Memristor Hardware Accelerator of Quantum Computations

Abstract

Quantum computing and quantum computers are a major part of the second quantum revolution. Existing quantum algorithms can natively solve complex problems, such as the prime number factorization and searching of unstructured databases, in a fast and efficient way. The main obstacle towards building large and efficient quantum computers is decoherence, which produces errors that have to be continuously corrected using quantum error correcting codes. Beyond the realisation of quantum computing systems with actual quantum hardware, quantum algorithms have been developed based on quantum logic gates that can be described and utilised by classical computers and proper interfaces based on linear algebra operations. Furthermore, memristive grids have been proposed as novel nanoscale and low-power hardware accelerators for the time-consuming matrix-vector multiplication and tensor products. In this work, given that for quantum computations simulation, the matrix-vector multiplication is the dominant algebraic operation, we utilize the unprecedented characteristics of memristive grids to implement circuit-level quantum computations. Since all quantum computations can be mapped to quantum circuits, memristive grids can also be used as efficient quantum simulators, as classical/quantum interfaces and also as accelerators in mixed classical-quantum computing systems.