Cambridge Quantum Computing has unveiled a new algorithm to speed up quantum Monte Carlo integration times

Cambridge Quantum Computing (CQC) has announced the discovery of a new algorithm that can speed up the quantum Monte Carlo integration operation time, reducing the time to achieve quantum advantage, in particular demonstrating the importance of quantum computing to the financial industry.

Monte Carlo integral is used to estimate the mean of probability distribution by means of sample means. It is used in financial risk analysis, drug development, supply chain logistics and other fields. With the current system, however, it usually takes hours of continuous computation to produce a result.

The algorithm described in a preprint of the paper, published by Steven Herbert, a senior research scientist at CQC, addresses this problem.

"The discovery of this new algorithm is a historic step forward, speeding up the computation time of quantum Monte Carlo integrals, and will be applied in the NISQ era and beyond." "We are now able to achieve quantum acceleration in a real sense, not in theory," says Steven Herbert. This is something existing quantum Monte Carlo integration (QMCI) algorithms will not be able to achieve in a short time."

"This is a major breakthrough by CQC scientists, which has important implications for the financial industry as well as many other industries," said CQC CEO Ilyas Khan. "It is the latest in a line of continuous innovation that confirms our world leadership in quantum computing."