Related papers: PAM-4 Transmission at 1550nm using Photonic Reserv…
The development of large-area homogeneous photo-detectors with sub-millimeter path lengths for direct Cherenkov light and for secondary-electrons opens the possibility of large time-of-flight systems for relativistic particles with…
To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient (UFEE) baseband processors. Traditional…
Photonic RF transversal signal processors, which are equivalent to reconfigurable electrical digital signal processors but implemented with photonic technologies, have been widely used for modern high-speed information processing. With the…
In this paper we propose and numerically study a neuromorphic computing scheme that applies delay-based reservoir computing in a laser system consisting of two mutually coupled phase modulated lasers. The scheme can be monolithic integrated…
The creation of high-performance narrowband filters is of great interest for many RF-signal processing applications. To this end, numerous schemes for electronic, MEMS-based, and microwave photonic filters have been demonstrated. Filtering…
For a future 5G Ethernet-based fronthaul architecture, 100G trunk lines of a transmission distance up to 10 km standard single mode fiber (SSMF) in combination with cheap grey optics to daisy chain cell site network interfaces are a…
Photonic technologies have received considerable attention for enhancement of radio-frequency (RF) electrical systems, including high-frequency analog signal transmission, control of phased arrays, analog-to-digital conversion, and signal…
Forecasting atmospheric flows with traditional discretization methods, also called full order methods (e.g., finite element methods or finite volume methods), is computationally expensive. We propose to reduce the computational cost with a…
Signal processing in wireless communications, such as precoding, detection, and channel estimation, are basically about solving inverse matrix problems, which, however, are slow and inefficient in conventional digital computers, thus…
Information processing has reached the era of big data. Big data challenges are difficult to address with traditional Von Neumann or Turing approach. Hence implementation of new computational techniques is highly essential. Nanophotonics…
High-precision time transfer over a long haul of fiber plays a significant role in many fields. The core method, namely cascading relay nodes for the compensation of signal attenuation and dispersion, is however insufficient to deal with…
Despite the extreme error-correction performance, the amount of computation of sequential decoding of the polarization-adjusted convolutional (PAC) codes is random. In sequential decoding of convolutional codes, the computational cutoff…
Nowadays we witness a miniaturisation trend in the semiconductor industry backed up by groundbreaking discoveries and designs in nanoscale characterisation and fabrication. To facilitate the trend and produce ever smaller, faster and…
Modern machine learning applications require huge artificial networks demanding in computational power and memory. Light-based platforms promise ultra-fast and energy-efficient hardware, which may help in realizing next-generation data…
Among the promising advantages of photonic computing over conventional computing architectures is the potential to increase computing efficiency through massive parallelism by using the many degrees of freedom provided by photonics. Here,…
High quality free-space and over-fibre transmission of mid-IR light is limited by factors such as material-related absorption, diffraction, light leakage and nonlinearity. Conventional vacuum apparatus can be utilized for high-quality…
It has always been a challenge for researchers to efficiently and accurately post process experimental data which is distorted by the noise. Superconducting microwave devices e.g. resonators, directional filters, beam-splitters etc. operate…
The recent rapid increase in demand for data processing has resulted in the need for novel machine learning concepts and hardware. Physical reservoir computing and an extreme learning machine are novel computing paradigms based on physical…
Accurate and high-resolution precipitation nowcasting from radar echo sequences is crucial for disaster mitigation and economic planning, yet it remains a significant challenge. Key difficulties include modeling complex multi-scale…
Reinforcement learning has been intensively investigated and developed in artificial intelligence in the absence of training data, such as autonomous driving vehicles, robot control, internet advertising, and elastic optical networks.…