On the discretization of probability density functions and the continuous Rényi entropy
On the basis of second mean-value theorem (SMVT) for integrals, a discretization method is proposed with the aim of representing the expectation value of a function with respect to a probability density function in terms of the discrete probability theory. This approach is applied to the continuous Rényi entropy, and it is established that a discrete probability distribution can be associated to it in a very natural way. The probability density functions for the linear superposition of two coherent states is used for developing a representative example.
Volume 96, 2022
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