Lectures & Tutorials
Introduction to Noise and Quantum Error Mitigation, Lecture 2
Part of the series Intro to Noise Mitigation (Summer School 2024); cited as one entry below.
Picks up from an introductory lecture and works through probabilistic error cancellation (PEC) in detail: canceling noise with quasi-probability sampling, the sampling overhead γ, and the statistics of estimating expectation values from finite shots. It then turns to learning the noise of real devices with sparse Pauli-Lindblad models, Ising-model experiments, and hardware outlook, with bonus derivations in superoperator notation and comprehension questions.
- PEC on one qubit: quasi-probabilities, signs, and the sampling overhead γ
- Empirical mean as an unbiased estimator, its variance, and error bars and confidence
- Quasi-probability decompositions that put PEC, circuit cutting and classical simulation on the same footing
- Optional appendix: stochastic Pauli channels and a full PEC derivation with super bra-ket notation
Summary and key points drafted by a language model from the slides, not yet reviewed by me. The slides are the source.
Cite
@misc{minev2024noisemitigationsummer,
author = {Zlatko K. Minev},
title = {{Intro to Noise Mitigation (Summer School 2024)}},
howpublished = {Lecture series, Near-Term Quantum Algorithms Summer School},
year = {2024},
url = {https://zlatko-minev.github.io/zlatko-minev-quantum-repository/series/intro-to-noise-mitigation-summer-school-2024/},
note = {Slides, 2 decks}
}Reuse
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