Discover How BQP's Quantum Assisted-PINN Algorithm Cuts Training Time, Cost, and Complexity

BQPhy's QCFD algorithm, Classiq’s compiler and NVIDIA GPU simulators enabled 100× circuit-depth reduction and successful scaling to the 2D Poisson equation for quantum-accelerated PDE solving.

QA-PINN achieved a 20% parameter reduction and cut training time from 85 hours to 3.5 hours using NVIDIA’s CUDA-Q simulator—enabling faster, scalable CFD experimentation.

Fuel-efficient, constraint-aware flight paths across ascent, hover, and descent