High precision framework for chaos many-body engine

In this paper we present a C# 4.0 high precision framework for simulation of relativistic many-body systems. In order to benefit from the, previously developed, chaos analysis instruments, all new modules were integrated with Chaos Many-Body Engine (Grossu et al. 2010, 2013). As a direct application, we used 46 digits precision for analyzing the “Butterfly Effect” of the gravitational force in a specific relativistic nuclear collision toy-model. Program summary Program title: Chaos Many-Body Engine v04.1 Catalogue identifier: AEGH_v4_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEGH_v4_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Microsoft Public License (Ms-PL) No. of lines in distributed program, including test data, etc.: 307938 No. of bytes in distributed program, including test data, etc.: 11953299 Distribution format: tar.gz Programming language: Visual C# Express 2010. Computer: PC. Operating system:  .Net Framework 4.0 running on MS Windows. RAM: 100 Megabytes Classification: 6.2, 6.5. External routines: BigRational structure provided by Microsoft Does the new version supersede the previous version?: yes Nature of problem: high precision simulation of relativistic many-body systems. Solution method: high precision calculations based on BigInteger .Net Framework 4.0 new feature. Reasons for new version: development of a high precision framework Summary of revisions: •• high precision framework based on the new BigInteger .Net Framework 4.0 structure •• high precision relativistic many-body engine •• concrete application: using 46 digit precision for analyzing the gravitational Butterfly Effect in a specific relativistic nuclear collision toy-model •• CMBE Reactions Module Bug Correction: in the particular case of two identical particles head-on collision, reactions were not treated in earlier versions of CMBE. •• Chaos Analysis: implementation of a new measure “Average Y” for computing the average of any function loaded in this module. •• Chaos Analysis: implementation of the phase space distance between two many-body systems, as a function of time. •• Chaos Analysis: Implementation of a decimal version of the Chaos Analysis module. •• Chaos Analysis: Implementation of some usual relativistic formulas for facilitating processing of Monte Carlo log files (Analysis∖∖Relativistic Formulas XLS). Additional comments: XCopy deployment strategy. Running time: Quadratic complexity, around 2 h for one C+C event, 50 Fm/c, on a dual core @ 2.0 GHz CPU