Coherence Retrieval Using Trace Regularization
The mutual intensity and its equivalent phase-space representations quantify an optical field's state of coherence and are important tools in the study of light propagation and dynamics, but they can only be estimated indirectly from measurements through a process called coherence retrieval, ot...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Society for Industrial and Applied Mathematics,
2018-11-14T17:56:50Z.
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| Subjects: | |
| Online Access: | Get fulltext |
| Summary: | The mutual intensity and its equivalent phase-space representations quantify an optical field's state of coherence and are important tools in the study of light propagation and dynamics, but they can only be estimated indirectly from measurements through a process called coherence retrieval, otherwise known as phase-space tomography. As practical considerations often rule out the availability of a complete set of measurements, coherence retrieval is usually a challenging high-dimensional ill-posed inverse problem. In this paper, we propose a trace-regularized optimization model for coherence retrieval and a provably convergent adaptive accelerated proximal gradient algorithm for solving the resulting problem. Applying our model and algorithm to both simulated and experimental data, we demonstrate an improvement in reconstruction quality over previous models as well as an increase in convergence speed compared to existing first-order methods. Keywords: coherence retrieval, phase-space tomography, trace regularization, adaptive restart Singapore. Ministry of Education (Research Grant MOE2012-T3-1-008) Singapore. Ministry of Education (Research Grant MOE2014-T2-1-065) Singapore. Prime Minister's Office (CREATE Programme) Singapore-MIT Alliance for Research and Technology (SMART). BioSystems and Micromechanics (BioSyM) IRG |
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