Towards the quantum computing of turbulence

Accurate numerical simulations of turbulent flows in practical applications are always difficult. A recent quantum-inspired computational method improves the way to account for cross-scale correlations in turbulence and further sheds light on the development of quantum computational algorithms for efficient turbulence simulations.

Turbulent fluid (i.e. gas and liquid) flows are ubiquitous. Most of the flows around us, such as flows around cars and airplanes, inside pipelines and internal combustion engines, and atmospheric flows, are turbulent. Therefore, understanding and predicting turbulent flows plays a crucial role for our sustainable society through more energy-efficient design of industrial products as well as minimizing damage from natural disasters. In the long history of turbulence research, direct numerical simulation (DNS)1which numerically solves the equation governing fluid flows without using additional models, has significantly advanced our understanding of structure and nonlinear interactions in turbulent flows since the 1970s2.3. However, the DNS computational cost strongly depends on the Reynolds number (Re): the number of discrete points required is proportional to Re9/4 in three-dimensional space1. Since Re in practical applications is often very high (e.g., system-wide Re amounts to ~107-ten9 for aircraft and ships4), this makes DNS computation extremely expensive for practical applications, and in fact, DNS of the practical streams shown above (i.e. planes, ships, etc.) is still not feasible even with state-of-the-art supercomputers of the conventional type (i.e. digital computers). Therefore, if DNS can be run on quantum computers, it will make DNS possible for such practical applications. write in Computational science of natureNikita Gourianov et al.5 report a DNS-equivalent method suitable for quantum computing, inspired by an approach used in quantum multibody systems that can accurately handle entanglements with lower computational cost.

Sherry J. Basler