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Photonic quantum memristors provide a measurement-induced route to nonlinear and history-dependent quantum dynamics. Experimental demonstrations have so far focused on isolated devices or simple cascaded devices configurations. Here, we…
Single photons enable the distribution of quantum information over large distances and thus play a major role in quantum technologies such as communication and computing. Solid-state emitters are practical and efficient sources of single…
Photonic molecules, named by analogy with chemical molecules, are clusters of closely located electromagnetically interacting microcavities or "photonic atoms". As two or several microcavities are brought close together, their optical modes…
The photon spin is an important resource for quantum information processing as is the electron spin in spintronics. However, for subwavelength confined optical excitations, polarization as a global property of a mode cannot be defined.…
The field of mimicking the structure of the brain on a chip is experiencing interest driven by the demand for machine intelligent applications. However, the power consumption and available performance of machine-learning (ML) accelerating…
Emerging applications of photonics in computing, sensing, and security increasingly demand complex input-output behaviors, including highly nonlinear transformations of optical signals. Traditional photonic systems rely on highly structured…
Spiking Neural Networks (SNNs) offer an event-driven and more biologically realistic alternative to standard Artificial Neural Networks based on analog information processing. This can potentially enable energy-efficient hardware…
Optical modulators are essential parts of photonic circuits to encode electro-optical signals to the optical domain. Here, using arrays of multipixel toroidal plasmonic terahertz (THz) metamolecules, we developed a plasmonic metamodulator…
The design of neural hardware is informed by the prominence of differentiated processing and information integration in cognitive systems. The central role of communication leads to the principal assumption of the hardware platform: signals…
Integrated optical devices that can realize a threshold filtration of signals are in demand in photonics. In particular, they play a key role in neuromorphic chips, acting as optical neurons. A list of requirements exist for thresholders to…
The integration of second-order optical nonlinearities into scalable photonic platforms remains a key challenge due to their large sensitivity to fabrication variations. Here, we present a scalable quadratic nonlinear platform that…
The development of artificial intelligence (AI) and robotics are both based on the tenet of "science and technology are people-oriented", and both need to achieve efficient communication with the human brain. Based on multi-disciplinary…
Artificial intelligence (AI) is transforming modern life, yet the growing scale of AI applications places mounting demands on computational resources, raising sustainability concerns. Photonic integrated circuits (PICs) offer a promising…
Silicon nitride photonics has enabled integration of a variety of components for applications in linear and nonlinear optics, including telecommunications, optical clocks, astrocombs, bio-sensing, and LiDAR. With the advent of inverse…
At the first glance, the expression "transparent superconductor" may seem an oxymoron. Still, the first principle calculations and experiments show that the materials that behave as superconductors at low frequencies and do not absorb in…
The merger between integrated photonics and quantum optics promises new opportunities within photonic quantum technology with the very significant progress on excellent photon-emitter interfaces and advanced optical circuits. A key missing…
The continuous growth in data volume has sparked interest in silicon-organic-hybrid nanophotonic devices integrated into silicon photonic integrated circuits (PICs). SOH devices offer improved speed and energy efficiency compared to silicon…
The fields of machine learning and artificial intelligence drive researchers to explore energy-efficient, brain-inspired new hardware. Reservoir computing encompasses recurrent neural networks for sequential data processing and matches the…
The realization of scalable systems for quantum information processing and networking is of utmost importance to the quantum information community. However, building such systems is difficult because of challenges in achieving all the…
Quantum systems combining indistinguishable photon generation and spin-based quantum information processing are essential for remote quantum applications and networking. However, identification of suitable systems in scalable platforms…