In optical computing, a pressing challenge is the efficient implementation of real-valued optical matrix vector multiplication (MVM). While optical computing offers advantages such as high bandwidth, low latency, and power efficiency, traditional optical matrix computing methods have been designed for complex-valued matrices, resulting in significant resource redundancy when dealing with matrices. of real values. This redundancy consumes additional power and leads to a larger chip footprint, raising concerns about space efficiency and scalability in large-scale optical neural networks (ONNs) and optimization problem solvers.
Efforts have been made to address this problem, with solutions such as a pseudo-real-valued MZI mesh. The pseudo-real-valued MZI mesh was intended to reduce the number of phase shifters required for real-valued matrices, but introduced complexities related to coherent detection and additional reference paths, which could introduce sources of error and design complexities.
In response to these challenges, a novel and simplified solution has emerged: a real-valued MZI mesh for incoherent optical MVM. This innovative approach scales down the required phase shifters to N^2 while maintaining an optical depth of N + 1. Instead of detecting the complex value of the output optical field, this method employs an additional port to perform optical power subtraction, which produces a production of real value. This not only streamlines hardware requirements but also simplifies the detection process, overcoming the limitations of previous solutions.
To evaluate the performance and feasibility of the proposed real-valued MZI mesh, extensive numerical evaluations were performed using particle swarm optimization (PSO). The results of these evaluations demonstrated the exceptional performance of the mesh on benchmark tasks, highlighting its potential as an efficient solution for real-value optical MVMs in ONN. Furthermore, error analyzes revealed its resistance to manufacturing errors, improving its reliability for practical applications.
Furthermore, the study introduced a nonlinear activation function on the matching chip, further emphasizing the suitability of the mesh for large-scale ONN. With its space efficiency, energy efficiency, scalability and robustness to manufacturing errors, Real-Valued MZI Mesh emerges as a promising solution to all the challenges of real-valued optical matrix computing. As the field of optical computing continues to evolve, this innovative approach holds great promise for the future of large-scale ONNs and combined optimization problem solvers, as it offers a more efficient and practical path forward.
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Niharika is a Technical Consulting Intern at Marktechpost. She is a third-year student currently pursuing her B.tech degree at the Indian Institute of technology (IIT), Kharagpur. She is a very enthusiastic person with a keen interest in machine learning, data science and artificial intelligence and an avid reader of the latest developments in these fields.
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