Remote state preparation (RSP) allows one party to remotely prepare a known quantum state on another party’s qubit using entanglement. This can be used in quantum networks to perform applications such as blind quantum computing or long-distance quantum key distribution (QKD) with quantum repeaters. Devices to perform RSP, referred to as a client, ideally have low hardware requirements, such as only sending photonic qubits. A weak coherent pulse source offers a practical alternative to true single-photon sources and is already widely used in QKD. Here, we introduce two protocols to the previously known protocol for RSP with a weak-coherent-pulse-based device. The known technique uses a double-click (DC) protocol, where a photon from both the server and the client needs to reach an intermediate Bell state measurement. Here, we add to that a single-click (SC) RSP protocol, which requires only one photon to reach the Bell state measurement, allowing for better performance in certain regimes. In addition, we introduce a double-single-click (DSC) protocol, where the SC protocol is repeated twice, and a cnot gate is applied between the resulting qubits. DSC mitigates the need for phase stabilization in certain regimes, lowering technical complexity while still improving performance compared to DC in some regimes. We compare these protocols in terms of fidelity and rate, finding that SC consistently achieves higher rates than DC and, interestingly, does not suffer from an inherently lower fidelity than DC, as is the case for entanglement generation. Although SC provides stronger performance, DSC can still show performance improvements over DC, and it may have reduced technical complexity compared to SC. Finally, we show how these protocols can be used in long-distance QKD using quantum repeaters.

We investigate the hardware requirements for quantum teleportation in an intercity-scale network topology consisting of two metropolitan-scale networks connected via a long-distance backbone link. Specifically, we identify the minimal improvements required beyond the state-of-the-art to achieve an end-to-end expected teleportation fidelity of (Formula presented), which represents the classical limit. To this end, we formulate the hardware requirements computation as optimisation problems, where the hardware parameters representing the underlying device capabilities serve as decision variables. Assuming a simplified noise model, we derive closed-form analytical expressions for the teleportation fidelity and rate when the network is realised using heterogeneous quantum hardware, including a quantum repeater chain with a memory cut-off. Our derivations are based on events defined by the order statistics of link generation durations in both the metropolitan networks and the backbone, and the resulting expressions are verified against NetSquid simulations. The analytical expressions facilitate efficient exploration of the optimisation parameter space without resorting to computationally intensive simulations. We then apply this framework to a representative realisation in which the metropolitan nodes are based on trapped-ion processors and the backbone is composed of ensemble-based quantum memories. Our results suggest that teleportation across metropolitan distances already reaches the classical limit with state-of-the-art hardware when the data qubit is prepared after end-to-end entanglement has been established, whereas extending teleportation to intercity scales requires additional, though plausibly achievable, improvements in hardware performance.

Coordination in distributed systems is often hampered by communication latency, which degrades performance. Quantum entanglement offers fundamentally stronger correlations than classically achievable without communication. Crucially, these correlations manifest instantaneously upon measurement, irrespective of the physical distance separating the systems. We investigate the application of shared entanglement to a dual-work optimization problem in a distributed system comprising two servers. The system must process both a continuously available, preemptible baseline task and incoming customer requests arriving in pairs. System performance is characterized by the trade-off between baseline task throughput and customer waiting time. We present a rigorous analytical model demonstrating that when the baseline task throughput function is strictly convex, rewarding longer uninterrupted processing periods, entanglement-assisted routing strategies achieve Pareto-superior performance compared to optimal communication-free classical strategies. We prove this advantage through queueing-theoretic analysis, nonlocal game formulation, and computational certification of classical bounds. We complement these formal results with simulations indicating that the advantage persists when arrivals are independent across routers and grows under bursty traffic. Our results suggest distributed scheduling and coordination as a candidate application domain for near-term entanglement-based quantum networks.

Quantum internet applications coordinate classical control, local quantum operations, and entanglement/communication across independent nodes under strict protocol ordering constraints. While Qoala and QNodeOS provide programming and execution abstractions for such applications, there is no compiler infrastructure that systematically lowers Qoala programs to executable node-level code while enabling optimization. We present the first multi-level compiler pipeline for Qoala quantum internet programs. The compiler lowers programs through three MLIR-based IRs that progressively expose hybrid control flow, explicit quantum memory, and Qoala block structure. On top of this pipeline, we implement (i) local peephole rewrites, and (ii) a block-reordering pass formulated as a MILP to reduce qubit lifetimes under precedence and resource constraints. We also provide static analyses for gate counts, qubit lifetimes, fidelity estimation, and quantum-memory efficiency. We evaluate on rotation-merging and blind quantum computing benchmarks using density-matrix simulation and IRderived estimates, showing that block reordering improves fidelity and memory reuse in latency-dominated regimes with modest compilation overhead.

Entanglement buffers are systems that maintain high-quality entanglement, ensuring it is readily available for consumption when needed. We study the performance of a two-node buffer, where each node has one long-lived quantum memory for entanglement storage and multiple short-lived memories for generation. Freshly generated entanglement may be used to purify stored entanglement, which degrades over time. Stored entanglement may be removed due to consumption or failed purification. We derive analytical expressions for the entanglement availability and the average fidelity upon consumption. Our solutions are computationally efficient and provide fundamental bounds to the performance of purification-based entanglement buffers. We also show that purification must be performed as frequently as possible to maximise the average fidelity of entanglement upon consumption, even if this often leads to the loss of high-quality entanglement due to purification failures. Moreover, we obtain heuristics for the design of good purification policies in practical systems.

Execution of quantum network applications requires a software stack for nodes. Recently, the first designs and demonstrations have been proposed for such software stacks, including QNodeOS and its extension, Qoala. The latter enables compilation strategies previously not possible in QNodeOS. Here, we show how the extensions provided by Qoala can be used by a compiler to improve the performance of quantum network applications. We define new compilation strategies that allow the compiler to influence the scheduling and execution of quantum programs on a quantum network node. Through simulation, we demonstrate that our compilation strategies can reduce the execution time by up to 29.53% and increase the success probability by up to 25.12%. Our work highlights the potential of compiler optimizations for quantum network programs.

The aim of a quantum network is to enable users to successfully execute applications on their quantum end nodes. Users of mature networks, such as the internet, the postal network, or the telephone network expect their demands for service to be satisfied reliably. Here, we present an extended abstract introducing Arqon, a suite of control applications capable of delivering reliable service to end nodes. We define a full set of reliability requirements and demonstrate through a numeric evaluation that Arqon is capable of simultaneously satisfying all requirements.

Coordination in distributed systems is often hampered by communication latency, which degrades performance. Quantum entanglement enables correlations stronger than classically possible without communication. Such correlations manifest instantaneously upon measurement, irrespective of the physical distance separating the systems. We investigate the application of shared entanglement to a dual-objective optimization problem in a distributed system comprising two servers. The servers process both a continuously available, preemptible baseline task and incoming paired customer requests, to maximize the baseline task throughput subject to a Quality of Service (QoS) constraint on average customer waiting time. We present a rigorous analytical model demonstrating that an entanglement-Assisted routing strategy allows the system to achieve higher baseline throughput compared to communication-free classical strategies, provided the baseline task's output exhibits sufficiently increasing returns with processing time. This advantage stems from entanglement enabling better coordination, which allows the system to satisfy the customer QoS constraint with a lower overall probability of splitting customer requests, leading to more favorable conditions for baseline task processing and thus higher throughput. We further show that the magnitude of this throughput gain is particularly pronounced for tasks exhibiting increasing returns, where output grows super-linearly with processing time. Our results identify optimization of scheduling in distributed systems as a novel application domain for near-Term quantum networks.

Network utility maximization (NUM) addresses the problem of allocating resources fairly within a network and explores the ways to achieve optimal allocation in real-world networks. Although extensively studied in classical networks, NUM is an emerging area of research in the context of quantum networks. In this work, we consider the quantum network utility maximization (QNUM) problem in a static setting, where a user's utility takes into account the assigned quantum quality (fidelity) via a generic entanglement measure, as well as the corresponding rate of entanglement generation. Under certain assumptions, we demonstrate that the QNUM problem can be formulated as an optimization problem with the rate allocation vector as the only decision variable. Using a change-of-variable technique known in the field of geometric programming, we then establish sufficient conditions under which this formulation can be reduced to a convex problem: a class of optimization problems that can be solved efficiently and with certainty even in high dimensions. We further show that this technique preserves convexity, enabling us to formulate convex QNUM problems in networks where some routes have certain entanglement measures that do not readily admit convex formulation while others do. This allows us to compute the optimal resource allocation in networks where heterogeneous applications run over different routes.

In this article, we propose an architecture for scheduling network operations enabling the end-to-end generation of entanglement according to user demand. The main challenge solved by this architecture is to allow for the integration of a network schedule with the execution of quantum programs running on processing end nodes in order to realize quantum network applications. A key element of this architecture is the definition of an entanglement packet to meet application requirements on near-term quantum networks where the lifetimes of the qubits stored at the end nodes are limited. Our architecture is fully modular and hardware agnostic and defines a framework for further research on specific components that can now be developed independently of each other. In order to evaluate our architecture, we realize a proof-of-concept implementation on a simulated six-node network in a star topology. We show that our architecture facilitates the execution of quantum network applications and that robust admission control is required to maintain quality of service. Finally, we comment on potential bottlenecks in our architecture and provide suggestions for future improvements.

We propose an architecture for scheduling network operations enabling the end-to-end generation of entanglement according to user demand. The main challenge solved by this architecture is to allow for the integration of a network schedule with the execution of quantum programs running on processing end nodes in order to realise quantum network applications. A key element of this architecture is the definition of an entanglement packet to meet application requirements on near-term quantum networks where the lifetimes of the qubits stored at the end nodes are limited. Our architecture is fully modular and hardware agnostic, and defines a framework for further research on specific components that can now be developed independently of each other. In order to evaluate our architecture, we realise a proof of concept implementation on a simulated 6-node network in a star topology. We show our architecture facilitates the execution of quantum network applications, and that robust admission control is required to maintain quality of service.

We consider the problem of multipath entanglement distribution to a pair of nodes in a quantum network consisting of devices with nondeterministic entanglement swapping capabilities. Multipath entanglement distribution enables a network to establish end-to-end entangled links across any number of available paths with preestablished link-level entanglement. Probabilistic entanglement swapping, on the other hand, limits the amount of entanglement that is shared between the nodes; this is especially the case when, due to practical constraints, swaps must be performed in temporal proximity to each other. Limiting our focus to the case where only bipartite entanglement is generated across the network, we cast the problem as an instance of generalized flow maximization between two quantum end nodes wishing to communicate. We propose a mixed-integer quadratically constrained program (MIQCP) to solve this flow problem for networks with arbitrary topology. We then compute the overall network capacity, defined as the maximum number of Einstein-Podolsky-Rosen (EPR) states distributed to users per time unit, by solving the flow problem for all possible network states generated by probabilistic entangled link presence and absence, and subsequently by averaging over all network state capacities. The MIQCP can also be applied to networks with multiplexed links. While our approach for computing the overall network capacity has the undesirable property that the total number of states grows exponentially with link multiplexing capability, it nevertheless yields an exact solution that serves as an upper bound comparison basis for the throughput performance of more easily implementable yet nonoptimal entanglement routing algorithms.

Quantum protocols commonly require a certain number of quantum resource states to be available simultaneously. An important class of examples is quantum network protocols that require a certain number of entangled pairs. Here, we consider a setting in which a process generates a quantum resource state with some probability p in each time step and stores it in a quantum memory that is subject to time-dependent noise. To maintain sufficient quality for an application, each resource state is discarded from the memory after w time steps. Let s be the number of desired resource states required by a protocol. We characterize the probability distribution X-{(w,s)} of the ages of the quantum resource states, once s states have been generated in a window w. Combined with a time-dependent noise model, knowledge of this distribution allows for the calculation of fidelity statistics of the s quantum resources. We also give exact solutions for the first and second moments of the waiting time \tau -{(w,s)} until s resources are produced within a window w, which provides information about the rate of the protocol. Since it is difficult to obtain general closed-form expressions for statistical quantities describing the expected waiting time \mathbb {E}(\tau -{(w,s)}) and the distribution X-{(w,s)}, we present two novel results that aid their computation in certain parameter regimes. The methods presented in this work can be used to analyze and optimize the execution of quantum protocols. Specifically, with an example of a blind quantum computing protocol, we illustrate how they may be used to infer w and p to optimize the rate of successful protocol execution.