Quantum computing firms are starting to get more eager and more organized about publicly discussing positive collaborations they are having with customers and partners. In that vein, IonQ has announced what it described as “promising early results” from a project with partner GE Research focused on exploring the benefits of quantum computing for modeling multi-variable distributions in risk management.
IonQ and GE Research, the central innovation unit of General Electric, were able to use a Quantum Circuit Born Machine-based framework on standardized, historical indexes, effectively training quantum circuits to learn correlations among three and four indexes. The partners used IonQ’s current-generation Aria system for the project.
The companies said in a statement, “The prediction derived from the quantum framework outperformed those of classical modeling approaches in some cases, confirming that quantum copulas can potentially lead to smarter data-driven analysis and decision-making across commercial applications,”
They further added:
While classical techniques to form copulas using mathematical approximations are a great way to build multi-variate risk models, they face limitations when scaling, the companies said. IonQ and GE Research successfully trained quantum copula models with up to four variables on IonQ’s trapped ion systems by using data from four representative stock indexes with easily accessible and variating market environments.
By studying the historical dependence structure among the returns of the four indexes during this timeframe, the research group trained its model to understand the underlying dynamics. Additionally, the newly presented methodology includes optimization techniques that allow models to scale by mitigating local minima and vanishing gradient problems common in quantum machine learning practices. Such improvements demonstrate a promising way to perform multi-variable analysis faster and more accurately, which GE researchers hope lead to new and better ways to assess risk with major manufacturing processes such as product design, factory operations, and supply chain management.
“As we have seen from recent global supply chain volatility, the world needs more effective methods and tools to manage risks where conditions can be so highly variable and interconnected to one another,” said David Vernooy, a Senior Executive and Digital Technologies Leader at GE Research. “The early results we achieved in the financial use case with IonQ shows the high potential of quantum computing to better understand and reduce the risks associated with these types of highly variable scenarios.”
The glimpse at IonQ’s work with GE Research is similar to the updates we have received from the company over the last year as it has worked with Hyundai Motor Company.
IonQ is not the only quantum computing company GE Research has worked with. It also has worked with technology from D-Wave Systems and IBM on other projects.
Image credit: IonQ, GE Research
Dan O’Shea has covered telecommunications and related topics including semiconductors, sensors, retail systems, digital payments and quantum computing/technology for over 25 years.