IonQ and the Fidelity Center for Applied Technology (FCAT) announced an efficient and reliable design as a critical first step in the application of quantum computing to Monte Carlo methods. The first-of-its-kind state preparation technique is scalable and has been demonstrated on IonQ hardware for up to 20 qubits. FCAT serves as an innovative technology resource for Fidelity Investments.
State preparation is a necessary component of many quantum algorithms and is fundamental in expediting Monte Carlo methods, which use randomness to simulate outcomes of complex problems. Financial institutions use Monte Carlo algorithms to understand the relationship between an outcome and multiple variables in complex systems, but their precision is frequently limited by the length of time needed to run the same algorithm repeatedly with different values of the variables.
IonQ and FCAT believe that when run on large and accurate quantum computers, this state preparation technique will help these institutions achieve faster results.
Peter Chapman, CEO at IonQ, said in a statement: “In finance, accuracy and speed can mean the difference between profit or loss. We believe this technique can provide financial institutions a tool they need to integrate quantum into their workflow and explore novel ways to inform portfolio engineering, retirement planning, and risk management in even the most complex of scenarios.”
This is an extension of IonQ’s project with the FCAT team, during which the two groups issued a paper describing how certain generative quantum machine learning algorithms may provide an advantage over their classical counterparts.
“The Monte Carlo protocol is an integral component of financial planning, as it helps us understand how several correlated variables interact with each other when one element is changed,” said Adam Schouela, head of Emerging Technology at FCAT, in a statement. “However, current state preparation techniques are either theoretical or have some type of deficiency when scaling. Today, we’re proud to announce alongside IonQ a state preparation algorithm that we believe is scalable and executable on NISQ hardware.”