Grover's algorithm and human memory

TL;DR

This paper proposes a quantum-inspired model of human memory based on Grover's algorithm, incorporating emotion regulation effects to explain experimental memory performance data.

Contribution

It introduces a novel quantum algorithm-based model of memory that accounts for emotional influences and interference effects, advancing cognitive modeling.

Findings

The model can accurately replicate experimental memory performance.

Emotion regulation strategies influence the phase parameter in the model.

Quantum interference effects are relevant to understanding memory processes.

Abstract

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.