gMdZddlZddlmZddlmZddlmZddl m Z ddl m Z ddl mZdd lmZdd lmZmZmZdd lmZdd lmZdd lmZmZmZGddeZdS)aj Given a template and a circuit: it applies template matching and substitutes all compatible maximal matches that reduces the size of the circuit. **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 `_ N)QuantumCircuit) DAGDependency)circuit_to_dagdependency)dagdependency_to_circuit)dag_to_dagdependency)dagdependency_to_dag)TransformationPass)template_nct_2a_1template_nct_2a_2template_nct_2a_3)Operator)TranspilerError)TemplateMatchingTemplateSubstitutionMaximalMatchesc2eZdZdZ dfd ZdZxZS)TemplateOptimizationz3 Class for the template optimization pass. Nct|)ttt g}||_||ng|_||ng|_||_dS)a Args: template_list (list[QuantumCircuit()]): list of the different template circuit to apply. heuristics_backward_param (list[int]): [length, survivor] Those are the parameters for applying heuristics on the backward part of the algorithm. This part of the algorithm creates a tree of matching scenario. This tree grows exponentially. The heuristics evaluate which scenarios have the longest match and keep only those. The length is the interval in the tree for cutting it and survivor is the number of scenarios that are kept. We advise to use l=3 and s=1 to have serious time advantage. We remind that the heuristics implies losing a part of the maximal matches. Check reference for more details. heuristics_qubits_param (list[int]): [length] The heuristics for the qubit choice make guesses from the dag dependency of the circuit in order to limit the number of qubit configurations to explore. The length is the number of successors or not predecessors that will be explored in the dag dependency of the circuit, each qubits of the nodes are added to the set of authorized qubits. We advise to use length=1. Check reference for more details. user_cost_dict (Dict[str, int]): quantum cost dictionary passed to TemplateSubstitution to configure its behavior. This will override any default values if None is not given. The key is the name of the gate and the value its quantum cost. N) super__init__r r r template_listheuristics_qubits_paramheuristics_backward_paramuser_cost_dict)selfrrrr __class__s q/granary/edev/quantum/lib/python3.11/site-packages/qiskit/transpiler/passes/optimization/template_optimization.pyrzTemplateOptimization.__init__/s8   .002C2E2EGXGZGZ[M*'>'J # #PR $*C)N % %TV &-c|}t|}|jD]}t|ttfst dt |jt |jkrYtj dt |jzt} t|tr"tt|j }nt|j }tj||}|st dn#t$rYnwxYwt|trt!|}n|}t#|||j|j} | | j} | rht-| } | | j} t3| | j| j|j} | | j}Ԑt?|}|S)a" Args: dag(DAGCircuit): DAG circuit. Returns: DAGCircuit: optimized DAG circuit. Raises: TranspilerError: If the template has not the right form or if the output circuit acts differently as the input circuit. z1A template is a Quantumciruit or a DAGDependency.)dtypez;A template is a Quantumciruit() that performs the identity.) rr isinstancerrrlenqubitsnpidentitycomplexr rdataallclose TypeErrorrrrrrun_template_matching match_listrrun_maximal_matchesmax_match_listrcircuit_dag_deptemplate_dag_depr run_dag_optdag_dep_optimizedr)rdag circuit_dagr/templater&r( comparisonr0 template_mmatchesmaximal max_matches substitutions rrunzTemplateOptimization.runYs .{;;*6 6 Hh(GHH [%&YZZZ8?##c/*@&A&AAA{1HO(<(<#rOsN  888888++++++OOOOOOOOOOOOGGGGGGGGGGGG;;;;;;dddddddddd;;;;;;888888ttttt-tttttr