Modeling and Detection Algorithms of the P-SLAM Optical Data Storage System

Abstract

The P-SLAM (parallel-sublambda) optical data storage system uses sub-wavelength features to store data and data densities of 5 Gbits/cm 2 are predicted. To detect the sub-wavelength features the near-field transmitted power is measured. The main hindrance to detection is interference from neighboring features. The FDTD method is used to model a limited span of the interference. A modified Viterbi algorithm is applied to a string of power measurements synthesized from the FDTD simulations and raw bit error rates of 10-4 are achieved indicating that this algorithm is effective