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Device-independent lower bounds on the conditional von Neumann entropy

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arxiv 2106.13692 v3 pith:RNHOAJT7 submitted 2021-06-25 quant-ph

classification quant-ph
keywords ratesmethodboundscomputeentropyprotocolsconditionaldi-qkd
verification ladder T0 review T1 audit T2 compute T3 formal
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The rates of several device-independent (DI) protocols, including quantum key-distribution (QKD) and randomness expansion (RE), can be computed via an optimization of the conditional von Neumann entropy over a particular class of quantum states. In this work we introduce a numerical method to compute lower bounds on such rates. We derive a sequence of optimization problems that converge to the conditional von Neumann entropy of systems defined on general separable Hilbert spaces. Using the Navascu\'es-Pironio-Ac\'in hierarchy we can then relax these problems to semidefinite programs, giving a computationally tractable method to compute lower bounds on the rates of DI protocols. Applying our method to compute the rates of DI-RE and DI-QKD protocols we find substantial improvements over all previous numerical techniques, demonstrating significantly higher rates for both DI-RE and DI-QKD. In particular, for DI-QKD we show a minimal detection efficiency threshold which is within the realm of current capabilities. Moreover, we demonstrate that our method is capable of converging rapidly by recovering all known tight analytical bounds up to several decimal places. Finally, we note that our method is compatible with the entropy accumulation theorem and can thus be used to compute rates of finite round protocols and subsequently prove their security.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Higher rates for semi-device-independent randomness expansion by recycling input randomness

    quant-ph 2026-04 unverdicted novelty 6.0 of 10

    Two new semi-device-independent randomness expansion protocols achieve high rates by recycling input randomness or biasing inputs, secure against quantum side information, with expansion possible in 10^5 to 10^6 rounds.

  2. Semidefinite optimization of the quantum relative entropy of channels

    quant-ph 2024-10 unverdicted novelty 6.0 of 10

    Semidefinite optimization yields arbitrarily tight upper and lower bounds on the quantum relative entropy of channels via discretized linearization of an integral representation.

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