COOL: A code for Dynamic Monte Carlo Simulation of molecular dynamics

Abstract

Cool is a program to simulate evaporative and sympathetic cooling for a mixture of two gases co-trapped in an harmonic potential. The collisions involved are assumed to be exclusively elastic, and losses are due to evaporation from the trap. Each particle is followed individually in its trajectory, consequently properties such as spatial densities or energy distributions can be readily evaluated. The code can be used sequentially, by employing one output as input for another run. The code can be easily generalised to describe more complicated processes, such as the inclusion of inelastic collisions, or the possible presence of more than two species in the trap. New version program summary Program title: COOL Catalogue identifier: AEHJ_v2_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEHJ_v2_0.html Program obtainable from: CPC Program Library, Queenʼs University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 1 097 733 No. of bytes in distributed program, including test data, etc.: 18 425 722 Distribution format: tar.gz Programming language: C++ Computer: Desktop Operating system: Linux RAM: 500 Mbytes Classification: 16.7, 23 Catalogue identifier of previous version: AEHJ_v1_0 Journal reference of previous version: Comput. Phys. Comm. 182 (2011) 388 Does the new version supersede the previous version?: Yes Nature of problem: Simulation of the sympathetic process occurring for two molecular gases co-trapped in a deep optical trap. Solution method: The Direct Simulation Monte Carlo method exploits the decoupling, over a short time period, of the inter-particle interaction from the trapping potential. The particle dynamics is thus exclusively driven by the external optical field. The rare inter-particle collisions are considered with an acceptance/rejection mechanism, that is, by comparing a random number to the collisional probability defined in terms of the inter-particle cross section and centre-of-mass energy. All particles in the trap are individually simulated so that at each time step a number of useful quantities, such as the spatial densities or the energy distributions, can be readily evaluated. Reasons for new version: A number of issues made the old version very difficult to be ported on different architectures, and impossible to compile on Windows. Furthermore, the test runs results could only be replicated poorly, as a consequence of the simulations being very sensitive to the machine background noise. In practise, as the particles are simulated for billions and billions of steps, the consequence of a small difference in the initial conditions due to the finiteness of double precision real can have macroscopic effects in the output. This is not a problem in its own right, but a feature of such simulations. However, for sake of completeness we have introduced a quadruple precision version of the code which yields the same results independently of the software used to compile it, or the hardware architecture where the code is run. Summary of revisions: A number of bugs in the dynamic memory allocation have been detected and removed, mostly in the cool.cpp file. All files have been renamed with a .cpp ending, rather than .c++, to make them compatible with Windows. The Random Number Generator routine, which is the computational core of the algorithm, has been re-written in C++, and there is no need any longer for cross FORTRAN-C++ compilation. A quadruple precision version of the code is provided alongside the original double precision one. The makefile allows the user to choose which one to compile by setting the switch PRECISION to either double or quad. The source code and header files have been organised into directories to make the code file system look neater. Restrictions: The in-trap motion of the particles is treated classically. Running time: The running time is relatively short, 1–2 hours. However it is convenient to replicate each simulation several times with different initialisations of the random sequence.