Quantum anomalous Hall effect (QAHE) is the zero-field version of the quantum Hall effect which shows dissipationless chiral edge electron transport and quantized Hall resistance without the help of external magnetic field. In this Dissertation, we study the growth of magnetic topological insulator (MTI) Cr-doped (BiSb)2Te3 thin film, which is the host of the QAH states, using molecular beam epitaxy. We report the first observation of QAHE in a milli-meter sized device with the thin film thickness beyond the two-dimension (2D) limit. In addition, by controlling the thin film thickness down to the 2D limit, we observe a metal-to-insulator transition behavior due to the hybridization effect introduced by the vertical quantum confinement.

We further investigate the temperature limiting factors of QAHE in the Cr-doped (BiSb)2Te3 system by studying the thickness and doping effects. We identify that for thin film thickness larger than 6 quintuple layers (QLs), the limiting factor is the overlap of Fermi level with the trivial bulk band. For thin film thickness equal to 6 QLs, weak ferromagnetism and pronounced superparamagnetism are the temperature limiting factors. However, modulation doping technique can significantly strengthen the ferromagnetism at this thickness. In addition, the metal-to-insulator transition behavior can also be tuned according to the doping profile of the thin film which can potentially affect the phase transition behavior in this material system.

To manipulate the QAH states, we investigate the heterogenous integration of the QAH insulator or TI with antiferromagnets. We first study the QAH insulator/Cr2O3 bilayer structure and realize the QAHE on a magnetically ordered system for the first time. We identify the positive exchange bias in this structure and discover the magnetic coupling between the two material systems using polarized neutron reflectometry (PNR). We then study the undoped TI/CrSe heterostructure and realize the antiferromagnet induced magnetic proximity effect in the TI layer confirmed by both PNR and X-ray magnetic dichroism techniques. We also discover the interface-dependent proximity behavior in the heterostructure that may help our understanding towards high temperature and functional QAH states.

Distributed sequential computing uses the collective memory of a network of workstations to reduce paging overhead. In contrast to the "page farm" approach, in which a stationary program remotely accesses data, distributed sequential computing moves the code to the data. In this paper, we show that mobile agents are the most natural and effective way to implement this approach. This is because mobile agents preserve the algorithmic integrity of sequential programs, while a message passing implementation requires a complete restructuring of the code.

The present study tested whether listeners hearing one form of a morpheme activate other forms of the same morpheme. Listeners performed lexical decisions while hearing Mandarin monosyllables; crucially, critical targets could be primed by related syllables that occurred 18–52 trials earlier (long-lag priming). The use of long-lag priming ensures that any facilitation effects are due to morphological relatedness and not to semantic or form relationships, which do not prime lexical decisions at long lags. Across three experiments (total N = 458), we consistently found that lexical decisions were primed when the same pronunciation of a morpheme occurred as prime and target (e.g., shiL – shiL) but were not primed when two different variants of the same morpheme occurred as prime and target (e.g., shiR – shiL, where both of these syllables are potential pronunciations of the same morpheme). In other words, we observed identity priming but not morphological priming, unlike other long-lag priming experiments, which almost invariably observe intramodal morphological priming if they test it. This surprising finding suggests that there are boundary conditions on the elicitation of long-lag morphological priming effects.

Message Passing ( MP) and Distributed Shared Memory (DSM) are the two most common approaches to distributed parallel computing. MP is difficult to use, whereas DSM is not scalable. Performance scalability and ease of programming can be achieved at the same time by using navigational programming (NavP). This approach combines the advantages of MP and DSM, and it balances convenience and flexibility. Similar to MP, NavP suggests to its programmers the principle of pivot-computes and hence is efficient and scalable. Like DSM, NavP supports incremental parallelization and shared variable programming and is therefore easy to use. The implementation and performance analysis of real-world algorithms, namely parallel Jacobi iteration and parallel Cholesky factorization, presented in this paper supports the claim that the NavP approach is better suited for general-purpose parallel distributed programming than either MP or DSM.