Table 3 QDataSet features for quantum noise spectroscopy.

From: QDataSet, quantum datasets for machine learning

Item

Description

Objective

Algorithm to estimate noise operators \(\{{V}_{O}\}\), thereby characterising relevant features of noise affecting quantum system.

Inputs

Pulse sequence, reconstructed from the pulse_parameters feature in the dataset.

Label

Set of measurements \(\{{E}_{O}\}\)

Intermediate inputs

Hamiltonians, Unitary operators, Initial states \({\rho }_{0}\)

Output

Estimate of measurements \(\left\{{\widehat{E}}_{O}\right\}\)

Metric

MSE (between estimates and label data)

\(MSE\left({E}_{O},{\widehat{E}}_{O}\right)\)                             (34)

  1. The left columns lists typical categories in a machine learning architecture. The right column describes the corresponding feature(s) of the QDataSet that would fall into such categories for the use of the QDataSet in training quantum tomography algorithms.
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