Abstract Photonic cluster states with tree-type encoding are an important resource for resisting photon loss. Here we develop an optimization framework for their efficient generation using time-delayed feedback. By analyzing the relation between feedback loops and entanglement structure through the adjacency matrix, we significantly reduce the resource overhead of state preparation by mapping the nonperiodic structure of the tree cluster state onto a periodic lattice. Combined with reinforcement learning, this framework identifies, under fixed resource constraints, the near-optimal tree structure for maximizing loss tolerance. Furthermore, we determine the practical loss-tolerant threshold set by the size of the near-optimal tree, the number of feedback loops, and realistic imperfections. These results provide a practical design strategy for loss-tolerant photonic cluster states in state-of-the-art quantum platforms.
Abstract Photonic cluster states with tree-type encoding are an important resource for resisting photon loss. Here we develop an optimization framework for their efficient generation using time-delayed feedback. By analyzing the relation between feedback loops and entanglement structure through the adjacency matrix, we significantly reduce the resource overhead of state preparation by mapping the nonperiodic structure of the tree cluster state onto a periodic lattice. Combined with reinforcement learning, this framework identifies, under fixed resource constraints, the near-optimal tree structure for maximizing loss tolerance. Furthermore, we determine the practical loss-tolerant threshold set by the size of the near-optimal tree, the number of feedback loops, and realistic imperfections. These results provide a practical design strategy for loss-tolerant photonic cluster states in state-of-the-art quantum platforms.
Cluster states, as highly entangled multi-qubit states, are widely used as essential resources for quantum communication and quantum computing. However, due to the diverse requirements of applications for cluster states with specific entanglement structures, a universal generation protocol is still lacking. Here we develop a matrix representation according to the characteristics of time-delayed feedback (TDF) and propose a protocol for generating arbitrary cluster states with multiple TDFs. The matrix representation also allows us to optimize the generation process to reduce TDF usage, thus improving efficiency. In particular, we demonstrate a tree-cluster-state generation process that requires only one TDF. Moreover, accounting for the critical loss mechanisms and imperfections in our protocol, we discuss the additional losses caused by multiple TDFs and evaluate the fidelity of the resulting cluster states.
A photonic cluster state with a tree-type entanglement structure constitutes an efficient resource for quantum error correction of photon loss. But the generation of a tree cluster state with an arbitrary size is notoriously difficult. Here, we propose a protocol to deterministically generate photonic tree states of arbitrary size by using only a single quantum emitter. Photonic entanglement is established through both emission and rescattering from the same emitter, enabling fast and resource-efficient entanglement generation. The same protocol can also be extended to generate more general tree-type entangled states.
We develop protocols for generating loss-tolerant quantum tree-codes; these are designed to safeguard information against qubit losses, with wide applications in quantum communications. Contrary to previous proposals, our method enables fast encoding and decoding, thereby reducing losses due to the lagging and photon-reordering at the repeater stations. At the hardware level, we show how to achieve this with a single quantum emitter equipped with a feedback mechanism, which we leverage to engineer entangling gates between a fed-back qubit and multiple emitted qubits in parallel. In addition, analyzing typical patterns within the error-correction decoding graphs, we find optimizations of the structure of tree-codes, which enable improved performance by also reducing the code size; these are based on the introduction of in the code, which mimic the intrinsic adaptiveness of the recovery procedure. We show numerically that these improvements together significantly enhance the loss-correction performance. Specifically, focusing on quantum repeater protocols, we show that our fast recovery scheme (decoding-encoding) allows for improved repeater rates with smaller photon numbers per code.
Large, multi-dimensional clusters of entangled photons are among the most powerful resources for emerging quantum technologies, as they are predicted to enable global quantum networks or universal quantum computation. Here, we propose an entirely new architecture and protocol for their generation based on recurrent quantum photonic neural networks (QPNNs) and focusing on tree-type cluster states. Unlike other approaches, QPNN-based generators are not limited by the the coherence of quantum emitters or by probabilistic multi-photon operations, enabling arbitrary scaling only limited by loss (which, unavoidably, also affects all other methods). We show that a single QPNN can learn to perform all of the many different operations needed to create a cluster state, from photon routing to entanglement generation, all with near-perfect fidelity and at loss-limited rates, even when it is created from imperfect photonic components. Although these losses ultimately place a limit on the size of the cluster states, we show that state-of-the-art photonics should already allow for clusters of 60 photons, which can grow into the 100s with modest improvements to losses. Finally, we present an analysis of a one-way quantum repeater based on these states, determining the requisite platform quality for a global quantum network and highlighting the potential of the QPNN to play a vital role in high-impact quantum technologies.
Cluster states are useful in many quantum information processing applications. In particular, universal measurement-based quantum computation (MBQC) utilizes two-dimensional cluster states [R. Raussendorf and H. J. Briegel, Phys. Rev. Lett. 86, 5188 (2001)] and topologically fault-tolerant MBQC requires cluster states of dimension 3 or higher [R. Raussendorf et al., New J. Phys. 9, 199 (2007)]. This work proposes a protocol to deterministically generate multidimensional photonic cluster states using a single atom-cavity system and time-delay feedback. The dimensionality of the cluster state increases linearly with the number of time-delay feedbacks. We first give a diagrammatic derivation of the tensor network states, which is valuable in simulating matrix product states and projected entangled pair states generated from sequential photons. Our method also provides a simple way to bridge and analyze the experimental imperfections and the logical errors of the generated states. In this method, we analyze the generated cluster states under realistic experimental conditions and address both one-qubit and two-qubit errors. Through numerical simulation, we observe an optimal atom-cavity cooperativity for the fidelity of the generated states, which is surprising given the prevailing assumption that higher-cooperativity systems are inherently better for photonic applications.
Photonic cluster states are fundamental resource for measurement-based quantum computing (MBQC), which is a promising approach for scalable quantum computing. These highly entangled states enable computation with applying local measurements rather than gate operations, which makes them essential for fault-tolerant quantum computing. Generation of the photonic cluster states requires high-quality entanglement and stability, which can be done by making use of cavity quantum electrodynamics (cavity QED), which is embedding quantum dots (QDs) into photonic microcavities. This method enables controlled single-photon emission and the entanglement of them, helping with key challenges in generating photonic cluster states. Enhancing the generation of the photonic cluster state requires improvement in the quality factor (Q-factor) and therefore, cooperativity of cavity and QD systems. A high Q-factor helps with reduction in photon loss and decoherence, ensuring more stable and high-fidelity quantum states. It also enables better light-matter interactions, improving cluster state quality. Cooperativity, which is a measure for the light-matter coupling strength relative to dissipation, directly impacts photon emission efficiency. Optimization of these parameters improves entanglement generation, which is essential for producing high-quality photonic cluster states. Therefore, optimized cavities are essential for improving the generation of the photonic cluster states. Scalability is also an important parameter for the generation of the large-scale cluster states used in quantum computing. In this paper, after reviewing MBQC, cluster states, and the generation of the photonic cluster states, we investigate the deterministic generation of the photonic cluster state resource for the purpose of MBQC, and highlights the importance of the inverse design techniques for this goal.