Related papers: Wireless Optogenetic Nanonetworks: Device Model an…
Body-coupled powering (BCP) is an innovative wireless power transfer (WPT) technique, recently explored for its potential to deliver power to cutting-edge biomedical implants such as nerve and muscle stimulators. This paper demonstrates the…
Recently, Optical wireless communication (OWC) have been considered as a key element in the next generation of wireless communications due to its potential in supporting unprecedented communication speeds. In this paper, infrared lasers…
Photonic computing chips have made significant progress in accelerating linear computations, but nonlinear computations are usually implemented in the digital domain, which introduces additional system latency and power consumption, and…
We introduce a fiber-optic architecture for neural recording without contrast agents, and study its properties theoretically. Our sensor design is inspired by electrooptic modulators, which modulate the refractive index of a waveguide by…
Physical challenges at the device and interconnect level limit both network and computing energy efficiency. While photonics is being considered to address interconnect bottlenecks, optical routing is still limited by electronic circuitry,…
Edge AI applications increasingly require ultra-low-power, low-latency inference. Neuromorphic computing based on event-driven spiking neural networks (SNNs) offers an attractive path, but practical deployment on resource-constrained…
The spatial confinement and temporal control of an optical excitation on nanometer length scales and femtosecond time scales has been a long-standing challenge in optics. It would provide spectroscopic access to the elementary optical…
Vertical Cavity Surface Emitting Lasers (VCSELs) have gained popularity in Optical Wireless Communication (OWC) due to their high modulation bandwidth, narrow spectral width, and directional beam, offering improved spectral efficiency and…
This paper predicts the ability to externally control the firing times of a cortical neuron whose behavior follows the Izhikevich neuron model. The Izhikevich neuron model provides an efficient and biologically plausible method to track a…
Artificial Neural Networks are computational network models inspired by signal processing in the brain. These models have dramatically improved the performance of many learning tasks, including speech and object recognition. However,…
Communications based solely on radio frequency (RF) networks cannot provide adequate quality of service for the rapidly growing demands of wireless connectivity. Since devices operating in the optical spectrum do not interfere with those…
Nanomachines promise to enable new medical applications, including drug delivery and real time chemical reactions' detection inside the human body. Such complex tasks need cooperation between nanomachines using a communication network.…
The design of energy-efficient mechanisms is one of the key challenges in emerging wireless small cell networks. In this paper, a novel approach for opportunistically switching ON/OFF base stations to improve the energy efficiency in…
Today, machine learning tools, particularly artificial neural networks, have become crucial for diverse applications. However, current digital computing tools to train and deploy artificial neural networks often struggle with massive data…
This work reports a nanostructure resonant tunnelling diode-photodetector (RTD-PD) device and demonstrates its operation as a controllable, optically-triggered excitable spike generator. The top contact layer of the device is designed with…
Optical computing is an emerging technology for next-generation efficient artificial intelligence (AI) due to its ultra-high speed and efficiency. Electromagnetic field simulation is critical to the design, optimization, and validation of…
Owing to their significant advantages in terms of bandwidth, power efficiency, and latency, optical neuromorphic systems have arisen as interesting alternatives to digital electronic devices. Recently, photonic crystal nanolasers with…
Superconducting optoelectronic hardware is being explored as a path towards artificial spiking neural networks with unprecedented scales of complexity and computational ability. Such hardware combines integrated-photonic components for…
Modern neuroscience is currently limited in its capacity to perform long term, wide-field measurements of neuron electromagnetics with nanoscale resolution. Quantum microscopy using the nitrogen vacancy centre (NV) can provide a potential…
High-speed optical imaging of dynamic neuronal activity is essential yet challenging in neuroscience. While calcium imaging has been firmly established as a workhorse technique for monitoring neuronal activity, its limited temporal…