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Analog photonic computing comprises a promising candidate for accelerating the linear operations of deep neural networks (DNNs), since it provides ultrahigh bandwidth, low footprint and low power consumption computing ca...

Mapping input signals to a high-dimensional space is a critical concept in various neuromorphic computing paradigms, including models such as reservoir computing (RC) and extreme learning machines (ELM). We propose using...

Photonic reservoir computing has been demonstrated to be able to solve various complex problems. Although training a reservoir computing system is much simpler compared to other neural network approaches, it still requir...

Photonic reservoir computing has been intensively investigated to solve machine learning tasks effectively. A simple learning procedure of output weights is used for reservoir computing. However, the lack of training of ...

The possibility of arbitrary spatial control of incident wavefronts with the subwavelength resolution has driven research into dielectric optical metasurfaces in the last decade. The unit-cell based metasurface design a...

ABSTRACT The growing use of neural networks in privacy‐sensitive applications necessitates architectures that inherently protect both data and model integrity. We present a model‐inversion‐resistant physical unclon...

Spatial differentiator is the key element for edge detection, which is indispensable in image processing, computer vision involving image recognition, image restoration, image compression, and so on. Spatial differentiat...

Entanglement is an essential feature of quantum theory and the core of the majority of quantum information science and technologies. Quantum computing is one of the most important fruits of quantum entanglement and requi...

Spectral reconstruction, critical for understanding sample composition, is extensively applied in fields like remote sensing, geology, and medical imaging. However, existing spectral reconstruction methods require bulky ...

Chaotic semiconductor lasers have been widely investigated for high-speed random bit generation, which is applied for the generation of cryptographic keys for classical and quantum cryptography systems. Here, we propose ...

Multi-level (qudit) entangled photon states are a key resource for both fundamental physics and advanced applied science, as they can significantly boost the capabilities of novel technologies such as quantum communicati...

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, ...

The portfolio optimization problem is a mathematical and financial decision-making method that aims to achieve an optimal trade-off between financial risk and return. This paper presents the first application of the nove...

Traditional malware detection techniques frequently fail to detect and stop malicious activity in an era where cyber threats are becoming more complex. Any software that enters a computer system without the administrator...