Framework for quantum data center emulation using digital quantum computers

Journal article, 2026

As quantum computers scale, single-chip architectures face inherent limitations in qubit count. This drives the need for modular quantum computing and quantum data centers (QDCs), where multiple quantum processor units (QPUs) are interconnected to enable the distributed execution of a quantum algorithm. However, evaluating distributed quantum computing (DQC) architectures is challenging. Classical simulation is limited by the exponential growth of the state vector, limiting its ability to model large systems and realistically capture hardware noise and timing. Meanwhile, implementing QDC introduces interconnect noise challenges such as transduction inefficiency and optical fiber loss. In this work, we introduce a hardware-based emulation framework by partitioning a single quantum processor’s qubit coupling map into multiple logical QPUs. We show how noise arising from transduction and optical fibers can be modeled by adding an ancilla qubit representing the environment, based on quantum collision dynamics. This model is then translated into a gate-based circuit, in which the couplings between each portion act as controllable noisy quantum communication channels. We demonstrate the framework on IBM quantum hardware by executing remote gates under controllable communication noise. To highlight the flexibility of the platform, we further replicate the implementation results of the distributed Grover’s search algorithm on an ion-trap system. Finally, we test a larger circuit, i.e., a five-qubit quantum Fourier transform (QFT), achieving reasonable fidelity across logical QPUs. Overall, the framework provides a scalable hardware-level emulation platform that captures noise sources through physical qubits and is compatible with any platform supporting the Qiskit SDK.