The synchronization of human networks is essential for our civilization and understanding its dynamics is important to many aspects of our lives. Human ensembles were investigated, but in noisy environments and with limited control over the network parameters which govern the network dynamics. Specifically, research has focused predominantly on all-to-all coupling, whereas current social networks and human interactions are often based on complex coupling configurations. Here, we study the synchronization between violin players in complex networks with full and accurate control over the network connectivity, coupling strength, and delay. We show that the players can tune their playing period and delete connections by ignoring frustrating signals, to find a stable solution. These additional degrees of freedom enable new strategies and yield better solutions than are possible within current models such as the Kuramoto model. Our results may influence numerous fields, including traffic management, epidemic control, and stock market dynamics.

We suggest a time-lens array with a filling factor of 200% and increased resolution of 60% without decreasing the number of lenses in the array. This time-lens array is based on a series of orthogonally polarized time-lenses. We investigate the different nonlinear interactions and show that when the pump waves of two adjacent time-lenses have orthogonal states of polarization, it is possible to overlap by 50% without unwanted nonlinear interactions.

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