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Factored form descent: a practical algorithm for coherence retrieval.

Zhengyun Zhang1, Zhi Chen, Shakil Rehman

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We developed a new algorithm for coherence retrieval, which reconstructs the correlation function of partially coherent light using intensity measurements. This method is memory-efficient and successfully tested on simulated and experimental data.

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Area of Science:

  • Optics and Photonics
  • Computational Physics

Background:

  • Coherence retrieval is crucial for characterizing partially coherent fields.
  • Existing methods for solving the underlying convex problem can be computationally intensive and memory-demanding.

Purpose of the Study:

  • To formulate coherence retrieval as a convex weighted least-squares problem.
  • To develop a novel, memory-efficient algorithm for solving this problem.
  • To validate the algorithm's performance using simulated and experimental data.

Main Methods:

  • Formulation of coherence retrieval as a convex weighted least-squares problem.
  • Development of a novel iterated descent algorithm.
  • Utilizing a coherent-modes factorization of the mutual intensity.
  • Reconstruction of mutual intensity for a Schell-model source.

Main Results:

  • The proposed iterated descent algorithm is more memory-efficient than standard interior point methods.
  • Successful reconstruction of mutual intensity from both simulated and experimental data.
  • Demonstrated feasibility of the novel approach for coherence retrieval.

Conclusions:

  • The novel iterated descent algorithm provides an efficient solution for coherence retrieval.
  • This method offers a practical alternative for characterizing partially coherent fields.
  • The approach is validated for real-world applications in optics and photonics.