Fluctuations are ubiquitous in nanometer-scale systems, spanning orders of magnitude in space and time. Real-space access to fluctuating states is impeded by a dilemma
between spatial and temporal resolution. Averaging over an extended period of time (or repetitions) is key for the majority of high-resolution imaging experiments, especially in weak
contrast systems. If, by lack of better knowledge, averaging is indiscriminate, it leads to a loss of temporal resolution and to motion-blurred images. We present coherent correlation imaging (CCI) – a high-resolution, full-field imaging technique that realizes multi-shot, time-resolved imaging of stochastic processes. The key of CCI is
the classification of camera frames that correspond to the same physical state (Fig. 1) even at low photon count, where imaging is not possible. CCI combines a correlation-based similarity
metric with powerful classification algorithm developed for genome research 1 realizing informed, non-sequential signal averaging while maintaining single frame temporal resolution. We apply CCI to study previously inaccessible magnetic fluctuations in a highly degenerate magnetic stripe domain state. Our material is a Co-based chiral ferromagnetic multilayer with
magnetic pinning low enough to exhibit stochastically recurring dynamics that resemble thermally-induced Barkhausen jumps near room temperature. CCI reconstructs sharp, high-contrast
images of all domain states by phase retrieval 2 and, unlike previous approaches, also tracks the time when these states occur. The spatiotemporal imaging reveals an intrinsic transition
network between the states and unprecedented details of the magnetic pinning landscape (Fig. 2).
1 G. Sherlock, et. al., Current Opinion in Immunology 12, 201-205 (2000) 2 Flewett, S. et al., Optics Express 20, 29210–29216, 2012
Principle of time-resolved coherent correlation imaging. Top: Sequence of camera frames showing Fourier-space coherent scattering patterns. Coherent correlation imaging classifies scattering frames by their underlying domain state, as indicated by the colors. Bottom: Real-space images reconstructed from an informed average of same-state frames.
Map of attractive (blue dots) and repulsive (red areas) pinning sites. The background shows the position of the domain walls and their relative occurrence observed in the experiment.