Multiscale passive scalar turbulence in a compressed subspace via tensor trains

Stefano Pisoni; Egor Tiunov; Chiara Calascibetta

Multiscale passive scalar turbulence in a compressed subspace via tensor trains

Fluid Dynamics 2026-07-31 v1 Computational Physics

Authors: Stefano Pisoni , Egor Tiunov , Chiara Calascibetta

Abstract

Capturing the multiscale statistics of turbulence in compressed form remains a central challenge for reduced-order modeling. We introduce a hybrid Tensor Train (TT) approach for a highly intermittent passive scalar. The hybrid TT matches Galerkin, wavelet, and standard TT decompositions for the structure functions while improving the representation of intermittent, non-Gaussian fluctuations. These results open a route toward evolving the linear dynamics of passive scalars directly in compressed tensor form, with potential applications to quantum algorithms for fluid transport.

Keywords

tensor trains passive scalar turbulence reduced-order modeling multiscale statistics intermittency

Cite

@article{arxiv.2608.00194,
  title  = {Multiscale passive scalar turbulence in a compressed subspace via tensor trains},
  author = {Stefano Pisoni and Egor Tiunov and Chiara Calascibetta},
  journal= {arXiv preprint arXiv:2608.00194},
  year   = {2026}
}