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- W4330340015 abstract "Quantum computing has potential to provide exponential speedups over classical computing for many important applications. However, today's quantum computers are in their early stages, and hardware quality issues hinder the scale of program execution. Benchmarking and simulation of quantum circuits on classical computers is therefore essential to advance the understanding of how quantum computers and programs operate, enabling both algorithm discovery that leads to high-impact quantum computation and engineering improvements that deliver to more powerful quantum systems. Unfortunately, the nature of quantum information causes simulation complexity to scale exponentially with problem size. In this paper, we debut Super.tech's SuperSim framework, a new approach for high fidelity and scalable quantum circuit simulation. SuperSim employs two key techniques for accelerated quantum circuit simulation: Clifford-based simulation and circuit cutting. Through the isolation of Clifford subcircuit fragments within a larger non-Clifford circuit, resource-efficient Clifford simulation can be invoked, leading to significant reductions in runtime. After fragments are independently executed, circuit cutting and recombination procedures allow the final output of the original circuit to be reconstructed from fragment execution results. Through the combination of these two state-of-art techniques, SuperSim is a product for quantum practitioners that allows quantum circuit evaluation to scale beyond the frontiers of current simulators. Our results show that Clifford-based circuit cutting accelerates the simulation of near-Clifford circuits, allowing 100s of qubits to be evaluated with modest runtimes." @default.
- W4330340015 created "2023-03-22" @default.
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- W4330340015 date "2023-03-19" @default.
- W4330340015 modified "2023-09-27" @default.
- W4330340015 title "Clifford-based Circuit Cutting for Quantum Simulation" @default.
- W4330340015 doi "https://doi.org/10.48550/arxiv.2303.10788" @default.
- W4330340015 hasPublicationYear "2023" @default.
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