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Change Log#

Version 0.4.0#

Added#

  • Full Torch Ewald/PME APIs support energy-derived forces, charge gradients, and strain-first virials, including second-order force/stress losses.

  • Full JAX Ewald/PME energy-only calls support first-order gradients for positions, charges, and row-vector displacement virials. JAX PME reciprocal higher-order support is limited to tested position and charge scalar losses; PME cell/stress/strain higher-order derivatives remain unsupported.

  • 2D slab correction is exposed through compute_slab_correction and the high-level Ewald/PME slab_correction= keyword in Torch and JAX.

  • Higher-order multipole electrostatics for charges, dipoles, and quadrupoles (l = 0, 1, 2) are available through Torch/Warp direct-k Ewald, PME, feature extraction, and SCF cache/step APIs.

  • Differentiable segment operations are available through nvalchemiops.torch.segment_ops and nvalchemiops.jax.segment_ops.

  • Neighbor-list APIs now include inline pair_fn potentials, optional per-pair vectors/distances, a cluster-pair tile strategy, partial rebuild flags, and public strategy cost/suggestion helpers.

  • compute_bspline_moduli_1d is exported from the top-level Torch and JAX electrostatics namespaces for PME precompute workflows.

Changed#

  • Direct-output flags on full Ewald/PME APIs remain functional but are deprecated for differentiable training. Use energy-only calls plus framework autograd for forces, charge gradients, and virials in training workflows.

  • neighbor_list(method=None) now uses a geometry cost model and can select fine-grained strategies such as naive_tile, cell_list_pair_centric, and cluster_tile when eligible.

  • The nvalchemiops.neighbors package was restructured into per-strategy subpackages (naive/, cell_list/, cluster_tile/, rebuild/). Flat compatibility modules continue to re-export with DeprecationWarning.

  • DFT-D3 dispersion kernels were optimized for improved performance.

  • PyTorch version requirements were loosened and CUDA backend extras were updated for CUDA 12/13 install workflows.

  • The minimum warp-lang requirement is now >= 1.13.

Fixed#

  • Fixed an issue with JAX naive PBC pair-output paths that dropped non-zero periodic images. The JAX naive_neighbor_list pair-output path (return_distances / return_vectors, and now pair_fn) launched its periodic kernel with the shift axis pinned to 1, so when cutoff exceeded half the cell width (R>1) every non-zero periodic image was silently dropped — yielding too few neighbors and incorrect per-pair distances/vectors/forces relative to the PyTorch binding. The launch now enumerates all shifts (max_shifts), matching PyTorch and the analytic neighbor set in the multi-image regime. The single-cutoff cutoff < half-cell (R==1) case is unchanged.

  • Fixed an issue with JAX per-pair distance/vector higher-order gradients. The JAX neighbor-list autograd returned the detached Warp-kernel distances/vectors and re-attached only a first-order gradient via a custom_vjp, so the Hessian / Hessian-vector-product was incorrect (~45% off) whenever the downstream loss was nonlinear in the returned distances (e.g. (distances**2).sum()); first-order gradients (forces) were unaffected. The geometry is now reconstructed as a live, differentiable pure-JAX function of positions/cell, so gradients of all orders are exact (matching PyTorch and the analytic Hessian). Affects all JAX return_distances/return_vectors bindings (naive, cell_list, cluster_tile, batched).

  • Fixed DFT-D3 forces and virials with S5 smoothing. When smoothing was active, the CN-chain dE/dCN used the unswitched pair energy, so CN-chain forces and virials did not exactly match the gradient of the switched energy. Only runs with S5 smoothing enabled were affected; the default (smoothing disabled) was already correct and is unchanged.

  • Naive PBC neighbor wrapping now leaves non-periodic axes unwrapped when per-axis pbc flags are supplied.

  • Fixed Torch Ewald gradients for non-uniform per-atom energy cotangents.

  • JAX electrostatics no longer imports the removed jax.custom_transpose; transpose rules use stable jax.custom_vjp paths.

  • FIRE2 variable-cell updates now advance positions and cell degrees of freedom consistently during constrained/variable-cell relaxation.

  • Neighbor-list launchers now reject unbatched methods when batch metadata is supplied.

  • MTK NPT/NPH cell propagation, velocity half-step coupling, and barostat half-step thermostat coupling now match the intended strain-rate formulation.

  • JAX naive PBC pair-output paths enumerate all periodic images in the multi-image regime.

  • JAX per-pair distance/vector outputs are reconstructed as live differentiable geometry, fixing higher-order gradients for nonlinear distance losses.

Deprecated and Removed#

  • compute_forces, compute_virial, compute_charge_gradients, and hybrid_forces direct-output flags on full Ewald/PME APIs are deprecated for differentiable training.

  • nvalchemiops.neighbors.zero_array is deprecated; call array.zero_() directly.

  • cells_inv and volumes dynamics arguments listed in CHANGELOG.md are deprecated.

  • cell_velocities now stores the strain rate ε̇ = p_g/W, not ḣ = dh/dt.

  • npt_barostat_half_step{,_aniso,_triclinic} drop the eta_dots argument.

  • The internal make_outer_neigh_offsets helper was removed.

Version 0.3.0#

Breaking Changes#

  • PyTorch is now an optional dependency: Core codebase consists of framework-agnostic warp-lang kernels with PyTorch bindings in separate namespace (nvalchemiops.torch.*). You can install the minimum supported version of PyTorch via uv pip install nvalchemiops[torch].

  • Naive PBC cached metadata changed: public Torch and JAX naive neighbor-list workflows now cache shift_range_per_dimension, num_shifts_per_system, and max_shifts_per_system. shift_offset and total_shifts are no longer part of the public API for cached naive-PBC inputs.

Migration Guide#

Tip

If PyTorch is detected in the environment, existing imports will continue to work for the next few minor version increments, but will emit warnings to remind users to update import paths (shown below).

  • Core modules comprise the pure warp-lang kernels and launchers.

  • PyTorch neighbor lists: Change nvalchemiops.neighborlist.neighbor_list to nvalchemiops.torch.neighbors.neighbor_list

  • DFT-D3: Change from nvalchemiops.interactions.dispersion import dftd3 to from nvalchemiops.torch.interactions.dispersion import dftd3

  • Coulomb: Change from nvalchemiops.interactions.electrostatics import coulomb_energy to from nvalchemiops.torch.interactions.electrostatics import coulomb_energy

  • Ewald: Change from nvalchemiops.interactions.electrostatics import ewald_summation to from nvalchemiops.torch.interactions.electrostatics import ewald_summation

  • PME: Change from nvalchemiops.interactions.electrostatics import particle_mesh_ewald to from nvalchemiops.torch.interactions.electrostatics import particle_mesh_ewald

  • Utility functions: estimate_cell_list_sizes and estimate_batch_cell_list_sizes are now imported directly from nvalchemiops.torch.neighbors (previously nvalchemiops.neighborlist.neighbor_utils)

Version 0.2.0#

  • Bug fixes associated with neighbor list computation.

  • Added electrostatics interface.

Version 0.1.0#

  • Initial public beta release of nvalchemiops.

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