Abstract:

This paper presents Quantum Wa-Tor, a pedagogical reinterpretation of the classic artificial life simulation Wa-Tor, designed to introduce undergraduate students to foundational quantum computing concepts (superposition, measurement, and entanglement) through an engaging, visual, and experiment-driven environment. The model redefines the stochastic rules of movement, predation, and reproduction in Dewdney’s original predator–prey world as quantum-inspired decisions derived from small Qiskit circuits. Each agent is associated with a temporary quantum register whose measurement determines its behavior, allowing students to observe how probabilities emerge from quantum state preparation and collapse. This creates a tangible link between abstract mathematical formalisms and visible ecological dynamics. From an instructional perspective, the project aims to lower the entry barrier to quantum computing by embedding core ideas within a familiar simulation framework widely used in computer science education. The approach supports multiple levels of Bloom’s revised taxonomy: factual knowledge of quantum operations, conceptual understanding of measurement and probability amplitudes, procedural competence in coding simple circuits, and metacognitive reflection on metaphorical modeling. The prototype, implemented in Python and Qiskit, runs efficiently on laptops and can be extended to multiprocessor environments, bridging quantum education and high-performance computing. By combining gamification, visual feedback, and active experimentation, Quantum Wa-Tor encourages curiosity and systems thinking while preserving scientific accuracy. The paper outlines the model’s design, instructional strategy, expected learning outcomes, and opportunities for future classroom evaluation and HPC-based extensions.

Keywords:

Quantum computing education, Wa-Tor, artificial life, gamification, HPC, undergraduate instruction.