adsabs/AstroCLIMB huggingface dataset:
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Schematic representation of the methodology for deriving the ice column densities using INDRA. The process includes continuum determination, followed by silicate feature removal and global ice fitting using NNLS. Statistical analysis is performed to assess fit quality and uncertainties after which final column densities are estimated.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Percentage contribution to the spectral area of different ice groups in the 5–8 μm range. The model provides a good fit across the region as shown in Figure 4, except for the 7.1–7.5 μm interval. Appropriate polynomial baselines are used to separate the different ice groups present in the same ice mixture.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: IR spectrum of the residue (blue) from the irradiated ice mixture H2O:NH3:CH3OH:CO:CO2 (2:1:1:1:1) at 12 K, adapted from G. M. Muñoz Caro & W. A. Schutte (2003). The top panel shows the spectrum in the 5–20 μm region, along with local polynomial baselines (dashed lines) used to isolate absorption features. These features are also indicated by labels in the text and gray dotted lines. They correspond to functional groups such as carbonyl (–C=O), carboxylate (–COO−), amine (–NH2), and –CN containing species. Because these features are blended within a broad profile, local baselines were required for accurate column density calculations. The bottom panel shows the baseline-corrected features (solid lines). Column densities were estimated using Equation (12) and band strengths listed in Appendix B. Uncertainties due to baseline selection are ≲20%. See G. M. Muñoz Caro & W. A. Schutte (2003) for details. Abbreviations: CAsalt = carboxylic acid salt; HMT = hexamethylenetetramine; POM = polyoxymethylene.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Comparison of ice column densities derived in this work (gold), using global fitting, with those from W. R. M. Rocha et al. (2024; dark blue), who used local fitting. The x-axis represents different ice species, while the y-axis shows the column densities in cm2. Error bars, shown in red, indicate the uncertainties associated with each measurement. For CH3OH, a factor of 2 or 3 is used in the two fitting methods denoted by a star. This agreement highlights the robustness of our global fitting approach using INDRA in capturing the ice inventory consistently with previous studies.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Comparison of ice abundances as a percentage of H2O of IRAS 2A with those of LYSOs (left panel) and MYSOs (right panel). The solid line represents a 1:1 reference, while the dotted and dashed lines indicate abundances that are reduced and increased by a factor of 10, respectively. Table 5 lists the values used for the comparison of LYSOs and MYSOs with IRAS 2A.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Comparison of ice abundances as a percentage of H2O of IRAS 2A with those of comet 67P/C-G from M. Rubin et al. (2019). The solid line represents a 1:1 reference, while the dashed and dotted lines indicate cometary abundances that are reduced by factors of 10 and 100, respectively.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: R2 value as each component is added to the model. The R2 for individual components is shown in green dots. The cumulative R2, the normalized sum of cumulative R2, is also plotted in blue dots to illustrate the relative change in R2. Components are added in descending order of their contribution, which is defined as the maximum optical depth of the respective component.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: The absorption profile of SO2:CH3OH (1:1) 10 K ice mixture is shown in blue. The bottom-left panel shows the SO2 features at 7.57 and 8.68 μm in blue and the corresponding local polynomial baseline in green. The resultant baseline-corrected profiles are shown in red in the bottom-right panel.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: F-values for each minor ice component as it is sequentially added to the model, illustrating the relative change in variance. A higher F-value signifies a greater contribution of that component to the overall fit. Components are categorized as strong (in green region), moderate (in yellow region), or weak (in red region) based on the relative change in variance.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: The absorption profile of 15 K ice mixture HCOOH:H2O:CH3OH (6:68:26; S. E. Bisschop et al. 2007) is shown in blue in the top panel. Features other than H2O are shown in the bottom-left panel in blue and the corresponding polynomial baseline in green. The H2O subtracted spectrum is shown in red.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: The absorption profile of H2O:CH4 (10:1) ice mixture (W. R. M. Rocha et al. 2017) is shown in blue. The bottom-left shows the CH4 bending mode at 7.6 μm in blue and the corresponding local polynomial baseline in green. The resultant isolated band of CH4 is shown in red.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Confidence interval analysis of the components having H2O bands based on χ2 contributing in the 5–6 μm region. The blue, red, and brown dotted lines indicate the 1σ, 2σ, and 3σ levels. The coefficients of the remaining components are kept constant while performing this analysis.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Confidence interval analysis of the components without H2O and CO2 bands based on χ2 in the 5–11 μm region. The blue, red, and brown dotted lines indicate the 1σ, 2σ, and 3σ levels. The coefficients of the remaining components are kept constant while performing this analysis.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Confidence interval analysis of the components having H2O bands based on χ2 in the 14.75–15.75 μm region. The blue, red, and brown dotted lines indicate the 1σ, 2σ, and 3σ levels. The coefficients of the remaining components are kept constant while performing this analysis.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Confidence interval analysis of the components without H2O and CO2 bands based on χ2 contributing in the 5–6 μm region. The blue, red, and brown dotted lines indicate the 1σ, 2σ, and 3σ levels. The coefficients of the remaining components are kept constant while performing this analysis.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Confidence interval analysis of the CO2 components based on χ2 in the 16.25–16.75 μm region. The blue, red, and brown dotted lines indicate the 1σ, 2σ, and 3σ levels. The coefficients of the remaining components are kept constant while performing this analysis.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Confidence interval analysis of the CO2 components based on χ2 in the 14.50–15 μm region. The blue, red, and brown dotted lines indicate the 1σ, 2σ, and 3σ levels. The coefficients of the remaining components are kept constant while performing this analysis.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Confidence interval analysis of the components without H2O and CO2 bands based on χ2 that are contributing in the 14.5–17.5 μm region. The blue, red, and brown dotted lines indicate the 1σ, 2σ, and 3σ levels. The coefficients of the remaining components are kept constant while performing this analysis.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Confidence interval analysis of the components having H2O bands based on χ2 that are contributing in the 9.5–10.5 μm region. The blue, red, and brown dotted lines indicate the 1σ, 2σ, and 3σ levels. The coefficients of the remaining components are kept constant while performing this analysis.
Paper: Expanding the Ice Inventory of NGC 1333 IRAS 2A with INDRA Using JWST Observations: Tracing Organic Refractories and Beyond
Authors: Prathap Rayalacheruvu, Liton Majumdar, W. R. M. Rocha, Michael E. Ressler, Pabitra Ranjan Giri, S. Maitrey, Karen Willacy, D. C. Lis, Yuan Chen, P. D. Klaassen
Figure caption: Confidence interval analysis of the CO2 components based on χ2 in the 15.25–15.75 μm region. The blue, red, and brown dotted lines indicate the 1σ, 2σ, and 3σ levels. The coefficients of the remaining components are kept constant while performing this analysis.
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: Comparison of Rubin Observatory ugrizy throughput curves, assuming original Al–Ag–Al and new Ag–Ag–Ag mirror coatings. The transition to all-silver coatings decreased throughput in the u band, but increased throughput in all of the grizy bands. These curves include contributions from the atmosphere (assuming airmass 1.2), mirror reflectivities, lens and filter throughputs, and detector sensitivity.
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: Photo-z metrics for simulations of several different u-band survey strategies. Each metric is averaged within 19 overlapping redshift bins of width 0.3, spanning the range 0 ≤ z ≤ 3. The redshift value for each bin is the mean redshift of galaxies in that bin. Uncertainties are estimated by bootstrapping 1000 times. For clarity, we plot only a small subset of the u-band strategies considered. Each panel displays the corresponding requirement for LSST science as a horizontal gray line (Ž Ivezić et al. 2019). These requirements provide a sense of scale for each metric, but whether or not this photo-z estimator achieves each limit in different redshift ranges is not predictive of the photo-z performance of DESC cosmology, due to the considerations discussed in Section 3.2.
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: Relative number density of z ∼ 3 u-band dropouts detected across the deepest 75% of the survey footprint for different simulations of u-band survey strategy. Left panel corresponds to LSST year 1; right panel to year 10. The block corresponding to baseline v3.4, [1.0×, 30 s u], is bordered by a solid red box, while the SCOC recommendation of [1.1×, 38 s u] is bordered by a dashed red box. The absolute number density for baseline v3.4 is 69 deg−2 in year 1 and 2113 deg−2 in year 10.
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: Projected number densities for ugriz dropouts as a function of magnitude cut in the detection band, assuming mcut = m5. For ugriz dropouts, the detection band in rizzy. Expected depths and number densities for the baseline v4.0 survey strategy are indicated by bars, dots, and stars for LSST WFD years 1 and 10, and COSMOS year 10, respectively.
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: Evolution of u-, g-, and r-band dropouts for a series of subsequent survey simulations. v3.4 is the baseline simulation after the adoption of the new Ag–Ag–Ag mirror coatings. v3.4 [1.1×, 38 s u] is the same as v3.4, except with 10% more visits in the u band, with a per-visit exposure time of 38 s (compared to 30 s in baseline v3.4). v3.5 is the new baseline after the adoption of the [1.1×, 38 s u] strategy, and includes a few other changes. v3.5 with ToOs is the same as baseline v3.5, except with some survey time dedicated to target of opportunities. Baselines v3.6 and v4.0 include more realistic simulations of year 1 observatory downtime.
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: LBG completeness curves for ugriz dropouts as a function of redshift, in bins of LBG magnitude relative to the 5σ depth in the detection band (rizzy, respectively). u-dropout completeness comes from M. A. Malkan et al. (2017); griz completeness comes from Y. Ono et al. (2018) and Y. Harikane et al. (2022).
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: Transmission of the A. K. Inoue et al. (2014) IGM model in black, plotted for several different source redshifts. The transmission of the LSST photometric bandpasses (with Ag–Ag–Ag coating) are plotted in color to help visualize how much IGM extinction impacts each band at different redshifts.
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: Same as Figure 5, zoomed in on the z < 1 region for each metric. Recall that the lowest-redshift bin extends to z = 0 and that the plotted redshift values are the mean redshift for galaxies in each bin.
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: IGM magnitude increments in the Rubin u and g bands for z > 1.5 galaxies in the simulated catalog. The scatter is due to scatter in UV slope, βUV.
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: Maps of extinction-corrected coadded 5σ point-source depth in the LSST u band, assuming survey strategy baseline v4.0. The left panel displays the depth map for LSST year 1, while the right displays year 10. By year 10, the u-band depth is much deeper (notice the change in color bar limits) as well as significantly more uniform.
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: Model for evolution of βUV, fit to data from Table 3 of R. J. Bouwens et al. (2014).
Paper: Quantifying the Impact of LSST u-band Survey Strategy on Photometric Redshift Estimation and the Detection of Lyman-break Galaxies
Authors: John Franklin Crenshaw, Boris Leistedt, Melissa Lynn Graham, Constantin Payerne, Andrew J. Connolly, Eric Gawiser, Tanveer Karim, Alex I. Malz, Jeffrey A. Newman, Marina Ricci
Figure caption: IGM magnitude increments for the Rubin u and g bands, as a function of source redshift and UV slope.
Paper: Electron Acceleration in Time-dependent Kinematic Three-dimensional Magnetic Reconnection: The Role of Induced Electric Fields and Magnetic Topology
Authors: Y. L. Chen, Y. Wang, F. S. Wei, X. S. Feng, Z. L. Zhou, B. Y. Wang, P. B. Zuo, X. J. Song, X. J. Xu
Figure caption: Energy spectra of electrons for non-null, spine, and fan reconnection configurations, with A-type and X-type null geometries indicated in the legend.
Paper: Electron Acceleration in Time-dependent Kinematic Three-dimensional Magnetic Reconnection: The Role of Induced Electric Fields and Magnetic Topology
Authors: Y. L. Chen, Y. Wang, F. S. Wei, X. S. Feng, Z. L. Zhou, B. Y. Wang, P. B. Zuo, X. J. Song, X. J. Xu
Figure caption: Probability density distributions of total electric field (a) and parallel electric field (b) for different magnetic reconnection configurations indicated in the legend. Vertical dotted lines indicate the mean field values for each topological configuration.
Paper: Electron Acceleration in Time-dependent Kinematic Three-dimensional Magnetic Reconnection: The Role of Induced Electric Fields and Magnetic Topology
Authors: Y. L. Chen, Y. Wang, F. S. Wei, X. S. Feng, Z. L. Zhou, B. Y. Wang, P. B. Zuo, X. J. Song, X. J. Xu
Figure caption: (a) Electron energy as a function of x. (b) Electron energy as a function of z. (c) Particle trajectories in the y = 0 plane. The dashed lines denote the projected magnetic field lines. (d) 3D visualization of particle trajectories, where bold-colored lines denote magnetic field lines, with color indicating the magnitude of the total electric field |E|.
Paper: Electron Acceleration in Time-dependent Kinematic Three-dimensional Magnetic Reconnection: The Role of Induced Electric Fields and Magnetic Topology
Authors: Y. L. Chen, Y. Wang, F. S. Wei, X. S. Feng, Z. L. Zhou, B. Y. Wang, P. B. Zuo, X. J. Song, X. J. Xu
Figure caption: (a) Electron energy as a function of x. (b) Electron energy as a function of z. (c) Particle trajectories in the y = 0 plane. The dashed lines denote the projected magnetic field lines. (d) 3D visualization of particle trajectories, where bold-colored lines denote magnetic field lines, with color indicating the magnitude of the total electric field ∣E∣.
Paper: Electron Acceleration in Time-dependent Kinematic Three-dimensional Magnetic Reconnection: The Role of Induced Electric Fields and Magnetic Topology
Authors: Y. L. Chen, Y. Wang, F. S. Wei, X. S. Feng, Z. L. Zhou, B. Y. Wang, P. B. Zuo, X. J. Song, X. J. Xu
Figure caption: Mean energy gain per particle (ΔW/N) as a function of k for non-null, spine, and fan reconnection configurations, with A-type and X-type null geometries indicated in the legend.