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Building blocks

This section introduces the building blocks of QruiseML. It covers the physical and mathematical foundations, and the methods used to model and optimise real-world quantum systems.

Each page introduces a building block in detail, outlining the different variants and choices available and helping you to understand its role in QruiseML. If you prefer to learn by doing, you can skip ahead to our example notebooks and return to this section whenever you need more context on specific topics.

General workflow

There's a lot you can do with QruiseML, and we've tried to make it as flexible as possible, so you can configure it precisely to your requirements. However, there's a general workflow we suggest following for simulation and optimisation:

  1. Set up your system
  2. Simulate your system
  3. Optimise your system (optional)

Let's walk through each step. Each section links to the relevant building block pages where you can find more details on the available options and how to use them.

1. Set up your system

This step is the most involved, as it requires defining your system and all its components, and specifying what you want to simulate.

  1. Define your time-dependent drive.
  2. Define your parameter space.
  3. Define your Hamiltonian.
  4. Construct your quantum simulation problem by specifying the appropriate time-evolution equation and all the information needed to run the simulation.

This workflow is universal. Whenever you need to set up a simulation or optimisation, you should follow these steps.

2. Simulate your system

Once you've gone through the hard work of setting everything up, you can run your simulation! All you need to do is:

  1. Start a session and choose the algorithm you want to use.
  2. Run your simulation!

3. Optimise your system (optional)

If you find that your system doesn't perform as well as you'd hoped, you can apply quantum optimal control. To do this, you need to:

  1. Define a target state and state-overlap measure.
  2. Construct a quantum optimal control problem using your simulation problem, target state, and overlap measure.
  3. Run your optimisation!

This might seem like a lot to learn (and it is!), but these docs are here to guide you every step of the way. Happy building!

Example notebooks

Remember we offer step-by-step guides for a variety of quantum platforms and use-cases to help you get started.