Cambridge Quantum Accelerates Monte Carlo Integration in Quantum Computers

Cambridge Quantum Computing ( CQC ) today announced the discovery of a new algorithm that accelerates Monte Carlo quantum integration , shortening the time to quantum advantages and confirming the critical importance of quantum computing for the financial industry in particular.

Monte Carlo integration – the process of numerically estimating the mean of a probability distribution by averaging samples – is used in financial risk analysis, drug development, supply chain logistics, and other applications commercial and scientific, but their realization often requires that the current systems invest many hours of continuous calculation. It is a critical aspect of the computational machinery that sustains the modern world.

CQC has solved the problem with a detailed algorithm in a published preprint of a paper by senior research scientist Steven Herbert , showing how historical challenges are eliminated and the full quadratic quantum advantage is obtained.

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“This new algorithm is a landmark advance that expands Monte Carlo quantum integration and will have applications both during and beyond the NISQ era,” Herbert said. “We are now able to achieve what was previously only theoretical quantum acceleration. That is something that none of the existing quantum Monte Carlo integration (QMCI) algorithms can do without substantial overhead that renders current methods useless.”

Ilyas Khan , CEO of Cambridge Quantum Computing, “This is an impressive breakthrough from the scientists at CQC that will be of great value to the financial sector as well as many other industries and is just the latest in a continuing series of innovations confirming our world leadership in quantum computing. “

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