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Superconducting Qubits Quantum Machine Learning

Emulation of Optically Interconnected Quantum Data Centers Topologies for Cost-Fidelity Benchmarking

arXiv

Authors: Seyed Navid Elyasi, Seyed Morteza Ahmadian, Rui Lin, Paolo Monti

Year

2026

Paper ID

63684

Status

Preprint

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~2 min

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Abstract

We emulate optically interconnected quantum processors in ring, star, and line topologies using a quantum computer. GHZ benchmarks show that the star provides the best trade-off between cost and fidelity under transduction and fiber noise.

Why This Paper Matters

This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
It adds a 2026 reference point for readers tracking recent quantum research.
We emulate optically interconnected quantum processors in ring, star, and line topologies using a quantum computer.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:2605.22267 [2] arXiv https://arxiv.org/abs/2605.22267 [3] Publisher https://arxiv.org/abs/2605.22267

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