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last post 31d ago by aqora_bot
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Posted 4mo ago

Distributed Quantum Property Testing with Communication Constraints

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Mina Doosti, Ryan Sweke, Chirag Wadhwa (Apr 08 2026).
Abstract: We introduce a framework for distributed quantum inference under communication constraints. In our model, mmm distributed nodes each receive one copy of an unknown ddd-dimensional quantum state ρ\rhoρ, before communicating via a constrained one-way communication channel with a central node, which aims to infer some property of ρ\rhoρ. This framework generalizes the classical distributed inference framework introduced by Acharya, Canonne, and Tyagi [COLT2019], by allowing quantum resources such as quantum communication and shared entanglement. Within this setting, we focus on the fundamental problem of quantum state certification: Given a complete description of some state σ\sigmaσ, decide whether ρ=σ\rho=\sigmaρ=σ or ∥ρ−σ∥1≥ϵ\|\rho-\sigma\|_1\geq \epsilon∥ρ−σ∥1​≥ϵ. Additionally, we focus on the case of limited quantum communication between distributed nodes and the central node. We show that when each communication channel is limited to only nq≤log⁡dn_q\leq \log dnq​≤logd qubits, then the sample complexity of distributed state certification is O(d22nqϵ2)\mathcal{O}(\frac{d^2}{2^{n_q}\epsilon^2})O(2nq​ϵ2d2​) when public randomness is available to all nodes. Moreover, under the assumption that the channels used by the distributed nodes are mixedness-preserving, we prove a matching lower bound. We further demonstrate that shared randomness is necessary to achieve the above complexity, by proving an Ω(d34nqϵ2)\Omega(\frac{d^3}{4^{n_q} \epsilon^2})Ω(4nq​ϵ2d3​) lower bound in the private-coin setting under the same assumption as above. Our lower bounds leverage a recently introduced quantum analogue of the celebrated Ingster-Suslina method and generalize arguments from the classical setting. Together, our work provides the first characterization of distributed quantum state certification in the regime of limited quantum communication and establishes a general framework for distributed quantum inference with communication constraints.
Arxiv: https://arxiv.org/abs/2604.05962

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