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The Atomistic Cookbook
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The Atomistic Cookbook
  • Recipes grouped by topic
    • Statistical sampling and dynamics
    • Analysis and post-processing
    • Machine learning models
    • Nuclear quantum effects
  • Recipes grouped by software used
    • i-PI
    • chemiscope
    • featomic
    • scikit-matter
    • cp2k
    • LAMMPS
    • metatensor
    • PLUMED
    • torch-pme
  • List of all recipes
    • A ML model for the electron density of states
    • Atomistic Water Model for Molecular Dynamics
    • Batch run of CP2K calculations
    • Constant-temperature MD and thermostats
    • Equivariant linear model for polarizability
    • Equivariant model for tensorial properties based on scalar features
    • Generalized Convex Hull construction for the polymorphs of ROY
    • Learning Capabilities with torchpme
    • Local Prediction Rigidity analysis
    • Long-distance Equivariants: a tutorial
    • MD using direct-force predictions with PET-MAD
    • Multiple time stepping and ring-polymer contraction
    • PCA/PCovR Visualization of a training dataset for a potential
    • Path integral metadynamics
    • Path integral molecular dynamics
    • Periodic Hamiltonian learning
    • Quantum heat capacity of water
    • Rotating equivariants
    • Sample and Feature Selection with FPS and CUR
    • The PET-MAD universal potential
  • Downloading and running the recipes
  • Contributing a recipe
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