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ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Supplementary Data: Learning time-dependent and integro-differential collision operators from plasma phase space data using differentiable simulators

Authors: Carvalho, Diogo D.; O. Silva, Luís; Alves, E. Paulo;

Supplementary Data: Learning time-dependent and integro-differential collision operators from plasma phase space data using differentiable simulators

Abstract

This repository contains some of the simulation data and post-processing tools for the paper "Learning time-dependent and integro-differential collision operators from plasma phase space data using differentiable simulators". We provide the following files: sim-X.zip: Each file contains the relevant data for one of the 3 simulations shown in the paper (see Table 4 in Appendix B of the paper). They contain the following subfolders: AD-Tracks/ (only for sim-1 & sim-2): Advection-diffusion models computed from particle track data. FDIST/: Phase space evolution of subpopulations. Subfolder names correspond to the sampled PDFs (e.g., normal_0_0 is a normal centered at zero in v_x and v_y) as described in Appendix C of the paper. MS/ (only for sim-1 & sim-2): Particle track information for 3 time-steps (used for distribution function plots in the paper). We do not include full tracks since the memory requirements would be too large for Zenodo. These can easily be generated by re-running the simulation with the provided input deck. os-stdin: OSIRIS input deck used to generate the data. This input deck should allow anyone to reproduce the simulations and is compatible with the open-source version of OSIRIS: https://osiris-code.github.io. Hardware-specific input parameters (e.g., node_conf) might need to be altered depending on the HPC system being used. utils.zip: Python scripts used to post-process raw particle track data. These were the tools used to generate the phase space evolution of subpopulations and compute advection-diffusion models from particle track information. The differentiable simulator framework developed to extract collision operators and perform the analysis presented in the paper is available at: https://github.com/diogodcarvalho/ml-pic-collision-operators

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average