Quantum computing and quantum computers are emerging technologies that have received considerable attention in recent years. What may not have been communicated as clearly, however, is that quantum computing comes in two main forms: gate-based (digital) quantum computing and analog quantum computing. The latter is focused on solving optimization problems, such as minimizing the carbon footprint of transportation systems or training neural networks for machine learning applications.
This can be achieved by exploiting what is known as the adiabatic theorem in quantum physics: if a system is initially in its ground state, the state of minimum energy, it will remain in the corresponding ground state of a changing system, provided that the change occurs slowly enough. By gradually "transforming" a well-understood quantum system into another whose ground state is unknown, we hope that nature itself can provide solutions to problems that are beyond the reach of conventional computers.