相关论文: Direct coupling of nonlinear integrated cavities f…
Nonlinear wave mixing in mesoscopic silicon structures is a fundamental nonlinear process with broad impact and applications. Silicon nanowire waveguides, in particular, have large third-order Kerr nonlinearity, enabling salient and…
Cavity optomechanics, a promising platform to investigate macroscopic quantum effects, has been widely used to study nonreciprocal entanglement with Sagnec effect. Here we propose an alternative way to realize nonreciprocal entanglemment…
We show that connectivity within the high-dimensional recurrent layer of a reservoir network is crucial for its performance. To this end, we systematically investigate the impact of network connectivity on its performance, i.e., we examine…
Reservoir Computing is a relatively recent computational framework based on a large Recurrent Neural Network with fixed weights. Many physical implementations of Reservoir Computing have been proposed to improve speed and energy efficiency.…
We study for the first time the effect of the geometry of quantum wire networks on their nonlinear optical properties and show that for some geometries, the first hyperpolarizability is largely enhanced and the second hyperpolarizability is…
The exact non-Markovian dynamics of a microcavity strongly coupled to a general reservoir at arbitrary temperature is studied. With the exact master equation for the reduced density operator of the cavity system, we analytically solve the…
Programable spatial light modulators (SLMs) have significantly advanced the configurable optical trapping of particles. Typically, these devices are utilized in the Fourier plane of an optical system, but direct imaging of an amplitude…
A precise understanding of nonlinear optical phenomena in whispering gallery mode (WGM) microresonators is crucial for developing next-generation integrated photonic devices. Applications include on-chip sensors for biomedical use, optical…
Efficient fiber-to-chip coupling has been a major hurdle to cost-effective packaging and scalable interconnections of photonic integrated circuits. Conventional photonic packaging methods relying on edge or grating coupling are constrained…
Modern machine learning models use an ever-increasing number of parameters to train (175 billion parameters for GPT-3) with large datasets to obtain better performance. Bigger is better has been the norm. Optical computing has been…
We discuss a general method for constructing nonreciprocal, cavity-based photonic devices, based on matching a given coherent interaction with its corresponding dissipative counterpart; our method generalizes the basic structure used in the…
A promising approach to merge atomic systems with scalable photonics has emerged recently, which consists of trapping cold atoms near tapered nanofibers. Here, we describe a novel technique to achieve strong, coherent coupling between a…
Nonlinearity is the key to introducing novel concepts in various technologies utilizing traveling waves. In contrast to the field of optics, where highly functional devices have been developed using optical Kerr nonlinearity, such a…
The quantum behavior of superconducting qubits coupled to resonators is very similar to that of atoms in optical cavities [1, 2], in which the resonant cavity confines photons and promotes strong light-matter interactions. The cavity…
Reservoir computers (RC) are randomized recurrent neural networks well adapted to process time series, performing tasks such as nonlinear distortion compensation or prediction of chaotic dynamics. Deep reservoir computers (deep-RC), in…
Arrays of photonic cavities are relevant structures for developing large-scale photonic integrated circuits and for investigating basic quantum electrodynamics phenomena, due to the photon hopping between interacting nanoresonators. Here,…
Advances in artificial intelligence are driven by technologies inspired by the brain, but these technologies are orders of magnitude less powerful and energy efficient than biological systems. Inspired by the nonlinear dynamics of neural…
We propose the use of weakly nonlinear passive materials for prospective applications in integrated quantum photonics. It is shown that strong enhancement of native optical nonlinearities by electromagnetic field confinement in photonic…
Reservoir computing is a bio-inspired machine learning paradigm that exploits the intrinsic dynamics of nonlinear systems with fading memory for efficient temporal information processing. Microelectromechanical resonators offer a promising…
Neural networks are currently transforming the field of computer algorithms, yet their emulation on current computing substrates is highly inefficient. Reservoir computing was successfully implemented on a large variety of substrates and…