PAIPAI V2.0

Stable PAIPAI v2.0 release.

PAIPAI is a Monte Carlo structure-search and finite-temperature sampling code for defective high-entropy alloys using machine-learning interatomic potentials.

This release includes:

• MLIP-assisted search-mode Monte Carlo sampling
• finite-temperature Monte Carlo workflows
• metal and interstitial move sets
• accepted-state post-processing tools, including Warren-Cowley SRO analysis and MC process packaging
• example CPU/GPU and SLURM scripts

If you use PAIPAI in academic work, please cite the associated publication listed in the README.

PAIPAI V1.0

Add README for PAIPAI package

Added detailed information about the PAIPAI package, including features, installation instructions, and quick start guide.