Information theory provides the fundamental framework for understanding and designing data compression algorithms. At its core lies the concept of entropy, a quantitative measure that reflects the ...

Grounded in Shannon’s seminal work, information theory quantifies the uncertainty—or entropy—in data sources and sets fundamental limits on how efficiently information can be represented.

Previous research has shown that black holes have entropy and emit radiation, phenomena that hint at deeper links between information theory and spacetime geometry.

In information theory, such tools have been used to characterize and gain new insights into the capacity (i.e., the maximum reliable rate) of multi-user networks. Tutorial Papers Dytso, A.; Bustin, R.

The holographic principle, string theory, and loop quantum gravity all struggle with the place of information and entropy in spacetime.

In information theory, it’s the logarithm of possible event outcomes. The logarithmic formula for Shannon entropy belies the simplicity of what it captures — because another way to think about Shannon ...

Entropy can be described in the language of quantum mechanics and conformal field theory is one model for this sort of description.

Entropy and information are both emerging as currencies of interdisciplinary dialogue, most recently in evolutionary theory. If this dialogue is to be fruitful, there must be general agreement about ...

The entropy and mutual information index are important concepts developed by Shannon in the context of information theory. They have been widely studied in the case of the multivariate normal ...