  In this article we consider an experimental study showing the influence of
emotion regulation strategies on human memory performance: part of such
experimental results are difficult to explain within a classic cognitive
allocation model. We provide a first attempt to build a model of human memory
processes based on a quantum algorithm, the Grover's algorithm, which allows to
search a particular item within an unsorted set of items more efficiently than
any classic search algorithm. Based on Grover's algorithm paradigm, this new
memory model results to have interesting features: it is an iterative process,
it uses parallelism and interference effects. Moreover, the strength of such
interference effects depends on a parameter of the generalized Grover's
algorithm, called the phase, which admits an interpretation in terms of the
emotions involved by the items and by the emotion regulation strategies. Thus
we show that a reasonable choice of the phase is able to describe correctly the
experimental results we consider.
