In a study published in the prestigious journal Advanced Science, Australian researchers have unveiled an innovative technique based on quantum machine learning (QML) that could revolutionize the complex process of designing electronic circuits.
This method, which uses the QKAR algorithm to convert classical data into quantum states, provides models for designing electronic circuits that are up to 20 percent more efficient than traditional methods.
This technique is particularly useful in the final stages of manufacturing electronic circuits, namely the packaging process, and could lead to significant advances in the semiconductor industry.
Researchers examined 159 samples of gallium nitride (GaN) HEMTS transistors used in advanced electronic equipment to identify key variables affecting ohmic resistance.
The data obtained using QKAR was converted into quantum states and analyzed by a quantum system to discover hidden patterns.
