adsabs/AstroCLIMB huggingface dataset:
Paper: It’s a Breeze: The Circumgalactic Medium of a Dwarf Galaxy Is Easy to Strip
Authors: Jingyao Zhu, Stephanie Tonnesen, Greg L. Bryan, Mary E. Putman
Figure caption: Azimuthally averaged gas surface density radial profiles (Σgas(R); see Section 4.3). Left: Σgas(R) time evolution under RPS. The black curves show MW-w from pre- to post-pericentric times, and the filled gray curve shows iso over the same time range. Middle: comparison between MW-w with and without the satellite CGM at t post, showing the respective iso control cases for reference. Lines are in the same style as Figure 4. Right: comparison among the three cases with CGM at t post. The McCarthy et al. (2008) stripping criteria evaluated at MW-w and weak-w peak ram pressure given our modeled Burkert dark matter profile are shown in solid and dotted black curves, respectively; the gray lines show the same thresholds when adopting an NFW profile instead; see Section 4.3 for details. We shaded the projected disk region (all panels) and the dark matter core region (right panel) as in Figure 2.
Paper: It’s a Breeze: The Circumgalactic Medium of a Dwarf Galaxy Is Easy to Strip
Authors: Jingyao Zhu, Stephanie Tonnesen, Greg L. Bryan, Mary E. Putman
Figure caption: Ram pressure thresholds (P ram,thresh) predicted for the WLM-like dwarf galaxy stripping (Section 3). The solid curve shows the radial profile of P ram,thresh across the entire dwarf galaxy (McCarthy et al. 2008; see Equation (5)), and the dashed horizontal line shows the core stripping criterion (Mori & Burkert 2000; see Equation (3)). The lighter- and darker-shaded regions show the projected disk and core regions, respectively. Where the solid curve intersects with ﹩R={r}_{\mathrm{disk}}/\sqrt{2}﹩ is the predicted CGM stripping condition, which motivated our modeling of the weak-w orbit (orange symbol; see Section 2.2).
Paper: It’s a Breeze: The Circumgalactic Medium of a Dwarf Galaxy Is Easy to Strip
Authors: Jingyao Zhu, Stephanie Tonnesen, Greg L. Bryan, Mary E. Putman
Figure caption: Simulation initial conditions. Left: temperature and density radial profiles at t = 0 Myr, defined as the moment wind enters the box after the CGM relaxation phase (Section 2.1). The solid lines show the density and temperature averages on the right- and left-hand y-axis, respectively, and the red-shaded region shows the temperature standard deviation (±σ  T ). The dwarf CGM extends beyond r vir ≈ 42 kpc to about 60 kpc. Right: gas temperature slice (at x = 0 kpc, edge-on). The dashed white circle annotates the disk–halo transition radius (r disk = 5.2 kpc;  see dashed line in the left panel and Section 2.1). Gas in the disk and inner halo is turbulent and multiphase.
Paper: It’s a Breeze: The Circumgalactic Medium of a Dwarf Galaxy Is Easy to Strip
Authors: Jingyao Zhu, Stephanie Tonnesen, Greg L. Bryan, Mary E. Putman
Figure caption: Instantaneous RPS criteria (McCarthy et al. 2008) for an LMC-like CGM, in a similar style as Figure 2. The line styles represent different power-law indices α adopted for the CGM profile (Equation (1)), where the total mass M CGM,LMC = 8.3 × 109 M ⊙ follows Lucchini et al. (2020, 2021). The profiles extend out to r vir,LMC ≈ 117 kpc (outermost radii not shown in this Figure). The horizontal lines show the P ram values at the MW pericenter, L21: Lucchini et al. (2021); MW-w: this work (Table 2); S15: Salem et al. (2015). In this calculation, we omit the ISM/disk region (here adopted to be R ≤ 5 kpc; shaded).
Paper: It’s a Breeze: The Circumgalactic Medium of a Dwarf Galaxy Is Easy to Strip
Authors: Jingyao Zhu, Stephanie Tonnesen, Greg L. Bryan, Mary E. Putman
Figure caption: Dwarf satellite ISM mass-loss curves under the Milky Way fiducial wind, showing ﹩{\rm{\Delta }}M{| }_{{t}_{0}}^{t}﹩: the ISM mass at time t minus that at a pre-ISM stripping time (t 0 = 700 Myr, Figure 3). ΔM is corrected for gas consumption by star formation; see Section 4.2. The shaded region annotates the effective ISM stripping phase (Section 4.1). The similar ISM mass-loss rates with and without a CGM suggest that the CGM shielding effect is weak.
Paper: Anomaly Detection and Approximate Similarity Searches of Transients in Real-time Data Streams
Authors: P. D. Aleo, A. W. Engel, G. Narayan, C. R. Angus, K. Malanchev, K. Auchettl, V. F. Baldassare, A. Berres, T. J. L. de Boer, B. M. Boyd, K. C. Chambers, K. W. Davis, N. Esquivel, D. Farias, R. J. Foley, A. Gagliano, C. Gall, H. Gao, S. Gomez, M. Grayling, D. O. Jones, C.-C. Lin, E. A. Magnier, K. S. Mandel, T. Matheson, S. I. Raimundo, V. G. Shah, M. D. Soraisam, K. M. de Soto, S. Vicencio, V. A. Villar, R. J. Wainscoat
Figure caption: Stacked light curve (left panel) and grid of host galaxy thumbnails (right panel) of Type Ia SN 2021ixf (bold) and its eight approximate nearest neighbors within 120 day feature-space (faded). The similarity search in our database was completed in only 3 ms. Note that we do not include SN type or redshift information in the similarity search. Thus, the similar light-curve evolution, SN types, redshift values, and host galaxy environments are as a result of the close proximity of SN 2021ixf and its neighbors in 120-dimensional feature-space.
Paper: Anomaly Detection and Approximate Similarity Searches of Transients in Real-time Data Streams
Authors: P. D. Aleo, A. W. Engel, G. Narayan, C. R. Angus, K. Malanchev, K. Auchettl, V. F. Baldassare, A. Berres, T. J. L. de Boer, B. M. Boyd, K. C. Chambers, K. W. Davis, N. Esquivel, D. Farias, R. J. Foley, A. Gagliano, C. Gall, H. Gao, S. Gomez, M. Grayling, D. O. Jones, C.-C. Lin, E. A. Magnier, K. S. Mandel, T. Matheson, S. I. Raimundo, V. G. Shah, M. D. Soraisam, K. M. de Soto, S. Vicencio, V. A. Villar, R. J. Wainscoat
Figure caption: The unweighted percentage (top panel) and weighted (bottom panel) percentage relative to the fraction present in our original databank (blue) of the retroactive SNe candidate discoveries recovered by our ANN = 8 search method (gold) and exhaustive method (green). From both methods combined, we recover nearly equal numbers from 2018 and 2021 (134 out of 325 (41%) and 131 out of 325 (40%), respectively). However, relative to the yearly fractions that comprise our databank, we find that the fraction of our total 2018 discoveries relative to all discoveries from this work (41%) is nearly 3 times that of the fraction relative to that which comprise our databank (11%), whereas our total 2021 discoveries (40%) make up nearly two-thirds relative to our databank (62%). Overall, the weighted fraction of discoveries is greatest in 2018, the first full year of the ZTF survey, and decreasing every year through 2022, implying an improvement in detection and reporting methods via increasing numbers of active broker teams in the ZTF Alert Stream.
Paper: Anomaly Detection and Approximate Similarity Searches of Transients in Real-time Data Streams
Authors: P. D. Aleo, A. W. Engel, G. Narayan, C. R. Angus, K. Malanchev, K. Auchettl, V. F. Baldassare, A. Berres, T. J. L. de Boer, B. M. Boyd, K. C. Chambers, K. W. Davis, N. Esquivel, D. Farias, R. J. Foley, A. Gagliano, C. Gall, H. Gao, S. Gomez, M. Grayling, D. O. Jones, C.-C. Lin, E. A. Magnier, K. S. Mandel, T. Matheson, S. I. Raimundo, V. G. Shah, M. D. Soraisam, K. M. de Soto, S. Vicencio, V. A. Villar, R. J. Wainscoat
Figure caption: Same as Figures 9, 10 but for TDE 2021gje/ZTF21aapvvtb. In this case, ANN = 2 (AT 2021ovg/ZTF21aazenvp) was previously reported to TNS but never previously identified as a TDE candidate until this work (FLEET = 85% TDE), and ANN = 6 (AT 2021ahwl/ZTF21aasdcgt) is a missed TDE candidate (FLEET = 70% TDE; now reported to TNS from this work). We bold these new TDE candidates (dark green and dark red for ZTF-g and ZTF-r, respectively) for visual purposes. The similarity search in our database was completed in only ∼230 ms.
Paper: Anomaly Detection and Approximate Similarity Searches of Transients in Real-time Data Streams
Authors: P. D. Aleo, A. W. Engel, G. Narayan, C. R. Angus, K. Malanchev, K. Auchettl, V. F. Baldassare, A. Berres, T. J. L. de Boer, B. M. Boyd, K. C. Chambers, K. W. Davis, N. Esquivel, D. Farias, R. J. Foley, A. Gagliano, C. Gall, H. Gao, S. Gomez, M. Grayling, D. O. Jones, C.-C. Lin, E. A. Magnier, K. S. Mandel, T. Matheson, S. I. Raimundo, V. G. Shah, M. D. Soraisam, K. M. de Soto, S. Vicencio, V. A. Villar, R. J. Wainscoat
Figure caption: Same as Figure 9, but for Type Ia-91bg-like SN 2021jvp/ZTF21aawihwx. In this case, ANN = 5 (SN 2021abpz/ZTF21achjwus) and ANN = 7 (SN 2020yje/ZTF20acnznol) are in fact SN Ia-91bg-like SNe previously missclassified as SN Ia-normal after reexamination of their TNS classification spectra, prompted by the results of this similarity search (see Table 8). We bold these reclassified events (dark green and dark red for ZTF-g and ZTF-r, respectively) for visual purposes. The similarity search in our database was completed in only ∼300 ms.
Paper: Anomaly Detection and Approximate Similarity Searches of Transients in Real-time Data Streams
Authors: P. D. Aleo, A. W. Engel, G. Narayan, C. R. Angus, K. Malanchev, K. Auchettl, V. F. Baldassare, A. Berres, T. J. L. de Boer, B. M. Boyd, K. C. Chambers, K. W. Davis, N. Esquivel, D. Farias, R. J. Foley, A. Gagliano, C. Gall, H. Gao, S. Gomez, M. Grayling, D. O. Jones, C.-C. Lin, E. A. Magnier, K. S. Mandel, T. Matheson, S. I. Raimundo, V. G. Shah, M. D. Soraisam, K. M. de Soto, S. Vicencio, V. A. Villar, R. J. Wainscoat
Figure caption: Same as Figures 9–12, but for Type Ia SN 2022cox/ZTF18aaiwewk, overplotted with the best-fit SALT3 model (Kenworthy et al. 2021). In this case, even though SN 2022cox is poorly sampled after peak with a 30 day gap, we can see fuller light-curve evolution and accompanying host galaxies of analogs through the similarity search, providing useful insights as to the possible classification and redshift range as well as the possible (unobserved) light-curve evolution of our reference. The SALT3 fit provides additional context, and we observe that analog light-curve epochs are positioned on or near this curve. The similarity search in our database was completed in only ∼2 ms.
Paper: Anomaly Detection and Approximate Similarity Searches of Transients in Real-time Data Streams
Authors: P. D. Aleo, A. W. Engel, G. Narayan, C. R. Angus, K. Malanchev, K. Auchettl, V. F. Baldassare, A. Berres, T. J. L. de Boer, B. M. Boyd, K. C. Chambers, K. W. Davis, N. Esquivel, D. Farias, R. J. Foley, A. Gagliano, C. Gall, H. Gao, S. Gomez, M. Grayling, D. O. Jones, C.-C. Lin, E. A. Magnier, K. S. Mandel, T. Matheson, S. I. Raimundo, V. G. Shah, M. D. Soraisam, K. M. de Soto, S. Vicencio, V. A. Villar, R. J. Wainscoat
Figure caption: The Spearman rank-correlation matrix for the LAISS databank of extracted ZTF-g, ZTF-r light-curve and PS1-grizy host galaxy features (see Appendix B), with red corresponding to positively correlated features and blue corresponding to negatively correlated features. Broadly, the light-curve features that measure amplitude or amplitude-adjacent properties are correlated, more strongly intrapassband vs. interpassband. There exists strong positive correlations between brightness and radial moments of host galaxies in each band, forming a repeating block structure. From a high level, the correlation between light-curve features to host galaxy features is poor. Overall, these features are chosen to maximize color and capture related but different information of the supernova light curve and host galaxy, and to reduce the impact of dependent or irrelevant features.
Paper: Anomaly Detection and Approximate Similarity Searches of Transients in Real-time Data Streams
Authors: P. D. Aleo, A. W. Engel, G. Narayan, C. R. Angus, K. Malanchev, K. Auchettl, V. F. Baldassare, A. Berres, T. J. L. de Boer, B. M. Boyd, K. C. Chambers, K. W. Davis, N. Esquivel, D. Farias, R. J. Foley, A. Gagliano, C. Gall, H. Gao, S. Gomez, M. Grayling, D. O. Jones, C.-C. Lin, E. A. Magnier, K. S. Mandel, T. Matheson, S. I. Raimundo, V. G. Shah, M. D. Soraisam, K. M. de Soto, S. Vicencio, V. A. Villar, R. J. Wainscoat
Figure caption: Same as Figures 9–11, but for Type Ia SN 2020whs/ZTF20aciuftf. In this case, ANN = 1 (AT 2018mfm/ZTF18abnzney), ANN = 3 (AT 2021ahvn/ZTF21abcluco), and ANN = 5 (AT 2021ahvo/ZTF17aadqidc) were missed SNe candidates (now reported to TNS from this work). We bold these SN discoveries (dark green and dark red for ZTF-g and ZTF-r, respectively) for visual purposes. The similarity search in our database was completed in only ∼140 ms.
Paper: Galaxy–Absorber Association in the Epoch of Reionization: Galactic Population Luminosity Distribution for Different Absorbers at 10 ≥ z ≥ 5.5
Authors: Samir Kušmić, Kristian Finlator, Ezra Huscher, Maya Steen
Figure caption: Diagram illustrating our “HOSTGAL” analysis. First, we map the absorber’s position (red dashed bump) from velocity space along the sight line (blue dotted arrow) into physical coordinates. Then, we identify gas particles (green dots) that lie close enough to contribute based on their smoothing lengths h  s . If a gas particle is flagged as a wind particle, then its LLP is extracted, and we search the LLP grid cell looking around a cubical search buffer b. We link galaxies lying within that buffer to the gas particle and absorber and appended to an output reference catalog.
Paper: Galaxy–Absorber Association in the Epoch of Reionization: Galactic Population Luminosity Distribution for Different Absorbers at 10 ≥ z ≥ 5.5
Authors: Samir Kušmić, Kristian Finlator, Ezra Huscher, Maya Steen
Figure caption: Slice of the simulation with calculated column densities for C II and C IV in a 512 × 512 × 16 comoving grid for x, y, and z, respectively. Light gray areas indicate where the ion column density ﹩\mathrm{log}N/{\mathrm{cm}}^{-2}\lt 11﹩, while orange areas are where ﹩\mathrm{log}N/{\mathrm{cm}}^{-2}\gt 16.1﹩. The inset is a zoomed-in sphere of the center of the slice with a radius of 2000 ckpc h −1. Each plot is titled with the redshift of the snapshot and the depth of the slice in km s−1. The magenta dots are galaxies.
Paper: JCMT 850 μm Continuum Observations of Density Structures in the G35 Molecular Complex
Authors: Xianjin Shen, Hong-Li Liu, Zhiyuan Ren, Anandmayee Tej, Di Li, Hauyu Baobab Liu, Gary A. Fuller, Jinjin Xie, Sihan Jiao, Aiyuan Yang, Patrick M. Koch, Fengwei Xu, Patricio Sanhueza, Pham Ngoc Diep, Nicolas Peretto, R. K. Yadav, Busaba H. Kramer, Koichiro Sugiyama, Mark G. Rawlings, Chang Won Lee, Ken'ichi Tatematsu, Daniel Harsono, David Eden, Woojin Kwon, Chao-Wei Tsai, Glenn J. White, Kee-Tae Kim, Tie Liu, Ke Wang, Siju Zhang, Wenyu Jiao, Dongting Yang, Swagat R. Das, Jingwen Wu, Chen Wang
Figure caption: Filament skeletons overlaid on the column density map. The color of each structure represents its average dust temperature derived from Herschel observations.
Paper: JCMT 850 μm Continuum Observations of Density Structures in the G35 Molecular Complex
Authors: Xianjin Shen, Hong-Li Liu, Zhiyuan Ren, Anandmayee Tej, Di Li, Hauyu Baobab Liu, Gary A. Fuller, Jinjin Xie, Sihan Jiao, Aiyuan Yang, Patrick M. Koch, Fengwei Xu, Patricio Sanhueza, Pham Ngoc Diep, Nicolas Peretto, R. K. Yadav, Busaba H. Kramer, Koichiro Sugiyama, Mark G. Rawlings, Chang Won Lee, Ken'ichi Tatematsu, Daniel Harsono, David Eden, Woojin Kwon, Chao-Wei Tsai, Glenn J. White, Kee-Tae Kim, Tie Liu, Ke Wang, Siju Zhang, Wenyu Jiao, Dongting Yang, Swagat R. Das, Jingwen Wu, Chen Wang
Figure caption: NH3(1–1) line width (rainbow colors) overlaid on 850 μm continuum map (gray).
Paper: JCMT 850 μm Continuum Observations of Density Structures in the G35 Molecular Complex
Authors: Xianjin Shen, Hong-Li Liu, Zhiyuan Ren, Anandmayee Tej, Di Li, Hauyu Baobab Liu, Gary A. Fuller, Jinjin Xie, Sihan Jiao, Aiyuan Yang, Patrick M. Koch, Fengwei Xu, Patricio Sanhueza, Pham Ngoc Diep, Nicolas Peretto, R. K. Yadav, Busaba H. Kramer, Koichiro Sugiyama, Mark G. Rawlings, Chang Won Lee, Ken'ichi Tatematsu, Daniel Harsono, David Eden, Woojin Kwon, Chao-Wei Tsai, Glenn J. White, Kee-Tae Kim, Tie Liu, Ke Wang, Siju Zhang, Wenyu Jiao, Dongting Yang, Swagat R. Das, Jingwen Wu, Chen Wang
Figure caption: Comparison of peak flux density of matched ATLASGAL clumps at 870 μm and predicted results from our observed 850 μm dust emission. The black line indicates equality.
Paper: JCMT 850 μm Continuum Observations of Density Structures in the G35 Molecular Complex
Authors: Xianjin Shen, Hong-Li Liu, Zhiyuan Ren, Anandmayee Tej, Di Li, Hauyu Baobab Liu, Gary A. Fuller, Jinjin Xie, Sihan Jiao, Aiyuan Yang, Patrick M. Koch, Fengwei Xu, Patricio Sanhueza, Pham Ngoc Diep, Nicolas Peretto, R. K. Yadav, Busaba H. Kramer, Koichiro Sugiyama, Mark G. Rawlings, Chang Won Lee, Ken'ichi Tatematsu, Daniel Harsono, David Eden, Woojin Kwon, Chao-Wei Tsai, Glenn J. White, Kee-Tae Kim, Tie Liu, Ke Wang, Siju Zhang, Wenyu Jiao, Dongting Yang, Swagat R. Das, Jingwen Wu, Chen Wang
Figure caption: Spatial distribution of HFSs overlaid on the Spitzer 8 μm image. The different colored curves sketch the filaments composing HFSs, with each color indicating its respective line mass.
Paper: Galaxy–Absorber Association in the Epoch of Reionization: Galactic Population Luminosity Distribution for Different Absorbers at 10 ≥ z ≥ 5.5
Authors: Samir Kušmić, Kristian Finlator, Ezra Huscher, Maya Steen
Figure caption: Histogram showing the displacement between each LLP grid cell from its center to the nearest galaxy.
Paper: Galaxy–Absorber Association in the Epoch of Reionization: Galactic Population Luminosity Distribution for Different Absorbers at 10 ≥ z ≥ 5.5
Authors: Samir Kušmić, Kristian Finlator, Ezra Huscher, Maya Steen
Figure caption: Number of host galaxies linked per gas particle by HOSTGAL at several redshifts. The point is the mean value, and errorbars extend out to 1σ.
Paper: Galaxy–Absorber Association in the Epoch of Reionization: Galactic Population Luminosity Distribution for Different Absorbers at 10 ≥ z ≥ 5.5
Authors: Samir Kušmić, Kristian Finlator, Ezra Huscher, Maya Steen
Figure caption: (Top) HGLD for each of the species throughout redshift, designated by the line for each species. The HGLD is the number of galaxies per magnitude bin per number of absorbers of a particular species. Each species is then split by an EW of 0.01 Å. The dashed and dotted lines are further divided based on a quartile split on strength: 25% and below (weaker) is dashed, and 75% and above (stronger) is dotted. (Bottom) Average number of galaxies per absorber vs. redshift, integrated from the top HGLD and also split by 50% EW. The UVLF for the higher EW line for a species is larger overall, which means more galaxies are necessary to create the stronger absorber.
Paper: Galaxy–Absorber Association in the Epoch of Reionization: Galactic Population Luminosity Distribution for Different Absorbers at 10 ≥ z ≥ 5.5
Authors: Samir Kušmić, Kristian Finlator, Ezra Huscher, Maya Steen
Figure caption: Scatter plots of the EW of all absorbers related to the mean stellar mass of all potential host galaxies for an absorber at redshift z with the line of best fit (pink dashed) found from least-squares linear regression. The (r, p) are the Pearson coefficients and p-values, respectively. Although weak, this suggests a positive correlation between EW and host stellar mass for most species aside from C IV, especially by z = 5.5.
Paper: Galaxy–Absorber Association in the Epoch of Reionization: Galactic Population Luminosity Distribution for Different Absorbers at 10 ≥ z ≥ 5.5
Authors: Samir Kušmić, Kristian Finlator, Ezra Huscher, Maya Steen
Figure caption: Host galaxy UV luminosity distribution throughout each redshift for each species (Equation (3); left) and their cumulative integrals compared to the cumulative field UVLF (right). The gray shaded region is the resolution limit of the simulation. This analysis does not indicate a luminosity dependence for the absorbers’ host galaxies.
Paper: Galaxy–Absorber Association in the Epoch of Reionization: Galactic Population Luminosity Distribution for Different Absorbers at 10 ≥ z ≥ 5.5
Authors: Samir Kušmić, Kristian Finlator, Ezra Huscher, Maya Steen
Figure caption: HGMD of each species split at different strengths. This has the same criteria as in Figure 6. The distributions do not appear to have any statistical difference, plus the difference in CDF has a high discrepancy that averages close to 0 in all bins. This does not necessarily suggest that most strong absorbers are closer to more-massive galaxies, just that more metals come from more-massive galaxies.
Paper: Galaxy–Absorber Association in the Epoch of Reionization: Galactic Population Luminosity Distribution for Different Absorbers at 10 ≥ z ≥ 5.5
Authors: Samir Kušmić, Kristian Finlator, Ezra Huscher, Maya Steen
Figure caption: HGMDs at three different redshifts (left). Comparison of cumulative HGMDs with the simulated field galaxy SMF (right). Similar to the HGLD, the HGMD is done with the same analysis with similar mathematical definitions as in Equation (3) but by the galaxy’s stellar mass instead of UV magnitude. The gray shaded region is the resolution limit of the simulation. A slight bias toward massive galaxies is apparent.
Paper: Galaxy–Absorber Association in the Epoch of Reionization: Galactic Population Luminosity Distribution for Different Absorbers at 10 ≥ z ≥ 5.5
Authors: Samir Kušmić, Kristian Finlator, Ezra Huscher, Maya Steen
Figure caption: Difference between the normalized HGLDs for each species for the nearest galaxy approach vs. our 95% box (left), the nearest galaxy vs. 100 pkpc box (middle), and the 95% box vs. 100 pkpc box (right). Errorbars plotted are from HGLD of the the nearest galaxy method for the left and middle plot. The right plot is from the 95% method as picked for the main body. We do not see significant differences between the HGLDs.
Paper: Atomic Data for Astrophysically Important Spectral Lines of Singly Ionized Nitrogen
Authors: M. C. Li, W. Li
Figure caption: Comparisons of the present transition data with the values from NIST-ASD and other theoretical calculations. Left panel: comparison of the A values in both Babushkin (B) and Coulomb (C) gauges from the present calculations with available compiled values from NIST-ASD. Right panel: comparison of present log(gf) values with other theoretical calculations by C. Froese Fischer & G. Tachiev (2004; solid circles), K. L. Bell et al. (1995; solid rectangles), and X. Shen et al. (2015, 2018; solid triangles).
Paper: Constructing a Galaxy Cluster Catalog in IllustrisTNG300 Using the Mulguisin Algorithm
Authors: Lael Shin, Jubee Sohn, Young Ju, Inkyu Park, Cristiano G. Sabiu
Figure caption: (a) The mean stellar age distribution (gray contour) of member subhalos of the 17 TNG FoF halos with multiple MGS counterparts (shown in Figure 3). The x-axis shows the 1D projected distance between member subhalos and the FoF BCG onto the axis connecting the two most massive MGS (sub)structure BCGs. We normalize the 1D projected distance with the distance between the two MGS BCGs. Circles mark the median distribution. Note that there is an upturn between two BCGs. (b) The same as panel (a), but based on the distance from the MGS BCGs normalized by the virial radius. Panels (c) and (d) display the quenched fraction distribution along with the clustercentric distance similar to panels (a) and (b), respectively.
Paper: Constructing a Galaxy Cluster Catalog in IllustrisTNG300 Using the Mulguisin Algorithm
Authors: Lael Shin, Jubee Sohn, Young Ju, Inkyu Park, Cristiano G. Sabiu
Figure caption: The gas temperature map (upper panels) and shock-dissipated energy map (lower panels) of four FoF systems with bow shocks and multiple MGS counterparts. Dashed contours indicate the number density of member subhalos from different MGS halos. We show the distribution of subhalos on the plane (e.g., the x–y, y–z, or x–z plane) where the separations of the multiple structures are most distinct. We note the minimum and maximum colormap values in units of kelvins and ergs per second at the lower right corner of each panel. IDMGS in each panel indicates the MGS cluster ID. The colors of the IDs correspond to the contour colors.