Martino Ferrari
03b63ba03a
Full implementation of Laguerre-Gauss modal reconstruction for gyrotron beam diagnostics, per the approved design spec, plus tests, docs, and a runnable end-to-end example. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
109 lines
3.8 KiB
Python
109 lines
3.8 KiB
Python
"""End-to-end demonstration of the he11lib reconstruction pipeline.
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Simulates a gyrotron beam that is mostly the LG_00 fundamental mode with a
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small admixture of LG_01, viewed by a thermal camera at four distances from
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the output window. The camera has an unknown transverse offset/pointing and
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adds sensor noise; the target also has some thermal-diffusion blur that we
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correct for. We then reconstruct the mode purity, beam center/pointing, and
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plot the diagnostics.
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Run with:
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python examples/full_pipeline_example.py
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"""
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from __future__ import annotations
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import matplotlib.pyplot as plt
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from he11lib import (
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BeamReconstructor,
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DiffusionDeconvolver,
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LGBasis,
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SyntheticBeamGenerator,
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plot_center_trace,
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plot_mode_purity,
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plot_residuals,
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)
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# --- Known reference beam parameters (from the gyrotron/mode-converter design) ---
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W0 = 5e-3 # reference waist radius, meters
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Z0 = 0.5 # reference waist location, meters from the output window
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WAVELENGTH = 1.76e-3 # radiation wavelength, meters (e.g. a 170 GHz gyrotron)
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# --- Ground truth for the synthetic beam (unknown to the reconstructor) ---
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TRUE_COEFFICIENTS = {(0, 0): 0.95 + 0j, (0, 1): 0.25 + 0.05j}
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TRUE_CENTER = (0.4e-3, -0.3e-3) # beam offset from the camera's optical axis
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TRUE_POINTING_DEG = 0.15 # beam pointing (tilt) angle
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CAMERA_VIEWING_ANGLE_DEG = 5.0 # oblique camera viewing angle (known)
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CAMERA_PIXEL_SCALE = 4e-4 # meters/pixel (known calibration)
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IMAGE_SHAPE = (81, 81)
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# Measurement plane distances, meters. Kept within roughly +/-2 Rayleigh
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# ranges of z0 so the (widening) beam stays well within the camera frame --
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# planes much farther out would be clipped by the finite frame, which
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# degrades the fit.
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Z_LIST = [0.4, 0.45, 0.55, 0.6]
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# --- Target thermal-diffusion blur (known target material properties) ---
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THERMAL_DIFFUSIVITY = 1e-6 # m^2/s
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DWELL_TIME = 0.2 # s
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def main() -> None:
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basis = LGBasis(w0=W0, z0=Z0, wavelength=WAVELENGTH)
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generator = SyntheticBeamGenerator(
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basis=basis, image_shape=IMAGE_SHAPE, pixel_scale=CAMERA_PIXEL_SCALE
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)
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planes = generator.generate(
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coefficients=TRUE_COEFFICIENTS,
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z_list=Z_LIST,
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center=TRUE_CENTER,
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pointing_angle_deg=TRUE_POINTING_DEG,
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viewing_angle_deg=CAMERA_VIEWING_ANGLE_DEG,
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noise_std=2e-4,
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seed=42,
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)
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# Apply the same thermal-diffusion blur a real target would exhibit.
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blur_deconvolver = DiffusionDeconvolver(
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thermal_diffusivity=THERMAL_DIFFUSIVITY, dwell_time=DWELL_TIME
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)
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for plane in planes:
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plane.flux = blur_deconvolver.blur(plane.flux, plane.pixel_scale)
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# The ground truth only has order-0 and order-1 content, so a max_order
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# of 1 is enough for automatic mode-set growth to find it; growing much
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# further would start fitting deconvolution/noise artifacts as spurious
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# higher-order modes.
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reconstructor = BeamReconstructor(
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w0=W0,
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z0=Z0,
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wavelength=WAVELENGTH,
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max_order=1,
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deconvolver=blur_deconvolver,
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)
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result = reconstructor.reconstruct(planes)
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print("Mode purity table (power fraction, phase [rad]):")
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for mode, (fraction, phase) in sorted(
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result.purity.items(), key=lambda item: -item[1][0]
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):
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print(f" LG_{mode[0]},{mode[1]}: {fraction:6.3%} (phase {phase:+.3f} rad)")
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print(f"\nFitted pointing angle: {result.pointing_angle_deg:.4f} deg")
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print("Fitted beam center per plane (m):")
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for plane, (cx, cy) in zip(planes, result.centers):
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print(f" z={plane.z:.2f} m -> ({cx:.3e}, {cy:.3e})")
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print(f"\nUsed phase-retrieval fallback: {result.used_phase_retrieval}")
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plot_mode_purity(result)
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plot_center_trace(planes, result)
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plot_residuals(planes, result)
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plt.show()
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if __name__ == "__main__":
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main()
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