Non-zero noise extrapolation: accurately simulating noisy quantum circuits with tensor networks
Anthony P. Thompson, Arie Soeteman, Chris Cade, and Ido Niesen

TL;DR
This paper introduces a non-zero noise extrapolation method that enhances tensor network simulations of noisy quantum circuits, enabling accurate modeling in the low-noise regime crucial for quantum error correction.
Contribution
The authors develop a novel extrapolation technique that improves tensor network simulation accuracy for high-fidelity quantum circuits by leveraging added noise and subsequent extrapolation.
Findings
Method significantly improves simulation accuracy in low-noise regimes
Allows simulation of large qubit systems under generic noise models
Retains tensor network efficiency for high-fidelity quantum circuits
Abstract
Understanding the effects of noise on quantum computations is fundamental to the development of quantum hardware and quantum algorithms. Simulation tools are essential for quantitatively modelling these effects, yet unless artificial restrictions are placed on the circuit or noise model, accurately modelling noisy quantum computations is an extremely challenging task due to unfavourable scaling of required computational resources. Tensor network methods offer a viable solution for simulating computations that generate limited entanglement or that have noise models which yield low gate fidelities. However, in the most interesting regime of entangling circuits (with high gate fidelities) relevant for error correction and mitigation tensor network simulations often achieve poor accuracy. In this work we develop and numerically test a method for significantly improving the accuracy of…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Computational Physics and Python Applications · Quantum and electron transport phenomena
