Frequency-domain electromagnetic FEM solver in Rust, with a Python API and an optional local web UI.
Project description
RapidFEM
Electromagnetic FEM solver written in Rust, distributed as a Python package on PyPI. Two backends behind one geometry/material/physics API: a frequency-domain solver (second-kind Nedelec edge elements, complex-symmetric sparse linear algebra) and a time-domain DGTD solver (discontinuous Galerkin, Krylov/ETD exponential time integration, model-order reduction). Optional Flask-based local UI with a code editor and live geometry viewer.
Install
pip install rapidfem # solver only
pip install rapidfem[ui] # solver + local UI
Wheels for Windows, Linux, and macOS are built via CI. The Rust core is compiled ahead of time — no Rust toolchain required on the user's machine.
Gmsh (Python wheel gmsh) is pulled in automatically as a dependency and
provides the OpenCASCADE-based geometry + mesher used by rapidfem.Geometry.
Quick start (Python API)
import numpy as np
import rapidfem as rf
# Build geometry; attach materials + physics directly to entities
g = rf.Geometry(maxh=rf.lambda_maxh(f_max=12e9))
air = g.box(22.86e-3, 10.16e-3, 30e-3, position=(-11.43e-3, -5.08e-3, 0),
material=rf.Air())
rf.RectWaveguidePort(air.faces.min(axis="z"))
rf.RectWaveguidePort(air.faces.max(axis="z"))
rf.PEC(*air.faces.unassigned)
g.mesh()
# Define the problem once, run any number of analyses on it
prob = rf.Problem(g)
result = prob.sweep(np.linspace(8e9, 12e9, 21))
print(result.frequencies.shape, result.sparams.shape)
# Same Problem can also drive an eigenmode solve or a far-field pattern:
# modes = prob.eigenmode(target_frequency=10e9, n_modes=6)
# pattern = prob.farfield(result, freq_idx=10, port_idx=0)
See python_src/rapidfem/examples/ for end-to-end runs of microstrip lines,
patch antennas (with PML enclosure + far-field), pyramidal horns, iris
filters, dielectric resonators, and more.
Local UI
rapidfem serve ./my_project/
Opens a browser window with:
- a CodeMirror Python editor on the left,
- a 3D geometry / mesh / field viewer on the right (raw WebGL2, viridis colormap for scalar fields),
- S-parameter plots in a separate tab,
- a
Generate Meshbutton (gmsh) and aRun Simulationbutton (FEM sweep).
The geometry view updates automatically every time you save the file
(Ctrl+S). Mesh and solver runs are explicit.
Use rapidfem.show(g) at the bottom of your script to send a geometry to
the viewer.
Features
- Nedelec-2 elements — 20 DOFs per tetrahedron, vector edge basis for the curl–curl form of Maxwell's equations
- Excitations — rectangular waveguide ports (arbitrary TE modes), lumped ports (TEM, multi-line voltage integral), and absorbing boundary conditions of order 1 and 2 (selectable coefficient types A–E)
- PML — anisotropic stretched-coordinate perfectly matched layer
- Lossy materials — complex permittivity with loss tangent + conductivity; frequency-independent caching speeds up sweeps
- Sparse solvers — pure-Rust
faerLU as a no-dependency baseline; optional MKL PARDISO (complex-symmetric LDLᵀ) on Windows / Linux; Apple Accelerate Bunch-Kaufman on macOS (~3× faster than faer) - Frequency sweep — assembles E/B once, refactors only the frequency- dependent K per point, reuses the symbolic LU pattern
- Eigenmode solver — shift-invert Lanczos on the complex-symmetric system
- Adaptive refinement — residual error estimator (volume residual + face jumps) with Dörfler marking, exports a size field for gmsh re-meshing
- Output — Touchstone (.s1p/.s2p/.snp), VTK field export, far-field NFFT
- Parallel assembly — rayon-based element matrix evaluation
Time-domain backend (DGTD)
Alongside the frequency-domain solver, RapidFEM has a time-domain
discontinuous-Galerkin (DGTD) backend — ProblemTD, behind the same
geometry / material / physics API. Where ProblemFD answers "what are the
S-parameters", ProblemTD compiles a structure into an explicit linear
ODE dy/dt = A·y and exposes it as a model at every level of
abstraction.
- DGTD spatial discretisation — nodal discontinuous Galerkin on tetrahedra, upwind or energy-conserving central flux
- Exponential time integration — matrix-free Krylov/ETD propagator, exact for the linear system at any step size (no CFL limit)
- Model export — the right-hand side, the verbatim sparse operator
A, an exponential stepper, or a handoff to an external ODE integrator - Model-order reduction — Krylov-projected reduced models
- Materials — heterogeneous, lossy, diagonal-anisotropic and Debye dispersive media; matched absorbing layers
- Output — field probes, the RFT transfer function, VTK field-animation export
import rapidfem as rf
ptd = rf.ProblemTD.box(size=(1, 1, 1), cells=(2, 2, 2), order=2)
traj = ptd.transient(y0, dt=0.02, steps=200) # turnkey transient
rom = ptd.reduce(y0, dim=60) # model-order reduction
A = ptd.state_space() # the verbatim operator
The time-domain backend is cross-validated against the frequency-domain
solver (0.04 % agreement on a shared cavity). Full method notes and the
ProblemTD API reference are in docs/td-backend.md.
Solver backends
| Solver | Type | Notes |
|---|---|---|
| faer | General sparse LU | Pure Rust, no native dependencies — always available |
| MKL PARDISO | Complex-symmetric LDLᵀ | Fastest path on Windows / Linux; opt-in, requires mkl_rt on PATH |
| Apple Accelerate | Sparse Bunch-Kaufman LDLᵀ | macOS only; ~3× faster than faer, no extra install (ships with macOS) |
Choose at simulation time with the RAPIDFEM_SOLVER environment variable
("auto", "pardiso", "accelerate", "faer") — set before
import rapidfem. The default "auto" tries PARDISO → Accelerate → faer
in that order, picking the first one that loads.
Installing MKL (optional)
- conda:
conda install mkl - pip:
pip install mkl - Intel oneAPI: download
Ensure mkl_rt.dll (or mkl_rt.2.dll) is on the system PATH.
Performance
WR-90 iris waveguide driven sweep, 10 GHz, 2-port:
| Mesh | DOFs | PARDISO | faer |
|---|---|---|---|
| 693 tets | 5 512 | 0.14 s | 0.22 s |
| 1 096 tets | 8 382 | 0.06 s | 0.45 s |
| 2 595 tets | 19 196 | 0.17 s | 1.39 s |
| 3 284 tets | 23 968 | 0.21 s | 1.98 s |
Larger problems:
- 327 k DOFs driven sweep (PARDISO): ~5 s per frequency
- 905 k DOFs eigenmode (3-turn spiral, shift-invert Lanczos): ~54 s
Verification
Element-level functions (curl–curl integrals, Robin BC, second-order ABC,
mode-power normalization, surface integrals) are checked to machine precision
(1e-12 – 1e-16) by cargo test --release.
End-to-end S-parameter accuracy is tracked in tests/validation/ against
analytical solutions and external reference solvers.
cargo test --release
License
GNU Affero General Public License v3.0 or later. If you run a modified version of rapidfem as a network service (e.g. SaaS), the AGPL requires that you make the modified source available to the users of that service. For commercial use under different terms, get in touch.
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