Researcher:
Vit, Aycan Deniz

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Master Student

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Aycan Deniz

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Vit

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Vit, Aycan Deniz

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2022 - 20244

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Researcher Of Publications: search.filters.isAuthorOfPublication.f3ca195c-1ad2-4881-b07b-4d3844b7f5e0

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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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    Towards universal polarization handling with silicon-based deep photonic networks
    (SPIE, 2024) Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Vit, Aycan Deniz; Görgülü, Kazım; Mağden, Emir Salih; Graduate School of Sciences and Engineering; College of Engineering
    We propose a novel methodology employing deep photonic networks comprising cascaded Mach-Zehnder Interferometers (MZIs) to illustrate the proficiency of on-chip polarization handling. By applying gradient-based optimization techniques to tailor specific phase profiles within successive layers of MZIs, we demonstrate the functionality of devices adept at power division in both polarization-dependent and polarization-independent modalities. In silico simulations underscore the cutting-edge performance metrics achieved, encompassing a bandwidth exceeding 120 nm centered at 1550 nm, an extinction ratio surpassing 15 dB, and transmission bands characterized by flat-top profiles. These results prove the comprehensive capabilities of our deep photonic network ecosystem in polarization management, thereby unveiling promising prospects for advanced optical applications necessitating versatile polarization handling capabilities. © 2024 SPIE.
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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.