Workshops Archive

TUSQ: Tracking, Uncomputation, and Sampling for Noisy Quantum Simulation

Workshop: WHPC: Building Community, Building Careers

Authors: Tina Oberoi (University of Chicago)

Abstract: Quantum computers have grown rapidly, enabling execution of complex quantum circuits. However, for most researchers, access to compute time on quantum hardware is limited. Thus we need to build simulators that mimic execution of quantum circuits on noisy quantum hardware efficiently.

Here, we propose TUSQ, that can perform noisy simulation of up to 30-qubit Adder circuits on single A100 GPU in lessthan 820seconds. To represent the stochastic noisy channels, we average the output of multiple quantum circuits with fixed noisy gates sampled from channels. This leads to increase in circuit overhead, which slows down the simulation. To eliminate this overhead, TUSQ uses two modules: the \textit{Error Characterization} (ECM), and the Tree-based Execution} (TEM).

The ECM tracks number of unique circuit executions to accurately represent noise. This is followed by TEM, which reuses computation across reduced circuits. We evaluate and report average speedup of $52.5\times$ and $12.53\times$ over Qiskit and CUDA-Q.

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