Grand challenges in computational physics

Three types of computational soft-matter problems revisited, an own-selection-based opinion

“…PE: The simulations can first be run safely on standard computers with preferred compilers, the computers being equipped with GPU units, possibly assimilated with CUDA environment. More atomisitic detail [1,2], unavoidable when embarking on biomolecule's folding events, can be tested by means of, e.g., Yasara software, or if really needed, in allatom framework. Or, predictions toward molecule's conformational changes can be made with popular CASP tests, preceding other attempts for probing some mutations in molecule's configuration subspace [14].…”

“…As addressed by Klingenberg [2] discretized mathematics and computer science have in last decades extensively developed their tools that virtually serve the (bio)physicists to be adopted within their dedicated areas of interests. Yet, a simple random-generator based Monte Carlo method (say, in Java) after being naturally applied to certain long-existing probelms, such as DLA/diffusion limited aggregation or percolation (also, Ising magnet) require a good basic knowledge for successful realization [3].…”

Grand challenges in computational physics

“…Furthermore, as my co-editor, C. Klingenberg, noted in his "grand challenges in computational physics" article (Klingenberg, 2013) the applicability of computational has changed: from mere validation to an all encompassing role.…”