Quantum neural network may be able to cheat the uncertainty principle

The Heisenberg uncertainty principle puts a limit on how precisely we can measure certain properties of quantum objects. But researchers may have found a way to bypass this limitation using a quantum version of a neural network. Given, for example, a chemically useful molecule, how can you predict what properties it might have in an hour or tomorrow? To make such predictions, researchers start by measuring its current properties. But for quantum objects, including some molecules, this can be unexpectedly difficult because each measurement can interfere with or change the outcome of the next measurement.