Nature Computational Science is a Transformative Journal; authors can publish using the traditional publishing route OR via immediate gold Open Access.

Our Open Access option complies with funder and institutional requirements.

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    • Compressing scientific data is essential to save on storage space, but doing so effectively while ensuring that the conclusions from the data are not affected remains a challenging task. A recent paper proposes a new method to identify numerical noise from floating-point atmospheric data, which can lead to a more effective compression.

      • Dorit M. Hammerling
      • Allison H. Baker
      News & Views
    • Quantum defects in two-dimensional materials offer promises for the next-generation quantum information technology. However, the rational design of these defects faces challenges, and thus, requires the development of advanced theoretical and computational models.

      • Yuan Ping
      • Tyler J. Smart
      Review Article
    • Mobile-phone data reveal a cognitive strategy in human navigation and motivate the development of a new route planning model, with potential implications for traffic forecasting and transportation planning.

      • Laura Alessandretti
      News & Views
    • Finding a parameter that can accurately identify the order–disorder phase transition, especially for complex physical systems with high-dimensional configurational space, is a challenging task. Recent work proposes a machine learning approach to effectively tackle this challenge.

      • Evert van Nieuwenburg
      News & Views
    • An efficient parallelization technique for tensor network contraction, developed by a careful balance between memory requirement and computational time, speeds up classical simulation of quantum computers.

      • Jordi Tura
      News & Views