Physicists, when modelling physical systems with a large number of degrees of freedom, and statisticians, when performing data analysis, have developed their own concepts and methods for making the best' inference. But are these methods equivalent, or not? What is the state of the art in making inferences? The physicists want answers. More: neural computation demands a clearer understanding of how neural systems make inferences; the theory of chaotic nonlinear systems as applied to time series analysis could profit from the experience already booked by the statisticians; and finally, there is...
Physicists, when modelling physical systems with a large number of degrees of freedom, and statisticians, when performing data analysis, have develope...
Molecular dynamics is a well-established technique for simulating complex many-particle systems in many areas of physics, chemistry, and astrophysics. The huge computational requirements for simulations of large systems, especially with long-range forces, demand the use of massively parallel computers. Designing efficient algorithms for these problems is a highly non-trivial task.
This book contains the invited talks and abstracts presented at a conference by more than 100 researchers from various fields: computer science, solid state physics, high energy physics, polymers, biochemistry,...
Molecular dynamics is a well-established technique for simulating complex many-particle systems in many areas of physics, chemistry, and astrophysics....
