Goldman Sachs has conducted research into the use of quantum computing in the options pricing market. The investment bank partnered with UK scale-up Quantum Motion to explore how complex multi-qubit operations can enhance pricing algorithms.
Traditional computers face challenges in accurately pricing options when handling large data sets or analyzing numerous potential scenarios. To address this, Goldman Sachs and Quantum Motion developed an efficient algorithm and investigated the requisite software and hardware capabilities needed to support rapid quantum computations, offering the bank a competitive edge.
Quantum Motion introduced a method to deconstruct the complex algorithms central to quantum software—known as oracles—into smaller tasks that can be executed concurrently. While this approach requires an increased number of qubits working in parallel, it significantly reduces the time needed to execute the algorithm. This enhancement in runtime is crucial for applications in financial services, where decisions often need to be made within seconds.
James Palles-Dimmock, CEO of Quantum Motion, stated, “The strategy at Quantum Motion is to deliver a scalable, integrated quantum architecture capable of building systems that yield real value. Our quantum chip components are at the same minute scale as conventional transistors, allowing for a potential abundance of qubits on a single chip. Collaborating with end-users like Goldman Sachs helps our researchers grasp the extensive quantum hardware requirements—often amounting to millions of physical qubits—necessary to run quantum algorithms that can have a transformative impact on business.”