Expand-Map-Reduce: A Elementary Framework for Understanding Quantum Algorithms

Quantum computing holds considerable potential for addressing challenges beyond the capabilities of conventional computing systems. The process of designing software that can leverage the capabilities of quantum computers is an active area of research. Inspired by the conventional MapReduce computing model, in this work we propose the Expand-Map-Reduce framework which aids programmers new to quantum computing in understanding quantum algorithms better. To demonstrate the applicability, this paper presents an explanation of the Deutsch-Josza algorithm through the Expand-Map-Reduce Framework. The research examines the variations in quantum data in superposition states and explores how this contributes to stages of the algorithm within the Expand-Map-Reduce framework. We envision that this framework will permit comparing quantum algorithms’ storage and computational costs with classical algorithms on parallel computation models (like MapReduce, PRAM, etc.).