We perform micromagnetic simulations to study the switching barriers in square artificial spin ice systems consisting of elongated single domain magnetic islands arranged on a square lattice. By considering a double vertex composed of one central island and six nearest neighbor islands, we calculate the energy barriers between two types of double vertices by applying the simplified and improved string method. We investigate by means of micromagnetic simulations the consequences of the neighboring islands, the inhomogeneities in the magnetization of the islands and the reversal mechanisms on the energy barrier by comparing three different approaches with increasing complexity. The micromagnetic models, where the string method is applied, are compared to a method commonly in use, the mean barrier approximation. Our investigations indicate that a proper micromagnetic modeling of the switching process leads to significantly lower energy barriers, by up to 35% compared to the mean-barrier approximation, so decreasing the expected average life time up to seven orders of magnitude. Hereby, we investigate the influence of parallel switching channels and the conceptional approach of using a mean-barrier to calculate the corresponding rates.

Collective dynamics in lithographically-defined artificial spin ices offer profound insights into emergent correlations and phase transitions of geometrically-frustrated Ising spin systems. Their temporal and spatial evolution are often simulated using kinetic Monte Carlo (kMC) simulations, which rely on the precise knowledge of the switching barriers to obtain predictive results in agreement with experimental observations. In many cases, however, the barriers are derived from simplified assumptions only, and do not take into account the full physical picture of nanomagnetic switching. Here we describe how the immediate magnetic square- or kagome-ice environment of a nanomagnet reversing via quasi-coherent rotation can induce clockwise and counter-clockwise switching channels with different barrier energies. This energy splitting for chiral reversal channels can be sizeable and, as string-method micromagnetic simulations show, is relevant for artificial spin ice systems made of both exchange- as well as magnetostatically-dominated units. Due to the barrier splitting and further reductions due to non-uniform reversal, transition rates can be exponentially enhanced by several orders of magnitude compared to mean-field predictions, especially in the limit of rare switching events where thermal excitation is less likely. This leads to significantly faster relaxation time scales and modified spatial correlations. Our findings are thus of integral importance to achieve realistic kMC simulations of emergent correlations in artificial spin systems, magnonic crystals, or the evolution of nanomagnetic logic circuits.

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Nanomagnetic logic, in which the outcome of a computation is embedded into the energy hierarchy of magnetostatically coupled nanomagnets, offers an attractive pathway to implement in-memory computation. This computational paradigm avoids energy costs associated with storing the outcome of a computational operation. Thermally driven nanomagnetic logic gates, which are driven solely by the ambient thermal energy, hold great promise for energy-efficient operation, but have the disadvantage of slow operating speeds due to the slowness and lack of spatial selectivity of currently employed global heating methods. As has been shown recently, this disadvantage can be removed by employing plasmon-assisted photoheating, where selective local heating is achieved by the polarization dependence of the optical absorption cross section of the nanomagnet. Here, we show by means of micromagnetic and finite-element simulations how such local heating can be exploited to design reconfigurable nanomagnetic Boolean logic gates. The reconfigurability of operation is achieved either by modifying the initializing field protocol or optically, by changing the order in which two orthogonally polarized laser pulses are applied. Our results thus demonstrate that nanomagnetic logic offers itself as a fast (up to gigahertz), energy-efficient and reconfigurable platform for in-memory computation that can be controlled via optical means.

Nanomagnetic logic, in which the outcome of a computation is embedded into the energy hierarchy of magnetostatically coupled nanomagnets, offers an attractive pathway to implement in-memory computation. This computational paradigm avoids separate energy costs associated with transporting and storing the outcome of a computational operation. Thermally-driven nanomagnetic logic gates, which are driven solely by the ambient thermal energy, hold great promise for energy-efficient operation, but have the disadvantage of slow operating speeds due to the lack of spatial selectivity of currently-employed global heating methods. As has been shown recently, this disadvantage can be removed by employing local plasmon-assisted photo-heating. Here, we show by means of micromagnetic and finite-elements simulations how such local heating can be exploited to design reconfigurable nanomagnetic Boolean logic gates. The reconfigurability of operation is achieved either by modifying the initialising field protocol or optically, by changing the order in which horizontally and vertically polarised laser pulses are applied. Our results thus demonstrate that nanomagnetic logic offers itself as a fast (up to GHz), energy-efficient and reconfigurable platform for in-memory computation that can be controlled via optical means.