Now that we've covered what circuits, models, and data sets are, let's see what we can do with them! This tutorial is intended to be an overview of the things that pyGSTi is able to do, with links to more detailed explanations and demonstrations as is appropriate. We begin with the simpler applications and proceed to the more complex ones. Here's a table of contents to give you a sense of what's here and so you can skip around if you'd like. Each of the sections here can more-or-less stand on its own.

- computing circuit outcome probabilities
- simulating observed data based on a model
- testing how well a model describes a set of data
- running Randomized Benchmarking (RB)
- running Robust Phase Estimation (RPE)
- performing data set comparison tests
- running Gate Set Tomography (GST)
- multi-qubit tomography

We'll begin by setting up a `Workspace`

so we can display pretty interactive figures inline (see the intro to Workspaces tutorial for more details).

In [1]:

```
import pygsti
import numpy as np
ws = pygsti.report.Workspace()
ws.init_notebook_mode(autodisplay=True)
```