Original version From This story Appeared in Quanta Magazine.
Ask a question for a magic ball 8, and answers yes, no, or something unparalleled. We think it as a child’s toy, but computer scientists use the same tool. They often imagine that they can consult with hypothetical devices called Oracle, which can be answered immediately and correctly to specific questions. These interesting tests are inspired by new algorithms and have helped researchers draw the computing scenery.
Researchers who use Oracles work in a subset of computer science called the theory of computational complexity. They are concerned about the inherent difficulty of problems, such as determining whether it is a main number or find the shortest path between the two points in a network. Some problems are easy to solve, others seem to be much harder, but there are solutions that are easy to check, while others are easy for quantum computers but are seemingly difficult for ordinary cases.
Complex theorists want to know if these apparent differences are fundamental. Is something inherently difficult about specific problems, or are we just smart enough to provide a good solution? Researchers address such questions by sorting problems in “complexity classes”-for example, easy problems in one class and all easy problems to examine in another period-and proof of the relationships between those classes. .
Unfortunately, mapping from a computational landscape is good, difficult. So in the mid -1970s, some researchers start studying if the rules of computation are different. This is where the Oracles enter.
Like the Magic 8 Balls, Oracles are devices that immediately answer questions without showing anything about their inner work. Unlike the magic 8 ball, they always say yes or no, and they are always true – the advantage of being a story. In addition, each given Oracle will only answer a specific question, such as “Is this the main number?”
What makes these fictional devices useful for understanding the real world? In short, they can show the hidden communication between different complexity classes.
Consider two famous classes of complexity. The class is one of the easily soluble problems, which the researchers call “P”, and the problems that are easy to examine, which the researchers call “NP”. Is all the easy review problems too? If so, that means that the NP will be equal to P, and all encryption will be easy to leave (including other consequences). Complex theorists think that the NP is not equal to P, but they cannot prove it, even if they have tried to reduce the relationship between the two classes for more than 50 years.
Oracles have helped them better understand what they are working with. Researchers have invented Oracle that answer questions that help solve different problems. In a world where every computer had a telephone line for one of these Oracles, all easy problems for review will be easy and P will be equal to NP. But more useful Oracles have a contrasting impact. In the world gathered by these Oracles, P and NP will be significantly different.
