6 Jun 2001 | Réka Albert and Albert-László Barabási
The article "Statistical Mechanics of Complex Networks" by Réka Albert and Albert-László Barabási reviews recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. Complex networks, which describe a wide range of systems in nature and society, such as the cell, chemical networks, and the Internet, are increasingly recognized to be governed by robust organizing principles rather than random graphs. The authors discuss empirical data that motivated the recent interest in networks, including the World Wide Web, power and neural networks, and protein folding. They cover key models and analytical tools, such as random graphs, small-world networks, and scale-free networks, and explore the interplay between topology and network robustness against failures and attacks. The article also delves into the Erdős-Rényi model, percolation theory, generalized random graphs, and the dynamics of evolving networks, providing a comprehensive overview of the theoretical developments and empirical findings in the field.The article "Statistical Mechanics of Complex Networks" by Réka Albert and Albert-László Barabási reviews recent advances in the field of complex networks, focusing on the statistical mechanics of network topology and dynamics. Complex networks, which describe a wide range of systems in nature and society, such as the cell, chemical networks, and the Internet, are increasingly recognized to be governed by robust organizing principles rather than random graphs. The authors discuss empirical data that motivated the recent interest in networks, including the World Wide Web, power and neural networks, and protein folding. They cover key models and analytical tools, such as random graphs, small-world networks, and scale-free networks, and explore the interplay between topology and network robustness against failures and attacks. The article also delves into the Erdős-Rényi model, percolation theory, generalized random graphs, and the dynamics of evolving networks, providing a comprehensive overview of the theoretical developments and empirical findings in the field.