2018/04/21 by Mehmet Süzen, Süzen, Mehmet
Chemistry · Computer Science · Physics and Astronomy · #Advanced Physical and Chemical Molecular Interactions #Computational Physics (physics.comp-ph) #FOS: Physical sciences #Parallel Computing and Optimization Techniques #Scientific Research and Discoveries #physics.comp-ph
paper · pdf · doi:10.48550/arxiv.1804.09781
5 pages, 2 figures
arxiv created 2018/04/21 · openalex publication_date 2018/04/21 · arxiv updated 2018/04/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Algorithms for rare event complex systems simulations are proposed. Compressed Sensing (CS) has \it revolutionized our understanding of limits in signal recovery and has forced us to re-define Shannon-Nyquist sampling theorem for sparse recovery. A formalism to reconstruct trajectories and transition paths via CS is illustrated as proposed algorithms. The implication of under-sampling is quite important. This formalism could increase the tractable time-scales \it immensely for simulation of statistical mechanical systems and rare event simulations. While, long time-scales are known to be a major hurdle and a challenge for realistic complex simulations for rare events. The outline of how to implement, test and possible challenges on the proposed approach are discussed in detail.