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Kyun! Ho Gaya Na Full Movie Hindi Movie HD 1080p Download of the coefficient $A_{i}(L/2)$, up to a universal constant. This has already been proved in [@Olesky2018]. We could also use a variant of the proof of Theorem \[thm:generalization\_plancherel\] to show directly that the expression $\sum_{i=1}^{L-1} \tilde{v}^*_i(\omega) \tilde{v}^*_i(\omega)$ achieves the minimal value for a finite $L$. Since the statement of Theorem \[thm:generalization\_plancherel\] can easily be generalized to the case of a random matrix $M$ instead of the deterministic $K$ used in the proof above, we obtain that, as $L$ tends to infinity, $\sum_{i=1}^{L-1} \tilde{v}^*_i(\omega) \tilde{v}^*_i(\omega)$ almost surely converges, hence the large deviation in is proved. It is not clear to us if the convergence holds also almost surely. A better understanding of the fluctuations of this expression would also allow to prove.
A more accurate asymptotic analysis of the tail probabilities would also provide a proof of Theorem \[thm:large\_deviation\_transition\_point\], using a similar approach to the one of [@Kargin2017].
Conclusion
==========
In this paper, we extended the Plancherel theorem to operators on $L^2(\mathbb{Z})$ that are either bounded or unbounded. By extending several lines of a previous work by Kargin and Olshanski, we established general conditions for the equality $$\label{intro:domination_condition}
(\mathbb{E}_{U\sim\mu}[A_\delta(U)])^2 \geq \left( \liminf_{\epsilon \rightarrow 0} \liminf_{L\rightarrow \infty} (\mathbb{E}_{\delta \in [0,1], U\sim\mu_{L,\delta}} [A_\ep