A new approach to analyzing visual images is proposed, based on the idea of converting an optical image into a spatially
varying pattern of polarized squeezed light, which is then used to produce a pattern of chiral edge currents in a thin film
topological insulator. Thin films of Bi or Bi doped with Sb which are punctured with an array of sub-micron holes may
be a way of realizing this kind of optical quantum information processing.
The Helmholtz machine provides what may be the best existing model for how the mammalian brain recognizes patterns. Based on the observation that the "wake-sleep" algorithm for training a Helmholtz machine is similar to the problem of finding the potential for a multi-channel Schrodinger equation, we propose that the construction of a Schrodinger potential using inverse scattering methods can serve as a model for how the mammalian brain learns to extract essential information from sensory data. In particular, inverse scattering theory provides a conceptual framework for imagining how one might use EEG and MEG observations of brain-waves together with sensory feedback to improve human learning and pattern recognition. Longer term, implementation of inverse scattering algorithms on a digital or optical computer could be a step towards mimicking the seamless information fusion of the mammalian brain.