Computational complexity

Computer scientists this year learned how to transmit perfect secrets, why transformers seem so good at everything, and how to improve on decades-old algorithms (with a little help from AI).

A quantum approach to data analysis that relies on the study of shapes will likely remain an example of a quantum advantage — albeit for increasingly unlikely scenarios.

Zero-knowledge proofs allow researchers to prove their knowledge without divulging the knowledge itself.

Three computer scientists have posted a proof of the NLTS conjecture, showing that systems of entangled particles can remain difficult to analyze even away from extremes.

Why verify every line of a proof, when just a few checks will do?

Finding out whether a question is too difficult to ever solve efficiently depends on figuring out just how hard it is. Researchers have now shown how to do that for a major class of problems.

Cryptographers want to know which of five possible worlds we inhabit, which will reveal whether truly secure cryptography is even possible.

The existence of secure cryptography depends on one of the oldest questions in computational complexity.

For years, intermediate measurements made it hard to quantify the complexity of quantum algorithms. New work establishes that those measurements aren’t necessary after all.