Stroboscopic Multi-Exposure Motion Trajectory AI Image Prompt

16:9 layout: stroboscopic multi-exposure along curved trajectory | 5 phases overlapping with transparency decay | motion vectors mapped as tension lines input: [{argument name="movement" default="tennis serve"}] :: [{argument name="physics principle" default="kinetic chain transfer"}] :: [{argument name="activity context" default="professional circuit"}] semantic_inference_chain: infer(phase_1 from [dynamic_process].initiation_state) infer(phase_3 from [principle].peak_force_or_efficiency) infer(phase_5 from [context].resolution_or_impact) infer(trajectory_curve from historical_motion_capture + physics_simulation) weighted_architecture: phase_n::1.0 * transparency_decay::0.82^(n-1) + (motion_blur_gradient::0.9 ^ stress_amplification::1.15) - (static_pose::0.7 + cartoon_speed_lines::0.8) spatial_law: trajectory follows cubic bezier | phase spacing compresses at peak force | negative space expands post-impact material_optics: phase 1: crisp edge, full opacity | phase 3: directional blur, subsurface stress glow | phase 5: fragmentation particles, atmospheric diffusion | surface shows micro-deformation at contact points typography: phase markers use technical indexing | force vectors labeled with newton/pascal values | baseline follows trajectory tangent negative: no anime speed lines, no frozen action clichés, no stock sports photography, no neon trails, no flat overlays