adsabs/AstroCLIMB huggingface dataset:
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: Dependence of the orbital variations of AH Pic on the outburst phase in light curves LC#1 (top) and LC#2 (bottom). The black graphs contain the light curves, binned in time intervals of 0.1 days. The red graphs (left-hand scale) show the amplitude of the orbital variations, the blue one shows the O − C values (right-hand scale) between the observed (O) and calculated (C) epochs of orbital minima.
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: Orbital waveforms of the AH Pic stars. The black graphs refers to the entire light curves, the red ones to outburst, and the blue ones to interoutburst phases.
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: Distribution functions of the absolute V-band magnitude of NLs and old novae (solid black), and of SS Cyg- and Z Cam-type dwarf novae during quiescence (solid red) and outburst maximum (dashed magenta). The blue bars indicate the absolute magnitudes of the AH Pic stars.
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: Kepler long-cadence light curve of KIC 9202990 (left) and its ASAS-SN light curve (right) structured in the same way as the right side of Figure 1.
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: Synoptic view of ASAS-SN light curves of NLs with stunted outbursts reported in the literature. As a reference for the aspect of an AH Pic-like light curve on the chosen horizontal (time) scale, the AH Pic light curve is reproduced in the upper frame. Blue dots represent data in the V band; g-band data are shown in red.
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: Top: limited section of the light curves of AH Pic and KIC 9202990. Bottom: average waveforms in a sliding window with a width of 10 orbital cycles as a function of time. Orbital minima are color coded in blue/purple, maxima in yellow/red. The vertical green bars mark intervals during which the sliding window contains fewer than 10 cycles due to gaps in the original light curves and therefore no average waveforms were calculated.
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: AAVSO and ASAS-SN light curves of V2837 Ori, structured in the same way as Figure 1. In the high time resolution versions of the light curve the eclipses have been removed.
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: Distribution functions of outburst amplitudes and intervals of the AH Pic stars.
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: AAVSO and ASAS-SN light curves of FY Per, structured in the same way as Figure 1.
Paper: Photochemical Hazes in Exoplanetary Skies with Diamonds: Microphysical Modeling of Haze Composition Evolution via Chemical Vapor Deposition
Authors: Kazumasa Ohno
Figure caption: Representative result of haze composition evolution. The left panel shows the vertical distribution of the mass mixing ratio of CVD diamonds (cyan) and soot (gray). The solid black line denotes the total mass mixing ratio of the haze particles, demonstrating that the CVD diamond is the dominant component. The middle panel shows timescales relevant for haze composition evolution. The solid red, blue, green, and purple lines denote the timescales of soot growth by the HACA mechanism, diamond growth by chemical vapor deposition, collision growth, and gravitational settling, respectively. The black dotted, dashed, and dashed–dotted lines show the timescales of graphitization, etching by atomic hydrogen, and oxidization. The right panel shows the vertical distribution of the mean particle radius. I assume T eq = 1000 K, [M/H] = 1.0, and C/O = 0.5 in this figure.
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: Power spectra of TESS and Kepler light curves of four systems with special features. For details, see text. The frequencies shown in the insets in the right column range between 14.5 and 16.5 day−1.
Paper: Photochemical Hazes in Exoplanetary Skies with Diamonds: Microphysical Modeling of Haze Composition Evolution via Chemical Vapor Deposition
Authors: Kazumasa Ohno
Figure caption: Fraction of surface radical sites on diamond ﹩{R}_{\mathrm{dia}}^{* }﹩ and soot ﹩{R}_{\mathrm{soot}}^{* }﹩ as a function of temperature. Solid, dashed, dashed–dotted, and dotted lines show the radical site fraction for the atomic hydrogen abundances of n H/n H2 = 10−2, 10−3, 10−4, and 10−5 respectively.
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: Top: power spectra of the two TESS light curves of LAMOST J065237.19+243622.1. The tentatively identified orbital signals are marked as Ω? (see text). Middle: light curve LC#2 of LAMOST J065237.19+243622.1. Bottom: time-resolved power spectrum of LC#2 on the same timescale. In order to enhance fainter features the power has been scaled to its fourth root.
Paper: Photochemical Hazes in Exoplanetary Skies with Diamonds: Microphysical Modeling of Haze Composition Evolution via Chemical Vapor Deposition
Authors: Kazumasa Ohno
Figure caption: Atmospheric TP profiles used in this study. Different colored lines show the profiles for different equilibrium temperature T eq. The solid, dashed, and dashed–dotted lines denote the profiles for atmospheric metallicity of [M/H] = 1.0, 2.0, and 3.0, respectively.
Paper: The AH Pictoris Syndrome: Continuous Trains of Stunted Outbursts in Novalike Variables
Authors: Albert Bruch
Figure caption: Detail of the ASAS-SN light curve of PS Eri containing dips and the transition to the normal outburst behavior.
Paper: Photochemical Hazes in Exoplanetary Skies with Diamonds: Microphysical Modeling of Haze Composition Evolution via Chemical Vapor Deposition
Authors: Kazumasa Ohno
Figure caption: Cartoon illustrating microphysical process considered in this study. Several processes, namely, the HACA mechanism, CVD process, etching, and oxidization, deposit and decompose soot and CVD diamonds, which would drive the evolution of the haze compositions.
Paper: Exploring the Diversity of Faint Satellites in the M81 Group
Authors: Katya Gozman, Eric F. Bell, In Sung Jang, Jose Marco Arias, Jeremy Bailin, Roelof S. de Jong, Richard D'Souza, Oleg Y. Gnedin, Antonela Monachesi, Paul A. Price, Vaishnav V. Rao, Adam Smercina
Figure caption: The ellipticity of select Local Volume satellites against the ratio of their elliptical half-light radii and tidal radii. Tidal radii are calculated assuming a systemic line-of-sight velocity dispersion of 5 km s−1 for M81 satellites and a rotational velocity of 230 km s−1 for all hosts. Each point is color-coded by the satellite’s absolute magnitude, M  V . We plot only well-measured satellites in the restricted luminosity range of M  V  < −6. D1006+69 and DWJ0954+6821 ellipticities are shown as 84% confidence upper limits. The blue horizontal line is drawn at an ellipticity of 0.55, matching the ellipticity cut in Figure 7 for highly elliptical satellites. Median errors in ellipticity are shown in the inset box for various magnitudes as binned from M  V  = −22 to M  V  = −6 in 4 dex bins. These errors are only calculated from the MW and M31 satellites, as K. Chiboucas et al. (2009) do not cite error bars for their ellipticity measurements. We do not see any trends between ellipticity and tidal radius fraction, indicating that tides are likely not the dominant factor that sets the ellipticity of low-mass satellites. Data for MW and M31 satellites are from the Local Volume Database, data for M81 satellites are compiled from K. Chiboucas et al. (2009).
Paper: Exploring the Diversity of Faint Satellites in the M81 Group
Authors: Katya Gozman, Eric F. Bell, In Sung Jang, Jose Marco Arias, Jeremy Bailin, Roelof S. de Jong, Richard D'Souza, Oleg Y. Gnedin, Antonela Monachesi, Paul A. Price, Vaishnav V. Rao, Adam Smercina
Figure caption: Same as Figure 9, except the ellipticity of select Local Volume satellites against their separation from their host galaxy. M81 and M31 satellites are measured as their projected separations between M81 and M31, respectively. MW satellites are measured as their galactocentric 3D distances. The color map and errors are identical to the one used in Figure 9. Data for MW and M31 satellites are from the Local Volume Database, data for M81 satellites are compiled from K. Chiboucas et al. (2009).
Paper: Exploring the Diversity of Faint Satellites in the M81 Group
Authors: Katya Gozman, Eric F. Bell, In Sung Jang, Jose Marco Arias, Jeremy Bailin, Roelof S. de Jong, Richard D'Souza, Oleg Y. Gnedin, Antonela Monachesi, Paul A. Price, Vaishnav V. Rao, Adam Smercina
Figure caption: Various isochrones overlaid on the RGB stars within 2a  h  of D1005+68. The panels going from left to right show isochrones varying in age, distance, and metallicity, respectively, keeping the other two quantities constant with nominal values of [M/H] = −1.5, age = 13 Gyr, and a distance of 3.6 Mpc.
Paper: Exploring the Diversity of Faint Satellites in the M81 Group
Authors: Katya Gozman, Eric F. Bell, In Sung Jang, Jose Marco Arias, Jeremy Bailin, Roelof S. de Jong, Richard D'Souza, Oleg Y. Gnedin, Antonela Monachesi, Paul A. Price, Vaishnav V. Rao, Adam Smercina
Figure caption: The mask images used to mask out bright stars and artifacts. RGB stars used for parameter fitting are overlaid as magenta points.
Paper: A Compact, Coherent Representation of Stellar Surface Variation in the Spectral Domain
Authors: Lily L. Zhao, Megan Bedell, David W. Hogg, Rodrigo Luger
Figure caption: Distributions of the RV rms after correcting against the constructed projection space (i.e., ﹩{{\boldsymbol{I}}}_{\bullet }﹩ and ﹩{{\boldsymbol{I}}}_{\circlearrowleft }﹩ space) in orange and correcting against activity indicator pairs in blue. Each box-and-whisker plot represents the RV rms distribution across all simulations, where the total number of simulations is given above each subplot. Different box-and-whisker plots represent different injected Keplerian signals; the properties of the injected planets are given along the x-axis, with semimajor axis K given in units of m s−1 and period P given in units of stellar rotation. The median RV rms for corrections against ﹩{{\boldsymbol{I}}}_{\bullet }﹩ and ﹩{{\boldsymbol{I}}}_{\circlearrowleft }﹩ is drawn across the set of simulations corresponding to each injected planet.
Paper: A Compact, Coherent Representation of Stellar Surface Variation in the Spectral Domain
Authors: Lily L. Zhao, Megan Bedell, David W. Hogg, Rodrigo Luger
Figure caption: Top: Common activity indicators measured from simulated spectra of a rotating star with a single spot over a grid of spot radii and latitudes (similar to Figure 6 left). The two indicators being compared and their relative values are given to the top and right of each subplot. The rotating spot spectra form a similar loop in indicator space as in the simplistically constructed ﹩{{\boldsymbol{I}}}_{\bullet }﹩ and ﹩{{\boldsymbol{I}}}_{\circlearrowleft }﹩ projection space used in this work. Bottom: RVs detrended relative to the measured indicators for each pair of indicators in shades of blue (similar to Figure 9). For comparison, RVs corrected with respect to projections onto ﹩{{\boldsymbol{I}}}_{\bullet }﹩ and ﹩{{\boldsymbol{I}}}_{\circlearrowleft }﹩ are shown in orange.
Paper: A Compact, Coherent Representation of Stellar Surface Variation in the Spectral Domain
Authors: Lily L. Zhao, Megan Bedell, David W. Hogg, Rodrigo Luger
Figure caption: Corrected RVs for a random example of each of the three different test cases (corresponding to each column) for different injected planetary systems (Corresponding to different rows) at an SNR of 500. Each plot shows the measured RVs (black), the corrected RVs (orange points), and the injected RV curve (orange solid line). The residuals between the corrected and injected RVs (ΔRV) are shown below each plot. The first row shows the case of no planet; in the next three rows, the semimajor amplitude K, and period P, of the injected planetary signal are given in the top left corner of the leftmost plot in the row.
Paper: Do Neutron Star Ultraluminous X-Ray Sources Masquerade as Intermediate-mass Black Holes in Radio and X-Ray?
Authors: Teresa Panurach, Kristen C. Dage, Ryan Urquhart, Richard M. Plotkin, Jeremiah D. Paul, Arash Bahramian, McKinley C. Brumback, Timothy J. Galvin, Isabella Molina, James C. A. Miller-Jones, Payaswini Saikia
Figure caption: Our sample of extragalactic neutron star ULXs (shown by cross symbols) projected onto the fundamental plane, showing the result if one were to naively estimate “black hole” masses via the radio and X-ray luminosities/limits (here, we have used Equation (15) of A. Merloni et al. 2003). The gray symbols show XRBs and AGNs from A. Merloni et al. (2003), and the dashed line shows their best-fit function. Since it is common for studies to employ joint radio and X-ray observations to search for AGNs in low-mass galaxies, this figure illustrates the parameter space where neutron star ULXs could potentially masquerade as IMBH/low-mass AGNs. (a) A projection of the fundamental plane with black hole mass as the dependent variable. The radio and X-ray luminosities/limits of our sample have led to erroneous mass estimates or upper limits of ∼102−105 M ⊙. (b) The same data projected onto the typical view of the fundamental plane. Note: the radio counterpart to M82 X-2 is likely from a coincident H II region, but we depict it as a radio detection here, to illustrate how such a misidentification would incorrectly imply a ≈105 M ⊙ IMBH. The Galactic source Swift J0243 is not included in this figure, as the fundamental plane correctly predicts this source cannot be a black hole (see Section 3.8). For comparison, we also include HLX-1 (as a plus symbol), as measured in X-ray and radio by D. Cseh et al. (2015b).
Paper: Radio Active Galactic Nuclei Activity in Low Redshift Galaxies Is Not Directly Related to Star Formation Rates
Authors: Arjun Suresh, Michael R. Blanton
Figure caption: Radio luminosity ν L  ν  from NVSS at 1.4 GHz and Hα star formation rates from MaNGA. The solid black line shows the relationship found by A. M. Hopkins et al. (2003) between radio synchrotron emission and star formation, with an offset to account for the usage of the Chabrier initial mass function instead of Salpeter. The solid gray line shows the luminosity that must be exceeded for an object to be considered a detected AGN in our analysis.
Paper: Radio Active Galactic Nuclei Activity in Low Redshift Galaxies Is Not Directly Related to Star Formation Rates
Authors: Arjun Suresh, Michael R. Blanton
Figure caption: FIRST radio cutouts of detected AGN in bins sSFR–M ⋆, with each cutout spanning 1.″5 on the sky. In each grid of sSFR–M ⋆, we have chosen a detected AGN to display. The blank locations in the image are locations where our sample does not have detected AGN. At low M ⋆ (﹩{\mathrm{log}}_{10}\left({M}_{\star }/{M}_{\odot }\right)\lt 10.4﹩), we see no detected AGN in the sample. At ﹩10.4\lt {\mathrm{log}}_{10}\left({M}_{\star }/{M}_{\odot }\right)\lt 11.3﹩, the detected AGN mostly seem to be compact sources. And at ﹩{\mathrm{log}}_{10}\left({M}_{\star }/{M}_{\odot }\right)\gt 11.3﹩, the AGN population seems to be a mix between compact and extended sources. The purpose of the image is purely for illustration. We do not recommend that any statistical inferences be made based on this image. See Section 5 for more comments on the figure.
Paper: Do Neutron Star Ultraluminous X-Ray Sources Masquerade as Intermediate-mass Black Holes in Radio and X-Ray?
Authors: Teresa Panurach, Kristen C. Dage, Ryan Urquhart, Richard M. Plotkin, Jeremiah D. Paul, Arash Bahramian, McKinley C. Brumback, Timothy J. Galvin, Isabella Molina, James C. A. Miller-Jones, Payaswini Saikia
Figure caption: The radio/X-ray luminosity correlation plane for accreting compact objects adapted from A. Bahramian et al. (2018). Quiescent/hard-state black holes are indicated by the dark green circles. We include the following neutron star populations: quiescent/hard-state neutron stars as blue squares and accreting millisecond X-ray pulsars (AMXPs) and transitional millisecond pulsars (tMSPs) as pink stars and mint triangles. The neutron star ULXs in our sample are indicated by large “X”s. We also include HLX-1 (D. Cseh et al. 2015b) for comparison. The gray line represents the best-fit regression for black holes from E. Gallo et al. (2006), while the blue line represents the proposed correlation for hard-state neutron stars from E. Gallo et al. (2018).
Paper: Radio Active Galactic Nuclei Activity in Low Redshift Galaxies Is Not Directly Related to Star Formation Rates
Authors: Arjun Suresh, Michael R. Blanton
Figure caption: Numbers of AGN as a function of Eddington ratio for two bins (high and low) in each of four properties (M ⋆, σ  v , SFR, and sSFR). The solid lines connect the observed number in each bin. The dashed lines show the model expectation value using the M ⋆ model and the expected 1σ distribution around it.
Paper: Radio Active Galactic Nuclei Activity in Low Redshift Galaxies Is Not Directly Related to Star Formation Rates
Authors: Arjun Suresh, Michael R. Blanton
Figure caption:  L 1.4 GHz vs. M ⋆, σ  v , SFR, and sSFR for the observations (top) and the best-fit model with Q = M ⋆ (bottom).
Paper: Radio Active Galactic Nuclei Activity in Low Redshift Galaxies Is Not Directly Related to Star Formation Rates
Authors: Arjun Suresh, Michael R. Blanton
Figure caption: Similar to Figure 3, with the bottom row corresponding to the best-fit Uniform model.
Paper: Modeling the Multiwavelength Detection of Protoclusters. I. An Excess of Submillimeter Galaxies in Protocluster Cores
Authors: Pablo Araya-Araya, Rachel K. Cochrane, Christopher C. Hayward, Robert M. Yates, Laerte Sodré, Marcelo C. Vicentin, Douglas Rennehan, Roderik Overzier, Marcel van Daalen
Figure caption: The redshift evolution of the fraction of galaxies with S 870 ≥ 0.5 mJy (first row) and S 870 ≥ 1.5 mJy (second row) in protocluster cores (solid lines) and protocluster outskirts (dashed lines) for the three protocluster types (left: Fornax type; middle: Virgo type; right: Coma type). The lines denote the median value at a given redshift, and the shaded regions indicate the 25–75th-percentile range. The submillimeter-bright fraction for the field is indicated by the dotted line. At z ≳ 1.5, protocluster cores exhibit an enhanced submillimeter-bright fraction relative to both protocluster outskirts and the field. The redshift evolution of the submillimeter-bright fraction in the core (both the peak and the duration) presents a clear dependence on the protocluster type. Protocluster outskirts have submillimeter-bright fractions only slightly elevated relative to the field. For the higher flux density threshold (S 870 ≥ 1.5 mJy), the same trend is present, but all fractions are lower.
Paper: Modeling the Multiwavelength Detection of Protoclusters. I. An Excess of Submillimeter Galaxies in Protocluster Cores
Authors: Pablo Araya-Araya, Rachel K. Cochrane, Christopher C. Hayward, Robert M. Yates, Laerte Sodré, Marcelo C. Vicentin, Douglas Rennehan, Roderik Overzier, Marcel van Daalen
Figure caption: The median SFR as a function of stellar mass for galaxies in protocluster cores (top row) and in protocluster outskirts (bottom row) minus the median SFR of field galaxies (i.e., the “excess SFR” relative to the field, denoted ﹩{\rm{\Delta }}\mathrm{log}(\mathrm{SFR})﹩) at z ∼ 2, 3, and 4 (dark blue, purple, and orange lines, respectively) for Fornax, Virgo, and Coma-type protoclusters (first, second, and third columns, respectively). The black dashed line indicates ﹩{\rm{\Delta }}\mathrm{log}(\mathrm{SFR})=﹩ 0 (median SFR equal to the field value). Overall, galaxies in protocluster cores and outskirts do not exhibit enhanced SFRs relative to the field, i.e., “starbursts” are uncommon. At lower stellar masses, galaxies in protocluster cores have lower SFRs than those in the field (by as much as an order of magnitude); this trend is stronger at lower redshift. Galaxies in protocluster outskirts have SFRs similar to those of field galaxies except for at z ∼ 2, where lower-mass galaxies have SFRs slightly suppressed relative to the field.
Paper: Modeling the Multiwavelength Detection of Protoclusters. I. An Excess of Submillimeter Galaxies in Protocluster Cores
Authors: Pablo Araya-Araya, Rachel K. Cochrane, Christopher C. Hayward, Robert M. Yates, Laerte Sodré, Marcelo C. Vicentin, Douglas Rennehan, Roderik Overzier, Marcel van Daalen
Figure caption: The fraction of SMGs with S 870 higher than x mJy that are in the field (orange dotted line), protocluster outskirts (purple dashed), or cores (black solid) at z ∼ 2, 3, and 4 (from left to right). The values on the top x-axes are rescaled flux densities, where we have boosted all model galaxies’ flux densities by a factor of 1.81; see text for details. At the lowest flux densities considered, most SMGs are located in the field. Above a transition flux density, which decreases with increasing redshift, the majority of SMGs are located in protocluster cores. At all redshifts and flux densities, ≲20% of SMGs are located in protocluster outskirts.
Paper: Modeling the Multiwavelength Detection of Protoclusters. I. An Excess of Submillimeter Galaxies in Protocluster Cores
Authors: Pablo Araya-Araya, Rachel K. Cochrane, Christopher C. Hayward, Robert M. Yates, Laerte Sodré, Marcelo C. Vicentin, Douglas Rennehan, Roderik Overzier, Marcel van Daalen
Figure caption: The redshift evolution of the fraction of dust-obscured galaxies (f obs ≡ SFR IR /SFRinst. ≥ 0.5) in the three different environments. Colored regions represent the 25th–75th percentile ranges for protocluster outskirts and cores, while the lines show the median N gal(f obs ≥ 0.5)/N tot value in a given redshift bin. We do not find any significant redshift evolution of the fraction of dust-obscured sources in the three environments. Across protocluster types, ∼65% of protocluster core galaxies are dust obscured, while this percentage is ∼40% for galaxies in protocluster outskirts and the field.
Paper: Modeling the Multiwavelength Detection of Protoclusters. I. An Excess of Submillimeter Galaxies in Protocluster Cores
Authors: Pablo Araya-Araya, Rachel K. Cochrane, Christopher C. Hayward, Robert M. Yates, Laerte Sodré, Marcelo C. Vicentin, Douglas Rennehan, Roderik Overzier, Marcel van Daalen
Figure caption: Normalized SMFs of galaxies in protocluster cores (solid lines), protocluster outskirts (dashed), and the field (gray dotted) at z ∼ 2, 3, and 4 (first, second, and third rows, respectively) for Fornax-, Virgo, and Coma-type protoclusters (first, second, and third columns, respectively). In all panels, protocluster cores exhibit a relative excess of high-mass galaxies compared to protocluster outskirts and the field. The SMFs of protocluster outskirts and the field are similar.