UK-based Quantum Motion has been working with Goldman Sachs to investigate how quantum computing can be used in financial services to perform complex calculations, including options pricing.

The scale-up, which was founded by professor John Morton, University College London (UCL), and professor Simon Benjamin, Oxford University, worked alongside the bank to explore how intricate multi-qubit operations can be applied within pricing algorithms.

Options pricing is based on variable market dynamics, volatility, and time-sensitivity, which means it can be both complex and risky.

Traditional computers can have trouble pricing options accurately when handling large amounts of data at a fast pace or exploring a significant range of possible scenarios.

Quantum Motion and Goldman Sachs worked together to develop an efficient algorithm, which included researching the necessary software and hardware capabilities, to enable quantum computations fast enough to improve the process.

The speed and accuracy of these calculations rely on quantum computers having large numbers of qubits. However, many quantum hardware architectures have only a modest number of qubits available at any one time.

This means that quantum software engineers must optimise their algorithms to run on smaller numbers of qubits at once which can result in slower computations overall.

But Quantum Motion says that to take full advantage of quantum computing in areas where the technology can have a big impact, like options pricing, these algorithms must run a lot faster.

As part of its research with Goldman Sachs, the company put forward a method in which the complex algorithms at the heart of quantum software – which are called 'oracles' – can be broken down into many small tasks that run simultaneously.

This increases the number of qubits that need to be operating in parallel but correspondingly reduces the time required to run the algorithm.

“People often don’t realise that even though quantum computers may sound like magic, in reality it’s not enough to have just any machine," explained Simon Benjamin, chief strategy officer, Quantum Motion. "To have real impact in sectors such as finance and pharmaceuticals, which involve exploring a huge space of possibilities, and demand accuracy, quantum computers need to have a large number of qubits available at once, and all of them capable of fast operations.”

Quantum Motion said that its improvement in runtime can be vital for applications – such as those in financial services – where the time, usually in the scale of seconds, is critical for delivering quantum advantage.

The business currently employs 60 people who are specialists across quantum theory, engineering, and software.

It is building what it describes as a "revolutionary technology platform" which is not just a qubit but a scalable array of qubits based on the ubiquitous silicon technology already used to manufacture the chips in smartphones and computers. It is also developing "fault tolerant" quantum computing architectures that are compatible with CMOS processes.

“The strategy at Quantum Motion is to deliver a scalable, integrated quantum architecture capable of building systems of sizes yielding real value," said James Palles-Dimmock, chief executive of Quantum Motion. "The components of our quantum chips are at the same minute scale as conventional transistors, which gives the potential for vast numbers of qubits on a single chip.

"Working alongside end-users, such as Goldman Sachs, enables our researchers to understand the quantum hardware requirements, often stretching to many millions of physical qubits, that are needed to run quantum algorithms that can deliver transformative impact for business.”

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