A generalized silicon photonics device suite: from communications to AI

الموضوعات

علوم تطبيقية وتكنولوجية

الملخص

The massive growth of telecommunications traffic has brought about the necessity for communication systems to be increasingly cheaper, faster, and more power efficient. Photonic integrated circuits (PICs) have attracted considerable interest due to their inherent advantages in meeting the ever-increasing bandwidth demand. These advantages include but are not limited to, low propagation loss, absence of Joule heating, and increased bandwidth. Certain techniques, such as wavelength division multiplexing (WDM) realized on silicon photonics platforms, pose very promising solutions for enhancing the aggregate bandwidth and enabling low-power, efficient transceivers. PICs aim to combine a vast number of optical devices in conjunction with microelectronics for optimized on-chip integration density. Aside from communications, PICs have also been rapidly gaining traction in the field of artificial intelligence (AI) accelerators. State-of-the-art AI algorithms rely on large amounts of linear algebra computations, i.e., multiply–accumulate operations (MAC). These computations can seamlessly be performed at the speed of light using meshes of photonic components such as Mach-Zehnder modulators (MZMs) and other photonic components. Even though PICs possess a wide range of advantages, one key challenge associated with them, is fabrication reproducibility, i.e., large performance variation across different locations on the silicon wafer. In this work, we experimentally demonstrate a set of silicon photonics devices aimed to be used in photonic transceivers and AI accelerators. The devices are fabricated on a state-ofthe-art, 45-nm, monolithic silicon photonics platform and are specifically designed to demonstrate fabrication robustness. We develop wavelength-independent power splitters, which demonstrate broadband performance and can be tuned to attain any value of power splitting ratio (SR) depending on the application. Subsequently, we employ these splitters on a compact Mach-Zehnder Interferometer (MZI)-based cWDM filter aiming at flat-top, high crosstalk response. The devices demonstrate excellent performance stability throughout different wafer sites. Lastly, we design heaters based on micro-ring resonator-assisted MZMs (RAMZMs) as low-power, lowoperating-voltage efficient optical interference units, and non-linear activation units for photonic neural networks. The fabricated passive and active devices operate in the O-band and can seamlessly be integrated into communications or AI applications. Finally, we design, train, and validate a photonic neural network based on a MZM mesh-based architecture for boolean logic applications.

روابط وملفات

التعريف والنوع

رقم الوثيقة

ffbdae44-f707-4bac-9dc6-94219ab54d2e

رقم العقد

0

نوع الوسائط

Crawler

نوع المحتوى

الرسائل العلمية

صيغة المصدر

رسائل دكتوراة

نوع الملف

pdf text

أسماء الملفات

2282644_1.pdf

بيانات النشر

ألقاب المؤلفين

[{"name_ar":"Jaime Viegas","title_ar":"اشراف","title_en":"Supervision"},{"name_ar":"Marios Papadovasilakis","title_ar":"اعداد","title_en":"Preparation"},{"name_ar":"Mihai Sanduleanu","title_ar":"اشراف","title_en":"Supervision"}]

اللغة

English

المصدر والدورية

اسم المصدر

A generalized silicon photonics device suite: from communications to AI

المحتوى والصفحات

عدد الصفحات

0

كلمات الباحثين

silicon photonics, photonic integrated circuits, photonic neural networks, wavelength division multiplexing, wavelength independent coupler

إشراف وإعداد

الإشراف

Jaime Viegas, Mihai Sanduleanu

الإعداد

Marios Papadovasilakis

الاقتباسات الببليوغرافية