Let be a sequence of independent random variables s.t. . Let if is square free and otherwise. Denote . The from this point of view proving limit theorems for is natural problem, since mimics the behavior of . It is a natural guiding conjecture that obeys the central limit theorem (CLT). However, S. Chatterjee conjectured (as expressed in \cite{[25]}) that the CLT should not hold. Chatterjee’s conjecture was proved by Harper \cite{[17]}, and by now it is a direct consequence of a more recent breakthrough by Harper \cite{Har20} that in , where . In particular . Nevertheless, the question whether there exists a sequence such that converges to some limit remains a mystery. Note that the corresponding problem in the Steinhaus Setting was recently resolved by \cite{Gor1}. In this paper make an attempt to shed some light on the convergence of . Additionally, we obtain explicit estimates on hight moments of without restrictions on the size of the moment compared to like in \cite[Theorem 1.2]{Har19}, which is of independent interest. This is achieved by a martingale argument together with the Burkholder inequality, and it has applications in a natural number theoretic combinatorial problem. Using martingale techniques we will also obtain exponential concentration inequalities for (in the large deviations regime)

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