Abstract:    Nowadays, scientific researchers are an important kind of economic resources and critical sources of creative power in the development of economy and society. With the increasing intense competition in science and technology, not only the government of our country has focused on attracting scientific researchers all over the world and puts it at the national strategic level, but most of provinces of China also have make relative policies for attracting scientific researchers in the nationwide and worldwide to improve the ability of scientific and technological innovation. It follows that a great number of scientific researchers move to other provinces in our country. The discussion on these topics is of great significance to optimize the system of scientific researchers policies, guide provinces to make policies for attracting and retaining scientific researchers, and construct a good environment for innovation, so that it must be explored with great conviction.To give a more confident and quantitative result, this paper establishes the networked model of scientific researchers mobility between 34 provinces of China during the years from 2010 to 2017 according to the database of scientist In with the help of complex network. In detail, 34 provinces （including Hong Kong, Taiwan, Macao） are noted by nodes, directed scientific researchers flows are viewed as directed edges, and the number of mobile scientific researchers are abstracted into edge weights. According to the scientific researchers mobility network, it is straight-forward that a great number of scientific researchers entering into developed provinces and cities directly under the Center Government in China. From the power fitting functions for the cumulative in-degree probability distribution and the cumulative out-degree probability distribution the mobility network is scale-free from 2010 to 2017. According to the computing results of the entropies, it is obtained that the network of scientific researchers inter-provincial mobility in China is heterogeneous, which means that a small part of nodes (provinces) have great importance than others. To some extent, the scientific researchers mobility depends on these provinces, and the heterogeneity for scientific researchers mobility is not obvious. After calculating the in-out degree assortativity coefficient, we know that the provinces with larger amount of leaving scientific researchers also attracts larger amount of entering scientific researchers on average, and this phenomenon is very significant. Then, we mention that the node-betweenness centralities for the provinces are also uneven. Considering the above discussion based on the tools and concepts of complex network, the network of scientific researchers mobility is not balanced, which means that few of developed provinces or cities, such as Beijing, Shanghai, and Jiangsu, have a great number of scientific researchers emigrating and immigrating, but most of the other provinces have limited number of scientific researchers emigrating and immigrating. Except a small part of provinces, there exists a balance at different provinces between the number of emigrating scientific researchers and immigrating scientific researchers. Moreover, some developed provinces are the centralities of scientific researchers mobility for the provinces around them, so that these developed provinces can be viewed as "agencies". For the evolution with time, the scientific researchers mobility is relatively stable, but the difference of the number of emigrating scientific researchers between developed provinces and other provinces has becoming more obvious. The average distance of network models has become shorter and shorter, which follows that the most prominent character of scientific researchers inter-provincial mobility in these eight years is that more and more scientific researchers join in the mobility, and the mobility to other areas for scientific researchers has become more convenient.

Key words:  scientific researchers, inter-provincial mobility, complex network, evolution trend