An experimental demonstration of the viability of energy minimizing computing using nano-magnets

There has been recent proposals for the use of nano-magnets to directly solve quadratic minimization problems, especially those arising in computer vision applications. This is unlike proposals for using nano-magnets to represent binary states. A collection of nano-magnets, when driven to their ground states, can be seen to optimize a quadratic energy function that is determined by their relative placement. By controlling the relative placement of nano-magnets, we can change the energy function being minimized. In this work, we experimentally demonstrate this capability by fabricating and testing an example of a quadratic optimization problem that accomplishes line grouping.