Researcher:
Amiri, Ali Najjar

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Master Student

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Ali Najjar

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Amiri

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Amiri, Ali Najjar

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2022 - 20244

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Researcher Of Publications: search.filters.isAuthorOfPublication.d4caeff6-4c84-44e9-9d44-09221af6656c

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    A wideband silicon photonic duplexer constructed from a deep photonic network of custom Mach-Zehnder interferometers
    (Society of Photographic Instrumentation Engineers (SPIE), 2024) Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Amiri, Ali Najjar; Görgülü, Kazım; Mağden, Emir Salih; Graduate School of Sciences and Engineering; College of Engineering
    Using a highly-scalable and physics-informed design platform with custom Mach-Zehnder interferometers (MZIs), we design and experimentally demonstrate a 1 x 2 wideband duplexer on silicon operating within 1450-1630 nm. The device is constructed from six layers of cascaded MZIs whose geometries are optimized using an equivalent artificial neural network, in a total timeframe of 75 seconds. Experimental results show below 0.72 dB deviation from the arbitrarily-specified target response, and less than 0.66 dB insertion loss. Demonstrated capabilities and the computational efficiency of our design framework pave the way towards the scalable deployment of custom MZI networks in communications, sensing, and computation applications.
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    Optimizing photonic devices under fabrication variations with deep photonic networks
    (SPIE-Int Soc Optical Engineering, 2024) Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Görgülü, Kazım; Vit, Aycan Deniz; Amiri, Ali Najjar; Mağden, Emir Salih; Graduate School of Sciences and Engineering; College of Engineering
    We propose a deep photonic interferometer network architecture for designing fabrication-tolerant photonic devices. Our framework incorporates layers of variation-aware, custom-designed Mach-Zehnder interferometers and virtual wafer maps to optimize broadband power splitters under fabrication variations. Specifically, we demonstrate 50/50 splitters with below 1% deviation from the desired 50/50 ratio, even with up to 15 nm over-etch and under-etch variations. The significantly improved device performance under fabrication-induced changes demonstrates the effectiveness of the deep photonic network architecture in designing fabrication-tolerant photonic devices and showcases the potential for improving circuit performance by optimizing for expected variations in waveguide width.
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    Deep photonic network platform enabling arbitrary and broadband optical functionality
    (Nature Portfolio, 2024)  ; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Amiri, Ali Najjar; Vit, Aycan Deniz; Görgülü, Kazım; Mağden, Emir Salih;  ; Graduate School of Sciences and Engineering; College of Engineering;  
    Expanding applications in optical communications, computing, and sensing continue to drive the need for high-performance integrated photonic components. Designing these on-chip systems with arbitrary functionality requires beyond what is possible with physical intuition, for which machine learning-based methods have recently become popular. However, computational demands for physically accurate device simulations present critical challenges, significantly limiting scalability and design flexibility of these methods. Here, we present a highly-scalable, physics-informed design platform for on-chip optical systems with arbitrary functionality, based on deep photonic networks of custom-designed Mach-Zehnder interferometers. Leveraging this platform, we demonstrate ultra-broadband power splitters and a spectral duplexer, each designed within two minutes. The devices exhibit state-of-the-art experimental performance with insertion losses below 0.66 dB, and 1-dB bandwidths exceeding 120 nm. This platform provides a tractable path towards systematic, large-scale photonic system design, enabling custom power, phase, and dispersion profiles for high-throughput communications, quantum information processing, and medical/biological sensing applications. An efficient and physically accurate platform is required to rapidly design high-performance integrated photonic devices. Here, the authors present a scalable framework for creating on-chip optical systems with complex and arbitrary functionality.
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    Optical neural networks with arbitrary and wideband photonic functionality
    (Optica Publishing Group, 2022) Department of Electrical and Electronics Engineering; N/A; N/A; N/A; Department of Electrical and Electronics Engineering; Mağden, Emir Salih; Görgülü, Kazım; Vit, Aycan Deniz; Amiri, Ali Najjar; Faculty Member; PhD Student; Master Student; Master Student; College of Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; 276368; N/A; N/A; N/A
    We demonstrate a highly scalable silicon photonic neural network architecture enabling arbitrarily complex, on-chip optical functionality. We use this architecture to demonstrate wideband power splitters, achieving near-lossless and flat-top transmission bands.