105 lines
3.6 KiB
Python
105 lines
3.6 KiB
Python
"""MFM Current Simulation — magnetic field from a current-carrying line."""
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from __future__ import annotations
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import numpy as np
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from backend.node_registry import register_node
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from backend.data_types import DataField
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# Vacuum permeability
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MU_0 = 4.0e-7 * np.pi
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@register_node(display_name="MFM Current Simulation")
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class MFMCurrentSimulation:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"field": ("DATA_FIELD",),
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"height": ("FLOAT", {
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"default": 100e-9, "min": 1e-9, "max": 10e-6, "step": 1e-9,
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}),
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"current": ("FLOAT", {
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"default": 1e-3, "min": 1e-9, "max": 1.0, "step": 1e-6,
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}),
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"width": ("FLOAT", {
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"default": 100e-9, "min": 1e-9, "max": 10e-6, "step": 1e-9,
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}),
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"tip_magnetization": ("FLOAT", {
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"default": 1e5, "min": 1.0, "max": 1e8, "step": 1.0,
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}),
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}
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}
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OUTPUTS = (
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('DATA_FIELD', 'hx'),
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('DATA_FIELD', 'hz'),
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('DATA_FIELD', 'force'),
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)
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FUNCTION = "process"
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DESCRIPTION = (
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"Simulates the magnetic field produced by an infinite current-carrying "
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"strip (running along the y-axis) and the resulting force on an MFM "
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"tip. Uses the Biot-Savart law for a flat strip of finite width to "
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"compute the Hx and Hz field components at a given observation height, "
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"then derives the z-force on a point-dipole tip from the analytical "
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"gradient dHz/dz."
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)
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def process(
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self,
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field: DataField,
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height: float,
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current: float,
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width: float,
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tip_magnetization: float,
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) -> tuple:
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data = np.asarray(field.data, dtype=np.float64)
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yres, xres = data.shape
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xreal = field.xreal
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# Spatial grid centred on the field: current line sits at x = 0.
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# Matches Gwyddion convention: x = j * xreal / xres - xreal / 2
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x = np.linspace(0, xreal, xres, endpoint=False) - xreal / 2.0
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# Pre-computed constants (following Gwyddion mfm.c notation)
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m = current / (2.0 * np.pi * width) # I / (2 pi w)
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w2 = 0.5 * width # half-width
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hh = height * height # h^2
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xpw2 = x + w2 # x + w/2
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xmw2 = x - w2 # x - w/2
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xpw2h2 = xpw2**2 + hh # (x + w/2)^2 + h^2
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xmw2h2 = xmw2**2 + hh # (x - w/2)^2 + h^2
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# --- Hx (1-D) ---
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# Gwyddion: m * atan(h * w / (h^2 + x^2 - w2^2))
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# Equivalent to (I / (2 pi w)) * [atan((x+w/2)/h) - atan((x-w/2)/h)]
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hx_1d = m * np.arctan2(height * width, hh + x**2 - w2**2)
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# --- Hz (1-D) ---
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# Gwyddion: 0.5 * m * ln((x-w/2)^2 + h^2) / ((x+w/2)^2 + h^2))
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hz_1d = 0.5 * m * np.log(xmw2h2 / xpw2h2)
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# --- dHz/dz (1-D), analytical derivative ---
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# Gwyddion: m * x * h * w / ((xmw2h2) * (xpw2h2))
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t = 1.0 / (xmw2h2 * xpw2h2)
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dhz_dz_1d = m * x * height * width * t
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# Tile 1-D rows into 2-D arrays (field is constant along y).
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hx_2d = np.tile(hx_1d, (yres, 1))
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hz_2d = np.tile(hz_1d, (yres, 1))
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# Force on a point-dipole tip: Fz = mu_0 * m_tip * dHz/dz
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fz_1d = MU_0 * tip_magnetization * dhz_dz_1d
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fz_2d = np.tile(fz_1d, (yres, 1))
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return (
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field.replace(data=hx_2d, si_unit_z="A/m"),
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field.replace(data=hz_2d, si_unit_z="A/m"),
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field.replace(data=fz_2d, si_unit_z="N"),
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)
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