A quantum approach to time could reduce memory requirements for future computer simulation models

Computer simulations are extremely useful for scientists who are trying to research by giving them the ability to use models that can make their work easier. Typically, computer models are developed by the scientists themselves while trying to work with the inherent limitations of whatever computer is available for their use. But new research suggests that there could be a way to radically change the conventional method of using computer simulations in future studies.

The secret, according to a couple of researchers from Singapore, lies in using the concept of quantum superposition to make better use of a computer’s resources, particularly, computer memory, when running simulations. The researchers responsible who came up with this idea are Mile Gu, from the National University of Singapore‘s Center for Quantum Technologies and Nanyang Technological University (NTU), and Thomas Elliott, who is also from NTU.

According to the researchers, it could be possible to use principles in quantum physics to greatly improve computer simulations. So-called quantum simulators could be in many different states at the same time, with each one having their own probability of becoming “real,” completely turning the classic method of building computer models on its head.

To better explain their idea, the researchers resorted to using simple analogies. To signify a classical computer and the way that it handles time, they bring up the concept of the hourglass. “Zoom in on an hourglass and one can see the individual grains of sand falling one by one,” said Gu. “It’s a granular flow,” which leaves time cut into uniform and discrete steps.

While useful for general purpose applications, this kind of setup is not the best for continuous simulation models, as running such programs would require an infinite amount of computer memory. Since there is always a finite amount of memory available for any regular computer, this is literally impossible. This is where a quantum simulator comes in. (Related: Supercomputer simulation models the entire known universe).

To understand quantum simulators, imagine yourself trying to catch a bus. If you arrive at the bus stop and the bus isn’t there, you could figure out when the next one will arrive by checking how much time has already passed since the last one left. The probability of the bus arriving isn’t always constant, so it really would depend on when the last bus left.

It is in these types of processes that a quantum simulator could shine. The researchers propose a system to encode the temporal probability distribution for any event that needs to be simulated into the probability weighing of each different state. The key here is to apply superposition to something like a particle’s position, which could lead to time itself being tracked continuously as well. If possible, this method could unlock a system with superior memory-efficiency, without needing to sacrifice predictive accuracy.

“With a quantum simulator, you can avoid the precision versus storage trade-off that you have to suffer with a classic device,” explained Elliott. This alternative method isn’t without flaws, however.

The researchers noted that the gains from quantum simulators would come at the expense of lost knowledge of the past. Evidently, elapsed time or records in time might be unrecoverable in some ways due to the superposition. Regardless, the forecasting ability of the simulator will be retained.

It’s a worthy compromise, according to the researchers. After all, making predictions about what would or could happen is all that really matters in running simulations. In any case, the first time a quantum simulator is used, it will surely hit the news, so watch out for it at some point in the future.

Read more about future uses of computers in Computing.news.

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