Quantinuum scientists have created a full Quantum Monte Carlo Integration (QMCI) engine. And report evidence of quantum advantage.

Given the projected increase in bank investment in quantum computing, the financial services sector will be watching with interest.

QMCI applies to problems that have no analytic solution. Examples include pricing financial derivatives or simulating the results of high-energy particle physics experiments. There is the promise of computational advances across business, energy, supply chain logistics and other sectors.

The QMCI tool utilises advanced quantum algorithms. According to the experts, this will allow quantum computers to perform estimations more efficiently and accurately than equivalent classical tools. Specifically, it infers an early-stage quantum advantage in areas such as derivative pricing, portfolio risk calculations and regulatory reporting. A white paper supporting the new tool reveals that QMCI benefits from a computational complexity advantage over classical MCI. And it suggests the engine has the potential to provide quantum usefulness in its current form.

Modular approach future-proofs the engine as quantum computing hardware advances

Ilyas Khan, Chief Product Officer of Quantinuum said “Quantinuum’s end-to-end QMCI engine is the first ever complete quantum solution. It offers the prospect of an immediate boost to the productivity of users in at least two sectors: banking and financial institutions. Scientists expect quantum computers to help them process the vast amounts of data generated in experimental fields such as high energy physics. Our QMCI engine is the culmination of years of work by our algorithms team. It highlights just how quantum computers will offer practical utility. Our modular approach also ‘future-proofs’ the engine as quantum computing hardware advances.”

Rapidly growing quantum demand from financial sector

Steven Herbert, Lecturer in Quantum Computing at the University of Cambridge added: “The QMCI engine taps into rapidly growing demand for tools that help global organisations in finance and other sectors explore and evaluate their route towards quantum advantage. Classical Monte Carlo integration is the preferred method in a range of computational areas where analytic solutions are unavailable. It is widely recognised that these methods will benefit from a quantum advantage. By taking a modular approach, we will equip those scientific and financial professionals with a platform that supports them flexibly through rapid technological advances in the years to come.”

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