Our papers are the official record of our discoveries. They allow others to build on and apply our work. Each paper is the result of many months of research, so we make a special effort to make them clear, beautiful and inspirational, and publish them in leading journals.

  • Date
  • Subject
  • Theme
  • Journal
  • Citations
  • Altmetric
  • SNIP
  • Author
x2
  • Machine learning Calabi-Yau hypersurfaces

    AI-assisted maths

    DSYHY. He Physical Review D

    Calabi-Yau anomalies

    Unsupervised machine-learning of the Hodge numbers of Calabi-Yau hypersurfaces detects new patterns with an unexpected linear dependence.

  • Scale of non-locality for a system of n particles

    Particle physics

    STITI. Teimouri Arxiv

    Scale of non-locality

    The number of particles in a higher derivative theory of gravity relates to its effective mass scale, which signals the theory’s viability.