treams-rs is a Rust port of treams with a Python interface and analytic gradients.
All credit for treams belongs to the original treams contributors. Their work is described in the treams paper; please cite it when using this port.
treams-rs computes electromagnetic scattering with T-matrices: spheres,
cylinders and layered or chiral particles, finite clusters, periodic arrays and
planar stacks, with their fields, cross sections and power. A T-matrix is the
linear map from the multipole coefficients of an incident wave to those of the
scattered wave. Advect, JAX, PyTorch and HIPS Autograd use its analytic derivatives
through the ordinary treams_rs API.
Relationship to treams
- Same conventions. treams-rs uses treams' units, polarization, mode ordering and normalization. Reference tests use treams 0.4.7; historical comparisons and benchmarks identify their original treams version.
- Same numerical modules.
special,sw,cw,pw,lattice,coeffs,misc,ebcmandiokeep the treams function and argument names. - Its own Python interface. Objects such as
TMatrix,Cluster,WaveandSMatrixcarry their basis, wavenumber and media as attributes, in place of annotated arrays. - A Rust core. At run time it needs only NumPy: no treams, SciPy or Cython.
Coming from treams maps treams workflows and names to treams-rs.
Install
pip install treams-rs
Gradient frameworks and HDF5 files are optional extras:
pip install "treams-rs[advect]" # or [jax], [torch], [autograd]
pip install "treams-rs[io]" # HDF5 T-matrix files
Wheels cover CPython 3.12–3.15 on Linux (glibc 2.17 or newer, x86-64 and
arm64), macOS (Intel and Apple silicon) and Windows (x86-64), and need no Rust
toolchain. Standard PyPI installs of the torch and io extras on CPython
3.15 are outside the release qualification. NumPy 2.3 and newer have
Linux wheels only for glibc 2.27 or newer; with an older glibc, use CPython 3.12
or 3.13 and pip install treams-rs "numpy<2.3". JAX and PyTorch have no Intel
macOS wheels; use the advect or autograd extra there. See
Install
for optional dependencies and source builds.
Example
Two absorbing dielectric spheres scatter a circularly polarized plane wave:
import treams_rs as tr
spheres = [
tr.sphere_tmatrix(k0=1.3, lmax=3, radius=r, material=4 + 0.1j) for r in (0.2, 0.25)
]
cluster = tr.Cluster(spheres, positions=[[0, 0, 0], [0, 0, 0.8]])
incident = tr.plane_wave(direction=[0, 0, 1], pol="positive_helicity", k0=1.3)
scattered = cluster.scatter(incident)
print(scattered.efield([[0.1, 0.2, 1.2]]))
Differentiation
Pass framework values to the same physics API: treams-rs selects the adapter
automatically. This gives the gradient of the scattering cross section with
respect to the sphere radius (pip install "treams-rs[advect]"):
from advect import grad
import treams_rs as tr
def scattering(radius):
sphere = tr.sphere_tmatrix(k0=1.3, lmax=2, radius=radius, material=3)
incident = tr.plane_wave([0, 0, 1], "positive_helicity", k0=1.3)
return sphere.cross_sections(incident).scattering
print(grad(scattering)(0.2))
The same scattering function works with jax.grad, torch.autograd and
autograd.grad. Optional adapters load only when needed; Python and NumPy
inputs retain NumPy behavior. Rust computes each derivative analytically.
The adapters support first-order CPU forward and reverse mode: JVPs give the
sensitivity of every output to one input direction; pullbacks give objective
gradients with respect to many inputs. Higher derivatives remain unsupported.
Direct records expose context.pushforward(*tangents) and
context.pullback(*cotangents), with one derivative action per context.
Framework-specific dtype and transform requirements are listed in
Differentiation.
Documentation
The documentation covers:
- Getting started: four short examples.
- Coming from treams: workflows, names and conventions side by side.
- User guide: particles, clusters, periodic arrays, planar stacks and numerical functions.
- Differentiation:
gradients through Advect, JAX, PyTorch, HIPS Autograd and the
diffmodule. - Examples: the treams gallery in treams-rs, plus gradient-based design.
- Validation: tests against treams, analytic results and published spectra.
- Performance: CPU timings against treams 0.4.5, with the measured builds and limitations recorded.
- Reference: every public function and class.
- Development: building from a checkout, tests and contributing.
Citing
If you use treams-rs, cite it with the metadata in CITATION.cff, and cite the treams paper:
D. Beutel, I. Fernandez-Corbaton and C. Rockstuhl, "treams – a T-matrix-based scattering code for nanophotonics", Computer Physics Communications 297, 109076 (2024), https://doi.org/10.1016/j.cpc.2023.109076.
License
treams-rs is released under the MIT license. It ports numerical methods from treams (LICENSE.treams) and from the other projects listed in THIRD_PARTY_NOTICES.md.
1 maintainer
Metadata
1 maintainer
Release files for treams-rs 0.2.2
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Source distribution (sdist)
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Built distributions (wheels)
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