Speeding-up simulations of quantum algorithms for material science

About

Due to its intrinsic quantum mechanical nature, applications in chemistry and materials science are among the strongest candidates for algorithmic quantum advantage. However, to understand the problem size at the break-equal point between quantum and classical solutions, one requires large-scale simulations of quantum circuits. Here, we propose to develop and investigate an emulation approach to reduce the cost of simulating trotterized Hamiltonian evolution (a very common subroutine of many chemistry applications) by efficiently emulating multi-qubit rotations. To assess the practical impact and efficiency of our emulation strategy, we are conducting comprehensive benchmarks. These benchmarks compare the performance and resource utilization of multi-qubit rotation implementations against the single and double-qubit rotations. Following the evaluation, we aim to explore ways to integrate the emulation strategy into the Intel Quantum SDK or other quantum computing frameworks to enhance their efficacy and accessibility for quantum chemistry computations..

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