D-Wave Scientist Explains Quantum Annealing

Quantum Computing  

In a new video from D-Wave, Dr. Dominic Walliiman offers an explanation of quantum annealing used in quantum computers.

Quantum annealing is essentially a way of using the intrinsic effects of quantum physics to help solve certain types of problems. It is the core foundation of the quantum computers built by D-Wave.

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Mainly, these are broken down into optimization problems, but they also relate to a sub-field called probabilistic sampling.

In optimization problems, the aim is to figure out the best configuration out of many different configurations. In Walliiman's example, he reflects how the process may be used to figure out the optimal household maintenance budget, based on a large list of items that could have money spent on them at a given period of time.

In physics, optimization problems are a characteristic of energy  minimization problems. Quantum annealing is an ideal method for finding the minimum energy states of systems.

These processes, in turn, are useful in machine learning, where the goal is to build a probabalistic picture of a system and quantum annealing can help to continuously improve the system over time. So far these types of problems have been extremely challenging for classical computers, and are a major stimulating factor behind the push to build functional quantum computer systems.

SOURCE  D-Wave

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