FDM Per-Magnet Grids¶

Python API¶

The complete runnable example is in the numbered example section below; the exact callable fields and arguments are in the numbered API section. These values are copied from the current Python contract, not inferred from the UI.

Symbols and SI units¶

All geometric lengths use \(\mathrm{m}\); dimensionless selectors use \(1\).

Assumptions and validity¶

Authoring validation does not prove mesh generation or solver qualification; the realized report is authoritative.

1. What it is and when to use it¶

Per-magnet grids let separate magnetic objects use distinct native Cartesian cell triples while retaining canonical object names. Use them for multilayer or strongly different length scales; use a default grid for a uniform model.

2. Physical and mathematical explanation¶

This page has no own physical equation. Each FDMGrid.cell selects the local discrete support; demagnetization coupling and any common communication grid are separate FDMDemag policies.

3. Example - complete Python script¶

# %% Per-magnet FDM grids
import fullmag as fm

nm = 1.0e-9
study = fm.study("fdm_per_magnet_grids")
study.engine("fdm")
study.device("cpu", precision="double")
study.mode("strict")
study.fdm(
    default_cell=(4 * nm, 4 * nm, 1 * nm),
    per_magnet={
        "free": fm.FDMGrid(cell=(2 * nm, 2 * nm, 1 * nm)),
        "reference": fm.FDMGrid(cell=(4 * nm, 4 * nm, 1 * nm)),
    },
)
free = study.geometry(fm.Box(40 * nm, 20 * nm, 2 * nm), name="free")
reference = study.geometry(fm.Box(40 * nm, 20 * nm, 2 * nm), name="reference")
for body in (free, reference):
    body.Ms = 800.0e3
    body.Aex = 13.0e-12
    body.m = fm.texture.uniform(1.0, 0.0, 0.0)
study.stages.add_relax(stage_id="relax", algorithm="llg_overdamped", dt=5e-13, max_steps=100)

4. Exact API¶

FDMGrid.__init__(cell) rejects malformed or non-positive triples. FDM.__init__ rejects empty names, non-FDMGrid values, and a missing default when no per-magnet grid can cover the authored objects.

ProblemIR¶

The request lowers to the mesh-workflow or discretization subtree; requested intent remains distinct from the resolved mesh asset and provenance report.

Round-trip and failure semantics¶

Requested intent is the Python policy; resolved execution is the realized mesh report. Validation errors identify the violated domain rule, and unsupported combinations fail explicitly without silent fallback.

Discrete realization¶

The backend consumes the realized Cartesian or finite-element asset, including topology, markers, quality, and provenance where available.

5. How to set it in Control Room¶

Route: Model Explorer -> Study -> Discretization -> FDM per-magnet grids. The route is partial and keyed by canonical geometry names. Apply the global study draft, then inspect the resolved grid resource. not implemented: frontend support for a dedicated typed editor when only advanced JSON is available. See Control Room capability register.

6. Backend and frontend support¶

Validation¶

Focused constructor, lowering, and mesh-report tests are the evidence boundary for this page.

7. Limitations and known pitfalls¶

• Mapping keys must equal authored geometry names.

• A local grid does not define the nonlocal demagnetization communication grid.

• Per-magnet authoring is not runtime or CPU/GPU parity evidence.

8. Scientific bibliography¶

1. C. Abert, “Micromagnetics and spintronics: models and numerical methods,” European Physical Journal B 92, 120 (2019), doi:10.1140/epjb/e2019-90599-6.

9. Source-code index¶

Source-code index¶

• Python contract source: packages/fullmag-py/src/fullmag/model/discretization.py and packages/fullmag-py/src/fullmag/world.py, where applicable. Backend realization is in the relevant backends/fdm or backends/fem lane named by the page.