adsabs/AstroCLIMB huggingface dataset:
Paper: A New X-Ray and Radio Burst Activity from the Magnetar SGR 1935+2154
Authors: Noor S. Rehan, Alaa I. Ibrahim
Figure caption: The fluence–duration correlation of the 2022-10 burst activity of SGR 1935+2154 and those since 2020 April with their 2D kernel density, fitted to a power law. The power-law index of each activity is shown; see also Section 4.2. In this correlation and also that of ﹩{R}_{\mathrm{BB}}^{2}\mbox{--}{{kT}}_{\mathrm{BB}}﹩ shown in Figure 5, the 2021–2022 activities show a comparable trend whereas that of 2020-04 shows a different pattern. Also shown are the X-ray bursts with radio counterparts in 2022-10 (XFRB9, Konus, 20–500 keV; GECAM, 20–100 keV) and 2020-04 (XFRB1, INTEGRAL, 20–200 keV), annotated on all panels to illustrate how they compare with the bursts of each activity. See Sections 4.4 and 4.5.
Paper: A New X-Ray and Radio Burst Activity from the Magnetar SGR 1935+2154
Authors: Noor S. Rehan, Alaa I. Ibrahim
Figure caption: Top: box plots of the duration, flux, and fluence of the X-ray bursts with radio counterparts from SGR 1935+2154 during the 2022 and 2020 activities. Middle: The X-ray-to-radio ratio of the duration, flux, and fluence for each X-ray and radio burst pair. See Section 4.4. Bottom: Comparison between the duration of all X-ray bursts with radio counterparts from SGR 1935+2154 during the 2022 and 2020 activities and the duration range and mean of the activity as observed by the same instrument (mean represented by the dots along the range). The energy ranges of the instruments are INTEGRAL (20–200 keV), Konus Wind (20–320 keV), GECAM (20–100 keV), Fermi-GBM (8–200 keV), and Insight-HXMT (1–250 keV). In HXMT HE detector (20–250 keV), comparable to the other instruments above, XFRB1's duration is ∼ 350 ms, and the mean duration is 102 ms; no duration range is provided. See Section 4.4.
Paper: A New X-Ray and Radio Burst Activity from the Magnetar SGR 1935+2154
Authors: Noor S. Rehan, Alaa I. Ibrahim
Figure caption: Distributions of the spectral parameters (panels (a)–(f)) of the SGR 1935+2154 bursts during the 2022 October (2022-10) activity as observed by the Fermi-GBM (8–200 keV), based on the CPL (cutoff power-law) and 2BB (two blackbodies) models, fitted to a Gaussian function (see their mean in Table 4). The flux (cyan blue) and fluence (red) distributions are shown in panel (g), each fitted to a power law with indices of −1.53 ± 0.18 and −1.21 ± 0.19, respectively. Their ranges and the indices of the 2020-04 activity are indicated. Also shown are the values for the X-ray bursts with radio counterparts in 2022-10 (XFRB9, Konus–Wind, 20–500 keV) and 2020-04 (XFRB1, INTEGRAL, 20–200 keV); see Section 4.4.
Paper: A New X-Ray and Radio Burst Activity from the Magnetar SGR 1935+2154
Authors: Noor S. Rehan, Alaa I. Ibrahim
Figure caption: The duration distribution of the SGR 1935+2154 bursts during the 2022 October activity as observed by Fermi-GBM (8–200 keV). The black solid line histogram and curve represent the distribution and best-fit Gaussian of the observed 113 bursts on a logarithmic scale, with a mean of 122.14 ± 1.03 ms. The dashed red line histogram represents the distribution of the 101 bursts with sufficient counts for the spectral analysis, whose log-Gaussian mean is 127.06 ± 1.04 ms. The shaded region represents the kernel density estimation of the 113 bursts. The vertical lines indicate the duration of (a) the 2022 X-ray bursts associated with radio bursts from the magnetar, XFRB11 (Fermi-GBM, 8–200 keV), XFRB9 (Konus Wind, 20–320 keV, and GECAM, 20–100 keV), and XFRB10 (Insight-HXMT, 20–250 keV); and (b) the 2020 XFRB1 from INTEGRAL (20–200 keV) and the mean duration of the activity from Fermi-GBM (8–200 keV; 182 ms). See also Figure 7 and Table 5.
Paper: A New X-Ray and Radio Burst Activity from the Magnetar SGR 1935+2154
Authors: Noor S. Rehan, Alaa I. Ibrahim
Figure caption:                         A sample of the burst light curves representing the diversity of bursts emitted by SGR 1935+2154 during its 2022 October (2022-10) activity as observed by Fermi-GBM in the 8–200 keV energy range. The activity spanned 2022 September 27 to 2022 October 17. See Table 1 for the burst temporal properties. Figure 10 of the Appendix gives the full catalog of light curves.
Paper: A New X-Ray and Radio Burst Activity from the Magnetar SGR 1935+2154
Authors: Noor S. Rehan, Alaa I. Ibrahim
Figure caption: The mean burst properties of all the burst activities of SGR 1935+2154. See Sections 4.1, 4.2, and 4.3. T100, nγ, ﹩{R}_{\mathrm{BBh}}^{2}﹩, ﹩{R}_{\mathrm{BBs}}^{2}﹩, fluence (S), and flux (F) are plotted on a vertical log scale. All others and the horizontal axis are plotted on a linear scale.
Paper: A New X-Ray and Radio Burst Activity from the Magnetar SGR 1935+2154
Authors: Noor S. Rehan, Alaa I. Ibrahim
Figure caption: The light curve of the faint X-ray burst associated with radio burst FRB11 (XFRB11) from SGR 1935+2154 on 2022 December 1 as observed by Fermi-GBM (8–200 keV). The burst has a duration and a total number of counts of 0.65 ± 0.31 s and 1743 (141 background-subtracted counts), respectively.
Paper: A New X-Ray and Radio Burst Activity from the Magnetar SGR 1935+2154
Authors: Noor S. Rehan, Alaa I. Ibrahim
Figure caption: The light curves of the bursts from SGR 1935+2154 during the 2022 October activity observed by the Fermi-GBM in the 8–200 keV energy range.
Paper: A New X-Ray and Radio Burst Activity from the Magnetar SGR 1935+2154
Authors: Noor S. Rehan, Alaa I. Ibrahim
Figure caption: Comparison between the duration, fluence, and luminosity ranges (blue) of SGR 1935+2154 bursts during its 2020 and 2022 activity. 2020 X-ray bursts are from all available observations of the source: Swift-BAT (in preparation), INTEGRAL IBIS (S. Mereghetti et al. 2020), Fermi-GBM (L. Lin et al. 2020b), and Insight HXMT (C. Cai et al. 2022a). The luminosity is obtained at a distance of 9 kpc for SGR 1935+2154. The luminosity range comparison also holds for the flux. The respective means are marked in red. The shorter bursts and the similar average make the fluence average lower than other samples.
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: Evolutionary tracks on the ﹩\mathrm{log}\ {T}_{\mathrm{eff}}﹩–﹩\mathrm{log}\ g﹩ diagram obtained from PARSEC 1.2S. The left panel shows the evolutionary tracks with different M i for Z = 0.02, Y = 0.284. The orange solid lines represent the main sequence (MS) selected based on the central hydrogen mass fraction, and the blue dashed–dotted lines shows the post–main sequence (post MS). The right panel shows the distribution of the mock data selected from PARSEC 1.2S. The different colors represent the M i. The parameters of the selected sample are indicated in the top left.
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: The T eff–﹩\mathrm{log}\ g﹩, T eff–[M/H], and [M/H]–log g distributions of the mock data and prediction sample are shown. The blue bins represent the distribution of the sample selected from M. Xiang et al. (2022), while the red wireframes indicate the ranges of T eff, ﹩\mathrm{log}g﹩, and [M/H] for our mock data from PARSEC 1.2S.
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: The prediction results of our trained model on the testing set. Different rows represent the predictions of L, M, t, and M i, and from left to right, the columns indicate the direct comparisons, absolute errors, and relative errors between the true values and predictions, respectively. Each panel is labeled with the value of dispersion or the mean and median of the error in the top-left corner.
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: The distribution of [M/H] in the catalogs of M. Xiang et al. (2022) (left) and Y. Guo et al. (2021) (right), showing only stars with S/N greater than 15.
Paper: A Compilation of Optical Starlight Polarization Catalogs
Authors: G. V. Panopoulou, L. Markopoulioti, F. Bouzelou, M. A. Millar-Blanchaer, S. Tinyanont, D. Blinov, V. Pelgrims, S. Johnson, R. Skalidis, A. Soam
Figure caption: Properties of the sources with successful crossmatches between C. Heiles (2000) and Gaia DR2. Top left: Angular separations between original coordinates given in catalog and the final Gaia matches in arcseconds. Does not include 56 sources with separations larger than 30″. Top right: Same as top left, but showing only the 56 sources with angular separations larger than 0.′5, note the change of horizontal axis units to arcminutes. Bottom left: distribution of G-band magnitudes of the successful matches from Gaia DR2. Bottom right: Comparison between Gaia G-band magnitudes and V-band magnitudes originally reported in C. Heiles (2000) for all sources with both G- and V- measurements. We overlay a fit to the data (red line) excluding sources with V = 0 (these are erroneous). The slope and intercept are shown in the legend. We also overlay the fit from the crossmatch of C. Heiles (2000) with Gaia DR2 from M.-n. Meng & X.-h. Sun (2021; cyan line), which shows a similar slope but very different intercept (see text).
Paper: Simulating a Steady-state Heliosphere
Authors: Jacob Heerikhuisen, Eric J. Zirnstein, Nikolai V. Pogorelov
Figure caption: Meridional slices of the magnetic field magnitude (left) and proton density (middle) for the plasma configuration from which three of the plasma–neutral models start. In both plots the contour lines are computed on a logarithmic scale to highlight the geometry of the low-density and low magnetic field regions inside the heliosphere. The right-hand plot shows the plasma density along the LISM flow axis on a logarithmic scale.
Paper: Simulating a Steady-state Heliosphere
Authors: Jacob Heerikhuisen, Eric J. Zirnstein, Nikolai V. Pogorelov
Figure caption: Meridional slices of the proton density for the four models considered, after the plasma has evolved for 100 yr (top row), 200 yr (middle row), and 400 yr (bottom row) from the initial condition. Here the color scale is linear, while contour lines have been added on a logarithmic scale to highlight the geometry of the low-density region downstream of the heliosphere.
Paper: Simulating a Steady-state Heliosphere
Authors: Jacob Heerikhuisen, Eric J. Zirnstein, Nikolai V. Pogorelov
Figure caption: Meridional slices of the magnetic field magnitude for the four models considered, after the plasma has evolved for 200 yr from the initial condition. Here the color scale is linear, while contour lines have been added on a logarithmic scale to highlight the geometry of the weaker field emanating from the polar regions of the Sun.
Paper: Simulating a Steady-state Heliosphere
Authors: Jacob Heerikhuisen, Eric J. Zirnstein, Nikolai V. Pogorelov
Figure caption: Proton density along the LISM flow axis for the four models considered, taken at different times after the initial condition. Here Models I–III have converged after 400 yr, while Model IV needs at least another 400 yr to reach the same steady state.
Paper: Simulating a Steady-state Heliosphere
Authors: Jacob Heerikhuisen, Eric J. Zirnstein, Nikolai V. Pogorelov
Figure caption: Contours of plasma temperature in the solar equatorial plane (bottom row) and meridional plane (top row) taken 200 yr after the initial condition.
Paper: Simulating a Steady-state Heliosphere
Authors: Jacob Heerikhuisen, Eric J. Zirnstein, Nikolai V. Pogorelov
Figure caption: Illustration of the density gradient method (Equation (1)) for locating the HP, at t = 200 yr (top row) and once a steady state has been achieved (bottom row). Here we plot two contours (c = 0.03 in blue, and c = 0.06 in red) of the density gradient perpendicular to the plasma flow, along with the temperature contour T = 100,000 K (dotted).
Paper: Simulating a Steady-state Heliosphere
Authors: Jacob Heerikhuisen, Eric J. Zirnstein, Nikolai V. Pogorelov
Figure caption: Contours of plasma temperature in the solar equatorial plane after 400 yr (Models I–III) and 800 yr (Model IV). By this time all four models have reached the same steady-state configuration.
Paper: Simulating a Steady-state Heliosphere
Authors: Jacob Heerikhuisen, Eric J. Zirnstein, Nikolai V. Pogorelov
Figure caption: Steady-state heliosphere (at t = 800 yr) for Model IV showing HP surface (green), SW streamlines (blue), and SW magnetic field lines (red). Note that the field lines were generated using multiple starting locations designed to best indicate the hoop structure in the heliotail. The isosurface on the right side of the plot shows the plasma flow speed at x = −1400 au. The row of plots below represent the source of plasma that reaches x = −1400 au. Streamlines as traced backwards and plasma of solar origin is colored pink, while plasma from the LISM is colored cyan.
Paper: A Compilation of Optical Starlight Polarization Catalogs
Authors: G. V. Panopoulou, L. Markopoulioti, F. Bouzelou, M. A. Millar-Blanchaer, S. Tinyanont, D. Blinov, V. Pelgrims, S. Johnson, R. Skalidis, A. Soam
Figure caption: Consistency of star polarization measurements for stars in common between C. Heiles (2000) and other catalogs. Top: relative difference between the polarization fraction measured in two separate catalogs, as a function of the comparison catalog RefID. Bottom: same but for relative difference of the polarization angle. Blue circles mark individual stars, while black points mark the median value of the distribution of relative differences for stars in a specific comparison catalog. Error bars denote the 15th and 84th percentiles of the distribution of differences per comparison catalog. Note the large discrepancies between PA measured in catalog 29 (F. P. Santos et al. 2011) compared to that of C. Heiles (2000).
Paper: A Compilation of Optical Starlight Polarization Catalogs
Authors: G. V. Panopoulou, L. Markopoulioti, F. Bouzelou, M. A. Millar-Blanchaer, S. Tinyanont, D. Blinov, V. Pelgrims, S. Johnson, R. Skalidis, A. Soam
Figure caption: Properties of Gaia EDR3 sources in the unique source catalog. Left: distribution of G-band magnitude. Right: distribution of the distance estimate r_med_photogeo for sources with SNR in distance >3 and not in the A. Lobo Gomes et al. (2015) catalog (see text).
Paper: A Compilation of Optical Starlight Polarization Catalogs
Authors: G. V. Panopoulou, L. Markopoulioti, F. Bouzelou, M. A. Millar-Blanchaer, S. Tinyanont, D. Blinov, V. Pelgrims, S. Johnson, R. Skalidis, A. Soam
Figure caption: Polarization properties of measurements in the extended catalog. Left: distribution of debiased polarization percentage for all measurements (black) and for significant detections (SNR p  ≥ 3) (red). Right: distribution of SNR of p for all measurements with non-NAN e  p .
Paper: A Compilation of Optical Starlight Polarization Catalogs
Authors: G. V. Panopoulou, L. Markopoulioti, F. Bouzelou, M. A. Millar-Blanchaer, S. Tinyanont, D. Blinov, V. Pelgrims, S. Johnson, R. Skalidis, A. Soam
Figure caption: Polarization properties of measurements in the unique source catalog. Left: 2D distribution of the logarithm of e  p (%) vs. G-band magnitude. Right: 2D distribution of SNR of p vs. G-band magnitude. In both panels, the color scale is logarithmic.
Paper: A Compilation of Optical Starlight Polarization Catalogs
Authors: G. V. Panopoulou, L. Markopoulioti, F. Bouzelou, M. A. Millar-Blanchaer, S. Tinyanont, D. Blinov, V. Pelgrims, S. Johnson, R. Skalidis, A. Soam
Figure caption: Map of the number of polarization measurements in the catalog per Nside = 64 pixel (∼1°) in Mollweide projection. The map is centered on (l, b) = (0°, 0°). White pixels contain no measurements. The inset shows the distribution of galactic latitudes of the stellar polarization measurements on a semilogarithmic axis.
Paper: A Compilation of Optical Starlight Polarization Catalogs
Authors: G. V. Panopoulou, L. Markopoulioti, F. Bouzelou, M. A. Millar-Blanchaer, S. Tinyanont, D. Blinov, V. Pelgrims, S. Johnson, R. Skalidis, A. Soam
Figure caption: Distribution of measurements in the various filters within the extended catalog. The vertical axis shows the logarithm of the number of data points in each filter (specified by the FilterID, see Table 2).
Paper: Prediction of Large Solar Flares Based on SHARP and High-energy-density Magnetic Field Parameters
Authors: Xuebao Li, Xuefeng Li, Yanfang Zheng, Ting Li, Pengchao Yan, Hongwei Ye, Shunhuang Zhang, Xiaotian Wang, Yongshang Lv, Xusheng Huang
Figure caption: The histogram depicts the mean and standard deviation of TSS and BSS for each individual HED parameter in ≥M class flare prediction. Specifically, panel (A) signifies the mean and standard deviation of TSS, while panel (B) denotes the mean and standard deviation of BSS, both of which are sorted in descending order. The “bar” denotes the standard deviation.
Paper: Prediction of Large Solar Flares Based on SHARP and High-energy-density Magnetic Field Parameters
Authors: Xuebao Li, Xuefeng Li, Yanfang Zheng, Ting Li, Pengchao Yan, Hongwei Ye, Shunhuang Zhang, Xiaotian Wang, Yongshang Lv, Xusheng Huang
Figure caption: The line chart illustrates the mean and standard deviation of BSS during the sequential reduction of SHARP parameters in predicting ≥M-class flares. Panel (A) represents the mean and standard deviation of BSS as the most important SHARP parameters are sequentially removed, starting from the most important. Panel (B) shows the mean and standard deviation of BSS as the least important SHARP parameters are sequentially removed, starting from the least important. The x-axis coordinates represent the combination of a parameter with all parameters to its right.
Paper: Prediction of Large Solar Flares Based on SHARP and High-energy-density Magnetic Field Parameters
Authors: Xuebao Li, Xuefeng Li, Yanfang Zheng, Ting Li, Pengchao Yan, Hongwei Ye, Shunhuang Zhang, Xiaotian Wang, Yongshang Lv, Xusheng Huang
Figure caption: The line chart illustrates the mean and standard deviation of BSS during the sequential reduction of HED parameters in predicting ≥M-class flares. Panel (A) represents the mean and standard deviation of BSS as the most important HED parameters are sequentially removed, starting from the most important. Panel (B) shows the mean and standard deviation of BSS as the least important HED parameters are sequentially removed, starting from the least important. The x-axis coordinates represent the combination of a parameter with all parameters to its right.
Paper: Prediction of Large Solar Flares Based on SHARP and High-energy-density Magnetic Field Parameters
Authors: Xuebao Li, Xuefeng Li, Yanfang Zheng, Ting Li, Pengchao Yan, Hongwei Ye, Shunhuang Zhang, Xiaotian Wang, Yongshang Lv, Xusheng Huang
Figure caption: The line chart illustrates the mean and standard deviation of TSS during the sequential reduction of HED parameters in predicting ≥M-class flares. Panel (A) represents the mean and standard deviation of TSS as the most important HED parameters are sequentially removed, starting from the most important. Panel (B) shows the mean and standard deviation of TSS as the least important HED parameters are sequentially removed, starting from the least important. The x-axis coordinates represent the combination of a parameter with all parameters to its right.
Paper: Prediction of Large Solar Flares Based on SHARP and High-energy-density Magnetic Field Parameters
Authors: Xuebao Li, Xuefeng Li, Yanfang Zheng, Ting Li, Pengchao Yan, Hongwei Ye, Shunhuang Zhang, Xiaotian Wang, Yongshang Lv, Xusheng Huang
Figure caption: The line chart illustrates the mean and standard deviation of TSS during the sequential reduction of SHARP parameters in predicting ≥M-class flares. Panel (A) represents the mean and standard deviation of TSS as the most important SHARP parameters are sequentially removed, starting from the most important. Panel (B) shows the mean and standard deviation of TSS as the least important SHARP parameters are sequentially removed, starting from the least important. The x-axis coordinates represent the combination of a parameter with all parameters to its right.
Paper: Prediction of Large Solar Flares Based on SHARP and High-energy-density Magnetic Field Parameters
Authors: Xuebao Li, Xuefeng Li, Yanfang Zheng, Ting Li, Pengchao Yan, Hongwei Ye, Shunhuang Zhang, Xiaotian Wang, Yongshang Lv, Xusheng Huang
Figure caption: The histogram depicts the mean and standard deviation of TSS and BSS for each individual SHARP parameter in ≥M class flare prediction. Specifically, panel (A) signifies the mean and standard deviation of TSS, while panel (B) denotes the mean and standard deviation of BSS, both of which are sorted in descending order. The “bar” denotes the standard deviation.
Paper: Prediction of Large Solar Flares Based on SHARP and High-energy-density Magnetic Field Parameters
Authors: Xuebao Li, Xuefeng Li, Yanfang Zheng, Ting Li, Pengchao Yan, Hongwei Ye, Shunhuang Zhang, Xiaotian Wang, Yongshang Lv, Xusheng Huang
Figure caption: The figure depicts the training loss curves and validation loss curves of a transformer model using HED parameters in ≥M class flare prediction. Panel (A) signifies the training loss curves, while panel (B) denotes the validation loss curves. The 10 different colored curves represent the changes of training and validation loss with epochs for the model trained and validated by 10 separate data sets.
Paper: Prediction of Large Solar Flares Based on SHARP and High-energy-density Magnetic Field Parameters
Authors: Xuebao Li, Xuefeng Li, Yanfang Zheng, Ting Li, Pengchao Yan, Hongwei Ye, Shunhuang Zhang, Xiaotian Wang, Yongshang Lv, Xusheng Huang
Figure caption: The line chart illustrates the mean and standard deviation of TSS and BSS during the reduction of AR numbers in predicting ≥M-class flares. Panel (A) represents the mean and standard deviation of TSS as the number of AR gradually decreases. Panel (B) shows the mean and standard deviation of BSS as the number of AR gradually decreases. The x-axis coordinates represent the reduced number of ARs.
Paper: Prediction of Large Solar Flares Based on SHARP and High-energy-density Magnetic Field Parameters
Authors: Xuebao Li, Xuefeng Li, Yanfang Zheng, Ting Li, Pengchao Yan, Hongwei Ye, Shunhuang Zhang, Xiaotian Wang, Yongshang Lv, Xusheng Huang
Figure caption: The procedure for generating 10-fold cross-validation set divisions for the SHARP/HED data sets.
Paper: Prediction of Large Solar Flares Based on SHARP and High-energy-density Magnetic Field Parameters
Authors: Xuebao Li, Xuefeng Li, Yanfang Zheng, Ting Li, Pengchao Yan, Hongwei Ye, Shunhuang Zhang, Xiaotian Wang, Yongshang Lv, Xusheng Huang
Figure caption: The architecture of the BiLSTM-Attention model.
Paper: Prediction of Large Solar Flares Based on SHARP and High-energy-density Magnetic Field Parameters
Authors: Xuebao Li, Xuefeng Li, Yanfang Zheng, Ting Li, Pengchao Yan, Hongwei Ye, Shunhuang Zhang, Xiaotian Wang, Yongshang Lv, Xusheng Huang
Figure caption: The architecture of the transformer model.
Paper: Mass, Luminosity, and Stellar Age of Early-type Stars from the LAMOST Survey
Authors: Qida Li, Jianping Xiong, Jiao Li, Yanjun Guo, Zhanwen Han, Xuefei Chen, Chao Liu
Figure caption: The T eff–﹩\mathrm{log}\ g﹩–[M/H] distribution of M. Xiang et al. (2022) in three-dimensional space. The catalog is divided into bins in three-dimensional space, and the scatter points mean the center coordinates of each bin. The polyhedron represents the convex hull created using T eff, ﹩\mathrm{log}\ g﹩, and [M/H] of the mock data. There are two types of points here. The circular ones indicate they are within the convex hull, and the triangular ones indicate they are outside the convex hull. The color shows the count of each bin.