parthenon-hpc-lab/parthenon

AI Summary: The task is to define a consistent model for handling particle metadata within the Parthenon AMR framework, addressing how derived, independent, and restart data are managed. This involves designing a system that ensures data integrity and efficient handling across different stages of simulation and data processing.

AI Summary: The task involves refactoring the Parthenon AMR infrastructure's ParameterInput system. This includes migrating from an internal representation to a TOML dictionary, maintaining backward compatibility, adding docstring support, implementing orphan variable detection, and addressing compilation and include issues. The goal is to improve the readability, maintainability, and usability of the parameter input mechanism.

AI Summary: The task involves enhancing the Parthenon AMR framework to improve its parameter handling. Specifically, it requires implementing warnings for non-dumpable parameter data types and adding support for serializing and deserializing structs within the parameter system. This will improve the framework's robustness and usability.