adsabs/AstroCLIMB huggingface dataset:
Paper: Testable Predictions of Outside-in Age Gradients in Dwarf Galaxies of All Types
Authors: Claire L. Riggs, Alyson M. Brooks, Ferah Munshi, Charlotte R. Christensen, Roger E. Cohen, Thomas R. Quinn, James Wadsley
Figure caption: The normalized age gradient value ﹩{{dt}}_{90}/{f}_{{R}_{e}}﹩ vs. global t 90 in gigayears since the Big Bang. Circles represent simulated field dwarfs, and stars represent simulated satellite galaxies. Error bars on ﹩{{dt}}_{90}/{f}_{{R}_{e}}﹩ enclose 68% of the age gradient values calculated over 100 random viewing angles. The color of the points corresponds to the stellar mass of the galaxy in solar masses. Light blue diamonds correspond to the simulated field galaxies presented in A. S. Graus et al. (2019), which have a stellar mass range of 105.67−8.73 M ⊙. Green triangles correspond to three observed galaxies, a subset of galaxies currently being analyzed (R. E. Cohen et al. 2024, in preparation). We also label three galaxies we refer to as “representative” galaxies, which are presented in Figure 2 and referenced throughout this work. Similar to A. S. Graus et al. (2019), we find that age gradients change from an outside-in trend (strongly negative ﹩{{dt}}_{90}/{f}_{{R}_{e}}﹩) to no age gradient as the global t 90 increases after ∼8 Gyr, i.e., galaxies with more extended SFHs have flatter age gradients. However, with our larger sample, we show that this trend reverses as t 90 decreases. We also find that both field dwarfs and satellites follow similar age gradient trends. Both sets of simulations are in good agreement with the observational results.
Paper: Testable Predictions of Outside-in Age Gradients in Dwarf Galaxies of All Types
Authors: Claire L. Riggs, Alyson M. Brooks, Ferah Munshi, Charlotte R. Christensen, Roger E. Cohen, Thomas R. Quinn, James Wadsley
Figure caption: Examination of gradients in three representative dwarf galaxies. From top to bottom, they are Rogue 10, Elektra 2, and Sonia 34. For the left and middle columns, we bin the star particles by their age in 1 Gyr bins, with the reddest color denoting star particles that formed 13–14 Gyr ago, and the bluest color representing stars that formed 0–1 Gyr ago. The left column shows average formation radius vs. average radius at z = 0 for the binned star particles in order to determine how the stellar positions have changed over time, with the vertical lines enclosing 90% of the formation radii of each bin. The middle column shows the fraction of stars of each age as a function of radial position at z = 0. The rightmost column shows the extent of star formation from the center of the galaxy over time. For all galaxies, the left plots show that the oldest stars have been pushed out the furthest from their initial formation radius. Steep, negative age gradients result from little growth in the size of the galaxy over time, while the oldest stars get pushed beyond the mean formation radius. Flat gradients result when the galaxy grows with time, such that young stars are forming at the radius that the oldest stars have been pushed to. The low-mass galaxies have stars of similar (old) ages and thus tend to have flat gradients due to a lack of evolution in star formation. A full repository of the age gradient and radial reshuffling plots for each galaxy in our sample is available online at doi:10.5281/zenodo.13887797.
Paper: Testable Predictions of Outside-in Age Gradients in Dwarf Galaxies of All Types
Authors: Claire L. Riggs, Alyson M. Brooks, Ferah Munshi, Charlotte R. Christensen, Roger E. Cohen, Thomas R. Quinn, James Wadsley
Figure caption: The top two panels show the sSFR for Elektra 2 (left) and Rogue 10 (right), and the bottom two panels show the average radial velocity over time of old stars (dashed red line), young stars (solid blue line), and cold gas (dotted–dashed green line) for these galaxies. Old stars are defined as having an age greater than 2 Gyr at the time step at which the radial velocity was calculated, while young stars have an age less than 50 Myr at the time step at which the radial velocity was calculated. Cold gas is gas with temperature T < 1000 K. Vertical dashed lines indicate when a minor merger occurred in each of these galaxies (neither galaxy experienced a major merger). Error bars are shown for all lines, which represent ﹩\sqrt{N}/{N}_{\mathrm{bin}}﹩ so that bins with fewer particles have a greater error. While we tend to see larger fluctuations in the radial velocities of stars and gas during the period of minor mergers, the outward radial velocities are substantially smaller in our simulations than those found in K. El-Badry et al. (2016), who found outward velocities of 20 km s−1. We find mean radial velocities near 0 outside of minor mergers or even a small net inflow. The oldest stars show no evidence of a large outward radial motion that could drive the creation of the age gradients we see in these same galaxies.
Paper: Revisiting the Chemical Composition of WD 1145+017: Impact of Circumstellar Disk Contamination on Photospheric Abundances
Authors: Érika Le Bourdais, Patrick Dufour, Siyi Xu, 偲艺 许
Figure caption: Display of our final solution over selected regions of the 2016 April 1 HIRES spectrum. The contribution from the photosphere alone is in gray while the combined photospheric and circumstellar disk contributions are in orange. The models and data used to produce the figures in this paper are available upon request.
Paper: Revisiting the Chemical Composition of WD 1145+017: Impact of Circumstellar Disk Contamination on Photospheric Abundances
Authors: Érika Le Bourdais, Patrick Dufour, Siyi Xu, 偲艺 许
Figure caption: Photospheric logX/Si relative to its ratio in CI Chondrite (dashed line; K. Lodders 2003), assuming steady state, in comparison to bulk Earth (W. McDonough 2003) and comet Halley (E. K. Jessberger et al. 1988), as well as the previous abundances for WD 1145+017 from S. Xu et al. (2016). Elements are ordered by condensation temperature. The abundances for the disk model are also shown for the elements with a clear circumstellar detection.
Paper: Revisiting the Chemical Composition of WD 1145+017: Impact of Circumstellar Disk Contamination on Photospheric Abundances
Authors: Érika Le Bourdais, Patrick Dufour, Siyi Xu, 偲艺 许
Figure caption: Selected regions of the 2016 March 28 HST COS spectrum. The contribution from the photosphere alone is in gray while the combined photospheric and circumstellar disk contributions are in orange. The 1215 Å emission line is a geocoronal contamination.
Paper: Revisiting the Chemical Composition of WD 1145+017: Impact of Circumstellar Disk Contamination on Photospheric Abundances
Authors: Érika Le Bourdais, Patrick Dufour, Siyi Xu, 偲艺 许
Figure caption: Chosen epochs of the C II doublet in the UV for the HST COS data taken on 2016 March 28, 2017 February 17, and 2018 May 1. ISM components (purple) with a velocity of −40 km s−1 are also included in the photospheric (gray) and disk (orange) models to fit all the features.
Paper: Revisiting the Chemical Composition of WD 1145+017: Impact of Circumstellar Disk Contamination on Photospheric Abundances
Authors: Érika Le Bourdais, Patrick Dufour, Siyi Xu, 偲艺 许
Figure caption: Disk and photospheric contribution to the spectrum in the O I 7775 Å triplet region for the 2016 February 3 HIRES data.
Paper: Revisiting the Chemical Composition of WD 1145+017: Impact of Circumstellar Disk Contamination on Photospheric Abundances
Authors: Érika Le Bourdais, Patrick Dufour, Siyi Xu, 偲艺 许
Figure caption: Example of a region with emission-like features for the 2017 February 17 HST COS data. The top spectrum shows our best fit without including the disk contribution, while the bottom spectrum shows the fit with the disk contribution included.
Paper: Revisiting the Chemical Composition of WD 1145+017: Impact of Circumstellar Disk Contamination on Photospheric Abundances
Authors: Érika Le Bourdais, Patrick Dufour, Siyi Xu, 偲艺 许
Figure caption: Same as Figure 8 for the 1415–1445 Å region.
Paper: The Lyα Dependence on Nebular Properties from the HETDEX and MOSDEF Surveys
Authors: Óscar A. Chávez Ortiz, Gene C. K. Leung, Steven L. Finkelstein, Dustin Davis, Ralph S. Sutherland, David C. Nicholls, Mabel Stephenson, Erin Mentuch Cooper, Micaela Bagley, Karl Gebhardt, Lindsay R. House, Chenxu Liu, Robin Ciardullo, Caryl Gronwall, Gary J. Hill, Daniel Farrow, Donald P. Schneider
Figure caption: This set of panels showcases the correlations between ﹩{f}_{\mathrm{esc}}^{\mathrm{Ly}\alpha }﹩ and various galaxy properties, where the Lyα-detected sample is shown in blue and the nondetected galaxies are given by red downward arrows indicating their upper limit on ﹩{f}_{\mathrm{esc}}^{\mathrm{Ly}\alpha }﹩. The purple shaded regions are the 1σ spread on the correlation using the Lyα-detected and nondetected samples, and the solid purple line is the best-fit line. The quantity ﹩{f}_{\mathrm{esc}}^{\mathrm{Ly}\alpha }﹩ is positively correlated with the Lyα equivalent width and ionization parameter [log10(Q)] at high significance (p-values of 0.00007 and 0.0002, respectively). There are convincing anticorrelations between ﹩{f}_{\mathrm{esc}}^{\mathrm{Ly}\alpha }﹩ and stellar mass, SFR, and Bagpipes-derived dust attenuation measuring −0.34 (p-value: 0.00015), −0.38 (p-value: 0.00002), and −0.41 (p-value: 0.000003). There are no correlations between ﹩{f}_{\mathrm{esc}}^{\mathrm{Ly}\alpha }﹩ and the velocity offset of Lyα measuring −0.06 (p-value: 0.78).
Paper: Mergers, Radio Jets, and Quenching Star Formation in Massive Galaxies: Quantifying Their Synchronized Cosmic Evolution and Assessing the Energetics
Authors: Timothy M. Heckman, Namrata Roy, Philip N. Best, Rohit Kondapally
Figure caption: We plot the cumulative amount of stellar mass in quiescent massive galaxies, normalized to its value at z = 0.35 as a function of redshift from D. McLeod et al. (2021—orange) and J. Weaver et al. (2023—red). The yellow-hatched-shaded region shows the disagreement between the two measurements. We overplot two independent measurements of the cumulative amount of kinetic energy injected by radio jets, also normalized to its value at z = 0.35 from HB23 (cyan) and K23 (blue). The gray-shaded region shows the disagreements between the two calculations. Note the overall similarity of the evolution of quiescent mass and jet kinetic energy. In green, we show the corresponding normalized amount of kinetic energy carried by AGN or massive star-driven winds (HB23 and K23). This does not match the evolution in mass and is offset to much earlier times.
Paper: Mergers, Radio Jets, and Quenching Star Formation in Massive Galaxies: Quantifying Their Synchronized Cosmic Evolution and Assessing the Energetics
Authors: Timothy M. Heckman, Namrata Roy, Philip N. Best, Rohit Kondapally
Figure caption: The cumulative growth in the number of major mergers of massive galaxies per unit volume (see the main text), normalized to the value at z = 0.35 as a function of redshift from J. O’Leary et al. (2021—red). This is compared to measurements of the normalized cumulative amount of kinetic energy per unit volume injected by radio jets (K23—blue) and the normalized mass per unit volume in quiescent galaxies per unit volume (M21—orange). All three curves agree extremely well with one another.
Paper: The Star-forming Main Sequence in JADES and CEERS at z > 1.4: Investigating the Burstiness of Star Formation
Authors: Leonardo Clarke, Alice E. Shapley, Ryan L. Sanders, Michael W. Topping, Gabriel B. Brammer, Trinity Bento, Naveen A. Reddy, Emily Kehoe
Figure caption: The Hα-to-UV luminosity ratio vs. stellar mass for our galaxy sample. The gray hatched region shows the parameter space that we are not sensitive to assuming a limiting survey flux and a UV luminosity to stellar mass ratio (which we derive from the parameters reported in Table 1). We take the limiting flux in our sample to be 2.0 × 10−19 erg s−1 cm−2 since this is the lowest Hα flux we observe at a significance greater than 5σ. The dashed gray lines denote the uncertainty on the region of our sensitivity limits due to the intrinsic scatter in SFR(UV) vs. stellar mass relation. The horizontal blue hatched region shows the equilibrium range of Hα-to-UV luminosity calculated by V. Mehta et al. (2023).
Paper: The Star-forming Main Sequence in JADES and CEERS at z > 1.4: Investigating the Burstiness of Star Formation
Authors: Leonardo Clarke, Alice E. Shapley, Ryan L. Sanders, Michael W. Topping, Gabriel B. Brammer, Trinity Bento, Naveen A. Reddy, Emily Kehoe
Figure caption: The intrinsic scatter in the SFMS σ int as a function of redshift. The points have an arbitrary offset in the x-axis to more easily see overlapping points. The blue, orange, and green points show the intrinsic scatter in the SFMS as determined from Hα, SED fitting, and UV luminosity, respectively.
Paper: Mergers, Radio Jets, and Quenching Star Formation in Massive Galaxies: Quantifying Their Synchronized Cosmic Evolution and Assessing the Energetics
Authors: Timothy M. Heckman, Namrata Roy, Philip N. Best, Rohit Kondapally
Figure caption: We replot the same data as in Figure 1, but now replace redshift with the time since the Big Bang on the x-axis, and zoom-in on the epoch before z = 1.5 (t < 4 Gyr). The rightward-facing arrows show the effect of a time-lag of 0.3 Gyr between the time star formation is actually quenched and when stellar evolution results in the red spectral energy distribution of a quiescent galaxy (see the main text).
Paper: Mergers, Radio Jets, and Quenching Star Formation in Massive Galaxies: Quantifying Their Synchronized Cosmic Evolution and Assessing the Energetics
Authors: Timothy M. Heckman, Namrata Roy, Philip N. Best, Rohit Kondapally
Figure caption: As in Figure 1, but replacing the jet kinetic energy with the cumulative amount of energy per unit volume in the form of radio synchrotron emission using the radio luminosity functions in R. Kondapally et al. (2022). The agreement with the growth curve for quench mass (from M21) is not as good as in Figure 1 for z > 2, but there is still good overall synchronization.
Paper: The Star-forming Main Sequence in JADES and CEERS at z > 1.4: Investigating the Burstiness of Star Formation
Authors: Leonardo Clarke, Alice E. Shapley, Ryan L. Sanders, Michael W. Topping, Gabriel B. Brammer, Trinity Bento, Naveen A. Reddy, Emily Kehoe
Figure caption: The Hα-based SFMS as determined from JWST observations in this study in the range 1.4 < z ≤ 2.7 (purple) and MOSDEF observations from R. L. Sanders et al. (2021) in the range 2.0 < z < 2.6 (gray). The MOSDEF data points have been shifted down by 0.32 dex to match the Hα luminosity to SFR conversion that we use in this paper.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The perpendicular component (left), the parallel component (center), and the magnitude (right) maps of ∇v LSR in the Perseus IC348 filaments. These filaments are displayed over two rows to prevent overlapping maps from obscuring one another. The footprints of the filaments not shown in each row are displayed in gray.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The same as Figure 19, but for Perseus NGC 1333.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The same as Figure 19, but for Perseus L1448.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The same as Figure 19, but for Perseus L1455.
Paper: Filament Accretion and Fragmentation in the Perseus Molecular Cloud
Authors: Michael Chun-Yuan Chen, James Di Francesco, Rachel K. Friesen, Jaime E. Pineda, Paola Caselli, Adam Ginsburg, Helen Kirk, Anna Punanova
Figure caption: The same as Figure 19, but for Perseus B1.
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: Optical metallicity diagnostics for the AGN narrow-line regions as predicted by AGN models with ﹩\mathrm{log}(P/k)=7.0﹩, NHlow nitrogen scaling relation, and varying ionization parameters (﹩\mathrm{log}(U)=﹩ −3.8, −3.4, −3.0, −2.6, −2.2 correspond to colors from dark to bright) and varying peak energy in the AGN radiation field (﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.0 in solid lines and ﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.5 in dashed lines).
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: UV metallicity diagnostics for the AGN narrow-line regions as predicted by AGN models with ﹩\mathrm{log}(P/k)=7.0﹩, NHlow nitrogen scaling relation, and varying ionization parameters (﹩\mathrm{log}(U)=﹩−3.8, −3.4, −3.0, −2.6, −2.2 correspond to colors from dark to bright) and varying peak energies in the AGN radiation field (﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.0 in solid lines and ﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.5 in dashed lines).
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: The effect of nitrogen scaling relation on UV metallicity diagnostics for the AGN narrow-line regions as predicted by AGN models with ﹩\mathrm{log}(P/k)=7.0﹩ and ﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.5. As in Figure 1, but with line styles representing the nitrogen scaling relation used in the AGN models. (NHlow in solid lines and NHhigh in dashed lines)
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: The effect of E  peak  on UV and optical gas pressure diagnostics for the AGN narrow-line regions as predicted by AGN models with ﹩\mathrm{log}(U)=﹩−3.0. As in Figure 6, but with line styles representing the peak energy in the AGN radiation field (﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.0 in solid lines and ﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.5 in dashed lines).
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: The effect of nitrogen scaling relation on UV and optical gas pressure diagnostics for the AGN narrow-line regions as predicted by AGN models with ﹩\mathrm{log}(U)=﹩−3.0 and ﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.25. As in Figure 6, but with line styles representing the nitrogen scaling relation used in the AGN models. (NHlow in solid lines and NHhigh in dashed lines).
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: The effect of gas pressure on UV metallicity diagnostics for the AGN narrow-line regions as predicted by AGN models with ﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.25. As in Figure 1, but with line styles representing gas pressure (﹩\mathrm{log}(P/k)=7.8﹩ in solid lines and ﹩\mathrm{log}(P/k)=6.2﹩ in dashed lines).
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: The effect of gas pressure on optical metallicity diagnostics for the AGN narrow-line regions as predicted by AGN models with ﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.25. As in Figure 3, but with line styles representing gas pressure (﹩\mathrm{log}(P/k)=7.8﹩ in solid lines and ﹩\mathrm{log}(P/k)=6.2﹩ in dashed lines).
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: The effect of nitrogen scaling relation on UV and optical ionization parameter diagnostics for the AGN narrow-line regions as predicted by AGN models with ﹩\mathrm{log}(P/k)=7.0﹩ and ﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.25. As in Figure 5, but with line styles representing the nitrogen scaling relation used in the AGN models. (NHlow in solid lines and NHhigh in dashed lines).
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: The effect of gas pressure on UV and optical E peak diagnostics for the AGN narrow-line regions as predicted by AGN models with ﹩\mathrm{log}(U)=﹩−3.0. As in Figure 7, but with line styles representing gas pressure (﹩\mathrm{log}(P/k)=7.8﹩ in solid lines and ﹩\mathrm{log}(P/k)=6.2﹩ in dashed lines).
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: The effect of gas pressure on UV and optical ionization parameter diagnostics for the AGN narrow-line regions as predicted by AGN models with ﹩\mathrm{log}({E}_{\mathrm{peak}}/\mathrm{keV})=﹩−1.25. As in Figure 5, but with line styles representing gas pressure (﹩\mathrm{log}(P/k)=7.8﹩ in solid lines and ﹩\mathrm{log}(P/k)=6.2﹩ in dashed lines).
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: Comparing the UV and optical ionization parameter diagnostics for AGN narrow-line regions (solid lines) and H II region (dashed lines) with varied metallicity (﹩12+\mathrm{log}({\rm{O}}/{\rm{H}})=7.7,8.3,8.4,8.8,9.1﹩ correspond to colors from dark to bright). Both AGN and H II ionization parameter diagnostics are derived from models with the same gas pressure ﹩\mathrm{log}(P/k)=7.0﹩.
Paper: Theoretical Diagnostics for Narrow-line Regions of Active Galactic Nuclei
Authors: Peixin Zhu, Lisa J. Kewley, Ralph S. Sutherland
Figure caption: Comparing the UV and optical gas pressure diagnostics for AGN narrow-line regions (solid lines) and H II region (dashed lines) with varied metallicity (﹩12+\mathrm{log}({\rm{O}}/{\rm{H}})=7.7,8.3,8.4,8.8,9.1﹩ correspond to colors from dark to bright). Both AGN and H II metallicity diagnostics are derived from models with the same ionization parameter log(U)=−3.0.
Paper: Low-latitude Auroras: Insights from 2023 April 23 Solar Storm
Authors: Geeta Vichare, Ankush Bhaskar, Rahul Rawat, Virendra Yadav, Wageesh Mishra, Dorje Angchuk, Anand Kumar Singh
Figure caption: Interplanetary and solar wind parameters along with magnetopause distance (MP) and geomagnetic activity index Sym-H during 2023 April 23–24. The shaded regions in pink and violet indicate the sheath and magnetic cloud regions of the ICME, respectively.
Paper: Low-latitude Auroras: Insights from 2023 April 23 Solar Storm
Authors: Geeta Vichare, Ankush Bhaskar, Rahul Rawat, Virendra Yadav, Wageesh Mishra, Dorje Angchuk, Anand Kumar Singh
Figure caption: Aurora seen on 2023 April 23 by the all-sky camera from Hanle, Ladakh, India (GGLat: 32.8°N, GGLon: 79°E; GMLat: 24.4°N, GMLon: 154°E), at 19:54 UT. The north direction is upward. The red diffuse glow is visible on the top side at Hanle.
Paper: Low-latitude Auroras: Insights from 2023 April 23 Solar Storm
Authors: Geeta Vichare, Ankush Bhaskar, Rahul Rawat, Virendra Yadav, Wageesh Mishra, Dorje Angchuk, Anand Kumar Singh
Figure caption: (Top two panels) Preliminary auroral electrojet indices on 2023 April 23 obtained from WDC, Kyoto. (Bottom panel) SMU and SML indices representing auroral activity obtained from SuperMAG. The peak of the eastward electrojet (SMU index) coincides with the Hanle observations of the aurora.