A depiction of a neural network formed by light scattering through a disordered medium.

June issue now live!

Our June issue includes a Perspective on using mobility data for epidemic modeling, a large-scale nonlinear photonic neural system, a call for papers in computational social science, and much more!

Announcements

  • A depiction of the brain using neurons and computing hardware.

    In this cross-journal collection, we aim to bring together cutting-edge research on neuromorphic architectures and hardware, computing, and algorithms, as well as related applications. We also invite commentaries from experts in the field.

    Open for submissions
  • A physical, real city overlaid with a representation of a digital city, which includes three-dimensional depictions of buildings.

    There has been a growing interest and enthusiasm in using digital twins to accelerate scientific discovery and to help researchers and stakeholders with critical decision-making tasks. Check out our Focus that highlights the state of the art, challenges, and opportunities in the development and use of digital twins across different domains.

  • An image that echoes the SDG logo and integrates the idea of analysis of data from the various goals.

    The year 2023 marks the mid-point of the 15-year period envisaged to achieve the Sustainable Development Goals. In this Nature Portfolio Collection, you will find studies across different journals that assess progress or that showcase interventions that have made a difference. We also welcome submissions of studies framed in a similar way.

    Open for submissions

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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  • In this study, the authors present a virtual node graph neural network to enable the prediction of material properties with variable output dimensions. This method offers fast and accurate predictions of phonon band structures in complex solids.

    • Ryotaro Okabe
    • Abhijatmedhi Chotrattanapituk
    • Mingda Li
    Article
  • Nonlinear optical computations have been essential yet challenging for developing optical neural networks with appreciable expressivity. In this paper, light scattering is combined with optical nonlinearity to empower a high-performance, large-scale nonlinear photonic neural system.

    • Hao Wang
    • Jianqi Hu
    • Sylvain Gigan
    Article
  • Human mobility research intersects with various disciplines, with profound implications for urban planning, transportation engineering, public health, disaster management, and economic analysis. Here, we discuss the urgent need for open and standardized datasets in the field, including current challenges and lessons from other computational science domains, and propose collaborative efforts to enhance the validity and reproducibility of human mobility research.

    • Takahiro Yabe
    • Massimiliano Luca
    • Esteban Moro
    Comment
  • Software is much more than just code. It is time to confront the complexity of licenses, uses, governance, infrastructure and other facets of software in science. Their influence is ubiquitous yet overlooked.

    • Alexandre Hocquet
    • Frédéric Wieber
    • Stefan Böschen
    Comment
  • As machine learning models are becoming mainstream tools for molecular and materials research, there is an urgent need to improve the nature, quality, and accessibility of atomistic data. In turn, there are opportunities for a new generation of generally applicable datasets and distillable models.

    • Chiheb Ben Mahmoud
    • John L. A. Gardner
    • Volker L. Deringer
    Comment