plot_accumulated_error

plot_accumulated_error(metadata, axes)

Plot the accumulated error.

This method populates the provided figure axes with a line-plot of the OBPMetadata.accumulated_error(). Below is an example where we plot some metadata which exists within our context.

>>> from matplotlib import pyplot as plt
>>> from qiskit_addon_obp.utils.visualization import plot_accumulated_error
>>> fig, axes = plt.subplots(1, 1)
>>> plot_accumulated_error(metadata, axes)

(png, hires.png, pdf)

As you can see in the figure above, the number of backpropagated slices is displayed along the x-axis. You can think of this as the “time” of the backpropagation algorithm. The accumulated error due to truncated Pauli terms is displayed along the y-axis. If OBPMetadata.truncation_error_budget.max_error_total is not numpy.inf, it is displayed as a red horizontal line. Each observable that was backpropagated, gets its own line.

This data is related to the one visualized by plot_slice_errors(). This method plots the cumulative sum of the slice errors along the x-axis.

Parameters:

• metadata (OBPMetadata) – the metadata to be visualized.

• axes (Axes) – the matplotlib axes in which to plot.