Related papers: Fabry-Perot Lasers as Enablers for Parallel Reserv…
Temporal correlations of radiation intensities of a multimode Fabry-Perot semiconductor laser are investigated. Strong intensity correlations with a fixed phase shift between different longitudinal modes of the laser are revealed. The…
Optical computing provides a promising path toward energy-efficient machine learning, yet implementing nonlinear transformations without complex electronics or high-power sources remains challenging. Here, we demonstrate that…
Reservoir computers are a type of neuromorphic computer that may be built a an analog system, potentially creating powerful computers that are small, light and consume little power. Typically a reservoir computer is build by connecting…
Fabry-P\'erot (FP) cavities are fundamental and ubiquitous optical elements frequently used in various sensing applications. Here, we introduce a general theoretical framework to study arbitrary light-cavity mode interactions for planar FPs…
Fiber Fabry--Perot (FFP) resonators of a few centimeters are optimized as a function of the reflectivity of the mirrors and the dimensions of the intra-cavity waveguide. Loaded quality factor in excess of 10^9, with an optimum of…
We show that a coherent network of lasers exhibits emergent neural computing capabilities. The proposed scheme is built on harnessing the collective behavior of laser networks for storing a number of phase patterns as stable fixed points of…
The proliferation of deep learning applications has intensified the demand for electronic hardware with low energy consumption and fast computing speed. Neuromorphic photonics have emerged as a viable alternative to directly process…
Fabry-P\'erot based photoacoustic tomography (FP-PAT) is a promising all-optical imaging modality for a wide range of preclinical and clinical applications. However, there exist several challenges in routinely applying FP-PAT in…
Photonic neuromorphic computing has emerged as a promising avenue toward building a low-latency and energy-efficient non-von-Neuman computing system. Photonic spiking neural network (PSNN) exploits brain-like spatiotemporal processing to…
We discuss applications of time-delayed feedback control to delay-coupled neural systems and lasers, in the framework of the FitzHugh-Nagumo neuron model and the Lang-Kobayashi laser model, respectively. In the context of neural systems, we…
Today's state of the art precision experiments in quantum, gravimetry, navigation, time keeping, and fundamental science have strict requirements on the level and spectral distribution of laser frequency noise. For example, the laser…
The Jagiellonian-PET (J-PET) collaboration is developing a prototype TOF-PET detector based on long polymer scintillators. This novel approach exploits the excellent time properties of the plastic scintillators, which permit very precise…
Tensor processing is the cornerstone of modern technological advancements, powering critical applications in data analytics and artificial intelligence. While optical computing offers exceptional advantages in bandwidth, parallelism, and…
Reservoir computing with optical devices offers an energy-efficient approach for time-series forecasting. Quantum dot lasers with feedback are modelled in this paper to explore the extent to which increased complexity in the charge carrier…
Machine-intelligence has become a driving factor in modern society. However, its demand outpaces the underlying electronic technology due to limitations given by fundamental physics such as capacitive charging of wires, but also by system…
Nonlinear computation is essential for a wide range of information processing tasks, yet implementing nonlinear functions using optical systems remains a challenge due to the weak and power-intensive nature of optical nonlinearities.…
We show that a constant number of self-attention layers can efficiently simulate, and be simulated by, a constant number of communication rounds of Massively Parallel Computation. As a consequence, we show that logarithmic depth is…
Recent years have witnessed growing interest in the development of small-footprint lasers for potential applications in small-volume sensing and on-chip optical communications. Surface-plasmons, electromagnetic modes evanescently confined…
Memristive devices present a promising foundation for next-generation information processing by combining memory and computation within a single physical substrate. This unique characteristic enables efficient, fast, and adaptive computing,…
Neural networks have enabled applications in artificial intelligence through machine learning, and neuromorphic computing. Software implementations of neural networks on conventional computers that have separate memory and processor (and…