233 lines
11 KiB
Plaintext
233 lines
11 KiB
Plaintext
---
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title: CrosstalkAdaptiveSchedule
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description: API reference for qiskit.transpiler.passes.CrosstalkAdaptiveSchedule
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in_page_toc_min_heading_level: 1
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python_api_type: class
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python_api_name: qiskit.transpiler.passes.CrosstalkAdaptiveSchedule
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---
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# CrosstalkAdaptiveSchedule
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<Class id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule" isDedicatedPage={true} github="https://github.com/qiskit/qiskit/tree/stable/0.18/qiskit/transpiler/passes/optimization/crosstalk_adaptive_schedule.py" signature="CrosstalkAdaptiveSchedule(*args, **kwargs)" modifiers="class">
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Bases: `qiskit.transpiler.basepasses.TransformationPass`
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Crosstalk mitigation through adaptive instruction scheduling.
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CrosstalkAdaptiveSchedule initializer.
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**Parameters**
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* **backend\_prop** ([*BackendProperties*](qiskit.providers.models.BackendProperties "qiskit.providers.models.BackendProperties")) – backend properties object
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* **crosstalk\_prop** (*dict*) –
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crosstalk properties object crosstalk\_prop\[g1]\[g2] specifies the conditional error rate of g1 when g1 and g2 are executed simultaneously. g1 should be a two-qubit tuple of the form (x,y) where x and y are physical qubit ids. g2 can be either two-qubit tuple (x,y) or single-qubit tuple (x). We currently ignore crosstalk between pairs of single-qubit gates. Gate pairs which are not specified are assumed to be crosstalk free.
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Example:
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```python
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crosstalk_prop = {(0, 1) : {(2, 3) : 0.2, (2) : 0.15},
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(4, 5) : {(2, 3) : 0.1},
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(2, 3) : {(0, 1) : 0.05, (4, 5): 0.05}}
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```
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The keys of the crosstalk\_prop are tuples for ordered tuples for CX gates e.g., (0, 1) corresponding to CX 0, 1 in the hardware. Each key has an associated value dict which specifies the conditional error rates with nearby gates e.g., `(0, 1) : {(2, 3) : 0.2, (2) : 0.15}` means that CNOT 0, 1 has an error rate of 0.2 when it is executed in parallel with CNOT 2,3 and an error rate of 0.15 when it is executed in parallel with a single qubit gate on qubit 2.
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* **weight\_factor** (*float*) – weight of gate error/crosstalk terms in the objective $weight_factor*fidelities + (1-weight_factor)*decoherence errors$. Weight can be varied from 0 to 1, with 0 meaning that only decoherence errors are optimized and 1 meaning that only crosstalk errors are optimized. weight\_factor should be tuned per application to get the best results.
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* **measured\_qubits** (*list*) – a list of qubits that will be measured in a particular circuit. This arg need not be specified for circuits which already include measure gates. The arg is useful when a subsequent module such as state\_tomography\_circuits inserts the measure gates. If CrosstalkAdaptiveSchedule is made aware of those measurements, it is included in the optimization.
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**Raises**
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**ImportError** – if unable to import z3 solver
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## Methods
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### assign\_gate\_id
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.assign_gate_id" signature="CrosstalkAdaptiveSchedule.assign_gate_id(dag)">
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ID for each gate
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</Function>
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### basic\_bounds
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.basic_bounds" signature="CrosstalkAdaptiveSchedule.basic_bounds()">
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Basic variable bounds for optimization
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</Function>
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### check\_dag\_dependency
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.check_dag_dependency" signature="CrosstalkAdaptiveSchedule.check_dag_dependency(gate1, gate2)">
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gate2 is a DAG dependent of gate1 if it is a descendant of gate1
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</Function>
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### check\_xtalk\_dependency
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.check_xtalk_dependency" signature="CrosstalkAdaptiveSchedule.check_xtalk_dependency(t_1, t_2)">
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Check if two gates have a crosstalk dependency. We do not consider crosstalk between pairs of single qubit gates.
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</Function>
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### coherence\_constraints
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.coherence_constraints" signature="CrosstalkAdaptiveSchedule.coherence_constraints()">
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Set decoherence errors based on qubit lifetimes
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</Function>
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### create\_updated\_dag
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.create_updated_dag" signature="CrosstalkAdaptiveSchedule.create_updated_dag(layers, barriers)">
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Given a set of layers and barriers, construct a new dag
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</Function>
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### create\_z3\_vars
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.create_z3_vars" signature="CrosstalkAdaptiveSchedule.create_z3_vars()">
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Setup the variables required for Z3 optimization
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</Function>
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### cx\_tuple
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.cx_tuple" signature="CrosstalkAdaptiveSchedule.cx_tuple(gate)">
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Representation for two-qubit gate Note: current implementation assumes that the CX error rates and crosstalk behavior are independent of gate direction
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</Function>
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### enforce\_schedule\_on\_dag
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.enforce_schedule_on_dag" signature="CrosstalkAdaptiveSchedule.enforce_schedule_on_dag(input_gate_times)">
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Z3 outputs start times for each gate. Some gates need to be serialized to implement the Z3 schedule. This function inserts barriers to implement those serializations
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</Function>
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### extract\_crosstalk\_relevant\_sets
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.extract_crosstalk_relevant_sets" signature="CrosstalkAdaptiveSchedule.extract_crosstalk_relevant_sets()">
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Extract the set of program gates which potentially have crosstalk noise
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</Function>
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### extract\_dag\_overlap\_sets
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.extract_dag_overlap_sets" signature="CrosstalkAdaptiveSchedule.extract_dag_overlap_sets(dag)">
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Gate A, B are overlapping if A is neither a descendant nor an ancestor of B. Currenty overlaps (A,B) are considered when A is a 2q gate and B is either 2q or 1q gate.
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</Function>
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### extract\_solution
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.extract_solution" signature="CrosstalkAdaptiveSchedule.extract_solution()">
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Extract gate start and finish times from Z3 solution
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</Function>
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### fidelity\_constraints
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.fidelity_constraints" signature="CrosstalkAdaptiveSchedule.fidelity_constraints()">
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Set gate fidelity based on gate overlap conditions
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</Function>
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### filter\_candidates
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.filter_candidates" signature="CrosstalkAdaptiveSchedule.filter_candidates(candidates, layer, layer_id, triplet)">
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For a gate G and layer L, L is a candidate layer for G if no gate in L has a DAG dependency with G, and if Z3 allows gates in L and G to overlap.
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</Function>
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### find\_layer
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.find_layer" signature="CrosstalkAdaptiveSchedule.find_layer(layers, triplet)">
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Find the appropriate layer for a gate
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</Function>
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### gate\_tuple
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.gate_tuple" signature="CrosstalkAdaptiveSchedule.gate_tuple(gate)">
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Representation for gate
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</Function>
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### generate\_barriers
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.generate_barriers" signature="CrosstalkAdaptiveSchedule.generate_barriers(layers)">
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For each gate g, see if a barrier is required to serialize it with some previously processed gate
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</Function>
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### is\_significant\_xtalk
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.is_significant_xtalk" signature="CrosstalkAdaptiveSchedule.is_significant_xtalk(gate1, gate2)">
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Given two conditional gate error rates check if there is high crosstalk by comparing with independent error rates.
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</Function>
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### name
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.name" signature="CrosstalkAdaptiveSchedule.name()">
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Return the name of the pass.
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</Function>
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### objective\_function
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.objective_function" signature="CrosstalkAdaptiveSchedule.objective_function()">
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Objective function is a weighted combination of gate errors and decoherence errors
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</Function>
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### parse\_backend\_properties
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.parse_backend_properties" signature="CrosstalkAdaptiveSchedule.parse_backend_properties()">
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This function assumes that gate durations and coherence times are in seconds in backend.properties() This function converts gate durations and coherence times to nanoseconds.
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</Function>
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### powerset
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.powerset" signature="CrosstalkAdaptiveSchedule.powerset(iterable)">
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Finds the set of all subsets of the given iterable This function is used to generate constraints for the Z3 optimization
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</Function>
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### r2f
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.r2f" signature="CrosstalkAdaptiveSchedule.r2f(val)">
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Convert Z3 Real to Python float
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</Function>
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### reset
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.reset" signature="CrosstalkAdaptiveSchedule.reset()">
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Reset variables
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</Function>
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### run
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.run" signature="CrosstalkAdaptiveSchedule.run(dag)">
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Main scheduling function
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</Function>
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### scheduling\_constraints
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.scheduling_constraints" signature="CrosstalkAdaptiveSchedule.scheduling_constraints()">
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DAG scheduling constraints optimization Sets overlap indicator variables
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</Function>
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### singleq\_tuple
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.singleq_tuple" signature="CrosstalkAdaptiveSchedule.singleq_tuple(gate)">
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Representation for single-qubit gate
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</Function>
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### solve\_optimization
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<Function id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.solve_optimization" signature="CrosstalkAdaptiveSchedule.solve_optimization()">
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Setup and solve a Z3 optimization for finding the best schedule
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</Function>
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## Attributes
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### is\_analysis\_pass
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<Attribute id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.is_analysis_pass">
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Check if the pass is an analysis pass.
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If the pass is an AnalysisPass, that means that the pass can analyze the DAG and write the results of that analysis in the property set. Modifications on the DAG are not allowed by this kind of pass.
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</Attribute>
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### is\_transformation\_pass
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<Attribute id="qiskit.transpiler.passes.CrosstalkAdaptiveSchedule.is_transformation_pass">
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Check if the pass is a transformation pass.
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If the pass is a TransformationPass, that means that the pass can manipulate the DAG, but cannot modify the property set (but it can be read).
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</Attribute>
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</Class>
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