where\(P(D | \theta _i)\)represents the likelihood between the experimental dataDand model output using parameter combinations\(\theta _i\);\(P(\theta _i)\)represents the a priori distribution of\(\theta _i\), which may be a belief based on past experience or physical considerations; ...
Given a k-step processϒon a dSdimensional subsystem, generated from global unitary dSEdimensionalSEdynamics distributed according to an ϵ-approximate unitaryt-design\({\mu }_{{{\mathsf{t}}}_{\epsilon }}\), the likelihood that its non-Markovianity exceeds any δ > 0 is bounded as...
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Finally, the √sm(rienco) distribution also feels to mass some scale and not the extent the effects from the inclusive UE, but always variables under hcoans siitdsepraeatikoninhtehree,n√easrm(rviencico)inaitpypoeaf rMs pto. Therefore, among the five provide the best estimate of the ...
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