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    Therefore parameter dependence is not necessary for contr... — Carmelics
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    Challenges→Parameter dependence is a necessary and sufficient condition for controllable probabilistic dependence in models where measurement outcome probabilities depend only on the pair's state and apparatus settings

    Therefore parameter dependence is not necessary for controllable dependence, since outcome-dependent models can permit statistical correlations exploitable for signaling.

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