New algorithmic framework breaks a decades-old speed ceiling for Markov chains, promising huge gains in chemistry, physics, and finance.
In a collaboration that blends academic theory and industrial application, Qubit Pharmaceuticals and Sorbonne University have demonstrated that quantum computers can beat what was long thought to be a fundamental speed limit for certain computations. Their work focuses on non-reversible Markov chains, a mathematical framework used to model one-way processes like chemical reactions, protein folding, heat flow, and financial dynamics.
Classically, algorithmic analysis of these systems is notoriously expensive. Earlier quantum research suggested at most a quadratic speedup for reversible Markov chains – simplified models where the evolution can be mathematically “rewound.” The new study shows that for real-world, irreversible systems, quantum algorithms can achieve greater-than-quadratic and potentially up-to-exponential speedups.
The team introduced two new techniques that allow quantum algorithms to naturally follow the forward-only flow of these processes without needing to simulate backward transitions. In practical terms, that means a quantum machine could replace billions of classical iterations with thousands of quantum steps, making large-scale simulations for drug design or materials discovery much more tractable.
Published in Nature Communications, the work also strengthens Qubit Pharmaceuticals’ own simulation platform, which aims to integrate these algorithms into real molecular pipelines. The project is supported by European research programs such as the ERC and France’s PEPR EPIQ and HQI initiatives, underlining Europe’s ambition to lead in quantum software and algorithms.
Conclusions
This result doesn’t just add another quantum algorithm to the toolbox; it redefines what “quantum advantage” can mean for systems that actually exist in nature. By proving that irreversible, noisy physical and economic phenomena can benefit from large quantum speedups, the work opens a path to practical quantum gains in pharma, materials, and quantitative finance once suitable hardware is available.
