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The signal-to-noise ratio (SNR) of a bit series written with heat-assisted magnetic recording (HAMR) on granular media depends on a large number of different parameters. The choice of material properties is essential for the obtained switching probabilities of single grains and therefore for the written bits quality in terms of SNR. Studies where the effects of different material compositions on transition jitter and the switching probability are evaluated were done, but it is not obvious, how significant those improvements will finally change the received SNR. To investigate that influence, we developed an analytical model of the switching probability phase diagram, which contains independent parameters for, inter alia, transition width, switching probability and curvature. Different values lead to corresponding bit patterns on granular media, where a reader model detects the resulting signal, which is finally converted to a parameter dependent SNR value. For grain diameters between 4 and 8nm, we show an increase of ~10dB for bit lengths between 4 and 12nm, an increase of ~9dB for maximum switching probabilities between 0.64 and 1.00, a decrease of ~5dB for down-track-jitter parameters between 0 and 4nm and an increase of ~1dB for reduced bit curvature. Those results are furthermore compared to the theoretical formulas for the SNR. We obtain a good agreement, even though we show slight deviations.
Enhancing light absorption in the recording media layer can improve the energy efficiency and prolong the device lifetime in heat assisted magnetic recording (HAMR). In this work, we report the design and implementation of a resonant nanocavity struc
In magnetic recording the signal-to-noise ratio (SNR) is a good indicator for the quality of written bits. However, a priori it is not clear which parameters have the strongest influence on the SNR. In this work, we investigate the role of the Gilber
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