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Random variables as functions We consider in this chapter real random variables (ie, realvalued random variables) In the chapter on Random Vectors and Joint Distributions, we extend the notion to vectorvalued random quantitesThe fundamental idea of a real random variable is the assignment of a real number to each elementary outcome \(\omega\) in the basic space \(\Omega\). (b) A different realization of the same model The hopping Hamiltonian h (k) = (t 1 t 2 cos k) σ x t 2 sin k σ z, and the dissipators are L x l = γ l c x A and L x g = γ g c x A †, (b) is equivalent to (a) via a basis change σ y ↔ σ z Because gain and loss is on site, (b) is more feasible experimentally Reuse & Permissions. Thus, it has a convergent subsequence by Ascoli's theorem.

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