To do this, the company, Multiverse Computing, will rely on quantum computing technology produced by Oxford Quantum Circuits in the UK and Moody’s Analytics in the U.S.
Quantum computing involves storing information using tiny subatomic particles instead of the larger circuits currently in use. When successful, this leads to incredibly powerful and efficient computers that can hold more information and perform more operations more quickly.
This means that the computer can run bigger programs — the same way that modern computers can run more complicated video games with more detailed graphics than past computers could. The computer has to do more calculations to keep track of each moving part, and older computers just don’t have the storage space or the speed to keep up.
That’s the same problem researchers have run into with large-scale flood models: There are too many moving parts. Too many factors in too many places affect flood risk in a given area, and older models have not been able to track it all and make detailed predictions quickly enough.
Multiverse Computing plans to change that. Moody’s managing director of Quantum and GenAI, Sergio Gago, told The Next Web, “Specifically, there is promising potential in the application of quantum machine learning to develop emulators as alternatives to traditional physics-based models.”
According to The Next Web, Multiverse Computing won a place in Phase One of Innovative UK’s Quantum Catalyst Fund competition, which comes with the equivalent of over $126,000 in funding. Multiverse Computing will use that money to develop the software and algorithms behind the new models. If it successfully moves on to Phase Two, it will receive over $1.5 million.
The UK Department of Environment, Food, and Rural Affairs will be the first to try the new modeling solution to predict floods, which are currently causing over $881 million in damages to the country yearly, The Next Web reported.
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