DAGDependency#

class qiskit.dagcircuit.DAGDependency[código fonte]#

Bases: object

Object to represent a quantum circuit as a Directed Acyclic Graph (DAG) 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.

Attributes

calibrations#

Return calibration dictionary.

The custom pulse definition of a given gate is of the form {'gate_name': {(qubits, params): schedule}}.

global_phase#

Return the global phase of the circuit.

Methods

add_clbits(clbits)[código fonte]#

Add individual clbit wires.

add_creg(creg)[código fonte]#

Add clbits in a classical register.

add_op_node(operation, qargs, cargs)[código fonte]#

Add a DAGDepNode to the graph and update the edges.

Parâmetros:
add_qreg(qreg)[código fonte]#

Add qubits in a quantum register.

add_qubits(qubits)[código fonte]#

Add individual qubit wires.

copy()[código fonte]#

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

depth()[código fonte]#

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

direct_predecessors(node_id)[código fonte]#

Direct predecessors id of a given node as sorted list.

Parâmetros:

node_id (int) – label of considered node.

Retorno:

direct predecessors id as a sorted list

Tipo de retorno:

List

direct_successors(node_id)[código fonte]#

Direct successors id of a given node as sorted list.

Parâmetros:

node_id (int) – label of considered node.

Retorno:

direct successors id as a sorted list

Tipo de retorno:

List

draw(scale=0.7, filename=None, style='color')[código fonte]#

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.

Parâmetros:
  • 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

Retorno:

if in Jupyter notebook and not saving to file, otherwise None.

Tipo de retorno:

Ipython.display.Image

get_all_edges()[código fonte]#

Enumeration of all edges.

Retorno:

corresponding to the label.

Tipo de retorno:

List

get_edges(src_id, dest_id)[código fonte]#

Edge enumeration between two nodes through method get_all_edge_data.

Parâmetros:
  • src_id (int) – label of the first node.

  • dest_id (int) – label of the second node.

Retorno:

corresponding to all edges between the two nodes.

Tipo de retorno:

List

get_in_edges(node_id)[código fonte]#

Enumeration of all incoming edges for a given node.

Parâmetros:

node_id (int) – label of considered node.

Retorno:

corresponding incoming edges data.

Tipo de retorno:

List

get_node(node_id)[código fonte]#
Parâmetros:

node_id (int) – label of considered node.

Retorno:

corresponding to the label.

Tipo de retorno:

node

get_nodes()[código fonte]#
Retorno:

iterator over all the nodes.

Tipo de retorno:

generator(dict)

get_out_edges(node_id)[código fonte]#

Enumeration of all outgoing edges for a given node.

Parâmetros:

node_id (int) – label of considered node.

Retorno:

corresponding outgoing edges data.

Tipo de retorno:

List

predecessors(node_id)[código fonte]#

Predecessors id of a given node as sorted list.

Parâmetros:

node_id (int) – label of considered node.

Retorno:

all predecessors id as a sorted list

Tipo de retorno:

List

replace_block_with_op(node_block, op, wire_pos_map, cycle_check=True)[código fonte]#

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.

Parâmetros:
  • 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.

Levanta:

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

size()[código fonte]#

Returns the number of gates in the circuit

successors(node_id)[código fonte]#

Successors id of a given node as sorted list.

Parâmetros:

node_id (int) – label of considered node.

Retorno:

all successors id as a sorted list

Tipo de retorno:

List

to_retworkx()[código fonte]#

Returns the DAGDependency in retworkx format.

topological_nodes()[código fonte]#

Yield nodes in topological order.

Retorno:

node in topological order.

Tipo de retorno:

generator(DAGNode)