BxC is a cutting-edge synthetic turbulence algorithm, designed as an aiding tool in the study and understanding of turbulent phenomena. The generated synthetic fields boast an actual “look-and-feel” resemblance to turbulent fields, together with presenting the proper higher-order statistics.

Turbulence is a complex and ubiquitous phenomenon that plays a critical role in various scientific disciplines, from hydrodynamics to astrophysics. Its universal presence makes the study of turbulence essential for understanding the physical processes driving numerous phenomena. Traditional methods of simulating turbulence, such as Direct Numerical Simulation (DNS), can be extremely computationally intensive. Synthetic turbulence models offer a valid and efficient aiding tool, allowing to reach unprecedented resolutions with minimal computational resources. Synthetic turbulence is crucial for advancing the analysis of turbulent flows, serving as bridge between theoretical studies, physics-based simulations, and observational data.


Synthetic turbulence as a random painting (artwork made using the BxC code, and inspired from Chevillard’s expression) Time and RAM memory required to generate one 3D B field realization with a 40-logical-cores desktop, as a function of resolution and for various numerical precisions.

In the context of synthetic models, BxC stands out for its alternative approach. The name stands for magnetic field from multiplicative chaos, turbulence-related field of study that first inspired the foundations of the algorithm. The core idea behind the development of BxC is to have a general, versatile tool, not restricted to any specific application. Although it is primarily tuned to recreate plasma and astrophysical scenarios, its use can easily be extended to hydrodynamics applications as well. Such versatility practically translates in user-controlled parameters that allow for a full customization of the power spectrum, and user-controlled features such as structured background fields and anisotropy, which are characteristic of real physical scenarios. See the page Features for a more detailed explanation of BxC functionalities and visual examples.

Development team

BxC was developed at the Centre for mathematical Plasma Astrophysics at the KU Leuven, Belgium, under the supervision of Prof. Rony Keppens. The people involved in the development process are:

  • Dr. Jean-Baptiste Durrive (): creator of the code and development team
  • Drs. Daniela Maci (): main developer, web-page creator and users-support
  • Prof. Rony Keppens (): guidance
  • Prof. Fabio Bacchini (): guidance

F. Boulanger (BxB:ANR leader, ENS Paris), K. Ferrière (IRAP Toulouse) and P. Lesaffre (ENS Paris) also contributed to the elaboration of the model.

Why choose our model?

  • Innovative Algorithm: based on the idea of multiplicative chaos, the BxC algorithm is unique in the landscape of synthetic turbulence models resulting in realistically looking and statistically fitting properties.
  • User-Friendly Interface: BxC is fully implemented in Python, which makes it straightforward to use and run on laptops or desktops.
  • Reliable Support: the development team can easily be contacted and is available to help in case of need.