Optical computing has recently attracted a great deal of interest as it offers the ability to process data in a parallel manner. In this report, an optical computing system based on a metamaterial structure made of graphene is designed and demonstrated. It is shown that the proposed structure is able to do different operations such as taking derivative, and integration of an incident field. In addition to this, it is shown that the proposed structure is reconfigurable due to the possibility of tuning the surface conductivities of the graphene flakes. The proposed configuration not only goes beyond the major restriction of traditional electronic computers, but also provides a dynamic operation.
TRON: Trainable, architecture-reconfigurable random optical neural networks
Laboratoire Kastler Brossel, ENS-Universite PSL, CNRS, Sorbonne Université, Collège de France（卡斯勒-布罗塞尔实验室，巴黎高等师范学院-PSL大学，法国国家科学研究中心，索邦大学，法兰西公学院）；Department of Electrical Engineering and Computer Science, University of California Irvine（加州大学尔湾分校电气与计算机工程系）；School of Applied and Engineering Physics, Cornell University（康奈尔大学应用工程物理学院）；NTT Physics and Informatics Laboratories, NTT Research, Inc.（NTT研究与创新公司NTT物理与信息学实验室）；Department of Applied Physics, Yale University（耶鲁大学应用物理系）
Metasurfaces, the two-dimensional counterpart of metamaterials, have caught great attention thanks to their powerful capabilities on manipulation of electromagnetic waves. Recent times have seen the emergence of a variety of metasurfaces exhibiting not only countless functionalities, but also a reconfigurable response. Additionally, digital or coding metasurfaces have revolutionized the field by describing the device as a matrix of discrete building block states, thus drawing clear parallelisms with information theory and opening new ways to model, compose, and (re)program advanced metasurface…
Reconfigurable photonic systems featuring minimal power consumption are crucial for integrated optical devices in real-world technology. Current active devices available in foundries, however, use volatile methods to modulate light, requiring a constant supply of power and significant form factors. Essential aspects to overcoming these issues are the development of nonvolatile optical reconfiguration techniques which are compatible with on-chip integration with different photonic platforms and do not disrupt their optical performances. In this paper, a solution is demonstrated using an optoele…
Photonic integrated circuits (PICs) are the foundation of on-chip optical technologies. Mach-Zehnder modulators are appealing building blocks of PICs which mostly rely on weak and volatile optical effects in materials. In contrast, phase change materials such as GSST are promising candidates to realize efficient and nonvolatile reconfigurable optical devices. However, the phase transitions of PCMs are accompanied by large changes in the imaginary parts of their refractive indices which make the design of MZMs challenging. In this paper, two interesting design methods named as loss-balancing an…
Dynamical Diversity for Reservoir Computing in Reconfigurable Nanomechanics
International Iberian Nanotechnology Laboratory (INL)（国际伊比利亚纳米技术实验室）；Bilkent University（比尔肯特大学）；UNAM - Institute of Materials Science and Nanotechnology, Bilkent University（比尔肯特大学 UNAM 材料科学与纳米技术研究所）；Sabanci University（萨班奇大学）；Koc University（科奇大学）
CMOS-based computing systems that employ the von Neumann architecture are relatively limited when it comes to parallel data storage and processing. In contrast, the human brain is a living computational signal processing unit that operates with extreme parallelism and energy efficiency. Although numerous neuromorphic electronic devices have emerged in the last decade, most of them are rigid or contain materials that are toxic to biological systems. In this work, we report on biocompatible bilayer graphene-based artificial synaptic transistors (BLAST) capable of mimicking synaptic behavior. The…
