Abstract. Geometric integration is the numerical integration of a differential equation, while preserving one or more of its “geometric ” properties exactly, i.e. to within round-off error. Many of these geometric properties are of crucial importance in physical applications: preservation of energy, momentum, angular momentum, phase space volume, symmetries, time-reversal symmetry, symplectic structure and dissipation are examples. In this paper we present a survey of geometric numerical integration methods for ordinary differential equations. Our aim has been to make the review of use for both the novice and the more experienced practitioner interested in the new developments and directions of the past decade. To this end, the reader who is interested in reading up on detailed technicalities will be provided with numerous signposts to the relevant literature. Geometric Integrators for ODEs 2 1.

A broad class of partitioned differential equations with possible algebraic constraints is considered, including Hamiltonian and mechanical systems with holonomic constraints. For mechanical systems a formulation eliminating the Coriolis forces and closely related to the Euler-Lagrange equations is presented. A new class of integrators is defined: the super partitioned additive Runge-Kutta (SPARK) methods. This class is based on the partitioning of the system into different variables and on the splitting of the differential equations into different terms. A linear stability and convergence analysis of these methods is given. SPARK methods allowing the direct preservation of certain properties are characterized. Different structures and invariants are considered: the manifold of constraints, symplecticness, reversibility, contractivity, dilatation, energy, momentum, and quadratic invariants. With respect to linear stability and structure-preservation, the class of s-stage Lobatto IIIA-B-C-C* SPARK methods is of special interest. Controllable numerical damping can be introduced by the use of additional parameters. Some issues related to the implementation of a reversible variable stepsize strategy are discussed.

Impulse splitting, with this severity worsening with the outer timestep, \Deltat; Constant Extrapolation is generally unstable, but the disturbances do not grow with \Deltat. Thus, the stochastic extrapolative combination can counteract generic instabilities and largely alleviate resonances with a sufficiently strong Langevin heat-bath coupling (fl), estimates for which are derived here based on the fastest and slowest motion periods. These resonance results generally hold for nonlinear test systems: a water tetramer and solvated protein. Proposed related approaches such as Extrapolation /Correction and Midpoint Extrapolation only work better than Constant Extrapolation for timesteps less than Tmin=2. An effective extrapolative stochastic approach for biomolecules that balances long-timestep stability with good accuracy for the fast subsystem is then applied to a biomolecule using a three-class partitioning:

This paper explains the basic elements of an approach to physically-based modeling which is well suited for interactive use. It is simple, fast, and quite stable, and in its basic version the method does not require knowledge of advanced mathematical subjects (although it is based on a solid mathematical foundation). It allows for simulation of both cloth; soft and rigid bodies; and even articulated or constrained bodies using both forward and inverse kinematics. The algorithms were developed for IO Interactive‟s game Hitman: Codename 47. There, among other things, the physics system was responsible for the movement of cloth, plants, rigid bodies, and for making dead human bodies fall in unique ways depending on where they were hit, fully interacting with the environment (resulting in the press oxymoron “lifelike death animations”). The article also deals with subtleties like penetration test optimization and friction handling. 1

Abstract. The purpose of the present article is to compare different phase-space sampling methods, such as purely stochastic methods (Rejection method, Metropolized independence sampler, Importance Sampling), stochastically perturbed Molecular Dynamics (Hybrid Monte Carlo, Langevin Dynamics, Biased Random Walk), and purely deterministic methods (Nosé-Hoover chains, Nosé-Poincaré and Recursive Multiple Thermostats (RMT) methods). After recalling some theoretical convergence properties for the various methods, we provide some new convergence results for the Hybrid Monte Carlo scheme, requiring weaker (and easier to check) conditions than previously known conditions. We then turn to the numerical efficiency of the sampling schemes for a benchmark model of linear alkane molecules. In particular, the numerical distributions that are generated are compared in a systematic way, on the basis of some quantitative convergence indicators. 1991 Mathematics Subject Classification. 82B80, 37M25, 65C05, 65C40.

An important challenge in virtual environment applications is to steer virtual characters through complex and dynamic worlds. The characters should be able to plan their paths and move toward their desired locations, avoiding at the same time collisions with the environment and with other moving entities. In this paper we propose a general method for realistic path planning, the Indicative Route Method (irm). In the irm, a so-called indicative route determines a global route for the character, whereas a corridor around this route is used to handle a broad range of other path planning issues, such as avoiding characters and computing smooth paths. As we will show, our method can be used for real-time navigation of many moving characters in complicated environments. It is fast, flexible and generates believable paths.

This paper describes a Wrapper Generator for wrapping high performance legacy codes as Java/CORBA components for use in a distributed component-based problemsolving environment. Using the Wrapper Generator we have automatically wrapped an MPI-based legacy code as a single CORBA object, and implemented a problemsolving environment for molecular dynamic simulations. Performance comparisons between runs of the CORBA object and the original legacy code on a cluster of workstations and on a parallel computer are also presented.

The structural, dynamical, and thermodynamic properties of a model potassium channel are studied using molecular dynamics simulations. We use the recently unveiled protein structure for the KcsA potassium channel from Streptomyces lividans. Total and free energy profiles of potassium and sodium ions reveal a considerable preference for the larger potassium ions. The selectivity of the channel arises from its ability to completely solvate the potassium ions, but not the smaller sodium ions. Self-diffusion of water within the narrow selectivity filter is found to be reduced by an order of magnitude from bulk levels, whereas the wider hydrophobic section of the pore maintains near-bulk self-diffusion. Simulations examining multiple ion configurations suggest a two-ion channel. Ion diffusion is found to be reduced to # 1 /3 of bulk diffusion within the selectivity filter. The reduced ion mobility does not hinder the passage of ions, as permeation appears to be driven by Coulomb repulsion...

Scientific discovery can be accelerated through computation and visualization. This acceleration results from the synergy of expertise, computing tools and hardware for enabling high-performance computation, information science and visualization that is provided by a team of computation and visualization scientists collaborating in a peer-to-peer effort with the research scientists.

Molecular dynamics simulation is a class of applications that require reducing the execution time of fixed-size problems. This reduction in execution time is important to drug design and protein interaction studies. Many implementations of parallel molecular dynamics have been developed, but very little work has addressed issues related to the use of machines with 50,000 processors for modest-sized problems in the range of 50,000 atoms. Current massively parallel machines present a major obstacle to achieving good performance: communication overhead. In this paper we quantify the communication latency and network bandwidth necessary to achieve 30--40% efficiency on future message-passing machines with sizes on the order of tens of thousands of processors, for executing molecular dynamics problems with the same order of atoms. We derive an analytical model of a benchmark application that simulates a system of helium atom executing on the Intel Touchstone Delta using an interaction decom...