Publication | Open Access
Which causal structures might support a quantum–classical gap?
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Citations
17
References
2017
Year
EngineeringCausal InferenceQuantum ComputingQuantum Mechanical PropertyProbabilistic ReasoningQuantum TheoryQuantum PhysicsQuantum MatterQuantum–classical GapStatisticsCausal ModelQuantum ScienceCausal ScenarioPhysicsEntropic InequalitiesProbability TheoryCausal StructureCausal ReasoningReasoningBayesian StatisticsGraph TheoryNatural SciencesImprecise ProbabilityMathematical FoundationsQuantum DevicesStatistical InferenceCausality
Abstract A causal scenario is a graph that describes the cause and effect relationships between all relevant variables in an experiment. A scenario is deemed ‘not interesting’ if there is no device-independent way to distinguish the predictions of classical physics from any generalised probabilistic theory (including quantum mechanics). Conversely, an interesting scenario is one in which there exists a gap between the predictions of different operational probabilistic theories, as occurs for example in Bell-type experiments. Henson, Lal and Pusey (HLP) recently proposed a sufficient condition for a causal scenario to not be interesting. In this paper we supplement their analysis with some new techniques and results. We first show that existing graphical techniques due to Evans can be used to confirm by inspection that many graphs are interesting without having to explicitly search for inequality violations. For three exceptional cases—the graphs numbered <?CDATA $\#15,16,20$?> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo>#</mml:mo> <mml:mn>15</mml:mn> <mml:mo>,</mml:mo> <mml:mn>16</mml:mn> <mml:mo>,</mml:mo> <mml:mn>20</mml:mn> </mml:math> in HLP—we show that there exist non-Shannon type entropic inequalities that imply these graphs are interesting. In doing so, we find that existing methods of entropic inequalities can be greatly enhanced by conditioning on the specific values of certain variables.
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