Researchers have developed InferQ, a new benchmark designed to evaluate the performance of relational database management systems (RDBMSs) in simulating quantum circuits. This benchmark generates a large dataset of diverse circuits and compiles their simulations into SQL queries, allowing for systematic research into query optimization and engine-level evaluation. Experiments show that RDBMSs can outperform traditional simulators like Qiskit Aer in memory usage for over half of the tested circuits. Furthermore, machine learning models trained on InferQ's extracted features can accurately predict when SQL-based simulation is preferable, enabling optimized simulator selection. AI
IMPACT Enables more efficient and data-driven selection of simulation tools for quantum computing research.
RANK_REASON The cluster contains a research paper introducing a new benchmark for evaluating quantum circuit simulation using database systems. [lever_c_demoted from research: ic=1 ai=0.7]
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