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Creators/Authors contains: "Rahim, Muhammad Ridwanur"

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  1. ; ; ; ; (, IEEE)
    A physics-aware simulation platform is proposed for optical neural networks (ONNs), incorporating phase-only modulation and passive free-space propagation. The platform enables end-to-end training under experimentally realistic constraints, with both the phase mask and propagation distance treated as learnable parameters. To facilitate classification, structured 2D output patterns are introduced, where each label corresponds to a fixed spatial light spot. When evaluated with the MNIST dataset, the system achieves 94.6% accuracy using a single phase modulation layer, demonstrating the effectiveness of spatial encoding in physically plausible ONNs. 
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    Free, publicly-accessible full text available July 6, 2026
  2. ; ; ; ; (, IEEE)
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  3. ; ; ; ; (, Title (Book/Conference Proceeding) Author Component Number ISBN Year Persistent Link Series Title Article Title 2023 23rd International Conference on Transparent Optical Networks (ICTON))
    The Optical Network Emulation (ONE) engine is a software tool that offers students the opportunity to learn how to control and operate open optical (wavelength division multiplexing) transport networks, such as those based on the Open ROADM MSA standards. This paper describes multiple modelling techniques that are implemented in the ONE engine to represent the signal power spectral density at any link/fiber section of the emulated transport network. These techniques make use of polynomial fitting and deconvolution computation methods. 
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    Full Text Available 
  4. ; ; ; ; ; ; ; ; ; (, 2023 Optical Fiber Communications Conference and Exhibition (OFC))
    The Optical Network Emulation (ONE) engine is a real-time and realistic platform for testing functionalities and FCAPS features of OpenROADM controllers. Its decentralized architecture, potential applications, and educational purposes are discussed in this paper. 
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