This paper introduces SiQAD, a computer-aided design tool enabling the rapid design and simulation of atomic silicon dangling bond quantum dot patterns capable of computational logic. Several simulation tools are included, each able to inform the designer on various aspects of their designs: a ground-state electron configuration finder, a non-equilibrium electron dynamics simulator, and an electric potential landscape solver with clocking electrode support. Simulations have been compared against past experimental results to inform the electron population estimation and dynamic behavior. New logic gates suitable for this platform have been designed and simulated, and a clocked wire has been demonstrated. This work paves the way for the exploration of the vast and fertile design space of atomic silicon dangling bond quantum dot circuits.
Robust automated design tools are crucial for the proliferation of any computing technology. We introduce the first automated design tool for the silicon dangling bond quantum dot computing technology, which is an extremely versatile and flexible single-atom computing circuitry framework. The automated designer is capable of navigating the complex, hyperdimensional design spaces of arbitrarily sized design areas and truth tables by employing a tabula rasa double-deep Q-learning reinforcement learning algorithm. Robust policy convergence is demonstrated for a wide range of two-input, one-output logic circuits and a two-input, two-output half-adder, designed with an order of magnitude fewer SiDBs in several orders of magnitude less time than the only other half-adder demonstrated in the literature. We anticipate that reinforcement learning-based automated design tools will accelerate the development of the SiDB quantum dot computing technology, leading to its eventual adoption in specialized computing hardware.
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