Modal decomposition of fiber modes based on direct far-field measurements at two different distances with a...

Area of Science:

• Optics and Photonics
• Fiber Optics Engineering
• Computational Physics

Background:

• Modal decomposition is crucial for understanding and controlling light propagation in optical fibers.
• Large-mode-area fibers offer advantages in power handling but present challenges in modal analysis.
• Existing methods for modal decomposition can be complex or lack precision.

Purpose of the Study:

• To present a novel and effective method for modal decomposition of composite beams in large-mode-area fibers.
• To achieve accurate modal decomposition using direct far-field pattern measurements.
• To validate the proposed method through numerical simulations and experimental verification.

Main Methods:

• Utilized direct far-field pattern measurements for modal decomposition.
• Employed finite-number bases of Hermite Gaussian modes for reconstructing far-field patterns.
• Applied a stochastic parallel gradient descent (SPGD)-based multi-variable optimization algorithm with the D4σ technique.
• Compensated for centroid mismatch between measured and reconstructed beams.
• Measured beam intensity profiles at two distinct distances to ensure solution uniqueness.

Main Results:

• Successfully demonstrated modal decomposition with high accuracy.
• Achieved fractional error tolerance below 1 × 10^-7 in numerical simulations.
• Attained fractional error tolerance below 3.5 × 10^-3 in experimental demonstrations.
• Confirmed that the method maintains high accuracy even for measurements at farther distances.

Conclusions:

• The proposed method provides a unique and reliable approach for modal decomposition of composite beams.
• The technique is feasible and effective for both numerical and experimental applications.
• The method's accuracy is robust and can be maintained over extended measurement distances.