Spincirc

Spincirc is a computational framework for modeling spintronic devices using equivalent-circuit spin-transport methods. The theoretical foundation is described in Alawein and Fariborzi, IEEE Journal on Exploratory Solid-State Computational Devices and Circuits (J-XCDC) 2018, which established circuit-level abstractions for spin-transport phenomena in nanoscale magnetic devices.

The core solvers are implemented in MATLAB and handle coupled transport-magnetodynamics simulations. These solvers integrate the Landau-Lifshitz-Gilbert (LLG) and Landau-Lifshitz-Gilbert-Slonczewski (LLGS) equations with thermal noise models, capturing both deterministic switching behavior and stochastic effects relevant to device reliability analysis. The framework supports a range of spintronic device types including magnetic tunnel junctions (MTJs), spin valves, all-spin logic architectures, and multiferroic devices.

Python analysis and machine learning tools extend the MATLAB solvers, providing data processing, parameter extraction, and predictive modeling capabilities. Verilog-A compact models are also included to enable integration with standard electronic design automation (EDA) tools, bridging the gap between physics-level simulation and circuit-level design workflows.

Spincirc is closely related to the maglogic project, which uses micromagnetic simulation (OOMMF/MuMax3) to model nanomagnetic logic gates at the physical level. Both projects are referenced by the scicomp cross-platform scientific computing framework. The repository is hosted at github.com/alawein/spincirc and is under active development in the physics domain with P2 priority.