DAGDependency

class DAGDependency

Bases: object

Object to represent a quantum circuit as a directed acyclic graph via operation dependencies (i.e. lack of commutation).

The nodes in the graph are operations represented by quantum gates. The edges correspond to non-commutation between two operations (i.e. a dependency). A directed edge from node A to node B means that operation A does not commute with operation B. The object’s methods allow circuits to be constructed.

The nodes in the graph have the following attributes: ‘operation’, ‘successors’, ‘predecessors’.

Example:

Bell circuit with no measurement.

      ┌───┐
qr_0: ┤ H ├──■──
      └───┘┌─┴─┐
qr_1: ─────┤ X ├
           └───┘

The dependency DAG for the above circuit is represented by two nodes. The first one corresponds to Hadamard gate, the second one to the CNOT gate as the gates do not commute there is an edge between the two nodes.

Reference:

[1] Iten, R., Moyard, R., Metger, T., Sutter, D. and Woerner, S., 2020. Exact and practical pattern matching for quantum circuit optimization. arXiv:1909.05270

Create an empty DAGDependency.

Methods

DAGDependency.add_clbits(clbits)

Add individual clbit wires.

DAGDependency.add_creg(creg)

Add clbits in a classical register.

DAGDependency.add_op_node(operation, qargs, cargs)

Add a DAGDepNode to the graph and update the edges.

Parameters

DAGDependency.add_qreg(qreg)

Add qubits in a quantum register.

DAGDependency.add_qubits(qubits)

Add individual qubit wires.

DAGDependency.copy()

Function to copy a DAGDependency object. :returns: a copy of a DAGDependency object. :rtype: DAGDependency

DAGDependency.depth()

Return the circuit depth. :returns: the circuit depth :rtype: int

DAGDependency.direct_predecessors(node_id)

Direct predecessors id of a given node as sorted list.

Parameters

node_id (int) - label of considered node.

Returns

direct predecessors id as a sorted list

Return type

List

DAGDependency.direct_successors(node_id)

Direct successors id of a given node as sorted list.

Parameters

node_id (int) - label of considered node.

Returns

direct successors id as a sorted list

Return type

List

DAGDependency.draw(scale=0.7, filename=None, style='color')

Draws the DAGDependency graph.

This function needs pydot < https://github.com/erocarrera/pydot >, which in turn needs Graphviz < https://www.graphviz.org/ >` to be installed.

Parameters

scale (float) – scaling factor
filename (str) – file path to save image to (format inferred from name)
style (str) – ‘plain’: B&W graph ‘color’ (default): color input/output/op nodes

Returns

if in Jupyter notebook and not saving to file,

otherwise None.

Return type

Ipython.display.Image

DAGDependency.get_all_edges()

Enumeration of all edges.

Returns

corresponding to the label.

Return type

List

DAGDependency.get_edges(src_id, dest_id)

Edge enumeration between two nodes through method get_all_edge_data.

Parameters

Returns

corresponding to all edges between the two nodes.

Return type

List

DAGDependency.get_in_edges(node_id)

Enumeration of all incoming edges for a given node.

Parameters

node_id (int) - label of considered node.

Returns

corresponding incoming edges data.

Return type

List

DAGDependency.get_node(node_id)

Parameters

node_id (int) - label of considered node.

Returns

corresponding to the label.

Return type

node

DAGDependency.get_nodes()

Returns

iterator over all the nodes.

Return type

generator(dict)

DAGDependency.get_out_edges(node_id)

Enumeration of all outgoing edges for a given node.

Parameters

node_id (int) - label of considered node.

Returns

corresponding outgoing edges data.

Return type

List

DAGDependency.predecessors(node_id)

Predecessors id of a given node as sorted list.

Parameters

node_id (int) - label of considered node.

Returns

all predecessors id as a sorted list

Return type

List

DAGDependency.replace_block_with_op(node_block, op, wire_pos_map, cycle_check=True)

Replace a block of nodes with a single node.

This is used to consolidate a block of DAGDepNodes into a single operation. A typical example is a block of CX and SWAP gates consolidated into a LinearFunction. This function is an adaptation of a similar function from DAGCircuit.

It is important that such consolidation preserves commutativity assumptions present in DAGDependency. As an example, suppose that every node in a block [A, B, C, D] commutes with another node E. Let F be the consolidated node, F = A o B o C o D. Then F also commutes with E, and thus the result of replacing [A, B, C, D] by F results in a valid DAGDependency. That is, any deduction about commutativity in consolidated DAGDependency is correct. On the other hand, suppose that at least one of the nodes, say B, does not commute with E. Then the consolidated DAGDependency would imply that F does not commute with E. Even though F and E may actually commute, it is still safe to assume that they do not. That is, the current implementation of consolidation may lead to suboptimal but not to incorrect results.

Parameters

node_block (List[DAGDepNode]) – A list of dag nodes that represents the node block to be replaced
op (qiskit.circuit.Operation) – The operation to replace the block with
wire_pos_map (Dict[Qubit, int]) – The dictionary mapping the qarg to the position. This is necessary to reconstruct the qarg order over multiple gates in the combined single op node.
cycle_check (bool) – When set to True this method will check that replacing the provided node_block with a single node would introduce a cycle (which would invalidate the DAGDependency) and will raise a DAGDependencyError if a cycle would be introduced. This checking comes with a run time penalty. If you can guarantee that your input node_block is a contiguous block and won’t introduce a cycle when it’s contracted to a single node, this can be set to False to improve the runtime performance of this method.

Raises

DAGDependencyError - if cycle_check is set to True and replacing the specified block introduces a cycle or if node_block is empty.

DAGDependency.size()

Returns the number of gates in the circuit

DAGDependency.successors(node_id)

Successors id of a given node as sorted list.

Parameters

node_id (int) - label of considered node.

Returns

all successors id as a sorted list

Return type

List

DAGDependency.to_retworkx()

Returns the DAGDependency in retworkx format.

DAGDependency.topological_nodes()

Yield nodes in topological order.

Returns

node in topological order.

Return type

generator(DAGNode)

Return calibration dictionary.

The custom pulse definition of a given gate is of the form

{‘gate_name’: {(qubits, params): schedule}}

Return the global phase of the circuit.

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