As a first experiment, we employ SwarmCG to calibrate the bonded parameters in building blocks of PC lipid models using Representation 1 (Fig. ), including in the training set lipids spanning tails of various lengths and degrees of unsaturation. The hypothesis motivating this CG representation is that mapping the lipid tails as precisely as possible, using regular beads to represent exactly 4 heavy atoms and small beads to represent exactly 3 heavy atoms, may allow an enhanced description of their flexibility and dynamics (n.b. exclusively regular beads were used to represent lipid tails thus far and Martini 3.0.0 4 offers well-calibrated smaller beads). We optimize model parameters by iteratively simulating 9 different patches of lamellar bilayers, having each of the 8 lipid types simulated in the liquid phase and only the DPPC bilayer simulated also in the tilted gel phase (Lβ') at 293K. We calibrate equilibrium values and force constants for all bonds and all angles defined in the lipid models, totaling 77 parameters across 16 bond types and 27 angle types (Fig. , equilibrium values remain set to 180 degrees for 9 angle types). The swarm of particles is initialized randomly within the 77-dimensional search space, except for the first particle that is provided with knowledge from AA-mapped MD simulations (initialized using average equilibrium values computed for all bond and angle types) and from previous Martini lipid models (initialized within relevant ranges of force constants). The steady decrease of the loss (Fig. : green curve) indicates the bonded parameters of the models are adapted successfully and allow approaching the objectives, until the optimization converges at swarm iteration 29. At convergence, the models overall correctly reproduce the APL and Dʜʜ experimental measurements defined as target (Fig. : yellow and blue curves converging towards reference black line, set to 0) and only the Dʜʜ values for DSPC and PDPC in the liquid phase remain meaningfully improvable (n.b. here we calculate the phosphate-to-phosphate bilayer thickness to approximate the Dʜʜ). This is also visible when calculating the loss separately for each simulation (Fig. : grey curves), which additionally indicates that fitting the objectives is harder for DSPC at 333K than it is for PDPC at 303K (Fig. : grey curves remain over green curves) in the context of the modeling choices of this experiment (CG representation, composition of the training set, etc.). The OT-B distances otherwise are minimized effectively, indicating that the structural features present in the reference AA-mapped MD trajectories are overall well reproduced in the CG descriptions of the systems (Figs. ). In terms of computational time, here the refinement of 77 bonded parameters of the lipid models using 9 informative simulations required 15 days (wall-clock time) to reach convergence (39 swarm iterations) using 27 particles in the swarm and using 64 CPU cores (each CG simulation running on a single CPU core, scaling horizontally by parallelizing the swarm of particles on an inexpensive CPU machine).