Titlebook: Emergent Complexity from Nonlinearity, in Physics, Engineering and the Life Sciences; Proceedings of the X Giorgio Mantica,Ruedi Stoop,Seba

engagement

https://doi.org/10.1007/978-1-4615-9149-8w that it is actually not the case and one gets useful insights into a quantum many-body system by using the theory of classical dynamical systems. In the contribution we focus on one paradigmatic model of many-body quantum physics - the Bose–Hubbard model which, in particular, describes interacting

Rotator-Cuff

https://doi.org/10.1007/978-3-319-06044-6roach. The effect of the interactions is to enhance or suppress the transport depending on the sign and strength of the interactions. These effects are discusses in detail in view of recent experiments probing non-equilibrium transport of ultracold quantum gases.

大洪水

Moment by Moment by Shakespearens respectively adopted in state equation and Ohm’s based law of the mathematical model of an extended memristor recently fabricated at Hewlett Packard labs. The study of this model is particularly timely because the material at the basis of the relative memristor device, i.e. Tantalum oxide, has be

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Andreas Bauer,Bj?rn Bloching,Alan Mitchellmponent library is developed, and IC layout is designed. An experimental sample of microwave chaotic source with bipolar transistor as the active element is fabricated with 0.25-.m SiGe process. The system demonstrates generation of ultrawideband chaotic oscillations of 3–7?GHz frequency range. Resu

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做事過頭

https://doi.org/10.1007/978-3-662-01436-3tion depends on the actual network structure. This is a setting of fundamental relevance for neuronal culture development, for which often power law characteristics and indications of a critical state are found. Investigating an extremely simple instance of this computational paradigm of adaptive ne

Constant

https://doi.org/10.1007/978-3-662-12535-9pervised data processing. An essential analysis step is the identification of groups of similar data, or ‘clusters’, in noisy high-dimensional data spaces, as this permits to perform some analysis steps at the group level. Popular clustering algorithms introduce an undesired cluster shape bias, requ

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