The universe is expanding, and scientists want to know how fast and what it's made of. To do that, they compare data from distant stellar explosions, sound waves in the early universe, and the faint glow left over from the Big Bang. Each dataset is like a piece of a mosaic, and the goal is to assemble them into a full picture.
A new quantum algorithm called AEQGA works like a breeder in a greenhouse. It takes a set of candidate answers, crosses them using quantum operations (much like mixing plant genes), and keeps only the most promising ones. In this way, it hunts for two numbers: the Hubble constant (the expansion rate) and the matter fraction of the universe. The algorithm was tested on three types of data, and its answers matched those from classical methods.
For now, this is just a proof of concept. But if quantum computers become more powerful, such algorithms could analyze vast amounts of data from future telescopes more quickly. Then the map of the universe would become more precise, and we would better understand where it is heading.
The Hubble constant is a number that tells how fast galaxies are receding. Its current value is about 70 kilometers per second per megaparsec, but different methods give slightly different answers, and that's one of cosmology's puzzles.