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Efficient Self-Consistent Learning of Gate Set Pauli Noise

Senrui Chen ^1,2,*, Zhihan Zhang³, Liang Jiang ¹, and Steven T. Flammia ^4,5

¹Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, USA
²Institute for Quantum Information and Matter, California Institute of Technology, Pasadena, California, USA
³Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing 100084, China
⁴Department of Computer Science, Virginia Tech, Alexandria, Virginia, USA
⁵Phasecraft Inc., Washington, DC, USA

^*Contact author: csenrui@gmail.com

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Articles Citing

Efficient Self-Consistent Learning of Gate Set Pauli Noise

Fermionic Averaged Circuit Eigenvalue Sampling

Disambiguating Pauli Noise in Quantum Computers

Universal Sample Complexity Bounds in Quantum Learning Theory via Fisher Information Matrix

Multilayer cycle benchmarking for high-accuracy error characterization

Mitigating errors in state preparation and measurement with noncomputational states

Correcting non-Pauli noise with detector error models estimated from syndrome measurements

Near-term fermionic simulation with subspace noise tailored quantum error mitigation

Entanglement-enhanced learning of quantum processes at scale

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