Related papers: Homodyne Photonic Tensor Processor exceeds 1,000-T…
The scalability of photonic implementations of fault-tolerant quantum computing based on Gottesman-Kitaev-Preskill (GKP) qubits is injured by the requirements of inline squeezing and reconfigurability of the linear optical network. In this…
We describe a new scheme for the measurement of mean photon flux at an arbitrary optical sideband frequency using homodyne detection. Experimental implementation of the technique requires an AOM in addition to the homodyne detector, and…
Coherent technologies have revolutionized optical communications, driving the capacity per fiber to multi-terabit per second (Tb/s) in combination with wavelength division multiplexing (WDM). With an ever-increasing deployment density of…
In this paper, we present a concurrent implementation of a powerful topological thinning operator. This operator is able to act directly over grayscale images without modifying their topology. We introduce an adapted parallelization…
The massive amounts of data generated by camera sensors motivate data processing inside pixel arrays, i.e., at the extreme-edge. Several critical developments have fueled recent interest in the processing-in-pixel-in-memory paradigm for a…
Silicon photonics promises to address the challenges for next-generation short-reach optical interconnects. Growing bandwidth demand in hyper-scale data centers and high-performance computing motivates the development of faster and…
Conventional integrated circuits (ICs) struggle to meet the escalating demands of artificial intelligence (AI). This has sparked a renewed interest in an unconventional computing paradigm: neuromorphic (brain-inspired) computing. However,…
Programmable photonic quantum processors face a critical challenge: despite significant advances in quantum state preparation and manipulation, measurements remain limited to projective techniques. Here, we demonstrate a programmable…
High-efficiency optical detectors that can determine the number of photons in a pulse of monochromatic light have applications in a variety of physics studies, including post-selection-based entanglement protocols for linear optics quantum…
We report a systematic methodology to obtain supermodes with equidistant effective index distribution and to excite arbitrary target supermodes with high precision. By employing a multi-well optical potential realized by a judiciously…
The edge processing of deep neural networks (DNNs) is becoming increasingly important due to its ability to extract valuable information directly at the data source to minimize latency and energy consumption. Frequency-domain model…
Integrated optics are used to achieve astronomical interferometry inside robust and compact materials, improving the instruments stability and sensitivity. In order to perform differential phase measurements at the H$\alpha$ line (656.3 nm)…
Recent advances in photonic integrated circuits (PICs) have enabled a new generation of "programmable many-mode interferometers" (PMMIs) realized by cascaded Mach Zehnder Interferometers (MZIs) capable of universal linear-optical…
Scalable implementation of quantum networks and photonic processors require integrated photonic memories with high efficiency, yet current integrated systems have been limited to storage efficiencies below 27.8%. Here, we demonstrate highly…
The explosion of artificial intelligence and machine-learning algorithms, connected to the exponential growth of the exchanged data, is driving a search for novel application-specific hardware accelerators. Among the many, the photonics…
Over the past few years, silicon photonics-based computing has emerged as a promising alternative to CMOS-based computing for Deep Neural Networks (DNN). Unfortunately, the non-linear operations and the high-precision requirements of DNNs…
In this paper, we propose the first optimum process scheduling algorithm for an increasingly prevalent type of heterogeneous multicore (HEMC) system that combines high-performance big cores and energy-efficient small cores with the same…
Optical quantum memory is an essential element for long distance quantum communication and photonic quantum computation protocols. The practical implementation of such protocols requires an efficient quantum memory with long coherence time.…
Recently, there has been a growing interest in integrated THz photonics for various applications in communications, spectroscopy and sensing. We present a new integrated photonic platform based on active and passive elements integrated in a…
Meeting the escalating demands of data transmission and computing, driven by artificial intelligence (AI), requires not only faster optical transceivers but also advanced integration technologies that can seamlessly combine photonic and…