Introduction

Tadah! is a modular C++17 framework for developing and deploying machine learning interatomic potentials (MLIPs). It ships:

  • a command-line driver, tadah, for training, prediction, dataset manipulation, and hyperparameter optimisation (tadah hpo); and

  • a LAMMPS pair style, pair_style tadah, that runs trained potentials in MD without a Python or Tadah! runtime dependency.

The two pieces correspond to two repositories — Tadah!MLIP (training side) and Tadah!LAMMPS (deployment side) — that share a common pot.tadah file format.

Key features

  • Pluggable descriptors and regressors — mix descriptor families (2-body, many-body, EAM-style) with linear or kernel regressors.

  • Nested fitting (HPO) — drive the training loop from an outer optimiser that scores trial potentials against physics-informed constraints (elastic constants, equilibrium volume, surface energies, …). See Nested Fitting.

  • LAMMPS interface — every descriptor and model exposed through pair_style tadah; LSCALE and ESHIFT round-trip through the potential file.

  • OpenMP build — desktop parallelism via OMP_NUM_THREADS. An MPI build target exists but is not functional in the 1.3.0-beta.1 release (see Installation).

  • C++ API — link against libtadah.mlip / libtadah.core for embedded use; see Compiling and Linking with Library.

CLI surface

The tadah driver exposes the following top-level commands (each documented in Command Line Interface):

  • tadah train / tadah predict — fit and apply potentials.

  • tadah hpo — nested fitting (hyperparameter optimisation).

  • tadah data — convert, balance, dedup, merge, sample, split, print, write datasets and structures (CIF, VASP, CASTEP, LAMMPS; online sources MP/COD/NOMAD via --structure).

  • tadah analysis — plot basis functions, cutoffs, descriptors.

  • tadah properties pairwise — pairwise energy between two atoms.

  • tadah explain <key> — print the help text for any configuration key.

Obtaining Tadah!

Tadah!MLIP and Tadah!LAMMPS are hosted at:

For build instructions see Installation. Selected published potentials produced with Tadah! by Prof. Ackland's group are listed in Trained MLIPs.