Optical Modeling and Performance Predictions X 2018
DOI: 10.1117/12.2321029
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On-chip photonic filter design via objective-first algorithm

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“…Recently, various techniques to design nanophotonic devices following a top-down approach, such as topology optimization [6][7][8], genetic algorithms [9,10], particle swarm optimization [11] or the objective-first approach [12], have emerged. The objective-first algorithm has proven particularly successful for designing high-efficiency and low-footprint nanophotonic devices [12][13][14][15] and currently constitutes one of the most promising nanophotonic inverse design methods. A problem of the objective-first approach however is that the resulting permittivity distribution consists of continuously varying values, while modern nanophotonic fabrication methods only allow for permittivity distributions containing two (few) discrete values, as each position in the design can only be occupied by either one material, e.g.…”
Section: Introductionmentioning
confidence: 99%
“…Recently, various techniques to design nanophotonic devices following a top-down approach, such as topology optimization [6][7][8], genetic algorithms [9,10], particle swarm optimization [11] or the objective-first approach [12], have emerged. The objective-first algorithm has proven particularly successful for designing high-efficiency and low-footprint nanophotonic devices [12][13][14][15] and currently constitutes one of the most promising nanophotonic inverse design methods. A problem of the objective-first approach however is that the resulting permittivity distribution consists of continuously varying values, while modern nanophotonic fabrication methods only allow for permittivity distributions containing two (few) discrete values, as each position in the design can only be occupied by either one material, e.g.…”
Section: Introductionmentioning
confidence: 99%