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Photonic processors use optical signals for computation, leveraging the high bandwidth and low loss of optical links. While many approaches have been proposed, including in memory photonic circuits, most efforts have focused on the physical…
The first contribution of this paper is the development of extremely dense, energy-efficient mixed-signal vector-by-matrix-multiplication (VMM) circuits based on the existing 3D-NAND flash memory blocks, without any need for their…
Photonic integrated circuits are finding use in a variety of applications including optical transceivers, LIDAR, bio-sensing, photonic quantum computing, and Machine Learning (ML). In particular, with the exponentially increasing sizes of…
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…
Computational hardware designed to mimic biological neural networks holds the promise to resolve the drastically growing global energy demand of artificial intelligence. A wide variety of hardware concepts have been proposed, and among…
In neuromorphic photonic systems, device operations are typically governed by analog signals, necessitating digital-to-analog converters (DAC) and analog-to-digital converters (ADC). However, data movement between memory and these…
With the increasing need for large volumes of data processing, transport, and storage, optimizing the trade-off between high-speed and energy consumption in today's optoelectronic devices is getting increasingly difficult. Heterogeneous…
Photonics offers a route to fast and distributed quantum computing in ambient conditions, provided that photon sources and logic gates can be operated deterministically. Quantum memories, capable of storing and re-emitting photons on…
Long regarded as a model system for studying insulator-to-metal phase transitions, the correlated electron material vanadium dioxide (VO$_2$) is now finding novel uses in device applications. Two of its most appealing aspects are its…
Nowadays, Information Photonics is extensively studied and sees applications in many fields. The interest in this breakthrough technology is mainly stimulated by the possibility of achieving real-time data processing for high-bandwidth…
The geometrical and performance scaling of silicon CMOS integrated circuit technology over the past 50 years has enabled many affordable new products for business and consumer applications. Recognizing that Flash is approaching its ultimate…
The coherent storage, buffering and retrieval of photons in a quantum memory enables the scalable creation of photonic entangled states via linear optics and repeat-until-success, unlocking applications in quantum communications and…
The majority of silicon photonics is built on silicon-on-insulator (SOI) wafers while the majority of electronics, including CPUs and memory, are built on bulk silicon wafers, limiting broader acceptance of silicon photonics. This…
As artificial intelligence continues to grow, so does the need for more efficient ways to process data. Besides moving from electronic to photonic circuits, a promising approach is to integrate phase-change materials. Vanadium dioxide…
Two-dimensional (2D) semiconductors are emerging as a versatile platform for nanophotonics, offering unprecedented tunability in optical properties through exciton resonance engineering, van der Waals heterostructuring, and external field…
We report an electrically actuated, low-loss non-volatile optical switch based on the phase-change material (PCM) Sb2Se3 integrated on a silicon nitride (Si3N4) platform. The device is fabricated using an 8-inch wafer-scale process flow,…
Optical switches are one of the most important elements of integrated photonics. Here, we designed, fabricated and characterized several nanophotonic optical switches (NOSs) in silicon that exhibit ultra-compact footprint, along with…
Resistive memories are outstanding electron devices that have displayed a large potential in a plethora of applications such as nonvolatile data storage, neuromorphic computing, hardware cryptography, etc. Their fabrication control and…
Neuromorphic networks of artificial neurons and synapses can solve computational hard problems with energy efficiencies unattainable for von Neumann architectures. For image processing, silicon neuromorphic processors outperform graphic…
For the last decade quantum memories have been intensively studied for potential applications to quantum information and communications using atomic and ionic ensembles. With the importance of a multimode storage capability in quantum…