docs: document LAMMPS support in root README, tidy lammps/README

Add a LAMMPS support section to the root README pointing to
lammps/README.md, and clean up lammps/README.md: drop internal phase
jargon, fix the stale "DGL-only" architecture note, and remove the
dangling design-notes reference. Also drop the outdated AdvancedSoft
third-party LAMMPS reference now that there is a first-party pair style.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

Author: shyuep

README.md

@@ -116,6 +116,14 @@ pip install matgl[ops]    # NVIDIA Warp kernels for TensorNet/QET (NVIDIA GPU, t
 pip install matgl[jax]    # JAX/XLA inference for TensorNet/QET (CPU / CUDA / Apple Silicon)
 ```
 
+## LAMMPS support
+
+MatGL ships a native LAMMPS `pair_style matgl` that evaluates a TorchScript-compiled MatGL **TensorNet** PES
+(energies, forces, and virials) on every timestep via LibTorch, with both a CPU/serial pair style and a Kokkos
+GPU/host variant (`pair_style matgl/kk`). Export a LAMMPS-loadable model from any pre-trained TensorNet with
+`mgl create-lammps-model`. Build and usage instructions, the input-deck syntax, and current limitations are in
+[`lammps/README.md`](lammps/README.md).
+
 ## Docker images
 
 Docker images have now been built for matgl, together with LAMMPS support. They are available at the
@@ -429,8 +437,6 @@ We wrote [tutorials] on how to use MatGL. These were generated from [Jupyter not
 - [API docs][apidocs] for all classes and methods.
 - [Developer Guide](developer.md) outlines the key design elements of `matgl`, especially for developers wishing to
   train and contribute matgl models.
-- AdvancedSoft has implemented a [LAMMPS interface](https://github.com/advancesoftcorp/lammps/tree/based-on-lammps_2Jun2022/src/ML-M3GNET)
-  to both the TF and MatGL version of M3GNet.
 
 ## References
 

lammps/README.md

@@ -17,9 +17,9 @@ This directory ships:
 The Python side (one repo up) ships `mgl create-lammps-model`, which
 produces the `.pt` artifact these pair styles consume.
 
-> **Status — Phases 2 + 3 of the MatGL LAMMPS-Kokkos plugin.** CPU CI
-> exists (`.github/workflows/lammps-build.yml`); GPU runs require a
-> CUDA-capable runner (not in CI yet).
+> **Status.** The CPU/serial pair style is exercised in CI
+> (`.github/workflows/lammps-build.yml`). The Kokkos GPU variant builds
+> but is not yet covered in CI, as GitHub-hosted runners have no GPU.
 
 ## Building
 
@@ -144,8 +144,9 @@ Currently a no-op.
   proportionally to the number of ranks.
 - **No restart support.** The model lives on disk; `restart` files don't
   capture the path. Re-issue `pair_style` / `pair_coeff` after a restart.
-- **TensorNet only.** M3GNet, CHGNet, MEGNet, SO3Net, QET are DGL-only
-  in the matgl repo and would need PyG ports first.
+- **TensorNet only.** The pair style loads a TorchScript-compiled
+  TensorNet PES. Other architectures (M3GNet, CHGNet, MEGNet, SO3Net,
+  QET) are not yet wired into the LAMMPS export path.
 
 ## Continuous integration
 
@@ -158,8 +159,8 @@ through `LAMMPSMatGLModel`, runs the `in.matgl_si` deck, and diffs the
 LAMMPS energy against the Python reference.
 
 The Kokkos variant is **not** exercised in CI today — GitHub-hosted
-runners have no GPU. Hardware-accelerated CI is on the Phase-3 follow-up
-list and likely lives on a self-hosted CUDA runner.
+runners have no GPU. Hardware-accelerated CI would need a self-hosted
+CUDA runner.
 
 ## Verifying a build
 
@@ -205,8 +206,5 @@ stresses (when nonzero) within `1e-3 GPa`.
 
 ## Reference
 
-Plan and design notes:
-[`develop-a-kokkos-plugin-eventual-hare.md`](https://github.com/materialyzeai/matgl/tree/lammps).
-
-The Python wrapper is documented inline at
-`src/matgl/ext/_lammps.py` in the matgl repo.
+The Python wrapper that exports LAMMPS-loadable models is documented
+inline at `src/matgl/ext/_lammps.py` in the matgl repo.