Quantum hardware timeline for finance simulations gets closer

May 04, 2021 // By Rich Pell
Quantum hardware timeline nearer for finance simulations
Researchers at investment banking and financial services company Goldman Sachs and quantum-computing-as-a-service company QC Ware say thay have marked a significant step in the roadmap for quantum advantage for financial applications.

The researchers have designed new, robust quantum algorithms that outperform state-of-the-art classical algorithms for Monte Carlo simulations - a mathematical technique used to estimate the possible outcomes of an uncertain event and that can be used to help assess the impact of risk and uncertainty in prediction and forecasting models. The new quantum algorithms, say the researchers, can be used on near-term quantum hardware expected to be available in five to 10 years.

In finance, Monte Carlo methods are used to evaluate risk and simulate prices for a variety of financial instruments, but involve complex calculations and consume significant time and computational resources. Typically, say the researchers, these calculations are executed once overnight, which means that in volatile markets, traders are forced to use outdated results.

Providing traders - who are always looking for an additional edge in the markets - with a quantum computing approach to perform these risk assessments with far greater speed means that simulations could be executed throughout the day and could transform the way financial markets worldwide operate.

"Our team at Goldman Sachs is focused on developing the best technology for the firm and our clients," says William Zeng, Head of Quantum Research, Goldman Sachs. "Quantum computing could have a significant impact on financial services, and our new work with QC Ware brings that future closer. To do this, we introduced new extensions to a core technique in quantum algorithms. This exemplifies the fundamental contributions that our group looks to make in the field of quantum technology."

While quantum computer researchers have known for some time of quantum algorithms that can perform Monte Carlo simulations 1000x faster than classical methods, these algorithms require error-corrected quantum hardware projected to be available in 10 to 20 years. Current quantum devices have very high error rates and can only perform a few calculation steps accurately before returning incorrect results.

For the past year, say the Goldman and QC


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