Automotive & Aerospace
Quantum computing addresses engineering optimization challenges in aerodynamics, fleet management, and satellite systems — problems where the search space is too large for classical solvers.Computational Fluid Dynamics (Q-CFD)
Simulating fluid flow around vehicles is computationally intensive. Quantum CFD accelerates aerodynamics simulations, enabling engineers to rapidly analyze and optimize vehicle design for drag reduction and fuel efficiency.Quantum Computation of Fluid Dynamics
Quantum-accelerated CFD for vehicle aerodynamics and turbulence modeling. Significant speedup over classical numerical methods.
Traffic Optimization
Urban traffic flow optimization modeled as a constrained quadratic problem. Minimizes congestion and travel time across road networks by finding optimal signal timing and routing assignments.Traffic Flow Optimization
CQM-based traffic optimization. Reduces average travel time and network congestion through quantum-optimized signal coordination.
EV Charging Station Placement
Optimal placement of electric vehicle charging infrastructure using quantum annealing. Maximizes coverage and accessibility while minimizing installation costs under geographic and demand constraints.Placement of EV Charging Stations
User- and destination-based location model for EV charging stations, formulated as a QUBO.
Aircraft Loading Optimization
Optimal cargo and passenger load distribution for aircraft, ensuring weight balance constraints while maximizing capacity utilization. Based on the Airbus Quantum Computing Challenge.Aircraft Loading Optimization
Airbus QCC Problem n°5: quantum optimization of aircraft weight and balance under structural and safety constraints.
Satellite Constellation Scheduling
Optimal scheduling of satellite observation tasks across a constellation, formulated as a weighted k-clique problem. Maximizes coverage and minimizes scheduling conflicts.Quantum Satellite Positioning
Heterogeneous quantum computing for satellite constellation optimization. Solves the weighted K-Clique problem for task scheduling.