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The inherently nonlinear interaction between light and motion in cavity optomechanical systems has experimentally been studied in a linearized description in all except highly driven cases. Here we demonstrate a nanoscale optomechanical…
We propose and demonstrate a novel scheme for optical nanoparticle characterization, optofluidic force induction (OF2i), which achieves real-time optical counting with single-particle sensitivity, high throughput, and for particle sizes…
Recent years have seen a considerable surge of research on developing heuristic approaches to realize analog computing using physical waves. Among these, neuromorphic computing using light waves is envisioned to feature performance metrics…
Magnetic fluids are excellent candidates for important research fields including energy harvesting, biomedical applications, soft robotics and exploration. However, notwithstanding relevant advancements such as shape reconfigurability, that…
Mechanical systems are one of the promising platforms for classical and quantum information processing and are already widely-used in electronics and photonics. Cavity optomechanics offers many new possibilities for information processing…
Neuromorphic Computing promises orders of magnitude improvement in energy efficiency compared to traditional von Neumann computing paradigm. The goal is to develop an adaptive, fault-tolerant, low-footprint, fast, low-energy intelligent…
This chapter discusses a hydrodynamics-inspired approach to trap and manipulate light in plasmonic nanostructures, which is based on steering optical powerflow around nano-obstacles. New insights into plasmonic nanofocusing mechanisms are…
Solid-state electronics have revolutionized modern society due to their exceptional computational capabilities. However, the power consumption of chips rises dramatically with increasing integration levels as post-treatment of individual…
Over the last few decades, extensive previous studies of the nonlinear response of metal nanoparticles report a wide variation of nonlinear coefficients, thus, revealing a highly confused picture of the underlying physics. This naturally…
We propose here a new platform for a realization of novel nonvolatile optical switching devices that takes an advantage of high field confinement provided by plasmonics and multi-state programming capabilities of chalcogenide phase change…
Multimode optical fibres are hair-thin strands of glass that efficiently transport light. They promise next-generation medical endoscopes that provide unprecedented sub-cellular image resolution deep inside the body. However, confining…
Research in photonic computing has flourished due to the proliferation of optoelectronic components on photonic integration platforms. Photonic integrated circuits have enabled ultrafast artificial neural networks, providing a framework for…
We report simulation of nanostructured memristor device using piecewise linear and nonlinear window functions for RRAM and neuromorphic applications. The linear drift model of memristor has been exploited for the simulation purpose with the…
Silicon photonics has evolved from lab research to commercial products in the past decade as it plays an increasingly crucial role in data communication for next-generation data centers and high performance computing1. Recently,…
The human brain has immense learning capabilities at extreme energy efficiencies and scale that no artificial system has been able to match. For decades, reverse engineering the brain has been one of the top priorities of science and…
Unconventional computing explores multi-scale platforms connecting molecular-scale devices into networks for the development of scalable neuromorphic architectures, often based on new materials and components with new functionalities. We…
Light pressure effect has been discovered long ago and has been used as an optical method to manipulate microand nanoparticles. It is usually considered as a nonresonant effect determined by the transfer of the momentum of light. However,…
Integrated photonic circuits have transformed data communication, biosensing, and light detection and ranging, and hold wide-ranging potential for optical computing, optical imaging and signal processing. These applications often require…
Highly efficient information processing in brain is based on processing and memory components called synapses, whose output is dependent on the history of the signals passed through them. Here we have developed an artificial synapse with…
The rise of artificial intelligence has triggered exponential growth in data volume, demanding rapid and efficient processing. High-speed, energy-efficient, and parallel-scalable computing hardware is thus increasingly critical. We…