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Modern software applications rarely live in isolation and nowadays it is common practice to rely on services or consume information provided by remote entities. In such a distributed architecture, integration is key. Mes...

In this paper, we review recent work on novel computing paradigms using coupled oscillatory dynamical systems. We explore systems of relaxation oscillators based on linear state transitioning devices, which switch betwee...

This thesis, entitled €High Performance Computing for solving large sparse systems. Optical Diffraction Tomography as a case of study€ investigates the computational issues related to the resolution of linear systems o...

Brain-inspired neuromorphic computing systems require hardware components analogous to biological neurons and synapses. Honey based natural organic memristor has demonstrated promising nonvolatile memristive behaviors, w...

Large language models (LLMs) are rapidly pushing the limits of contemporary computing hardware. For example, training GPT-3 has been estimated to consume around 1,300 MWh of electricity, and projections suggest future ...

Optical computing offers potential for ultra high-speed and low-latency computation by leveraging the intrinsic properties of light, such as parallelism and linear as well as nonlinear ultra-high bandwidth signal transfo...

Diffractive Neural Networks (DNNs) leverage the power of light to enhance computational performance in machine learning, offering a pathway to high-speed, low-energy, and large-scale neural information processing. Howeve...

Topological insulators have shown great potential for future optoelectronic technology due to their extraordinary optical and electrical properties. Photodetectors, as one of the most widely used optoelectronic devices, ...

Abstract Hot data identification plays a critical role in a wide range of computing systems, including memory hierarchy management, database optimization, and large-scale storage infrastructures. Its importance has furth...

Abstract The objective of this paper is to develop a parallel Pole numerical integration method suitable for renaming in MIMD computing systems. In this paper we improve the Pole Method for numerical integration by parti...

Cloud computing environments face persistent structural challenges in cost control, dynamic resource allocation, and security risk management, which traditional infrastructure approaches fail to address adequately. This ...

Object identification and three-dimensional reconstruction techniques are always attractive research interests in machine vision, virtual reality, augmented reality, and biomedical engineering. Optical computing metasurf...

Abstract The Internet of Things (IoT) and emerging technologies have converged to drive the remarkable development of intelligent systems. The interconnection of physical objects, sensors, and tiny communication devices ...

Structural health monitoring (SHM) has become a central tool for managing civil infrastructure. In modern SHM, the physical structure and the SHM system together form a coupled cyber-physical system. Due to the networked...

Photonic reservoir computing (RC) is a simple and efficient neuromorphic computing framework for human cortical circuits, which is featured with fast training speed and low training cost. Photonic time delay RC, as a sim...

Optical reservoir computing (ORC) promises fast, energy-efficient temporal inference by harnessing the rich transient dynamics of photonic systems. Yet most ORC demonstrations still depend on fiber delay lines or camera-...

Event-activated biological-inspired subwavelength (sub-λ) photonic neural networks are of key importance for future energy-efficient and high-bandwidth artificial intelligence systems. However, a miniaturized light-emit...

We show that coherent laser networks (CLNs) exhibit 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 s...

Wave-based signal processing has witnessed a significant expansion of interest in a variety of science and engineering disciplines, as it provides new opportunities for achieving high-speed and low-power operations. Alth...

Unitarity serves as a fundamental concept for characterizing linear and conservative wave phenomena in both classical and quantum systems. Developing platforms that perform unitary operations on light waves in a universa...

Exploiting alternative physical dimensions beyond the spatial domain has been intensively explored to improve the scalability in photonic computing. One approach leverages dynamical systems for time-domain computation, e...

Accurately forecasting the high-dimensional chaotic dynamics of semiconductor laser (SL) networks is essential in photonics research. In this study, we propose a spatiotemporal multiplexed photonic reservoir computing (S...

Advances in lighting and quantum computing will require new degrees of control over the emission of photons, where localized defects and the quantum confinement of carriers can be utilized. In this contribution, recent d...

Abstract Quantum-mechanical simulations provide the most fundamental description of matter, yet their computational cost commonly limits applications to systems containing at most thousands of atoms. Here, we present an ...