{"product_id":"photonic-matrix-computing-using-optical-interference-and-waveguide-arrays-to-accelerate-neural-multiplication-at-minimal-energy-cost-9798195773212","title":"Photonic Matrix Computing: Using Optical Interference and Waveguide Arrays to Accelerate Neural Multiplication at Minimal Energy Cost","description":"\u003cp\u003e • Author(s): Harlan Quince\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Physics - Optics \u0026amp; Light\u003c\/p\u003e\u003cp\u003e\u003cb\u003ePhotonic matrix computing for modern neural workloads\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eThis book presents a practical, system-level view of how optical interference, coherent light, and programmable waveguide arrays can be used to perform matrix multiplication with far less energy than conventional digital MAC pipelines. It bridges core physics, hardware design, and neural network deployment, making it useful for readers who want to understand both the promise and the engineering limits of photonic acceleration.\u003c\/p\u003e\u003cp\u003eBeginning with the computational role of matrix operations in neural networks, the book explains how dataflow, numerical formats, and matrix shapes influence hardware efficiency. It then builds the optical foundation, covering coherence, phase control, intensity detection, and the linear behavior that makes photonic transforms possible.\u003c\/p\u003e\u003cp\u003eFrom there, the focus shifts to real architectures, including reconfigurable photonic meshes, beam splitters, phase shifters, and calibration methods for realizing target matrices. Detailed coverage shows how to encode inputs, handle positive and negative values, scale outputs, and run batch or tiled workloads for larger layers.\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eHardware-aware training and inference\u003c\/b\u003e for optical weight constraints\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eNonidealities and mitigation\u003c\/b\u003e including loss, crosstalk, quantization, and detector noise\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eEnergy accounting\u003c\/b\u003e across optical power, modulation, control, I\/O, and synchronization\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eIntegration strategies\u003c\/b\u003e for combining photonic tiles with digital systems\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eCalibration, verification, and maintenance\u003c\/b\u003e workflows for stable operation\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eThe later chapters bring these ideas together through case studies and design methodology, showing how to estimate energy budgets, choose encodings, and co-design accuracy with power consumption. Worked examples throughout the book make the material concrete and help readers move from theory to implementation.\u003c\/p\u003e\u003cp\u003e\u003ci\u003eIdeal for engineers, researchers, and advanced students working in photonics, hardware acceleration, and efficient neural computation.\u003c\/i\u003e\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47882627907735,"sku":"9798195773212","price":1503.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798195773212.webp?v=1781096345","url":"https:\/\/atlanticbooks.com\/products\/photonic-matrix-computing-using-optical-interference-and-waveguide-arrays-to-accelerate-neural-multiplication-at-minimal-energy-cost-9798195773212","provider":"Atlantic Books","version":"1.0","type":"link"}