adsabs/AstroCLIMB huggingface dataset:
Paper: Relationship between Successive Flares in the Same Active Region and SHARP Parameters
Authors: Hao Ran, Ying D. Liu, Yang Guo, Rui Wang
Figure caption: The 16 SHARP parameters and the flare envelope for AR 12673. The black curve shows different SHARP parameters and the green curve is the flare envelope. The left y-axes represent the values of the SHARP parameters, and the right y-axes represent the flare index. The correlation coefficients (CCs) are shown at the top of each panel. The SHARP parameters are normalized.
Paper: Relationship between Successive Flares in the Same Active Region and SHARP Parameters
Authors: Hao Ran, Ying D. Liu, Yang Guo, Rui Wang
Figure caption: Illustration of the change in the coverage and the number of PILs in AR 12673. Panel (a), panel (b), and panel (c) are the composite maps of the Br map and their PILs at different times. The PIL area is marked by the purple lines. Panel (d) shows the change in the number of pixels of PILs in AR 12673. The three vertical lines in panel (d) correspond to the times of panels (a)–(c).
Paper: Spatial Scales and Time Variation of Solar Subsurface Convection
Authors: Alexander V. Getling, Alexander G. Kosovichev
Figure caption: The correlation between the solar cycle variations of the total power of all the flow harmonics and the monthly average sunspot number for unmasked (black curves) and masked (red curves) velocity divergence fields.
Paper: Relationship between Successive Flares in the Same Active Region and SHARP Parameters
Authors: Hao Ran, Ying D. Liu, Yang Guo, Rui Wang
Figure caption: The original GOES SXR curve and the flare “envelope” of AR 12673. Panel (a) refers to the original GOES SXR curve, and panel (b) represents the corresponding flare “envelope.” The temporal resolution of both panels is 720 s, which is the same as that of the SHARP data.
Paper: Magnetic Helicity Evolution and Eruptive Activity in NOAA Active Region 11158
Authors: L. M. Green, J. K. Thalmann, G. Valori, E. Pariat, L. Linan, K. Moraitis
Figure caption: Evolution of the line-of-sight photospheric magnetic field as observed with SDO/HMI throughout all five phases. Bipoles that emerge during the time periods under study are indicated by blue ovals and discussed in the relevant sections.
Paper: Magnetic Helicity Evolution and Eruptive Activity in NOAA Active Region 11158
Authors: L. M. Green, J. K. Thalmann, G. Valori, E. Pariat, L. Linan, K. Moraitis
Figure caption: Phase 2: Hinode/XRT images on 2011 February 13 taken with the Ti poly filter. Data are displayed using a log scale to bring out fainter plasma emission structures. The images in the panels of the middle row show faint changes in the corona associated with a failed eruption, and in the bottom row a second phase of loop growth is shown.
Paper: Magnetic Helicity Evolution and Eruptive Activity in NOAA Active Region 11158
Authors: L. M. Green, J. K. Thalmann, G. Valori, E. Pariat, L. Linan, K. Moraitis
Figure caption: Evolution of the mean helicity ratio during Phase 3 (February 13 07:00 to 19:00 UT) is shown in the top panel (continuous line). The bottom panel shows the full Sun GOES 1–8 Å light curve (continuous line) and the AIA 131 Åactive region light curve. The vertical dotted blue (red) line indicates the time of a failed eruption (CME, i.e., successful eruption).
Paper: Magnetic Helicity Evolution and Eruptive Activity in NOAA Active Region 11158
Authors: L. M. Green, J. K. Thalmann, G. Valori, E. Pariat, L. Linan, K. Moraitis
Figure caption: Evolution of the mean helicity ratio during Phase 2 (February 13 00:00 to 07:00 UT) shown in the top panel (continuous line). The bottom panel shows the full Sun GOES 1–8 Å light curve (continuous line) and the AIA 131 Å active region light curve. The vertical dotted blue line indicates the time of a failed eruption.
Paper: Magnetic Helicity Evolution and Eruptive Activity in NOAA Active Region 11158
Authors: L. M. Green, J. K. Thalmann, G. Valori, E. Pariat, L. Linan, K. Moraitis
Figure caption: Phase 3 failed eruption: summary image showing the growth of EUV-emitting loops in NOAA active region 11158 followed by a failed eruption from the region during Phase 3. From top to bottom, the rows show data from AIA 1700 Å waveband, AIA 94 Å waveband data, XRT Ti Poly filter images, and STEREO-B EUVI 195 Å waveband data.
Paper: Magnetic Helicity Evolution and Eruptive Activity in NOAA Active Region 11158
Authors: L. M. Green, J. K. Thalmann, G. Valori, E. Pariat, L. Linan, K. Moraitis
Figure caption: Evolution of the mean helicity ratio (continuous line) for the time period 2011 February 12–15, inclusive, and helicity ratio phases labeled P1 through P5 corresponding to Phase 1 through Phase 5 (colored panels). The threshold helicity ratio value of 0.1 is marked with a horizontal dashed line.
Paper: Magnetic Helicity Evolution and Eruptive Activity in NOAA Active Region 11158
Authors: L. M. Green, J. K. Thalmann, G. Valori, E. Pariat, L. Linan, K. Moraitis
Figure caption: Evolution of the mean helicity ratio during Phase 1 (February 12 00:00 to 23:59 UT) is shown in the top panel (continuous line). The bottom panel shows the full Sun GOES light curve (continuous line) and the AIA 131 Å active region light curve. The vertical dotted black line indicates the start of the emergence of Bipole 3.
Paper: Magnetic Helicity Evolution and Eruptive Activity in NOAA Active Region 11158
Authors: L. M. Green, J. K. Thalmann, G. Valori, E. Pariat, L. Linan, K. Moraitis
Figure caption: Evolution of the mean helicity ratio during Phase 4 (February 13 19:00 to February 14 04:00 UT) shown in the top panel (continuous line). The bottom panel shows the full Sun GOES 1–8 Å light curve (continuous line) and the AIA 131 Å active region light curve. The vertical dotted green (red) lines show the times of jets (CMEs).
Paper: The Galactic Nova Rate: Estimates from the ASAS-SN and Gaia Surveys
Authors: A. Kawash, L. Chomiuk, J. Strader, K. V. Sokolovsky, E. Aydi, C. S. Kochanek, K. Z. Stanek, Z. Kostrzewa-Rutkowska, S. T. Hodgkin, K. Mukai, B. Shappee, T. Jayasinghe, M. Rizzo Smith, T. W.-S. Holoien, J. L. Prieto, T. A. Thompson
Figure caption: Comparison of the month of first detections of model novae (solid histograms) vs. discovered samples (scatter points with Poisson error bars). Both surveys have a seasonal gap while the Sun is in Sagittarius from November to January, and Gaia (shown in red) has an additional seasonal gap 6 months later because of the rotation direction of the satellite. When a field comes out of solar constraint, the model predicts an excess of nova discoveries.
Paper: Strategies for Determining the Cascade Rate in MHD Turbulence: Isotropy, Anisotropy, and Spacecraft Sampling
Authors: Yanwen Wang, Rohit Chhiber, Subash Adhikari, Yan Yang, Riddhi Bandyopadhyay, Michael A. Shay, Sean Oughton, William H. Matthaeus, Manuel E. Cuesta
Figure caption: A collection of estimates of dissipation rate using Method I, the 1D form third-order law (Equation (10)), applied to data from the high σ  c , ﹩{{\boldsymbol{B}}}_{0}=2\hat{{\boldsymbol{z}}}﹩ anisotropic simulation III. Left: each curve represents the average of the ﹩{Y}_{{\ell }}^{+}/{\ell }﹩ and ﹩{Y}_{{\ell }}^{-}/{\ell }﹩ terms for a fixed lag direction. The dashed horizontal line indicates the actual energy dissipation rate. Peak values estimate the dissipation rate and (horizontal) location of a peak roughly locates in the middle of the inertial range. Right: same data as the left panel, normalized by ϵ diss, and averaged over azimuthal angle ϕ. Each curve is for a fixed polar angle θ, and averaged over six equally spaced azimuthal angles with ﹩{\rm{\Delta }}\phi =\tfrac{\pi }{3}﹩.
Paper: Strategies for Determining the Cascade Rate in MHD Turbulence: Isotropy, Anisotropy, and Spacecraft Sampling
Authors: Yanwen Wang, Rohit Chhiber, Subash Adhikari, Yan Yang, Riddhi Bandyopadhyay, Michael A. Shay, Sean Oughton, William H. Matthaeus, Manuel E. Cuesta
Figure caption: Terms of the von Kármán–Howarth equation, Equation (7), evaluated using the anisotropic (﹩{{\boldsymbol{B}}}_{0}=2\hat{{\boldsymbol{z}}}﹩) simulation III at t = 3.2. Here, ﹩\tfrac{\partial }{\partial t}\langle {(\delta {{\boldsymbol{z}}}^{\pm })}^{2}\rangle ={T}^{\pm }﹩, 〈δ  z  ∓∣δ  z  ±∣2〉 =  Y  ±, and ﹩\langle {(\delta {{\boldsymbol{z}}}^{\pm })}^{2}\rangle ={G}^{\pm }﹩. The green, red, and blue curves correspond to the three left-hand side (LHS) terms in Equation (8), averaged over many directions of vector lag  ℓ . Lag is expressed in units of the simulation box length (2π). The orange horizontal dashed line indicates the exact dissipation rate ϵ diss = ν〈ω 2 + J 2〉. The black curve is the sum of the three (LHS) terms: the large-scale energy supply, the nonlinear transfer rate to smaller scales, and the dissipation at scales larger than ℓ. As expected, they add up to the total dissipation rate.
Paper: Strategies for Determining the Cascade Rate in MHD Turbulence: Isotropy, Anisotropy, and Spacecraft Sampling
Authors: Yanwen Wang, Rohit Chhiber, Subash Adhikari, Yan Yang, Riddhi Bandyopadhyay, Michael A. Shay, Sean Oughton, William H. Matthaeus, Manuel E. Cuesta
Figure caption: Estimating the dissipation rate using Method I, the 1D form third-order law (Equation (10)), applied to data from the isotropic simulation I. Recall ﹩{Y}_{{\ell }}^{\pm }=\langle (\hat{{\boldsymbol{\ell }}}\cdot \delta {{\boldsymbol{z}}}^{\mp })| \delta {{\boldsymbol{z}}}^{\pm }{| }^{2}\rangle ﹩. Different curves represent the results of 36 different lag directions uniformly distributed on a sphere. Each curve represents the average of the ﹩{Y}_{{\ell }}^{+}/{\ell }﹩ and ﹩{Y}_{{\ell }}^{-}/{\ell }﹩ terms for a fixed lag direction. The dark blue dashed horizontal line (at 0.795) indicates the actual energy dissipation rate. A standard procedure is to assume that the peak values provide estimates of the dissipation rate and the corresponding ℓ values locate in the middle of the inertial range.
Paper: Sigmoid Formation through Slippage of a Single J-shaped Coronal Loop
Authors: Hanya Pan, Tingyu Gou, Rui Liu
Figure caption: Asymmetric dimming. Panels (a)–(f) show base difference images of six AIA EUV passbands. The normalized brightness of the six EUV passbands from the elliptical area in the dimming region is plotted in Figure 2(c). The red curve indicates the sigmoidal loop, extracted from the image taken at 06:32 (Figure 4(e)). Panel (g) gives the EM = DEM · ΔT averaged over the elliptical dimming region at different time instants (color coded) within the temperature range ﹩{\mathrm{log}}_{10}T[{\rm{K}}]=[5.5,7.1]﹩, which is divided into logarithmically uniform intervals of ﹩{{\rm{\Delta }}{\rm{l}}{\rm{o}}{\rm{g}}}_{10}T=0.05﹩ in the DEM analysis.
Paper: Sigmoid Formation through Slippage of a Single J-shaped Coronal Loop
Authors: Hanya Pan, Tingyu Gou, Rui Liu
Figure caption: Evolution of the source active region. Panels (a)–(d) show vector magnetic field detected by SDO/HMI, with a white rectangle to mark the region from which we obtain the magnetic flux in Figure 2(a). In panels (e)–(h), photospheric flow field calculated by DAVE4VM (Schuck 2008) is averaged every 12 hr. Panels (i)–(l) show maps of column current density, obtained by integrating the unsigned current density over the same height range as in Figure 5(b), overplotted by orange (blue) contours indicating B  z  of +400 (−400) G.
Paper: Sigmoid Formation through Slippage of a Single J-shaped Coronal Loop
Authors: Hanya Pan, Tingyu Gou, Rui Liu
Figure caption: Semicircular loop bundle in relation to the J-to-S transformation. Snapshots of AIA 131 Å original and running difference images are selected to show that the semicircular loop (yellow arrow) remained nearly stationary before slipping motions (left), when the sigmoidal loop was formed (middle), and when the sigmoid erupted (right).
Paper: Strategies for Determining the Cascade Rate in MHD Turbulence: Isotropy, Anisotropy, and Spacecraft Sampling
Authors: Yanwen Wang, Rohit Chhiber, Subash Adhikari, Yan Yang, Riddhi Bandyopadhyay, Michael A. Shay, Sean Oughton, William H. Matthaeus, Manuel E. Cuesta
Figure caption: Time evolution of 〈J 2〉 and 〈ω 2〉 for Runs I (left), II (middle), and III (right). The vertical orange line indicates the time for performing the analysis.
Paper: On the Mass Ratio Distribution of Black Hole Mergers in Triple Systems
Authors: Miguel A. S. Martinez, Carl L. Rodriguez, Giacomo Fragione
Figure caption: Distribution of mass ratios for the different BBH formation channels. The merging sample is weighted by star (cluster) formation history for the field (cluster) mergers (left) and detectability (right), to produce realistic astrophysical and detectable populations in the local universe. In addition to the field non-LK (solid blue) and field LK (dashed black) distributions, we also include the mass ratio distributions from GCs using data presented in Kremer et al. (2020), split into 1G (dotted orange) and 2G (dotted green) channels. The median for the mass ratio distribution from the power-law model from GWTC-2 (solid purple line) is presented in the left panel, normalized such that the power law integrated from 0.1 to 1 sums to 1.
Paper: On the Mass Ratio Distribution of Black Hole Mergers in Triple Systems
Authors: Miguel A. S. Martinez, Carl L. Rodriguez, Giacomo Fragione
Figure caption: Top: median and 50 percentile of the initial inner binary mass ratio as a function of inner semimajor axis. Bottom: normalized distribution of the inner semimajor axis prior to stellar evolution for all initial triples in the sample, including those that did not result in a merger (solid blue), merging binaries (dashed–dotted red), and merging triples (dashed green).
Paper: On the Mass Ratio Distribution of Black Hole Mergers in Triple Systems
Authors: Miguel A. S. Martinez, Carl L. Rodriguez, Giacomo Fragione
Figure caption: Distribution of mass ratios for different cuts to the triple sample. The dashed–dotted black line matches that of the left panel of Figure 1. The solid blue, dotted orange, and dashed green lines represent the sample where all stars which may have experienced LK-driven RLOF are discarded for different assumed values of the maximum stellar radius.
Paper: On the Mass Ratio Distribution of Black Hole Mergers in Triple Systems
Authors: Miguel A. S. Martinez, Carl L. Rodriguez, Giacomo Fragione
Figure caption: Contour plots for mass ratio–total mass distributions for different channels. The contours show the regions containing 99.5% (solid), 90% (dashed), and 60% (dotted) of all data points. The left column shows astrophysically weighted samples while the right column shows the same samples weighted by detectability. In each row, the field LK channel (black) is compared to the field non-LK (top, blue), cluster 1G (middle, orange), and cluster 2G (bottom, green) channels. Also included in the right column is the detection of GW190412 during O3a (Abbott et al. 2020). Note the differing range in the y-axis of each row. In the field populations, the total mass of the merging binary is limited by pulsational pair instability. However, in the cluster populations, the maximum birth mass of a BH from stellar collapse can be over this limit because of repeated stellar mergers prior to stellar collapse.
Paper: Dusty, Self-obscured Transients from Stellar Coalescence
Authors: Morgan MacLeod, Kishalay De, Abraham Loeb
Figure caption: Predicted obscuration in the context of the HRD. This figure adopts wind and torus models with q = 1/3. The primary star’s properties are realized from MIST stellar tracks of solar metallicity. The lower-mass, extended-radii primary stars that lead to the highest predicted A  V  occur on the giant branch of primary stars with M * ≲ 4 M ⊙. These systems have low T eff ≲ 4000 K, and relatively high luminosities of L ≳ 102  L ⊙. By contrast, the progenitors of optical LRNe have a wide range of masses, but a narrow range of temperatures, primarily being mildly evolved yellow giants crossing the Hertzsprung gap, properties that correspond to low levels of pre-outburst obscuration.
Paper: Dusty, Self-obscured Transients from Stellar Coalescence
Authors: Morgan MacLeod, Kishalay De, Abraham Loeb
Figure caption: Relative population of merger transients as a function of the primary-star mass. In this model, we assume all mergers have q = 1/3. We compute the predicted A  V  along MIST solar metallicity tracks, and show the fractions of merging systems with low, intermediate, and high A  V , assuming a logarithmic merging separation distribution. Among the approximately solar-mass stars, on the order of half of the transients will be highly dust-obscured, primarily infrared transients. As we consider higher mass systems, a greater fraction will be primarily optical transients.
Paper: Dusty, Self-obscured Transients from Stellar Coalescence
Authors: Morgan MacLeod, Kishalay De, Abraham Loeb
Figure caption: Predicted obscuration just prior to merger in the wind and torus (equatorial line of sight) models given the primary-star mass and radius. Each model assumes q = 1/3. The progenitor properties of known LRNe are marked with diamonds. In both models, low-mass, extended-radius primary stars should lead to highly dust-obscured transients, in some cases reaching A  V  ≫ 10. By contrast, more compact or massive primary stars should lead to low levels of pre-outburst obscuration. The observed population of optical LRNe traces predicted A  V  ≲ 1 in either model.
Paper: Dusty, Self-obscured Transients from Stellar Coalescence
Authors: Morgan MacLeod, Kishalay De, Abraham Loeb
Figure caption: Time evolution of the orbital period, circumbinary mass-loss rate, and optical obscuration, in an example merging binary system. This system consists of an M * = M ⊙, R * =  30 R ⊙ primary star unstably transferring mass to an M ⊙/3 companion. We integrate this example until the separation equals R * and the pair merges. In both the wind and torus models of pre-outburst obscuration, the degree of obscuration increases as the mass loss intensifies and the system’s merger approaches.
Paper: Dusty, Self-obscured Transients from Stellar Coalescence
Authors: Morgan MacLeod, Kishalay De, Abraham Loeb
Figure caption: Predicted obscuration in the context of the primary star’s binding energy and luminosity; otherwise identical to Figure 4. Low-binding-energy primary stars are those that are more likely to lead to successful common envelope ejection in interactions with a companion object. We find that a low binding energy correlates with predictions of highly obscured mergers, while higher binding energies have low predicted A  V . The population of optical LRNe traces the low-obscuration, high binding energy phase space of merger outcomes.
Paper: Dusty, Self-obscured Transients from Stellar Coalescence
Authors: Morgan MacLeod, Kishalay De, Abraham Loeb
Figure caption: The characteristic radius of dust formation in LRNe as measured by r 90 and as predicted by various models. The thermal equilibrium dust formation radii are much larger than r 90 for all of the observed systems, which are better modeled by virialized ejecta with f vir ∼ 10−2 and β ∼ 1. The constant virial fraction implied by β ∼ 1 is highly suggestive of internal shocks shaping the ejecta thermodynamics.
Paper: Gravitational Wave Sources in Our Galactic Backyard: Predictions for BHBH, BHNS, and NSNS Binaries Detectable with LISA
Authors: T. Wagg, F. S. Broekgaarden, S. E. de Mink, N. Frankel, L. A. C. van Son, S. Justham
Figure caption: Properties of detectable systems for a 4 yr LISA mission in our fiducial model. Each panel shows a kernel density estimator for a single property, colored by DCO type. Each curve has been normalized individually. The shaded areas show the 1σ and 2σ sampling uncertainties (obtained via bootstrapping). The dotted line in panel (e) shows the star formation history we have assumed in our Milky Way model. See Section 3.2 for a discussion. </>
Paper: Gravitational Wave Sources in Our Galactic Backyard: Predictions for BHBH, BHNS, and NSNS Binaries Detectable with LISA
Authors: T. Wagg, F. S. Broekgaarden, S. E. de Mink, N. Frankel, L. A. C. van Son, S. Justham
Figure caption: The LISA sensitivity curve is shown together with the density distribution of the characteristic strain and the dominant frequency for all detectable sources in our simulations (top) and separated by type (bottom). Contours show the percentage of the enclosed population. The remaining 2% of the population is shown as dots with a size that scales with the sampling weight. To guide the interpretation, we show reference lines marking where a circular binary would reside for a given distance (diagonal line) and the remaining inspiral time (vertical lines), assuming an average chirp mass ﹩\left\langle {{ \mathcal M }}_{c}\right\rangle ﹩, orientation, and sky location. The colored lines in the bottom panels show a contour that encloses 90% of the population that is circular. LISA verification binaries are overplotted in the top panel (stars). See also Figure F2 and Section 3.1 for a discussion. </>
Paper: Resolving the Peak of the Black Hole Mass Spectrum
Authors: Ebraheem Farag, Mathieu Renzo, Robert Farmer, Morgan T. Chidester, F. X. Timmes
Figure caption: The location of the lower edge of the BH mass gap as a function of the temperature-dependent uncertainty in the 12C(α,γ)16O reaction rate. The dark purple line marks the revised lower mass gap boundary calculated in this work using the updated 12C(α,γ)16O adopted in Mehta et al. (2022) and f 3α  = 1 (Angulo et al. 1999). The orange line marks the revised lower mass gap boundary calculated in this work using the updated 12C(α,γ)16O adopted in Mehta et al. (2022) and f 3α  = 1.378 (Kibedi et al. 2020). The white region denotes the mass gap and the yellow–orange regions highlight the differences between the models computed with f 3α  = 1 and f 3α  = 1.378 with the same uncertainty in 12C(α,γ)16O. All the BH masses with M BH≥45 M ⊙ included in GWTC-3 are shown with the dark red points, with the blue error bars showing the uncertainty in their inferred mass. The approximate astrophysical S-factor corresponding to each probability distribution function–sourced σ value is labeled on the top of the x-axis.
Paper: Resolving the Peak of the Black Hole Mass Spectrum
Authors: Ebraheem Farag, Mathieu Renzo, Robert Farmer, Morgan T. Chidester, F. X. Timmes
Figure caption: The location of the lower edge of the BH mass gap as a function of the temperature-dependent uncertainty in the 12C(α,γ)16O reaction rate. The lines mark the lower mass gap boundaries predicted by the adopted 12C(α,γ)16O rate uncertainties. The pink line marks the lower mass gap boundary as found in Figure 5 of Farmer et al. (2020), predicted by the Kunz et al. (2002) rate as expressed in the STARLIB reaction rate library (Sallaska et al. 2013). The dark purple line marks the lower mass gap boundary predicted by models adopting the resolution from Farmer et al. (2020) and the original 52–temperature point 12C(α,γ)16O rate provided by deBoer et al. (2017). The coral blue line marks the lower mass gap boundary using the updated 12C(α,γ)16O calculated and implemented in Mehta et al. (2022). The dark blue line marks the revised lower mass gap boundary calculated in this work using the updated 12C(α,γ)16O adopted in Mehta et al. (2022). Note that σ[12C(α,γ)16O] represent different astrophysical S-factors for each rate source.
Paper: Gravitational Wave Sources in Our Galactic Backyard: Predictions for BHBH, BHNS, and NSNS Binaries Detectable with LISA
Authors: T. Wagg, F. S. Broekgaarden, S. E. de Mink, N. Frankel, L. A. C. van Son, S. Justham
Figure caption: A schematic illustrating how we model the Milky Way. The left panel illustrates the different model aspects: star formation history of three galactic components (individually shown in the dotted lines), radial distribution, metallicity-radius-time relation, and height distribution. The right panel shows an example instance of the Milky Way with 250,000 binaries shown as points colored by metallicity. The top panel shows a side-on view and the bottom panel a face-on view. </>