Machine Learning Gets a Quantum Speedup


Two teams have shown how quantum approaches can solve problems faster than classical computers, bringing physics and computer science closer together.

For Valeria Saggio to boot up the computer in her former Vienna lab, she needed a special crystal, only as big as her fingernail. Saggio would place it gently into a small copper box, a tiny electric oven, which would heat the crystal to 77 degrees Fahrenheit. Then she would switch on a laser to bombard the crystal with a beam of photons.

This crystal, at this precise temperature, would split some of those photons into two photons. One of these would go straight to a light detector, its journey finished; the other would travel into a tiny silicon chip — a quantum computing processor. Miniature instruments on the chip could drive the photon down different paths, but ultimately there were only two outcomes: the right way, and the many wrong ways. Based on the result, her processor could choose another path and try again.

The sequence feels more Rube Goldberg than Windows, but the goal was to have a quantum computer teach itself a task: Find the right way out.

Read the full story in Quanta Magazine