Clapton: Clifford-Assisted Problem Transformation for Error Mitigation in Variational Quantum Algorithms
Lennart Maximilian Seifert, Siddharth Dangwal, Frederic T. Chong,, Gokul Subramanian Ravi

TL;DR
Clapton is a novel error mitigation method for variational quantum algorithms that transforms problem Hamiltonians using classically estimated good states and noise models, significantly improving solution accuracy on noisy quantum devices.
Contribution
It introduces Clapton, a new framework that enhances VQA accuracy by applying Hamiltonian transformations based on classical estimates and noise modeling.
Findings
Achieves up to 13.3x improvement over baseline in VQA accuracy.
Effectively mitigates noise impact on quantum solutions.
Demonstrates benefits across physics and chemistry applications.
Abstract
Variational quantum algorithms (VQAs) show potential for quantum advantage in the near term of quantum computing, but demand a level of accuracy that surpasses the current capabilities of NISQ devices. To systematically mitigate the impact of quantum device error on VQAs, we propose Clapton: Clifford-Assisted Problem Transformation for Error Mitigation in Variational Quantum Algorithms. Clapton leverages classically estimated good quantum states for a given VQA problem, classical simulable models of device noise, and the variational principle for VQAs. It applies transformations on the VQA problem's Hamiltonian to lower the energy estimates of known good VQA states in the presence of the modeled device noise. The Clapton hypothesis is that as long as the known good states of the VQA problem are close to the problem's ideal ground state and the device noise modeling is reasonably…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture
