Efficient compressed database of equilibrated configurations of ring-linear polymer blends for MD simulations

Katsumi Hagita, Takahiro Murashima, Masao Ogino, Manabu Omiya, Kenji Ono, Tetsuo Deguchi, Hiroshi Jinnai, Toshihiro Kawakatsu

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

To effectively archive configuration data during molecular dynamics (MD) simulations of polymer systems, we present an efficient compression method with good numerical accuracy that preserves the topology of ring-linear polymer blends. To compress the fraction of floating-point data, we used the Jointed Hierarchical Precision Compression Number - Data Format (JHPCN-DF) method to apply zero padding for the tailing fraction bits, which did not affect the numerical accuracy, then compressed the data with Huffman coding. We also provided a dataset of well-equilibrated configurations of MD simulations for ring-linear polymer blends with various lengths of linear and ring polymers, including ring complexes composed of multiple rings such as polycatenane. We executed 109 MD steps to obtain 150 equilibrated configurations. The combination of JHPCN-DF and SZ compression achieved the best compression ratio for all cases. Therefore, the proposed method enables efficient archiving of MD trajectories. Moreover, the publicly available dataset of ring-linear polymer blends can be employed for studies of mathematical methods, including topology analysis and data compression, as well as MD simulations.

Original languageEnglish
Article number40
JournalScientific Data
Volume9
Issue number1
DOIs
Publication statusPublished - Dec 2022

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Information Systems
  • Education
  • Computer Science Applications
  • Statistics, Probability and Uncertainty
  • Library and Information Sciences

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