pwc_signal

Graph.pwc_signal(values, duration, *, name=None)

Creates a piecewise-constant signal (scalar-valued function of time).

Use this function to create a piecewise-constant signal in which the constant segments all have the same duration.

Parameters
  • values (np.ndarray or Tensor) – The values \(\{\alpha_n\}\) of the \(N\) constant segments. These can represent either a single sequence of segment values or a batch of them. To create a batch of \(B_1 \times \ldots \times B_n\) signals, represent these values as a tensor of shape \(B_1 \times \ldots \times B_n \times N\).

  • duration (float) – The total duration \(\tau\) of the signal.

  • name (str, optional) – The name of the node.

Returns

The piecewise-constant function of time \(\alpha(t)\), satisfying \(\alpha(t)=\alpha_n\) for \(t_{n-1}\leq t\leq t_n\), where \(t_n=n\tau/N\) (where \(N\) is the number of values in \(\{\alpha_n\}\)). If you provide a batch of values, the returned Pwc represents a corresponding batch of \(B_1 \times \ldots \times B_n\) functions \(\alpha(t)\).

Return type

Pwc

See also

complex_pwc_signal()

Create complex Pwc signals from their moduli and phases.

pwc()

Corresponding operation with support for segments of different durations.

pwc_operator()

Create Pwc operators.

pwc_sum()

Sum multiple Pwcs.

symmetrize_pwc()

Symmetrize Pwcs.

Examples

Create a piecewise-constant signal with uniform segment duration.

>>> graph.pwc_signal(duration=0.1, values=np.array([2, 3]), name="signal")
<Pwc: name="signal", operation_name="pwc_signal", value_shape=(), batch_shape=()>
>>> result = qctrl.functions.calculate_graph(graph=graph, output_node_names=["signal"])
>>> result.output["signal"]
[{'value': 2.0, 'duration': 0.05}, {'value': 3.0, 'duration': 0.05}]

See more examples in the Get familiar with graphs tutorial.