Gate and Operation GuidelinesΒΆ

This developer document explains what is expected of a gate or operation exposed by Cirq. In particular, we have a stricter standard than what is required of users of the library.

For a user of Cirq, specifying either a _unitary_ method or a _decompose_ method is sufficient to get a gate working. Most other protocols will infer what they need from these two methods. A gate specified in this way will not be particularly performant, but it will work. For internal gates, we also want high performance, and so we require several other protocol methods to be implemented.

In general, the source of truth for what has to be implemented is enforced by the cirq.testing.assert_implements_consistent_protocols method. This method verifies the following properties:

  1. The class has a __repr__ method that produces a python expression that evaluates to an object equal to the original value. The expression assumes that cirq, sympy, numpy as np, and pandas as pd have been imported.

  2. If the class is unitary, it specifies a _has_unitary_ method.

  3. The classes various protocols agree with each other. For example, the decomposition that _decompose_ produces should have the same effect as the unitary produced by _unitary_ or the transformation applied by _apply_unitary_.

If the gate is exposed by cirq/__init__.py or another public module, other tests will notice it and verify that it is serializable. See the serialization guidelines.

There are several other informal constraints:

  1. Large gates should have a _decompose_ method that returns a composition of smaller gates. This allows optimizers and other tools that cannot understand the gate to break it into pieces that they do understand.

  2. Gates should specify a good _circuit_diagram_info_ method. In some cases the default behavior of using __str__ is sufficient.

  3. Gates should have a good __str__ method.

  4. If the __repr__ is cumbersome, gates should specify a _repr_pretty_ method. This method will be used preferentially by Jupyter notebooks, ipython, etc.

  5. Gates should specify an _apply_unitary_ method. This is not necessary for single or two qubit gates, but it is a huge performance difference for larger gates.

  6. Gates that take parameters (e.g. a rotation angle) should generally allow for those parameters to be sympy objects instead of floats, and implement corresponding _is_parameterized_ and _resolve_parameters_ methods.

  7. Prefer creating a Gate over creating an Operation. In some cases it makes sense to only have an Operation, but these cases are generally surprising to users. If you have to use an operation, try to have the .gate property of the operation can return something useful instead of None.

  8. Consider adding interop methods like _qasm_. These methods will fallback to using things like _decompose_, but the output is usually much better when specialized.