Grover's Oracle for the Shortest Vector Problem and Its Application in Hybrid Classical–Quantum Solvers

Finding the shortest vector in a lattice is a problem that is believed to be hard both for classical and quantum computers. Many major postquantum secure cryptosystems base their security on the hardness of the shortest vector problem (SVP) (Moody, 2023). Finding the best classical, quantum, or hybrid classical–quantum algorithms for the SVP is necessary to select cryptosystem parameters that offer a sufficient level of security. Grover's search quantum algorithm provides a generic quadratic speedup, given access to an oracle implementing some function, which describes when a solution is found. In this article, we provide concrete implementation of such an oracle for the SVP. We define the circuit and evaluate costs in terms of the number of qubits, the number of gates, depth, and T-quantum cost. We then analyze how to combine Grover's quantum search for small SVP instances with state-of-the-art classical solvers that use well-known algorithms, such as the block Korkine Zolotorev (Schnorr and Euchner, 1994), where the former is used as a subroutine. This could enable solving larger instances of SVP with higher probability than classical state-of-the-art records, but still very far from posing any threat to cryptosystems being considered for standardization. Depending on the technology available, there is a spectrum of tradeoffs in creating this combination.