Related papers: Static and dynamic wavelength routing via the grad…

Highly coherent optical sources are a key element in several fields of physics, in particular in time frequency metrology. Over the past decennia, there has been particular efforts in developing such sources to the expense of sophisticated…

Neuromorphic computing systems are set to revolutionize energy-constrained robotics by achieving orders-of-magnitude efficiency gains, while enabling native temporal processing. Spiking Neural Networks (SNNs) represent a promising…

In this work, we present numerical results concerning an integrated photonic non-linear activation function that relies on a power independent, non-linear phase to amplitude conversion in a passive optical resonator. The underlying…

Recently, spiking neural networks (SNNs) have demonstrated substantial potential in computer vision tasks. In this paper, we present an Efficient Spiking Deraining Network, called ESDNet. Our work is motivated by the observation that rain…

The tailoring of the physical properties of semiconductor nanomaterials by strain has been gaining increasing attention over the last years for a wide range of applications such as electronics, optoelectronics and photonics. The ability to…

A laser is not necessarily a sophisticated device: Pumping energy into an amplifying medium randomly filled with scatterers, a powder for instance, makes a perfect "random laser." In such a laser, the absence of mirrors greatly simplifies…

Advancements in light modulator technology have been driving discoveries and progress across various fields. The problem of large-scale coherent optical control of atomic quantum systems-including cold atoms, ions, and solid-state color…

With the rapid development of artificial intelligence technology, the field of reinforcement learning has continuously achieved breakthroughs in both theory and practice. However, traditional reinforcement learning algorithms often entail…

Optically generated electron-hole plasma in high-index dielectric nanostructures was demonstrated as a means of tuning of their optical properties. However, until now an ultrafast operation regime of such plasma driven nanostructures has…

Spiking Neural Networks (SNNs) have emerged as a promising tool for event-based optical flow estimation tasks due to their ability to leverage spatio-temporal information and low-power capabilities. However, the performance of SNN models is…

The functionalities of a wide range of optical and opto-electronic devices are based on resonance effects and active tuning of the amplitude and wavelength response is often essential. Plasmonic nanostructures are an efficient way to create…

We enhanced the total transmission of light through a disordered waveguide with spatially inhomogeneous scattering and loss by shaping the incident wavefront of a laser beam. Using an on-chip tapered lead, we were able to access all input…

We present a silicon optomechanical nanobeam design with a dynamically tunable acoustic mode at 10.2 GHz. The resonance frequency can be shifted by 90 kHz/V^2 with an on-chip capacitor that was optimized to exert forces up to 1 $\mu$N at 10…

Backpropagation through nonlinear neurons is an outstanding challenge to the field of optical neural networks and the major conceptual barrier to all-optical training schemes. Each neuron is required to exhibit a directionally dependent…

Plasmonic nano-antennas can focus light to nanometre length-scales providing intense field enhancements. For the tightest optical confinements (0.5-5 nm) achieved in plasmonic gaps, the gap spacing, refractive index, and facet width play a…

Spiking neural networks (SNNs) represent a promising approach in machine learning, combining the hierarchical learning capabilities of deep neural networks with the energy efficiency of spike-based computations. Traditional end-to-end…

Optical parametric oscillation (OPO) is distinguished by its wavelength access, that is, the ability to flexibly generate coherent light at wavelengths that are dramatically different from the pump laser, and in principle bounded solely by…

Deeplearning algorithms are revolutionising many aspects of modern life. Typically, they are implemented in CMOS-based hardware with severely limited memory access times and inefficient data-routing. All-optical neural networks without any…

We report shifting of the frequency of an 850 nm laser with an instantaneous bandwidth of (350-1650), MHz and an efficiency between 35% (minimum) to 80% (best at frequencies around 600 and 1500, MHz) by phase modulation with a sawtooth…

Instrumental aberrations strongly limit high-contrast imaging of exoplanets, especially when they produce quasistatic speckles in the science images. With the help of recent advances in deep learning, we have developed in previous works an…