Information Theory is the scientific study of the quantification, storage, and communication of digital information. The field was fundamentally established by the works of Harry Nyquist and Ralph Hartley, in the 1920s, and Claude Shannon in the 1940s. The field is at the intersection of probability theory, statistics, computer science, statistical mechanics, information engineering, and electrical engineering.
—Wikipedia, “Information Theory”
In fact, by the early 1980s, the answers to the first two questions—Are there codes that can drive the data rate even higher? If so, how much higher? And what are those codes?—were more than 30 years old. They’d been supplied in 1948 by Claude Shannon SM ’37, PhD ’40 in a groundbreaking paper that essentially created the discipline of Information Theory. “People who know Shannon’s work throughout science think it’s just one of the most brilliant things they’ve ever seen,” says David Forney, an adjunct professor in MIT’s Laboratory for Information and Decision Systems.
—MIT News, “Explained: The Shannon limit”
The Shannon limit or Shannon capacity of a communication channel refers to the maximum rate of error-free data that can theoretically be transferred over the channel if the link is subject to random data transmission errors, for a particular noise level. It was first described by Shannon (1948), and shortly after published in a book by Shannon and Warren Weaver entitled The Mathematical Theory of Communication (1949). This founded the modern discipline of Information Theory.
—Wikipedia, “Noisy-channel coding theorem“