Trust Theme

Designing quantum algorithms for optimisation that are considerably faster than classical computations, providing secure cryptographic protocols, and performing efficient data analysis at scale, are only beneficial when these claims can be verified, validated, and trusted. Does the quantum algorithm genuinely run faster than its classical counterpart? Is it robust to small errors, and useful in practice? Have the full breadth of mathematical problems underlying potential cryptographic protocols been tested? Is the data analysis pipeline leaking sensitive information? Are claims of ‘quantum security’ and ‘quantum advantage’ truly as good as claimed in both theory and practice?

Our goal is to ground quantum algorithms, their analysis, and purported performance on solid mathematical foundations, to provide rigorous guarantees and clear, reliable understanding on what they do and how useful they are. We will create novel quantum algorithms for searching at scale, mechanisms to assess their robustness and complexity, and rigorous pathways for training machine learning and AI algorithms on quantum computers. We will create benchmarking frameworks that comprehensively compare quantum and classical algorithms across diverse problem landscapes, ensuring that our understanding of quantum algorithms is grounded in both mathematical rigour and practical reality.