A comparative study of three entanglement management paradigms for multi-core quantum processors shows that adaptive entanglement managements can substantially improve communication efficiency in scalable quantum multi-core systems.
Abstract
Scalable quantum computing architectures increasingly rely on multi-core designs, where qubits are distributed across multiple processing cores interconnected through a quantum Network-on-Chip (NoC). In such systems, inter-core communication is typically realized through entanglement-assisted quantum teleportation, making efficient entanglement generation critical for performance. In this paper, we perform a comparative study of three entanglement management paradigms for multi-core quantum processors: reactive on-demand generation (ODG), proactive continuous pre-generation (CGP), and an adaptive continuous pre-generation approach (ACGP). While ODG generates entanglement only when required, CGP reduces average teleportation latency by pre-generating EPR pairs in the background. To improve upon this, we propose ACGP which dynamically adjusts entanglement generation probabilities based on observed inter-core communication patterns. We evaluate these approaches using an extended SeQUeNCe simulator on mesh-based multi-core architectures on real benchmark circuits. Results show that ACGP significantly reduces average teleportation latency compared to ODG and CGP. Although pre-generation introduces fidelity degradation due to storage time, entanglement purification effectively restores fidelity with minimal impact on latency. These results demonstrate that adaptive entanglement managements can substantially improve communication efficiency in scalable quantum multi-core systems.
In distributed quantum computing (DQC), executing monolithic quantum circuits across multiple interconnected quantum processing units (QPUs) requires dedicated communication qubits to generate and distribute entanglement. Because the number of physical qubits within a QPU is finite, a trade-off emerges where allocating more communication qubits increases the capacity of quantum channels for concurrent non-local operations, but reduces the number of computational qubits available for local gate operations. Distributed quantum compilation routinely ignores this channel capacity, while hardware architects lack a method to determine it prior to quantum circuit partitioning. Moreover, scheduling entanglement on demand introduces severe latency, whereas pre-fetching exposes stored pairs to decoherence. We propose an economic order quantity model from perishable inventory theory to optimize the trade-off between entanglement distribution latency and the time cost of decoherence. The resulting estimate is driven by algorithmic demand and physical constraints, offering a dual application for the hardware-software co-design of high-performance DQC: for hardware architects, it gives the optimal allocation of dedicated communication qubits in static heterogeneous architectures; for compiler developers, it gives the optimal number to reserve dynamically in homogeneous architectures.
Raymond P. H. Wu, Chathurika Ranaweera, Sutharshan Rajasegarar et al.· 0 citations
Quantum data-center (QDC) architectures aim to scale distributed quantum computing (DQC) by interconnecting multiple quantum processing units (QPUs), but their performance depends strongly on how algorithmic communication patterns interact with entanglement generation, switch reconfiguration, and network topology. This paper studies the Quantum Approximate Optimization Algorithm (QAOA) as a graph-structured optimization workload for QDC-based distributed quantum computing. We adapt QAOA to SwitchQNet, a distributed quantum compiler framework that schedules communication and entanglement generation over switch-based QDC networks, by adding a routing generator that converts graph-dependent two-qubit cost interactions into remote-CX communication requests across QPUs. Using this extension, we evaluate QAOA instances across Clos, fat-tree, and spine-leaf topologies, measuring communication latency, EPR-pair overhead, EPR wait time, retry overhead, and sensitivity to buffer size, look-ahead depth, communication-qubit count, EPR latency, and EPR fidelity assumptions. The results show that QAOA obtains modest but consistent latency reductions, highlighting its value as a diagnostic benchmark for studying the interaction between algorithm structure, entanglement management, and quantum-network architecture.
Samanvay Sharma, Siyuan Niu, Amin Taherkhani et al.· 0 citations
Distributed architectures extend quantum simulation of many-body dynamics beyond the reach of any single processor, with shared entanglement mediating interactions between spatially separated devices. Conventional implementations rely on quantum teleportation, which provides a universal realization of nonlocal operations but incurs a fixed entanglement cost per gate, irrespective of its strength. This becomes increasingly inefficient in product formula simulation, where higher accuracy requires ever more numerous, yet progressively weaker, nonlocal rotations, causing the entanglement cost to diverge in the high-accuracy limit. Here we introduce a simple repeat-until-success protocol that makes entanglement consumption adaptive to interaction strength. Incorporating this primitive into distributed product formulas yields a total entanglement cost that scales linearly with evolution time and remains independent of Trotter error. A matching lower bound from quantum communication complexity proves this time scaling to be optimal, establishing a resource-efficient foundation for high-accuracy quantum simulation across networked processors.
Tianfeng Feng, Jinzhao Sun, Yun-Long Xiao et al.· 0 citations
Modular quantum computing is a leading paradigm for scaling quantum computation beyond the resource limitations of monolithic devices. In this architecture, multiple quantum processing units (QPUs), employing identical or distinct qubit modalities, are interconnected via shared entanglement. Here, we investigate how errors at module interfaces and within individual QPUs affect fault-tolerant computation when qubits are encoded using the rotated surface code. Going beyond the logical-memory benchmark, we perform circuit-level simulations of fault-tolerant nonlocal CNOT gates implemented via lattice surgery between QPUs connected by noisy Bell pairs, and analyze the resulting logical error rates. Our results show that interfaces can tolerate noise up to an order of magnitude higher than intra-QPU noise, with only a minor reduction in the fault-tolerance threshold. We further develop an efficient protocol for preparing distributed fault-tolerant logical GHZ states, reducing ancilla overhead, time, and nonlocal Bell-pair consumption. We show that ancilla minimization in this setting is equivalent to a vertex-cover problem on an associated graph, and introduce a polynomial-time heuristic algorithm for finding low-overhead solutions. Our results provide quantitative evidence that distributed quantum error correction can enable scalable, fault-tolerant quantum computation in modular architectures.
S. Chelluri, R. Mengoni, Tom Darras et al.· 0 citations
A metropolitan-scale entanglement-based quantum communication network enabled by a quantum reconfigurable optical add-drop multiplexer (q-ROADM), which dynamically distributes polarisation-entangled photon pairs from a broadband source to six users over deployed campus and metropolitan fibre, is demonstrated.
Rui Wang, Marcus J. Clark, O. Alia et al.· 1 citation
The realization of large-scale quantum networks requires more than advances in quantum repeaters, memories, and processors, it requires a framework explaining how heterogeneous quantum technologies evolve from isolated deployments into interconnected infrastructures. While the classical Internet evolved under strong utility incentives associated with resource sharing and communication demands, quantum networking currently lacks dominant applications capable of generating comparable incentives. As a consequence, contemporary quantum networks are largely formed through technology-driven decisions motivated by technical feasibility, experimental validation, and expected future value. This work argues that the absence of utility-driven network formation is not solely a consequence of immature applications, but also of insufficient abstraction. In particular, heterogeneous quantum platforms remain tightly coupled to the functionalities they provide, preventing the definition of technology-independent utility functions. A hierarchical architecture consisting of Physical Platforms (PP), Functionalities (F), Services (S), Applications (A), and Use-Cases (UC) is proposed, together with the argument that quantum interconnects constitute the enabling technology required to decouple physical implementations from network functionalities. Such decoupling permits the definition of utility functions at the functionality level and establishes the conditions under which strategic (agent-based) network formation becomes applicable. Quantum interconnects should therefore be viewed not only as interoperability devices, but also as fundamental enablers of strategic quantum network evolution.