High schoolers excel at Oxford quantum course using pictorial mathematics
Abstract
We are at the dawn of the second quantum revolution, where our ability to create and control individual quantum systems is poised to drive transformative advancements in basic science, computation, and everyday life. However, quantum theory has long been conceived as notoriously hard to learn, creating a significant barrier to workforce development, informed decision-making by stakeholders and policymakers, and broader public understanding. This paper is concerned with Quantum Picturalism, a novel visual mathematical language for quantum physics. Originally developed over two decades ago to explore the foundational structure of quantum theory, this rigorous diagrammatic framework has since been adopted in both academia and industry as a powerful tool for quantum computing research and software development. Here, we demonstrate its potential as a transformative educational methodology. We report the findings from a pilot study involving 54 UK high school students, randomly selected from a pool of 734 volunteers across the UK. Despite the absence of advanced mathematical prerequisites, these students demonstrated a strong conceptual grasp of key quantum principles and operations. On an assessment comprising university graduate-level exam questions, participants achieved an 82% pass rate, with 48% obtaining a distinction-level grade. These results pave the way for making quantum more inclusive, lowering traditional cognitive and demographic barriers to quantum learning. This approach has the potential to broaden participation in the field and provide a promising new entry point for stakeholders, future experts, and the general public.
Keywords
Cite
@article{arxiv.2512.00141,
title = {High schoolers excel at Oxford quantum course using pictorial mathematics},
author = {Bob Coecke and Aleks Kissinger and Stefano Gogioso and Selma Dündar-Coecke and Caterina Puca and Lia Yeh and Muhammad Hamza Waseem and Emmanuel M. Pothos and Sieglinde Pfaendler and Vincent Wang-Mascianica and Thomas Cervoni and Ferdi Tomassini and Vincent Anandraj and Peter Sigrist and Ilyas Khan},
journal= {arXiv preprint arXiv:2512.00141},
year = {2025}
}
Comments
9 pages, many pictures