Kuehn, H. Lin, J. L. Marshall, P. Melchior, J. Mena-Fernández, F. Menanteau, R. Miquel, A. Palmese, F. Paz-Chinchón, A. Pieres, A. A. Plazas Malagón, J. Prat, M. Rodriguez-Monroy, A. K. Romer, E. Sanchez, V. Scarpine, I. Sevilla-Noarbe, M. Smith, E. Suchyta, C. To, N. Weaverdyck
Figure caption: Examples of lens candidates from Huang et al. (2020, 2021) that were classified by our network. Images from DELVE DR2, which has a larger overlap with the DECaLS footprint than DELVE DR1 but was not fully searched in this work, are included to gauge model performance. For each image, the score assigned by our network as well as the grade assigned by Huang et al. are shown. Candidates that do not pass the color–magnitude preselection criteria used in this work are outlined in red. Left: Huang candidates that were highly ranked by our network. In general, these candidates show prominent blue arcs that are well separated from the lens. Right: Huang candidates that received a low ranking from our network. These candidates show a combination of close-separation lenses and very far separation lenses, some of which are on the edge of the field of view of our image cutouts. Cutouts are approximately 11.″8 × 11.″8.