ddsim package#

Submodules#

ddsim.hybridqasmsimulator module#

Backend for DDSIM Hybrid Schrodinger-Feynman Simulator.

class HybridQasmSimulatorBackend(name='hybrid_qasm_simulator', description='MQT DDSIM Hybrid Schrodinger-Feynman simulator')[source]#

Bases: QasmSimulatorBackend

Python interface to MQT DDSIM Hybrid Schrodinger-Feynman Simulator.

property target#

A qiskit.transpiler.Target object for the backend.

Return type:: Target

ddsim.hybridstatevectorsimulator module#

Backend for DDSIM Hybrid Schrodinger-Feynman Simulator.

class HybridStatevectorSimulatorBackend[source]#

Bases: HybridQasmSimulatorBackend

Python interface to MQT DDSIM Hybrid Schrodinger-Feynman Simulator.

property target#

A qiskit.transpiler.Target object for the backend.

Return type:: Target

ddsim.job module#

class DDSIMJob(backend, job_id, fn, experiments, parameter_values, **args)[source]#

Bases: JobV1

DDSIMJob class.

_executor#

executor to handle asynchronous jobs

Type:: futures.Executor

backend()[source]#

Return the instance of the backend used for this job.

Return type:: Optional[BackendV2]

cancel()[source]#

Attempt to cancel the job.

Return type:: bool

result(timeout=None)[source]#

Get job result. The behavior is the same as the underlying concurrent Future objects, https://docs.python.org/3/library/concurrent.futures.html#future-objects.

Parameters:

timeout (float) – number of seconds to wait for results.

Returns:

qiskit.Result – Result object

Raises:

concurrent.futures.TimeoutError – if timeout occurred.
concurrent.futures.CancelledError – if job cancelled before completed.

status()[source]#

Gets the status of the job by querying the Python’s future.

Returns:

JobStatus – The current JobStatus

Raises:

JobError – If the future is in unexpected state
concurrent.futures.TimeoutError – if timeout occurred.

submit()[source]#

Submit the job to the backend for execution.

Raises:: JobError – if trying to re-submit the job.
Return type:: None

requires_submit(func)[source]#

Decorator to ensure that a submit has been performed before calling the method.

Parameters:: func (callable) – test function to be decorated.
Returns:: callable – the decorated function.

ddsim.pathqasmsimulator module#

Backend for DDSIM Task-Based Simulator.

class PathQasmSimulatorBackend(name='path_sim_qasm_simulator', description='MQT DDSIM Simulation Path Framework')[source]#

Bases: QasmSimulatorBackend

Python interface to MQT DDSIM Simulation Path Framework.

property target#

A qiskit.transpiler.Target object for the backend.

Return type:: Target

create_tensor_network(qc)[source]#

Return type:: TensorNetwork

get_simulation_path(qc, max_time=60, max_repeats=1024, parallel_runs=1, dump_path=True, plot_ring=False)[source]#

Return type:: list[tuple[int, int]]

read_tensor_network_file(filename)[source]#

Return type:: list[Tensor]

ddsim.pathstatevectorsimulator module#

Backend for DDSIM.

class PathStatevectorSimulatorBackend[source]#

Bases: PathQasmSimulatorBackend

Python interface to MQT DDSIM Simulation Path Framework.

property target#

A qiskit.transpiler.Target object for the backend.

Return type:: Target

ddsim.provider module#

class DDSIMProvider[source]#

Bases: ProviderV1

backends(name=None, filters=None, **kwargs)[source]#

Return a list of backends matching the specified filtering.

Parameters:

name (str) – name of the backend.
**kwargs (dict[str, Any]) – dict used for filtering.

Returns:

list[BackendV2] – list[Backend] –

a list of Backends that match the filtering: criteria.

get_backend(name=None, **kwargs)[source]#

Return a single backend matching the specified filtering.

Parameters:

name (str) – name of the backend.
**kwargs (dict[str, Any]) – dict used for filtering.

Returns:

Backend – a backend matching the filtering.

Raises:

QiskitBackendNotFoundError – if no backend could be found or more than one backend matches the filtering criteria.

ddsim.pyddsim module#

Python interface for the MQT DDSIM quantum circuit simulator

class CircuitSimulator#

Bases: pybind11_object

__init__(self: mqt.ddsim.pyddsim.CircuitSimulator, circ: object, approximation_step_fidelity: float = 1.0, approximation_steps: int = 1, approximation_strategy: str = 'fidelity', seed: int = -1) → None#

expectation_value(self: mqt.ddsim.pyddsim.CircuitSimulator, observable: object) → float#

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.CircuitSimulator, filename: str, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → None#: Write a Graphviz representation of the currently stored DD to a file.

export_dd_to_graphviz_str(self: mqt.ddsim.pyddsim.CircuitSimulator, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → str#: Get a Graphviz representation of the currently stored DD.

get_active_matrix_node_count(self: mqt.ddsim.pyddsim.CircuitSimulator) → int#: Get the number of active matrix nodes, i.e., the number of matrix DD nodes in the unique table with a non-zero reference count.

get_active_vector_node_count(self: mqt.ddsim.pyddsim.CircuitSimulator) → int#: Get the number of active vector nodes, i.e., the number of vector DD nodes in the unique table with a non-zero reference count.

get_max_matrix_node_count(self: mqt.ddsim.pyddsim.CircuitSimulator) → int#: Get the maximum number of (active) matrix nodes, i.e., the maximum number of matrix DD nodes in the unique table at any point during the simulation.

get_max_vector_node_count(self: mqt.ddsim.pyddsim.CircuitSimulator) → int#: Get the maximum number of (active) vector nodes, i.e., the maximum number of vector DD nodes in the unique table at any point during the simulation.

get_name(self: mqt.ddsim.pyddsim.CircuitSimulator) → str#: Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.CircuitSimulator) → int#: Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.CircuitSimulator) → float#: Get the tolerance for the DD package.

get_vector(self: mqt.ddsim.pyddsim.CircuitSimulator) → List[complex]#: Get the state vector resulting from the simulation.

set_tolerance(self: mqt.ddsim.pyddsim.CircuitSimulator, tol: float) → None#: Set the tolerance for the DD package.

simulate(self: mqt.ddsim.pyddsim.CircuitSimulator, shots: int) → Dict[str, int]#: Simulate the circuit and return the result as a dictionary of counts.

statistics(self: mqt.ddsim.pyddsim.CircuitSimulator) → Dict[str, str]#: Get additional statistics provided by the simulator

class ConstructionMode#

Bases: pybind11_object

Members:

recursive

sequential

__init__(self: mqt.ddsim.pyddsim.ConstructionMode, value: int) → None#

property name#

recursive = <ConstructionMode.recursive: 1>#

sequential = <ConstructionMode.sequential: 0>#

property value#

class HybridCircuitSimulator#

Bases: pybind11_object

__init__(self: mqt.ddsim.pyddsim.HybridCircuitSimulator, circ: object, approximation_step_fidelity: float = 1.0, approximation_steps: int = 1, approximation_strategy: str = 'fidelity', seed: int = -1, mode: mqt.ddsim.pyddsim.HybridMode = <HybridMode.amplitude: 1>, nthreads: int = 2) → None#

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.HybridCircuitSimulator, filename: str, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → None#: Write a Graphviz representation of the currently stored DD to a file.

export_dd_to_graphviz_str(self: mqt.ddsim.pyddsim.HybridCircuitSimulator, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → str#: Get a Graphviz representation of the currently stored DD.

get_active_matrix_node_count(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → int#: Get the number of active matrix nodes, i.e., the number of matrix DD nodes in the unique table with a non-zero reference count.

get_active_vector_node_count(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → int#: Get the number of active vector nodes, i.e., the number of vector DD nodes in the unique table with a non-zero reference count.

get_final_amplitudes(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → List[complex]#

get_max_matrix_node_count(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → int#: Get the maximum number of (active) matrix nodes, i.e., the maximum number of matrix DD nodes in the unique table at any point during the simulation.

get_max_vector_node_count(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → int#: Get the maximum number of (active) vector nodes, i.e., the maximum number of vector DD nodes in the unique table at any point during the simulation.

get_mode(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → mqt.ddsim.pyddsim.HybridMode#

get_name(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → str#: Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → int#: Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → float#: Get the tolerance for the DD package.

get_vector(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → List[complex]#: Get the state vector resulting from the simulation.

set_tolerance(self: mqt.ddsim.pyddsim.HybridCircuitSimulator, tol: float) → None#: Set the tolerance for the DD package.

simulate(self: mqt.ddsim.pyddsim.HybridCircuitSimulator, shots: int) → Dict[str, int]#: Simulate the circuit and return the result as a dictionary of counts.

statistics(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → Dict[str, str]#: Get additional statistics provided by the simulator

class HybridMode#

Bases: pybind11_object

Members:

amplitude

DD = <HybridMode.DD: 0>#

__init__(self: mqt.ddsim.pyddsim.HybridMode, value: int) → None#

amplitude = <HybridMode.amplitude: 1>#

property name#

property value#

class PathCircuitSimulator#

Bases: pybind11_object

__init__(*args, **kwargs)#

Overloaded function.

__init__(self: mqt.ddsim.pyddsim.PathCircuitSimulator, circ: object, config: mqt.ddsim.pyddsim.PathSimulatorConfiguration = {

“mode”: “sequential”

}) -> None

__init__(self: mqt.ddsim.pyddsim.PathCircuitSimulator, circ: object, mode: mqt.ddsim.pyddsim.PathSimulatorMode = <PathSimulatorMode.sequential: 0>, bracket_size: int = 2, starting_point: int = 0, gate_cost: List[int] = [], seed: int = 0) -> None

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.PathCircuitSimulator, filename: str, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → None#: Write a Graphviz representation of the currently stored DD to a file.

export_dd_to_graphviz_str(self: mqt.ddsim.pyddsim.PathCircuitSimulator, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → str#: Get a Graphviz representation of the currently stored DD.

get_active_matrix_node_count(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → int#: Get the number of active matrix nodes, i.e., the number of matrix DD nodes in the unique table with a non-zero reference count.

get_active_vector_node_count(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → int#: Get the number of active vector nodes, i.e., the number of vector DD nodes in the unique table with a non-zero reference count.

get_max_matrix_node_count(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → int#: Get the maximum number of (active) matrix nodes, i.e., the maximum number of matrix DD nodes in the unique table at any point during the simulation.

get_max_vector_node_count(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → int#: Get the maximum number of (active) vector nodes, i.e., the maximum number of vector DD nodes in the unique table at any point during the simulation.

get_name(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → str#: Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → int#: Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → float#: Get the tolerance for the DD package.

get_vector(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → List[complex]#: Get the state vector resulting from the simulation.

set_simulation_path(self: mqt.ddsim.pyddsim.PathCircuitSimulator, arg0: List[Tuple[int, int]], arg1: bool) → None#

set_tolerance(self: mqt.ddsim.pyddsim.PathCircuitSimulator, tol: float) → None#: Set the tolerance for the DD package.

simulate(self: mqt.ddsim.pyddsim.PathCircuitSimulator, shots: int) → Dict[str, int]#: Simulate the circuit and return the result as a dictionary of counts.

statistics(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → Dict[str, str]#: Get additional statistics provided by the simulator

class PathSimulatorConfiguration#

Bases: pybind11_object

Configuration options for the Path Simulator

__init__(self: mqt.ddsim.pyddsim.PathSimulatorConfiguration) → None#

property bracket_size#: Size of the brackets one wants to combine

property gate_cost#: A list that contains the number of gates which are considered in each step

json(self: mqt.ddsim.pyddsim.PathSimulatorConfiguration) → nlohmann::json_abi_v3_11_2::basic_json<std::map, std::vector, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, bool, long, unsigned long, double, std::allocator, nlohmann::json_abi_v3_11_2::adl_serializer, std::vector<unsigned char, std::allocator<unsigned char> >, void>#

property mode#: Setting the mode used for determining a simulation path

property seed#: Seed for the simulator

property starting_point#: Start of the alternating or gate_cost strategy

class PathSimulatorMode#

Bases: pybind11_object

Members:

sequential

pairwise_recursive

cotengra

bracket

alternating

gate_cost

__init__(*args, **kwargs)#

Overloaded function.

__init__(self: mqt.ddsim.pyddsim.PathSimulatorMode, value: int) -> None
__init__(self: mqt.ddsim.pyddsim.PathSimulatorMode, arg0: str) -> None

alternating = <PathSimulatorMode.alternating: 3>#

bracket = <PathSimulatorMode.bracket: 2>#

cotengra = <PathSimulatorMode.cotengra: 4>#

gate_cost = <PathSimulatorMode.gate_cost: 5>#

property name#

pairwise_recursive = <PathSimulatorMode.pairwise_recursive: 1>#

sequential = <PathSimulatorMode.sequential: 0>#

property value#

class UnitarySimulator#

Bases: pybind11_object

__init__(self: mqt.ddsim.pyddsim.UnitarySimulator, circ: object, approximation_step_fidelity: float = 1.0, approximation_steps: int = 1, approximation_strategy: str = 'fidelity', seed: int = -1, mode: mqt.ddsim.pyddsim.ConstructionMode = <ConstructionMode.recursive: 1>) → None#

construct(self: mqt.ddsim.pyddsim.UnitarySimulator) → None#: Construct the DD representing the unitary matrix of the circuit.

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.UnitarySimulator, filename: str, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → None#: Write a Graphviz representation of the currently stored DD to a file.

export_dd_to_graphviz_str(self: mqt.ddsim.pyddsim.UnitarySimulator, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → str#: Get a Graphviz representation of the currently stored DD.

get_active_matrix_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#: Get the number of active matrix nodes, i.e., the number of matrix DD nodes in the unique table with a non-zero reference count.

get_active_vector_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#: Get the number of active vector nodes, i.e., the number of vector DD nodes in the unique table with a non-zero reference count.

get_construction_time(self: mqt.ddsim.pyddsim.UnitarySimulator) → float#

get_final_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#

get_max_matrix_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#: Get the maximum number of (active) matrix nodes, i.e., the maximum number of matrix DD nodes in the unique table at any point during the simulation.

get_max_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#

get_max_vector_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#: Get the maximum number of (active) vector nodes, i.e., the maximum number of vector DD nodes in the unique table at any point during the simulation.

get_mode(self: mqt.ddsim.pyddsim.UnitarySimulator) → mqt.ddsim.pyddsim.ConstructionMode#

get_name(self: mqt.ddsim.pyddsim.UnitarySimulator) → str#: Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#: Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.UnitarySimulator) → float#: Get the tolerance for the DD package.

set_tolerance(self: mqt.ddsim.pyddsim.UnitarySimulator, tol: float) → None#: Set the tolerance for the DD package.

statistics(self: mqt.ddsim.pyddsim.UnitarySimulator) → Dict[str, str]#: Get additional statistics provided by the simulator

dump_tensor_network(circ: object, filename: str) → None#: dump a tensor network representation of the given circuit

get_matrix(sim: mqt.ddsim.pyddsim.UnitarySimulator, mat: numpy.ndarray[numpy.complex128]) → None#

ddsim.qasmsimulator module#

Backend for DDSIM.

class QasmSimulatorBackend(name='qasm_simulator', description='MQT DDSIM QASM Simulator')[source]#

Bases: BackendV2

Python interface to MQT DDSIM.

property max_circuits#

The maximum number of circuits (or Pulse schedules) that can be run in a single job.

If there is no limit this will return None

static max_qubits(for_matrix=False)[source]#

Return type:: int

run(quantum_circuits, parameter_values=None, **options)[source]#

Run on the backend.

This method returns a Job object that runs circuits. Depending on the backend this may be either an async or sync call. It is at the discretion of the provider to decide whether running should block until the execution is finished or not: the Job class can handle either situation.

Parameters:

run_input (QuantumCircuit or Schedule or ScheduleBlock or list) – An individual or a list of ScheduleBlock, or Schedule objects to run on the backend.
options – Any kwarg options to pass to the backend for running the config. If a key is also present in the options attribute/object then the expectation is that the value specified will be used instead of what’s set in the options object.

Returns:

Job – The job object for the run

status()[source]#

Return backend status.

Returns:: BackendStatus – the status of the backend.

property target#

A qiskit.transpiler.Target object for the backend.

Return type:: Target

ddsim.statevectorsimulator module#

Backend for DDSIM.

class StatevectorSimulatorBackend[source]#

Bases: QasmSimulatorBackend

Python interface to MQT DDSIM.

property target#

A qiskit.transpiler.Target object for the backend.

Return type:: Target

ddsim.unitarysimulator module#

Backend for DDSIM Unitary Simulator.

class UnitarySimulatorBackend[source]#

Bases: QasmSimulatorBackend

Decision diagram-based unitary simulator.

property target#

A qiskit.transpiler.Target object for the backend.

Return type:: Target

Module contents#

class CircuitSimulator#

Bases: pybind11_object

expectation_value(self: mqt.ddsim.pyddsim.CircuitSimulator, observable: object) → float#

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.CircuitSimulator, filename: str, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → None#: Write a Graphviz representation of the currently stored DD to a file.

export_dd_to_graphviz_str(self: mqt.ddsim.pyddsim.CircuitSimulator, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → str#: Get a Graphviz representation of the currently stored DD.

get_active_matrix_node_count(self: mqt.ddsim.pyddsim.CircuitSimulator) → int#: Get the number of active matrix nodes, i.e., the number of matrix DD nodes in the unique table with a non-zero reference count.

get_active_vector_node_count(self: mqt.ddsim.pyddsim.CircuitSimulator) → int#: Get the number of active vector nodes, i.e., the number of vector DD nodes in the unique table with a non-zero reference count.

get_max_matrix_node_count(self: mqt.ddsim.pyddsim.CircuitSimulator) → int#: Get the maximum number of (active) matrix nodes, i.e., the maximum number of matrix DD nodes in the unique table at any point during the simulation.

get_max_vector_node_count(self: mqt.ddsim.pyddsim.CircuitSimulator) → int#: Get the maximum number of (active) vector nodes, i.e., the maximum number of vector DD nodes in the unique table at any point during the simulation.

get_name(self: mqt.ddsim.pyddsim.CircuitSimulator) → str#: Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.CircuitSimulator) → int#: Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.CircuitSimulator) → float#: Get the tolerance for the DD package.

get_vector(self: mqt.ddsim.pyddsim.CircuitSimulator) → List[complex]#: Get the state vector resulting from the simulation.

set_tolerance(self: mqt.ddsim.pyddsim.CircuitSimulator, tol: float) → None#: Set the tolerance for the DD package.

simulate(self: mqt.ddsim.pyddsim.CircuitSimulator, shots: int) → Dict[str, int]#: Simulate the circuit and return the result as a dictionary of counts.

statistics(self: mqt.ddsim.pyddsim.CircuitSimulator) → Dict[str, str]#: Get additional statistics provided by the simulator

class ConstructionMode#

Bases: pybind11_object

Members:

recursive

sequential

property name#

recursive = <ConstructionMode.recursive: 1>#

sequential = <ConstructionMode.sequential: 0>#

property value#

class DDSIMProvider[source]#

Bases: ProviderV1

backends(name=None, filters=None, **kwargs)[source]#

Return a list of backends matching the specified filtering.

Parameters:

name (str) – name of the backend.
**kwargs (dict[str, Any]) – dict used for filtering.

Returns:

list[BackendV2] – list[Backend] –

a list of Backends that match the filtering: criteria.

get_backend(name=None, **kwargs)[source]#

Return a single backend matching the specified filtering.

Parameters:

name (str) – name of the backend.
**kwargs (dict[str, Any]) – dict used for filtering.

Returns:

Backend – a backend matching the filtering.

Raises:

QiskitBackendNotFoundError – if no backend could be found or more than one backend matches the filtering criteria.

class HybridCircuitSimulator#

Bases: pybind11_object

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.HybridCircuitSimulator, filename: str, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → None#: Write a Graphviz representation of the currently stored DD to a file.

export_dd_to_graphviz_str(self: mqt.ddsim.pyddsim.HybridCircuitSimulator, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → str#: Get a Graphviz representation of the currently stored DD.

get_active_matrix_node_count(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → int#: Get the number of active matrix nodes, i.e., the number of matrix DD nodes in the unique table with a non-zero reference count.

get_active_vector_node_count(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → int#: Get the number of active vector nodes, i.e., the number of vector DD nodes in the unique table with a non-zero reference count.

get_final_amplitudes(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → List[complex]#

get_max_matrix_node_count(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → int#: Get the maximum number of (active) matrix nodes, i.e., the maximum number of matrix DD nodes in the unique table at any point during the simulation.

get_max_vector_node_count(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → int#: Get the maximum number of (active) vector nodes, i.e., the maximum number of vector DD nodes in the unique table at any point during the simulation.

get_mode(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → mqt.ddsim.pyddsim.HybridMode#

get_name(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → str#: Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → int#: Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → float#: Get the tolerance for the DD package.

get_vector(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → List[complex]#: Get the state vector resulting from the simulation.

set_tolerance(self: mqt.ddsim.pyddsim.HybridCircuitSimulator, tol: float) → None#: Set the tolerance for the DD package.

simulate(self: mqt.ddsim.pyddsim.HybridCircuitSimulator, shots: int) → Dict[str, int]#: Simulate the circuit and return the result as a dictionary of counts.

statistics(self: mqt.ddsim.pyddsim.HybridCircuitSimulator) → Dict[str, str]#: Get additional statistics provided by the simulator

class HybridMode#

Bases: pybind11_object

Members:

amplitude

DD = <HybridMode.DD: 0>#

amplitude = <HybridMode.amplitude: 1>#

property name#

property value#

class PathCircuitSimulator#

Bases: pybind11_object

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.PathCircuitSimulator, filename: str, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → None#: Write a Graphviz representation of the currently stored DD to a file.

export_dd_to_graphviz_str(self: mqt.ddsim.pyddsim.PathCircuitSimulator, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → str#: Get a Graphviz representation of the currently stored DD.

get_active_matrix_node_count(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → int#: Get the number of active matrix nodes, i.e., the number of matrix DD nodes in the unique table with a non-zero reference count.

get_active_vector_node_count(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → int#: Get the number of active vector nodes, i.e., the number of vector DD nodes in the unique table with a non-zero reference count.

get_max_matrix_node_count(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → int#: Get the maximum number of (active) matrix nodes, i.e., the maximum number of matrix DD nodes in the unique table at any point during the simulation.

get_max_vector_node_count(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → int#: Get the maximum number of (active) vector nodes, i.e., the maximum number of vector DD nodes in the unique table at any point during the simulation.

get_name(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → str#: Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → int#: Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → float#: Get the tolerance for the DD package.

get_vector(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → List[complex]#: Get the state vector resulting from the simulation.

set_simulation_path(self: mqt.ddsim.pyddsim.PathCircuitSimulator, arg0: List[Tuple[int, int]], arg1: bool) → None#

set_tolerance(self: mqt.ddsim.pyddsim.PathCircuitSimulator, tol: float) → None#: Set the tolerance for the DD package.

simulate(self: mqt.ddsim.pyddsim.PathCircuitSimulator, shots: int) → Dict[str, int]#: Simulate the circuit and return the result as a dictionary of counts.

statistics(self: mqt.ddsim.pyddsim.PathCircuitSimulator) → Dict[str, str]#: Get additional statistics provided by the simulator

class PathSimulatorConfiguration#

Bases: pybind11_object

Configuration options for the Path Simulator

property bracket_size#: Size of the brackets one wants to combine

property gate_cost#: A list that contains the number of gates which are considered in each step

json(self: mqt.ddsim.pyddsim.PathSimulatorConfiguration) → nlohmann::json_abi_v3_11_2::basic_json<std::map, std::vector, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, bool, long, unsigned long, double, std::allocator, nlohmann::json_abi_v3_11_2::adl_serializer, std::vector<unsigned char, std::allocator<unsigned char> >, void>#

property mode#: Setting the mode used for determining a simulation path

property seed#: Seed for the simulator

property starting_point#: Start of the alternating or gate_cost strategy

class PathSimulatorMode#

Bases: pybind11_object

Members:

sequential

pairwise_recursive

cotengra

bracket

alternating

gate_cost

alternating = <PathSimulatorMode.alternating: 3>#

bracket = <PathSimulatorMode.bracket: 2>#

cotengra = <PathSimulatorMode.cotengra: 4>#

gate_cost = <PathSimulatorMode.gate_cost: 5>#

property name#

pairwise_recursive = <PathSimulatorMode.pairwise_recursive: 1>#

sequential = <PathSimulatorMode.sequential: 0>#

property value#

class UnitarySimulator#

Bases: pybind11_object

construct(self: mqt.ddsim.pyddsim.UnitarySimulator) → None#: Construct the DD representing the unitary matrix of the circuit.

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.UnitarySimulator, filename: str, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → None#: Write a Graphviz representation of the currently stored DD to a file.

export_dd_to_graphviz_str(self: mqt.ddsim.pyddsim.UnitarySimulator, colored: bool = True, edge_labels: bool = False, classic: bool = False, memory: bool = False, format_as_polar: bool = True) → str#: Get a Graphviz representation of the currently stored DD.

get_active_matrix_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#: Get the number of active matrix nodes, i.e., the number of matrix DD nodes in the unique table with a non-zero reference count.

get_active_vector_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#: Get the number of active vector nodes, i.e., the number of vector DD nodes in the unique table with a non-zero reference count.

get_construction_time(self: mqt.ddsim.pyddsim.UnitarySimulator) → float#

get_final_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#

get_max_matrix_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#: Get the maximum number of (active) matrix nodes, i.e., the maximum number of matrix DD nodes in the unique table at any point during the simulation.

get_max_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#

get_max_vector_node_count(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#: Get the maximum number of (active) vector nodes, i.e., the maximum number of vector DD nodes in the unique table at any point during the simulation.

get_mode(self: mqt.ddsim.pyddsim.UnitarySimulator) → mqt.ddsim.pyddsim.ConstructionMode#

get_name(self: mqt.ddsim.pyddsim.UnitarySimulator) → str#: Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.UnitarySimulator) → int#: Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.UnitarySimulator) → float#: Get the tolerance for the DD package.

set_tolerance(self: mqt.ddsim.pyddsim.UnitarySimulator, tol: float) → None#: Set the tolerance for the DD package.

statistics(self: mqt.ddsim.pyddsim.UnitarySimulator) → Dict[str, str]#: Get additional statistics provided by the simulator

dump_tensor_network(circ: object, filename: str) → None#: dump a tensor network representation of the given circuit

get_matrix(sim: mqt.ddsim.pyddsim.UnitarySimulator, mat: numpy.ndarray[numpy.complex128]) → None#