2019
DOI: 10.1145/3290346
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Quantum relational Hoare logic

Abstract: We present a logic for reasoning about pairs of interactive quantum programs -quantum relational Hoare logic (qRHL). This logic follows the spirit of probabilistic relational Hoare logic (Barthe et al. 2009) and allows us to formulate how the outputs of two quantum programs relate given the relationship of their inputs. Probabilistic RHL was used extensively for computer-verified security proofs of classical cryptographic protocols. Since pRHL is not suitable for analyzing quantum cryptography, we present qRHL… Show more

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Cited by 56 publications
(91 citation statements)
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“…This language is intentionally minimalistic. It seems to lack a number of features that are present, e.g., in [19]: Initializing variables with states other than |0 . Performing measurements.…”
Section: Quantum Programsmentioning
confidence: 99%
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“…This language is intentionally minimalistic. It seems to lack a number of features that are present, e.g., in [19]: Initializing variables with states other than |0 . Performing measurements.…”
Section: Quantum Programsmentioning
confidence: 99%
“…Extensions of this basic quantum Hoare logic can make some statements about probabilities: Quantum Hoare logic whose pre-/postconditions are expectations [7,20] can, e.g., express that a certain predicate will hold with a certain probability. And [19] can express that the outputs of two programs are identical, even taking into account their distributions. But both still lack the possibility of stating, as part of a pre-/postcondition, e.g., that a variable has a particular distribution.…”
Section: Hoare Logic With Ghostsmentioning
confidence: 99%
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“…For a recent overview of the developments on this subject, that successfully parallel the developments of the customary Hoare's logic, see [Yin19]. A related approach of [Unr19] follows the line of research started with [Ben04] and [BGB09] and introduces quantum Relational Hoare Logic (qRHL) that allows one to reason about how the outputs of two quantum programs relate given a relation between their inputs.…”
Section: Final Remarks: a Summary And An Assessmentmentioning
confidence: 99%