Efficient Calculation of Low Energy Configurations of Nanoparticle Ensembles for Magnetoresistive Sensor Devices by means of Stochastic Spin Dynamics and Monte Carlo Methods

We present results of Monte Carlo and stochastic spin dynamics simulations of a magnetic nanoparticle model system based on experimentally produced samples. Thermodynamic investigations as well as spin dynamics studies show characteristic features, both resembling magnetic dipole glass behaviour. While spin dynamics studies at T = 0 yield a multitude of low energy configurations, thermodynamic simulations show a clear transition between a paramagnetic and a frozen magnetic state. Moreover, we demonstrate the application of experimentally inspired demagnetization protocols to compute low energy configurations of the systems under consideration efficiently.