Computing benefits from some helpers that, although they have a mystical name, are actually much more useful to science than divine oracles: a great help in solving mathematical problems.
Science is the enemy of magic, they say, but the game changes when even scientists turn to a clairvoyant.
In computing, however, instead of a crystal ball, computer scientists have created dummy devices who respond quickly and correctly to questions.
These have become a powerful tool in computational complexity theory, account to. Just like the instruments that read people’s fortunes, these devices are also called oracles.
Complexity theorists try to understand whether these apparent differences in difficulty are fundamental. classify computational problems according to their inherent difficulty. And this is where oracles come in — and they’re a big help.
Computer scientists and mathematicians then create “complexity classes”. There is the class of easy-to-solve problems, which researchers call “P“, and the class of easy-to-verify problems, the “NP“.
Complexity theorists suspect that NP is not equal to P, but they cannot prove it and have been trying to understand the relationship between the two classes for 50 years.
Oracles, programmed to answer a single question, helped us better understand what they are working with. Basically, an oracle is an abstract machine used to study decision problems.
For example, it is possible to ask this instrument “is this number prime?”, and the answer will always be precise and correct.
In a world where every computer had a direct line to one of these oracles, Quanta summarizes, all problems that are easy to verify would also be easy to solve and P would equal NP.
In addition to all these characteristics, researchers have also studied the performance of quantum computers through problems involving oracles.
What does the future say? The oracles of science do not yet predict, but their certainties can help shape it forever.
Carolina Bastos Pereira, ZAP //
