Towards large-scale ab initio Molecular Dynamics Simulation with Efficient Sampling-based Quantum Computing Algorithms

arXiv:2611.11084v1 Announce Type: new Abstract: Ab initio molecular dynamics (AIMD) requires the calculation of highly accurate electronic-structure energies and nuclear forces at every time step, which can quickly become computationally expensive. Sample-based quantum diagonalization offers a route to such calculations on quantum hardware, but its use in AIMD simulations has so far been limited to active spaces of about 20 qubits. In these spaces, exact diagonalization is tractable, and the quantum circuits are typically built from standard coupled-cluster amplitudes. Here, we introduce SqDRIFT-AIMD, which combines randomized sample-based Krylov quantum diagonalization (SqDRIFT) with analytical nuclear gradients.