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Photonic processors use optical signals for computation, leveraging the high bandwidth and low loss of optical links. While many approaches have been proposed, including in memory photonic circuits, most efforts have focused on the physical…
Spontaneous Parametric Down Conversion (SPDC) holds a pivotal role in quantum physics, facilitating the creation of entangled photon pairs, heralded single photons and squeezed light, critical resources for many applications in quantum…
The complexity of experimental quantum information processing devices is increasing rapidly, requiring new approaches to control them. In this paper, we address the problems of practically modeling and controlling an integrated optical…
In this paper we introduce a design for an optical topological cluster state computer constructed exclusively from a single quantum component. Unlike previous efforts we eliminate the need for on demand, high fidelity photon sources and…
Relativistic spin effects drive subtle molecular phenomena ranging from intersystem crossing in photodynamic therapy to spin-mediated catalysis and high-resolution spectroscopy. These effects are described by the Pauli-Breit Hamiltonian,…
Photonic computing shows great potential for signal processing and artificial intelligence (AI) acceleration due to its ultra-high speed, low energy consumption, and inherent parallelism. Existing photonic computing research has mainly…
In recent years, there has been growing interest in using photonic technology to perform the underlying linear algebra operations required by different applications, including neuromorphic photonics, quantum computing and microwave…
Reprogrammable linear optical circuits are essential elements of photonic quantum technology implementations. Integrated optics provides a natural platform for tunable photonic circuits, but faces challenges when high dimensions and high…
With its unique parallel processing capability, optical neural network has shown low-power consumption in image recognition and speech processing. At present, the manufacturing technology of programmable photonic chip is not mature, and the…
Realizing the advantages of quantum computation requires access to the full Hilbert space of states of many quantum bits (qubits). Thus, large-scale quantum computation faces the challenge of efficiently generating entanglement between many…
The integration of computing with memory is essential for distributed, massively parallel, and adaptive architectures such as neural networks in artificial intelligence (AI). Accelerating AI can be achieved through photonic computing, but…
We propose an all-linear-optical scheme to ballistically generate a cluster state for measurement-based topological fault-tolerant quantum computation using hybrid photonic qubits entangled in a continuous-discrete domain. Availability of…
Photonic technologies offer great prospects for novel ultrafast, energy-efficient and hardware-friendly neuromorphic (brain-like) computing platforms. Moreover, neuromorphic photonic approaches based upon ubiquitous, technology-mature and…
We present an efficient way of heralding photonic qubit signals using linear optics devices. First we show that one can obtain asymptotically perfect heralding and unit success probability with growing resources. Second, we show that even…
Optical networks with parallel processing capabilities are significant in advancing high-speed data computing and large-scale data processing by providing ultra-width computational bandwidth. In this paper, we present a photonic integrated…
Up to now, all the works about constructing quantum logic gates, an essential part in quantum computing, are focused on operating on one degree of freedom (DOF) of quantum systems. Here, we investigate the possibility to achieve a scalable…
Quantum technologies, such as quantum communication, sensing and imaging, need a platform which is flexible, miniaturizable and works at room temperature. Integrated photonics is a promising and fast-developing platform. This requires to…
We propose a hybrid quantum-classical approximate optimization algorithm for photonic quantum computing, specifically tailored for addressing continuous-variable optimization problems. Inspired by counterdiabatic protocols, our algorithm…
The development of large-scale optical quantum information processing circuits ground on the stability and reconfigurability enabled by integrated photonics. We demonstrate a reconfigurable 8x8 integrated linear optical network based on…
Computational imaging enables compact infrared systems, but deep-learning pipelines that combine image reconstruction and object detection often introduce substantial inference latency. Most existing acceleration strategies compress the…