Talk Python in Massive Quantum Physics Simulations


Quantum path-integral Monte Carlo algorithms allow to simulate the behaviour of a Bose gas of up to 100,000 particles in interaction [1]. Because of the nature of this physical system, in such a simulation, one both needs to handle very complex objects, and a time-efficient algorithm that is to run on computational clusters. Thus, Python+Cython gives the opportunity of both using very high-level objects such as sets and dictionaries, which allow, for example, to refer to a particle via its position instead of unphysical indices, and low-level operations for time-consuming tasks, such as the computation of the effect of the interaction. Our simulations therefore show that Python+Cython has become a real alternative to low-level programming languages used by most physicists, and also that Cython needs further development, in order to become a useful tool for a greater number of physicists.

[1]N. Navon, S. Piatecki, K. J. Günter, Trong Canh Nguyen, F. Chevy, W. Krauth, and C. Salomon, Dynamics and Thermodynamics of the Low-Temperature Strongly Interacting Bose Gas, arXiv:1103.4449v1 [cond-mat.quant-gas]
tagged by
no related entity