adsabs/AstroCLIMB huggingface dataset:
Paper: The Fermi-LAT Lightcurve Repository 
Authors: S. Abdollahi, M. Ajello, L. Baldini, J. Ballet, D. Bastieri, J. Becerra Gonzalez, R. Bellazzini, A. Berretta, E. Bissaldi, R. Bonino, A. Brill, P. Bruel, E. Burns, S. Buson, R. A. Cameron, R. Caputo, P. A. Caraveo, N. Cibrario, S. Ciprini, P. Cristarella Orestano, M. Crnogorcevic, S. Cutini, F. D'Ammando, S. De Gaetano, S. W. Digel, N. Di Lalla, L. Di Venere, A. Domínguez, V. Fallah Ramazani, S. J. Fegan, E. C. Ferrara, A. Fiori, H. Fleischhack, A. Franckowiak, Y. Fukazawa, P. Fusco, V. Gammaldi, F. Gargano, S. Garrappa, C. Gasbarra, D. Gasparrini, N. Giglietto, F. Giordano, M. Giroletti, D. Green, I. A. Grenier, S. Guiriec, M. Gustafsson, E. Hays, D. Horan, X. Hou, G. Jóhannesson, M. Kerr, D. Kocevski, M. Kuss, L. Latronico, J. Li, I. Liodakis, F. Longo, F. Loparco, L. Lorusso, B. Lott, M. N. Lovellette, P. Lubrano, S. Maldera, A. Manfreda, G. Martí-Devesa, M. N. Mazziotta, I. Mereu, M. Meyer, P. F. Michelson, T. Mizuno, M. E. Monzani, A. Morselli, I. V. Moskalenko, M. Negro, N. Omodei, E. Orlando, J. F. Ormes, D. Paneque, G. Panzarini, J. S. Perkins, M. Persic, M. Pesce-Rollins, R. Pillera, T. A. Porter, G. Principe, J. L. Racusin, S. Rainò, R. Rando, B. Rani, M. Razzano, S. Razzaque, A. Reimer, O. Reimer, M. Sánchez-Conde, P. M. Saz Parkinson, Jeff Scargle, L. Scotton, D. Serini, C. Sgrò, E. J. Siskind, G. Spandre, P. Spinelli, D. J. Suson, H. Tajima, D. J. Thompson, D. F. Torres, J. Valverde, T. Venters, Z. Wadiasingh, S. Wagner, K. Wood
Figure caption: Top: counts map for a 3 day time bin with 0 minimum exposure; bottom: exposure map for the same time bin. The white pixels mark the positions of LCR sources. The light blue and magenta circles in the maps highlight the cases of two ROIs lying in a region of the sky with zero and nonflat exposures, respectively. These maps are Mollweide projections of the entire sky in Galactic coordinates, centered at the Galactic Center. Longitudes increase from right to left. The color scales in both maps are linear.
Paper: The Fermi-LAT Lightcurve Repository 
Authors: S. Abdollahi, M. Ajello, L. Baldini, J. Ballet, D. Bastieri, J. Becerra Gonzalez, R. Bellazzini, A. Berretta, E. Bissaldi, R. Bonino, A. Brill, P. Bruel, E. Burns, S. Buson, R. A. Cameron, R. Caputo, P. A. Caraveo, N. Cibrario, S. Ciprini, P. Cristarella Orestano, M. Crnogorcevic, S. Cutini, F. D'Ammando, S. De Gaetano, S. W. Digel, N. Di Lalla, L. Di Venere, A. Domínguez, V. Fallah Ramazani, S. J. Fegan, E. C. Ferrara, A. Fiori, H. Fleischhack, A. Franckowiak, Y. Fukazawa, P. Fusco, V. Gammaldi, F. Gargano, S. Garrappa, C. Gasbarra, D. Gasparrini, N. Giglietto, F. Giordano, M. Giroletti, D. Green, I. A. Grenier, S. Guiriec, M. Gustafsson, E. Hays, D. Horan, X. Hou, G. Jóhannesson, M. Kerr, D. Kocevski, M. Kuss, L. Latronico, J. Li, I. Liodakis, F. Longo, F. Loparco, L. Lorusso, B. Lott, M. N. Lovellette, P. Lubrano, S. Maldera, A. Manfreda, G. Martí-Devesa, M. N. Mazziotta, I. Mereu, M. Meyer, P. F. Michelson, T. Mizuno, M. E. Monzani, A. Morselli, I. V. Moskalenko, M. Negro, N. Omodei, E. Orlando, J. F. Ormes, D. Paneque, G. Panzarini, J. S. Perkins, M. Persic, M. Pesce-Rollins, R. Pillera, T. A. Porter, G. Principe, J. L. Racusin, S. Rainò, R. Rando, B. Rani, M. Razzano, S. Razzaque, A. Reimer, O. Reimer, M. Sánchez-Conde, P. M. Saz Parkinson, Jeff Scargle, L. Scotton, D. Serini, C. Sgrò, E. J. Siskind, G. Spandre, P. Spinelli, D. J. Suson, H. Tajima, D. J. Thompson, D. F. Torres, J. Valverde, T. Venters, Z. Wadiasingh, S. Wagner, K. Wood
Figure caption: Top: histogram of the source types included in the LCR population, defined as having a variability index above 21.67, corresponding to <1% chance of steady emission. Center and bottom: the populations of sources included in the LCR (empty markers). In gray we report the 4FGL-DR2 population not included in the LCR as reference. The energy range of integration is 0.1−100 GeV.
Paper: The Fermi-LAT Lightcurve Repository 
Authors: S. Abdollahi, M. Ajello, L. Baldini, J. Ballet, D. Bastieri, J. Becerra Gonzalez, R. Bellazzini, A. Berretta, E. Bissaldi, R. Bonino, A. Brill, P. Bruel, E. Burns, S. Buson, R. A. Cameron, R. Caputo, P. A. Caraveo, N. Cibrario, S. Ciprini, P. Cristarella Orestano, M. Crnogorcevic, S. Cutini, F. D'Ammando, S. De Gaetano, S. W. Digel, N. Di Lalla, L. Di Venere, A. Domínguez, V. Fallah Ramazani, S. J. Fegan, E. C. Ferrara, A. Fiori, H. Fleischhack, A. Franckowiak, Y. Fukazawa, P. Fusco, V. Gammaldi, F. Gargano, S. Garrappa, C. Gasbarra, D. Gasparrini, N. Giglietto, F. Giordano, M. Giroletti, D. Green, I. A. Grenier, S. Guiriec, M. Gustafsson, E. Hays, D. Horan, X. Hou, G. Jóhannesson, M. Kerr, D. Kocevski, M. Kuss, L. Latronico, J. Li, I. Liodakis, F. Longo, F. Loparco, L. Lorusso, B. Lott, M. N. Lovellette, P. Lubrano, S. Maldera, A. Manfreda, G. Martí-Devesa, M. N. Mazziotta, I. Mereu, M. Meyer, P. F. Michelson, T. Mizuno, M. E. Monzani, A. Morselli, I. V. Moskalenko, M. Negro, N. Omodei, E. Orlando, J. F. Ormes, D. Paneque, G. Panzarini, J. S. Perkins, M. Persic, M. Pesce-Rollins, R. Pillera, T. A. Porter, G. Principe, J. L. Racusin, S. Rainò, R. Rando, B. Rani, M. Razzano, S. Razzaque, A. Reimer, O. Reimer, M. Sánchez-Conde, P. M. Saz Parkinson, Jeff Scargle, L. Scotton, D. Serini, C. Sgrò, E. J. Siskind, G. Spandre, P. Spinelli, D. J. Suson, H. Tajima, D. J. Thompson, D. F. Torres, J. Valverde, T. Venters, Z. Wadiasingh, S. Wagner, K. Wood
Figure caption: Comparison of the fluxes [ph cm−2 s−1] in time bins obtained with the fitting pipeline keeping the spectral index fixed vs. letting the spectral index be free. The empty circles indicate results from analyses that did not converge, i.e., MINUIT Return Code q ≠ 0. MINUIT (James 1994) is the optimizer adopted in the likelihood analysis. The plot shows the fluxes measured for the quasar Ton 599. In this case, the fit for the highest-flux point (with TS ∼ 4) converged when the spectral index was set free, but did not converge when the spectral index was fixed.
Paper: The Fermi-LAT Lightcurve Repository 
Authors: S. Abdollahi, M. Ajello, L. Baldini, J. Ballet, D. Bastieri, J. Becerra Gonzalez, R. Bellazzini, A. Berretta, E. Bissaldi, R. Bonino, A. Brill, P. Bruel, E. Burns, S. Buson, R. A. Cameron, R. Caputo, P. A. Caraveo, N. Cibrario, S. Ciprini, P. Cristarella Orestano, M. Crnogorcevic, S. Cutini, F. D'Ammando, S. De Gaetano, S. W. Digel, N. Di Lalla, L. Di Venere, A. Domínguez, V. Fallah Ramazani, S. J. Fegan, E. C. Ferrara, A. Fiori, H. Fleischhack, A. Franckowiak, Y. Fukazawa, P. Fusco, V. Gammaldi, F. Gargano, S. Garrappa, C. Gasbarra, D. Gasparrini, N. Giglietto, F. Giordano, M. Giroletti, D. Green, I. A. Grenier, S. Guiriec, M. Gustafsson, E. Hays, D. Horan, X. Hou, G. Jóhannesson, M. Kerr, D. Kocevski, M. Kuss, L. Latronico, J. Li, I. Liodakis, F. Longo, F. Loparco, L. Lorusso, B. Lott, M. N. Lovellette, P. Lubrano, S. Maldera, A. Manfreda, G. Martí-Devesa, M. N. Mazziotta, I. Mereu, M. Meyer, P. F. Michelson, T. Mizuno, M. E. Monzani, A. Morselli, I. V. Moskalenko, M. Negro, N. Omodei, E. Orlando, J. F. Ormes, D. Paneque, G. Panzarini, J. S. Perkins, M. Persic, M. Pesce-Rollins, R. Pillera, T. A. Porter, G. Principe, J. L. Racusin, S. Rainò, R. Rando, B. Rani, M. Razzano, S. Razzaque, A. Reimer, O. Reimer, M. Sánchez-Conde, P. M. Saz Parkinson, Jeff Scargle, L. Scotton, D. Serini, C. Sgrò, E. J. Siskind, G. Spandre, P. Spinelli, D. J. Suson, H. Tajima, D. J. Thompson, D. F. Torres, J. Valverde, T. Venters, Z. Wadiasingh, S. Wagner, K. Wood
Figure caption: In light blue, we show the distribution of LCR sources by number of time bins with zero photons within the ROI used for their analysis. In magenta, we show the distribution of LCR sources according the number of time bins with fewer than 20 photons within the ROI used for their analysis. Darker shades of the lines refer to the 3 day cadence, while lighter dashed lines refer to the weekly cadence. The low-exposure time bins represent the 0.1% of the total time bins.
Paper: The Fermi-LAT Lightcurve Repository 
Authors: S. Abdollahi, M. Ajello, L. Baldini, J. Ballet, D. Bastieri, J. Becerra Gonzalez, R. Bellazzini, A. Berretta, E. Bissaldi, R. Bonino, A. Brill, P. Bruel, E. Burns, S. Buson, R. A. Cameron, R. Caputo, P. A. Caraveo, N. Cibrario, S. Ciprini, P. Cristarella Orestano, M. Crnogorcevic, S. Cutini, F. D'Ammando, S. De Gaetano, S. W. Digel, N. Di Lalla, L. Di Venere, A. Domínguez, V. Fallah Ramazani, S. J. Fegan, E. C. Ferrara, A. Fiori, H. Fleischhack, A. Franckowiak, Y. Fukazawa, P. Fusco, V. Gammaldi, F. Gargano, S. Garrappa, C. Gasbarra, D. Gasparrini, N. Giglietto, F. Giordano, M. Giroletti, D. Green, I. A. Grenier, S. Guiriec, M. Gustafsson, E. Hays, D. Horan, X. Hou, G. Jóhannesson, M. Kerr, D. Kocevski, M. Kuss, L. Latronico, J. Li, I. Liodakis, F. Longo, F. Loparco, L. Lorusso, B. Lott, M. N. Lovellette, P. Lubrano, S. Maldera, A. Manfreda, G. Martí-Devesa, M. N. Mazziotta, I. Mereu, M. Meyer, P. F. Michelson, T. Mizuno, M. E. Monzani, A. Morselli, I. V. Moskalenko, M. Negro, N. Omodei, E. Orlando, J. F. Ormes, D. Paneque, G. Panzarini, J. S. Perkins, M. Persic, M. Pesce-Rollins, R. Pillera, T. A. Porter, G. Principe, J. L. Racusin, S. Rainò, R. Rando, B. Rani, M. Razzano, S. Razzaque, A. Reimer, O. Reimer, M. Sánchez-Conde, P. M. Saz Parkinson, Jeff Scargle, L. Scotton, D. Serini, C. Sgrò, E. J. Siskind, G. Spandre, P. Spinelli, D. J. Suson, H. Tajima, D. J. Thompson, D. F. Torres, J. Valverde, T. Venters, Z. Wadiasingh, S. Wagner, K. Wood
Figure caption: An example 3 day lightcurve as can be found in the LCR. It spans more than 11 yr of LAT data and refers to the source at the center of Figure 2, FSRQ 4C +28.07. This lightcurve is obtained by specifying the analysis option that the spectral index of the source is free to vary. The data gap in 2018 is due to the temporary shut down of the instrument because of a solar panel anomaly.
Paper: The Fermi-LAT Lightcurve Repository 
Authors: S. Abdollahi, M. Ajello, L. Baldini, J. Ballet, D. Bastieri, J. Becerra Gonzalez, R. Bellazzini, A. Berretta, E. Bissaldi, R. Bonino, A. Brill, P. Bruel, E. Burns, S. Buson, R. A. Cameron, R. Caputo, P. A. Caraveo, N. Cibrario, S. Ciprini, P. Cristarella Orestano, M. Crnogorcevic, S. Cutini, F. D'Ammando, S. De Gaetano, S. W. Digel, N. Di Lalla, L. Di Venere, A. Domínguez, V. Fallah Ramazani, S. J. Fegan, E. C. Ferrara, A. Fiori, H. Fleischhack, A. Franckowiak, Y. Fukazawa, P. Fusco, V. Gammaldi, F. Gargano, S. Garrappa, C. Gasbarra, D. Gasparrini, N. Giglietto, F. Giordano, M. Giroletti, D. Green, I. A. Grenier, S. Guiriec, M. Gustafsson, E. Hays, D. Horan, X. Hou, G. Jóhannesson, M. Kerr, D. Kocevski, M. Kuss, L. Latronico, J. Li, I. Liodakis, F. Longo, F. Loparco, L. Lorusso, B. Lott, M. N. Lovellette, P. Lubrano, S. Maldera, A. Manfreda, G. Martí-Devesa, M. N. Mazziotta, I. Mereu, M. Meyer, P. F. Michelson, T. Mizuno, M. E. Monzani, A. Morselli, I. V. Moskalenko, M. Negro, N. Omodei, E. Orlando, J. F. Ormes, D. Paneque, G. Panzarini, J. S. Perkins, M. Persic, M. Pesce-Rollins, R. Pillera, T. A. Porter, G. Principe, J. L. Racusin, S. Rainò, R. Rando, B. Rani, M. Razzano, S. Razzaque, A. Reimer, O. Reimer, M. Sánchez-Conde, P. M. Saz Parkinson, Jeff Scargle, L. Scotton, D. Serini, C. Sgrò, E. J. Siskind, G. Spandre, P. Spinelli, D. J. Suson, H. Tajima, D. J. Thompson, D. F. Torres, J. Valverde, T. Venters, Z. Wadiasingh, S. Wagner, K. Wood
Figure caption: A model map, with 0.°1 resolution, for a single weekly time bin of the region surrounding FSRQ 4C +28.07. This source contains 15 other variable sources within a 12° radius, highlighting the need to model all the variable sources within the ROI.
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Footprint of the baseline cadence with the number of WFD observations in the first 3 yr (1.5 yr of nonrolling followed by 1.5 yr of rolling cadence). The dark bands correspond to the “active” area of the rolling cadence, which is observed at a higher cadence, and the light bands correspond to the “background.”
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Test-set recall (left panel) and precision (right panel) as a function of light-curve length per SNe class for the Y0-3 baseline. The shaded areas correspond to the 95% confidence limits obtained by bootstrapping the recall and precision values for each bin. The dashed lines mark the high performance region between 50 and 175 days. To remove small-number effects we present only the results for bins with more than 300 events.
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Test-set density of events as a function of light-curve length for the Y1.5-3 baseline versus no-roll (left panel) and Y0-3 baseline versus presto-color (right panel). The dashed lines mark the high performance region between 50 and 175 days.
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Normalized test-set confusion matrix for the classifier trained on the augmented training set of the Y0-3 baseline (left panel) and the presto-color cadences (right panel). The uncertainty in the log-loss corresponds to the 95% confidence intervals obtained by bootstrapping. The results show that visiting each event twice per night (baseline cadence) instead of three times yields a ∼10% higher SNe classification performance.
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Normalized test-set confusion matrix for the classifier trained on the augmented training set of the Y1.5-3 baseline (left panel) and the no-roll cadences (right panel). The uncertainty in the log-loss corresponds to the 95% confidence intervals obtained by bootstrapping. The results show a slightly higher SNe classification performance when rolling is implemented at the level in the baseline cadence.
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Normalized test-set confusion matrices for the classifier trained on the augmented training set of the Y1.5-3 baseline cadence. The left panel shows the results for the active region of the rolling cadence, and the right panel, for the background region. The uncertainty in the log-loss corresponds to the 95% confidence intervals obtained by bootstrapping. The results show a significantly higher SNe classification performance for the active region of the rolling cadence.
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Host galaxy photometric redshift distribution per supernova class for Y0-3 baseline, where SN Ia, SN Ibc, and SN II are shown, respectively, on the left, middle, and right panels. The training-set distribution (solid line) is not representative of the test set (dashed line), but the augmented training set (bold solid line) is close to the desired test distribution.
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Test-set recall (left panel) and precision (right panel) as a function of internight gap per SN class for the Y0-3 baseline. The shaded areas correspond to the 95% confidence limits obtained by bootstrapping the recall and precision values for each bin. To remove small-number effects, we present only the results for bins with more than 300 events.
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Test-set density of events as a function of internight gap for the Y1.5-3 baseline versus no-roll (left panel) and Y0-3 baseline versus presto-color (right panel).
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Test-set recall (left panel) and precision (right panel) as a function of the number of observations near peak per SN class for the Y0-3 baseline. The shaded areas correspond to the 95% confidence limits obtained by bootstrapping the recall and precision values for each bin. To remove small-number effects we present only the results for bins with more than 300 events.
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Test-set recall (left panel) and precision (right panel) as a function of the length of the longest internight gap per SN class for the Y0-3 baseline. The shaded areas correspond to the 95% confidence limits obtained by bootstrapping the recall and precision values for each bin. To remove small-number effects we present only the results for bins with more than 300 events. The reduced performance below 8 days corresponds to less than 5% of the events that tend to have very short light curves and therefore are not well classified.
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Host-galaxy photometric redshift distribution per supernova class, where SN Ia, SN Ibc, and SN II are shown, respectively, on the left, middle, and right panels. Each row shows the training (solid line), augmented training (bold solid line), and test-set distributions (dashed line) for each observing strategy. For all the observing strategies, the augmented training-set distribution is closer to the test set than the original training set.
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Test-set density of events as a function of the length of the longest internight gap for the Y1.5-3 baseline versus no-roll (left panel) and Y0-3 baseline versus presto-color (right panel).
Paper: Impact of Rubin Observatory Cadence Choices on Supernovae Photometric Classification
Authors: Catarina S. Alves, Hiranya V. Peiris, Michelle Lochner, Jason D. McEwen, Richard Kessler
Figure caption: Test-set density of events as a function of the number of observations near peak for the Y1.5-3 baseline versus no-roll (left panel) and Y0-3 baseline versus presto-color (right panel).
Paper: New Observational H(z) Data from Full-spectrum Fitting of Cosmic Chronometers in the LEGA-C Survey
Authors: Kang Jiao, Nicola Borghi, Michele Moresco, Tong-Jie Zhang
Figure caption: Difference between our final H(z) measurement (obtained with four fixed z bins × two quantile σ ⋆ bins) and the other values obtained by varying the bin settings, in particular the bin type (blue) and size (green), by applying different quality flags (violet) as described in Section 4.1 or fitting an alternative DPL SFH (red). The horizontal dark and light shaded regions represent the statistical and total uncertainty of the final H(z), the latter defined as ﹩\sqrt{{\sigma }_{\mathrm{stat}.}^{2}+{\sigma }_{\mathrm{syst}.}^{2}}﹩. The values obtained without binning in σ ⋆ (vertical shaded region) are the most significant contributors of the systematics error budget.
Paper: New Observational H(z) Data from Full-spectrum Fitting of Cosmic Chronometers in the LEGA-C Survey
Authors: Kang Jiao, Nicola Borghi, Michele Moresco, Tong-Jie Zhang
Figure caption: Distributions of redshift (z), stellar velocity dispersion (σ ⋆), age, and formation timescale (τ) obtained from the fit of LEGA-C DR2 CCs with spectroscopic data alone (upper panels) and adding photometric data from Muzzin et al. (2013; lower panels). In each panel, we show the histograms of the full sample (purple) and those obtained when applying the quality flags described in Section 4.1, namely, better SEDs (blue), unimodal (green), not truncated (yellow), and H/K well modeled (red).
Paper: New Observational H(z) Data from Full-spectrum Fitting of Cosmic Chronometers in the LEGA-C Survey
Authors: Kang Jiao, Nicola Borghi, Michele Moresco, Tong-Jie Zhang
Figure caption: Distributions of stellar ages, star formation timescales (τ), metallicities (Z), and logarithmic stellar masses (﹩\mathrm{log}({M}_{\star }/{M}_{\odot }﹩)) vs. z obtained from the full-spectrum fitting of 335 individual CCs in LEGA-C DR2. Each galaxy is color-coded by its stellar velocity dispersion (σ ⋆). The first three panels span the entire parameter space explored; for a more detailed description, see Section 3.
Paper: New Observational H(z) Data from Full-spectrum Fitting of Cosmic Chronometers in the LEGA-C Survey
Authors: Kang Jiao, Nicola Borghi, Michele Moresco, Tong-Jie Zhang
Figure caption: Full-spectrum fitting results for an example galaxy (ID = 215424) obtained with spectroscopic data alone (first panel) and adding photometry (second and third panels). The observational spectra from LEGA-C DR2 (Straatman et al. 2018) and photometric data points from the UltraVISTA catalog of Muzzin et al. (2013) are shown in light and dark blue, respectively. The best-fit BAGPIPES spectra and photometric points from fitting spectroscopy and spectroscopy+photometry are shown in black and orange, respectively. The fourth panel shows the best-fit BAGPIPES SFR (as a function of lookback time); the solid curves are the median posteriors, the shaded regions are the 1σ confidence regions, and the horizontal axis is the lookback time since t(z obs).
Paper: New Observational H(z) Data from Full-spectrum Fitting of Cosmic Chronometers in the LEGA-C Survey
Authors: Kang Jiao, Nicola Borghi, Michele Moresco, Tong-Jie Zhang
Figure caption: Distributions of four key parameters for the LEGA-C DR2 parent sample (blue) and the 350 passive galaxies analyzed in this work (yellow). The redshift (z), stellar velocity dispersion (σ ⋆), and stellar mass (M ⋆) are taken from LEGA-C DR2, while the sSFRs are from COSMOS2015. The arrows mark out the median values.
Paper: New Observational H(z) Data from Full-spectrum Fitting of Cosmic Chronometers in the LEGA-C Survey
Authors: Kang Jiao, Nicola Borghi, Michele Moresco, Tong-Jie Zhang
Figure caption: Galaxy ages fitted by a full spectroscopic and photometric fitting based on the DED model vs. those fitted under the same fitting configurations but based on the DPL model. The thin error bars represent measurements of individual massive and passive galaxies selected in LEGA-C DR2, while the thick error bars are the binned results (obtained with the four fixed z bins × two quantile σ ⋆ bins), which are both colored by their σ ⋆, with the lower bins in blue and higher bins in red. The green dashed–dotted line marks the diagonal direction.