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Towards Scalable Quantum Simulation on Wafer-Scale Engines

SessionResearch, ACM SRC, and Doctoral Showcase Posters

DescriptionQuantum computing poses many benefits to the computing world, given its efficiency over classical computers in problem spaces. However, the high noise and low logical qubit count of contemporary noisy-intermediate-scale-quantum (NISQ) devices make the development and execution of quantum algorithms difficult. As such, developers and researchers have used classical simulation to prototype and validate their algorithms, often utilizing specialized classical hardware such as GPUs and FPGAs for their parallelization capabilities. We propose an optimized and scalable method for quantum simulation using the complex general matrix-vector product (GEMV) operation on the Cerebras wafer-scale engine (WSE) architecture. We experimentally determine the scalability of our method for differing qubit counts. Finally, we demonstrate viability and scalability by simulating practical quantum image processing circuits using our method.

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