The approach outlines a way to teach an AI to make an interconnected set of adjustments to quantum dots, which are among the many promising devices for creating the quantum bits (qubits) that form the switches in a quantum computer’s processor. Precisely tweaking the dots, say the researchers, is crucial for transforming them into properly functioning qubits, and until now the job had to be done painstakingly by human operators, requiring hours of work to create even a small handful of qubits for a single calculation.
A practical quantum computer with many interacting qubits requires far more dots - and adjustments - than a human could manage, so the accomplishment, say the researchers, might bring quantum dot-based processing closer from the realm of theory to engineered reality.
"Quantum computer theorists imagine what they could do with hundreds or thousands of qubits, but the elephant in the room is that we can actually make only a handful of them work at a time,” says Justyna Zwolak, a NIST mathematician. "Now we have a path forward to making this real."
A quantum dot typically contains electrons that are confined to a tight boxlike space in a semiconductor material. The box’s "walls" are several metallic electrodes - or gates - above the semiconductor surface that have electric voltage applied to them, influencing the quantum dot’s position and number of electrons. Depending on their position relative to the dot, the gates control the electrons in different ways.
To control the dots - for example, to make them act as one sort of qubit logic switch or another - the gate voltages must be tuned to just the right values. This tuning is done manually, by measuring currents flowing through the quantum dot system, then changing the gate voltages a bit, then checking the current again. And the more dots (and gates) involved, the harder it is to tune them all simultaneously so that the