The  Weizmann  Institute  of  Science
                  Faculty of Mathematics and Computer Science


                            Computer Science Seminar

                                   Dorit Ron



                                 will speak on


                 Optimal Derivation of Macroscopic Description
                  for Statistical Systems: Ising spin example

Abstract:
All simulations in statistical physics suffer from slow down which severly
increases with the size of the system.  We present a new general approach, the
Renormalization Multigrid (RMG), which combines ideas from the renormalization
group theory, developed in theoretical physics for treating critical systems,
with multigrid ideas developed in applied mathematics for solving partial
differential equations. The RMG generates a sequence of increasingly coarser
numerical descriptions of the simulated system. The systematic use of all
available information enables a controlled truncation error. Moreover, it is
``statistically optimal" in the sense that it calculates a macroscopic
observable to accuracy $E$ using only $O[1/(E*E)]$ random-number generations.

The RMG was first developed for the 2-dimensional Ising model as will be
described in details. However, the generality of the method makes it applicable
also to non-lattice problems including fluids, solids and macromolecules.

No physical background in assumed.





                      The lecture will take place in the 
                     Lecture Hall, Room 1, Ziskind Building
                          on Monday, January 17, 2000
                                    at 14:30