Soft matter is omnipresent in a wide spectrum of scientific disciplines, from biology and medicine to materials science andchemical industrial applications. A characteristic feature of soft matter is that phenomena of interest typically occur on mesoscopic length-scales—ranging from nano- to micrometers—and at energyscales comparable to the thermal energy, which implies high sensitivity to external fields and ubiquitous and significantnon-equilibrium phenomena. This particularly applies to active biological systems, which are able to perform directed motion supported by an internal machinery or external fields. Two aspects are of paramount importance for such systems: On the one hand, they are typical exposed to crowded and hence viscoelastic environments [1], and, on the other hand, hydrodynamic interactions determine their motion and swarming behavior [2-4].

Due to the complexity of the systems, simulations play a particularly important role in soft matter research. The systems are challenging for conventional simulation techniques because of the disparate time, length, and energy scales, and novel simulation techniques are required to be able  to access the relevant scales. 

Moreover, hydrodynamic interactions have to be taken into account adequately. Considerable effort has been devoted to the development of mesoscale simulation methods such as Dissipative Particle Dynamics (DPD) [5,6], Lattice-Boltzmann (LB) [7,8], and Multiparticle Collision Dynamics (MPC) (or Stochastic Rotation Dynamics (SRD)) [9-11] to resolve the scale problems of soft matter systems. By now, the various methods are well established and are applied to a broad spectrum of problems, with the goal to achieve insight into the mechanisms which lead to the formation of the mesoscopic and hierarchical structures originating from a large number of internal degrees of freedom of the constituents.