We investigate how quantum computers can be used to emulate quantum networks and study their performance under practical impairments. In particular, we evaluate how degraded entanglement and communication latency affect teleportation-based distributed multipartite-entanglement-state construction. We model imperfect Bell-pair sources using depolarizing noise channels and classical communication delays using thermal relaxation. We implement the depolarization using Stinespring dilation, randomly applied Pauli errors, and quasi-probability decompositions, evaluating the latter two on IQM quantum hardware and all three in simulation. We then study the performance of the entanglement distribution under noise generated by the aforementioned models. Although these noise models are mathematically equivalent, we find that hardware constraints result in profound differences in the corresponding results, highlighting the importance of careful experiment design.
We investigate how quantum computers can be used to emulate quantum networks and study their performance under practical impairments. In particular, we evaluate how degraded entanglement and communication latency affect teleportation-based distributed multipartite-entanglement-state construction. We model imperfect Bell-pair sources using depolarizing noise channels and classical communication delays using thermal relaxation. We implement the depolarization using Stinespring dilation, randomly applied Pauli errors, and quasi-probability decompositions, evaluating the latter two on IQM quantum hardware and all three in simulation. We then study the performance of the entanglement distribution under noise generated by the aforementioned models. Although these noise models are mathematically equivalent, we find that hardware constraints result in profound differences in the corresponding results, highlighting the importance of careful experiment design.
Quantum computers in the noisy intermediate-scale quantum (NISQ) era are constrained by limited qubit counts, imperfect gate fidelities, and short coherence times. NISQ-era computers often have too few qubits to run many algorithms, and those that do run often have limited quantum advantage. Distributed quantum computing (DQC) is a promising approach to overcome this, where multiple quantum processors are interconnected through shared entanglement. This work serves as a system overview of an entanglement distribution system. We achieve this by examining a zero-added loss multiplexing (ZALM) entanglement generation source, simulating multi-hop, repeater-less networks, and various routing algorithms to distribute entanglement, and real-hardware quantum experiments that reconstruct entanglement links of degraded fidelity and simulate classical-communication delay. Network simulations evaluate routing and spectrum-allocation algorithms under entanglement-generation-imposed rate constraints, by evaluating both fairness and throughput across network sizes and topologies. We identify two polynomial-time approximation algorithms that perform well, or better than others under these metrics. Using both simulations and quantum hardware, we evaluate how degraded entanglement and communication latency affect teleportation-based distributed multipartite-entanglement-state construction. The results reveal the coupled influence of source rate, routing efficiency, fidelity, and classical delay on networked entanglement distribution and DQC performance, providing a reproducible framework for both experimental and simulated studies of near-term DQC.
Quantum entanglement is a central resource for quantum computation and state transfer, yet the usefulness of multipartite entanglement depends on how rapidly coherence and nonclassical correlations degrade as the register size and communication depth increase. This methodology paper develops a reproducible density-matrix simulation for studying entanglement and information transfer in multi-qubit systems. GHZ and W states containing 3, 4, 5, 6 and 8 qubits are generated and exposed to independent local depolarizing noise. State fidelity and bipartite negativity are used to quantify preservation of the prepared resource, while an entanglement-assisted multi-hop teleportation model measures the fidelity of transferred single-qubit information. The simulation shows a systematic decrease in state fidelity and negativity with increasing register size at a fixed local error probability. At a local depolarizing probability of 0.02, GHZ fidelity decreases from 0.941 for three qubits to 0.852 for eight qubits, whereas W-state fidelity decreases from 0.943 to 0.877. In a separate transfer experiment with an effective error probability of 0.10 per teleportation hop, average transfer fidelity decreases from 0.933 after one hop to 0.745 after five hops, while remaining above the classical benchmark of 2/3. These results illustrate how multipartite entanglement quality; noise accumulation and path depth jointly determine the reliability of information transfer in multi-qubit computing architectures.
This work presents a simulation-based study of quantum teleportation for secure communication under ideal, noisy, and adversarial conditions using IBM’s Qiskit framework and the Qiskit Aer simulator. The study begins with the verification of Bell-state entanglement to establish quantum correlation, followed by the implementation of a standard three-qubit quantum teleportation protocol. The teleportation system is evaluated across four experimental scenarios: (i) ideal noiseless teleportation, (ii) depolarizing noise environments, (iii) basis disturbance attacks using unauthorized Hadamard operations, and (iv) entanglement injection attacks introducing an external qubit into the communication channel. Each scenario is analyzed using measurement statistics, probability distributions, and state behavior of the receiver qubit. The results demonstrate that quantum teleportation achieves high fidelity under ideal conditions, while environmental noise introduces statistical degradation in state reconstruction. Furthermore, adversarial interference significantly disrupts teleportation performance, with basis disturbance producing near-uniform probability distributions and entanglement injection altering receiver-side measurement statistics. This study highlights both the robustness and vulnerability of quantum communication protocols and emphasizes the importance of noise mitigation, entanglement security, and attack detection mechanisms in future quantum networking systems. The work is entirely simulation-based and implemented using Python and Qiskit.
Quantum computers connected through classical and quantum communication channels can be combined to function as a single unit to run large quantum circuits that each device is unable to execute on their own. The distributed quantum computing paradigm is therefore often seen as a potential pathway to scaling quantum computing to capacities necessary for practical and large-scale applications. Whether connecting multiple quantum processing units (QPUs) in clusters or over networks, quantum communication requires entanglement to be generated and distributed over distances. Using entanglement, the remote CX protocol can be performed, which allows the application of the CX gate involving qubits located in different QPUs. In this work, we use a specialized simulation framework for a high-level evaluation of the impact of the protocol when executed under noise in various network configurations using different number of QPUs. We compare naive and graph partitioning qubit assignment strategies and how they affect the fidelity in experiments run on Grover, GHZ, VQC, and random circuits. The results provide insights on how QPU and network configurations or naive scheduling can degrade performance.
We consider entanglement-based quantum networks, where multipartite entangled resource states are distributed and stored among the nodes and locally manipulated upon request to establish the desired target configuration. Separating the generation process from the requests enables a pre-preparation of resources, hence a reduced network latency. It also allows for an optimization of the entanglement topology, which is independent of the underlying network geometry. We concentrate on establishing Bell pairs or tripartite GHZ states between arbitrary parties. We study the influence of noise in this process, where we consider imperfections in state preparation, memories, and measurements - all of which can be modeled by local depolarizing noise. We compare different resource states corresponding to linear chains, trees, or multi-dimensional rectangular clusters, as well as centralized topologies using bipartite or tripartite entangled states. We compute the fidelity of the target states using a recently established efficient method, the noisy stabilizer formalism, and identify the best resource states within these classes. This allows us to treat networks of large size containing millions of nodes. We find that in large networks, high-dimensional cluster states are favorable and lead to a significantly higher target state fidelity.
End-to-end entanglement distribution is a key capability of upcoming quantum networks, enabling applications like distributed quantum computing, quantum sensor networks, and secure communications. Hence, its realistic and efficient simulation is crucial for quantum network design and for assessing the ability of a network to run certain applications. This work provides tools to scale-up and improve the realism of entanglement generation simulations in quantum networks. This is achieved by deriving analytical results that directly return the success probability, the output state and corresponding fidelity of a selected entanglement generation protocol, while accounting for a variety of noise sources affecting the protocol. These results are then integrated and streamlined in an upgraded version of SeQUeNCe, one of the most popular quantum network simulators. The resulting simulator features increased scalability by reducing computation time by more than 60%, while allowing for a variety of realistic noise sources, including imperfect mode matching, dark counts, and imperfect memory initialization. The simulator is also benchmarked with real experimental data and is capable of replicating the average entanglement generation time and the final state fidelity of a selected experiment. Altogether, the results can enhance current quantum network simulation capabilities towards large-scale networks, paving the way for the future quantum internet.