An integrated-circuit-based probabilistic computer that uses voltage-controlled magnetic tunnel junctions as its entropy source

Abstract

Probabilistic Ising machines could be used to solve computationally hard problems more efficiently than deterministic algorithms on von Neumann computers. Stochastic magnetic tunnel junctions are potential entropy sources for such Ising machines. However, scaling up stochastic magnetic tunnel junction probabilistic Ising machines requires the fine control of a small magnetic energy barrier and duplication of area-intensive digital-to-analogue converter elements across large numbers of devices. The non-spintronic components of these machines are also typically created using general-purpose processors or field-programmable gate arrays. Here we report a probabilistic computer that is based on an application-specific integrated circuit fabricated using 130-nm foundry complementary metal–oxide–semiconductor technology and uses voltage-controlled magnetic tunnel junctions as its entropy source. With the system, we implement integer factorization as a representative hard optimization problem using probabilistic Ising-machine-based invertible logic gates created with 1,143 probabilistic bits. The application-specific integrated circuit uses stochastic bit sequences read from an adjacent voltage-controlled magnetic tunnel junction chip. The magnetic tunnel junctions are thermally stable in the absence of a voltage and synchronously generate random bits without the use of digital-to-analogue converter elements using the voltage-controlled magnetic anisotropy effect. An application-specific integrated circuit that is fabricated in 130-nm foundry complementary metal–oxide–semiconductor technology, and uses stochastic bit sequences read from an adjacent voltage-controlled magnetic tunnel junction chip, can be used to solve integer factorization problems.