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Optical Manipulation, Transport and Storage of Spin Coherence in Semiconductors

Chapter
Part of the NanoScience and Technology book series (NANO)

Abstract

The drive to build a framework for coherent semiconductor spintronic devices provides a strong motivation for understanding the coherent evolution of spin states in semiconductors [1,2]. The fundamental aim in this context is to discover regimes in which carefully prepared quantum states based upon spin can evolve coherently long enough to allow the storage, manipulation and transport of quantum information in devices. Such devices might exploit, for instance, the interference between two coherently-occupied spin states whose time variation occurs at a frequency ΔE/h, where ΔE is their energy separation. Since typical spin splittings in semiconductors are in the range of meV, the rapidly varying oscillations of a classical observable such as the spin orientation (magnetization) can occur at GHz-THz frequencies, providing the basis for ultrafast devices. Another possibility is that this quantum interference may actually be used as part of a calculation within the context of quantum computing algorithms [3]. It is hence crucial to develop experimental tools that probe spin coherence in semiconductors and that allow one to map out schemes for its manipulation, storage and transport. The previous chapter formulated the theoretical foundations underlying coherent spin dynamical phenomena in semiconductors and introduced specific mechanisms that may be responsible for spin relaxation and spin decoherence, pointing out the important physical distinctions between longitudinal and transverse spin relaxation times (T 1 and T 2, respectively) [4]. We note that it is the latter timescale that is of direct relevance to coherent spin devices and hence we focus on experimental techniques that probe the transverse spin relaxation time in semiconductors.

Keywords

Quantum Well Spin Polarization Pump Pulse Faraday Rotation Dynamic Nuclear Polarization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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