CYBERSECURITY
Quantum computing has long promised to calculate market risks at lightning speed, but this vision has been blocked by the data bottleneck. Getting complex, realworld financial data into a quantum computer is notoriously difficult.
Now, new joint research from HSBC and quantum software startup Haiqu suggests a breakthrough. Their findings prove that financial risk modelling applications are much closer to practical reality than previously thought.
The research shows that financial institutions can provide financial data to a quantum computer through a process called Quantum State Preparation. Normally, encoding heavytailed distributions – mathematical
models used to predict extreme market crashes – requires complex circuits that today’ s quantum hardware simply can’ t handle.
These circuits become overwhelmed, causing the quantum computer to crash before it finishes the calculation. HSBC and Haiqu solved this by using a method called Matrix Product States.
This allowed them to create shallow circuits, which are essentially a more streamlined, efficient way to pack data.
Instead of trying to store every single piece of data in the computer’ s memory at once, they used a sampling-based workflow that“ avoids storing the full discretised dataset in classical memory, enabling larger encoding circuits to be generated,” according to HSBC.