Advantage of measurement‑based quantum computing on NISQ devices

Determine whether measurement‑based quantum computing (MBQC) can provide a practical advantage on noisy intermediate‑scale quantum (NISQ) devices by identifying tasks, architectures, or regimes where MBQC outperforms circuit‑model approaches or classical algorithms under realistic noise and resource constraints.

Background

Measurement‑based quantum computing (MBQC) proceeds by preparing a highly entangled cluster state and performing sequential, adaptive single‑qubit measurements to drive computation. Many important algorithms have been translated into this framework.

The paper explicitly states that, despite these translations, it is unclear how MBQC yields advantages on current NISQ hardware. This frames a concrete open question about identifying practical benefits or demonstrating tasks where MBQC can surpass alternatives under NISQ limitations.

References

Though we have translated many important algorithms into this framework, it is unclear how they can present an advantage for NISQ devices.

— Quantum machine learning -- lecture notes  (2512.05151 - Žunkovič, 3 Dec 2025) in Section: Models of quantum computation, Paragraph: Measurement‑based and continuous variable quantum computation

This naturally raises the question of whether the same strategy extends to other $CZ$-based architectures, including more general IQP circuits , other quantum advantage schemes and measurement-based quantum computation (MBQC) . Whether these architectures can likewise help remains an interesting open question.

— Constant-depth global shadow estimation  (2609.10408 - Zhang et al., 9 Sep 2026) in Section 3.1, subsection “Constant-depth synthesis and cost analysis” (the paragraph following Proposition 2)