Researchers at Notre Dame have created what is known as an analog algorithm. Basically it is a set of equations used to solve problems like how to make your car safer, smaller and more efficient, all while hitting a given price point.
This new analog algorithm is essentially, a set of equations. Not simple ones like this but instead, differential equations, that are rather complex.
“Our algorithm is more like a set of equations that describe fluid flows like the movement of air in the atmosphere,” explains Zoltan Toroczkai Professor of Physics at Notre Dame.
Algorithms like this can be used in computer models that help predict the weather and they might have played a role in making that cell phone that is in your pocket.
“They are frequently occurring in industry, in product design, and engineering but also in basic sciences,” explains Toroczkai. “Basically what you have is a list of constraints that your product has to fulfill and as we evolve, the industry evolves, and technology evolves there are more and more constraints like your iPhone. It has to be smaller it has to be tough, all these things.”
As you can imagine these problems can be quite complex, but researchers are using the ever popular Sudoku number game, as a simpler example.
“It is a bit similar to Sudoku, of course Sudoku is just a toy version of that,” says Toroczkai.
Most people playing Sudoku eventually have to guess and check after all the easy numbers are filled in. This algorithm does it a little bit different. It never has to guess and check.
So in theory, this newly developed algorithm is faster than traditional digital computer algorithms, but I say in theory because, the device to run this set of equations has not been created yet. In this case researchers have put the proverbial cart before the horse.
“We are very much looking forward to see where this leads to and what sort of applications it can have,” says Toroczkai.
Zoltan along with Maria Ercsey-Ravasz recently had their work published in "Nature," a peer reviewed physics publication.