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')

Bases: QasmSimulatorBackend

Python interface to MQT DDSIM Hybrid Schrodinger-Feynman Simulator.

property target: Target

A qiskit.transpiler.Target object for the backend.

Return type:

Target

ddsim.hybridstatevectorsimulator module

Backend for DDSIM Hybrid Schrodinger-Feynman Simulator.

class HybridStatevectorSimulatorBackend

Bases: HybridQasmSimulatorBackend

Python interface to MQT DDSIM Hybrid Schrodinger-Feynman Simulator.

property target: 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)

Bases: JobV1

DDSIMJob class.

_executor

executor to handle asynchronous jobs

Type:

futures.Executor

backend()

Return the instance of the backend used for this job.

Return type:

BackendV2 | None

cancel()

Attempt to cancel the job.

Return type:

bool

result(timeout=None)

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()

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()

Submit the job to the backend for execution.

Raises:

JobError – if trying to re-submit the job.

Return type:

None

requires_submit(func)

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')

Bases: QasmSimulatorBackend

Python interface to MQT DDSIM Simulation Path Framework.

property target: Target

A qiskit.transpiler.Target object for the backend.

Return type:

Target

create_tensor_network(qc)

Return type:

TensorNetwork

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

Return type:

list[tuple[int, int]]

read_tensor_network_file(filename)

Return type:

list[Tensor]

ddsim.pathstatevectorsimulator module

Backend for DDSIM.

class PathStatevectorSimulatorBackend

Bases: PathQasmSimulatorBackend

Python interface to MQT DDSIM Simulation Path Framework.

property target: Target

A qiskit.transpiler.Target object for the backend.

Return type:

Target

ddsim.provider module

class DDSIMProvider

Bases: ProviderV1

backends(name=None, filters=None, **kwargs)

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)

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 DeterministicNoiseSimulator

Bases: pybind11_object

__init__(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator, circ: object, approximation_step_fidelity: float = 1.0, approximation_steps: int = 1, approximation_strategy: str = 'fidelity', seed: int = -1, noise_effects: str = 'APD', noise_probability: float = 0.01, amp_damping_probability: float | None = 0.02, multi_qubit_gate_factor: float = 2) → None

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator, 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.DeterministicNoiseSimulator, 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.DeterministicNoiseSimulator) → 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.DeterministicNoiseSimulator) → 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.DeterministicNoiseSimulator) → 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.DeterministicNoiseSimulator) → 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.DeterministicNoiseSimulator) → str

Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator) → int

Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator) → float

Get the tolerance for the DD package.

get_vector(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator) → list[complex]

Get the state vector resulting from the simulation.

set_tolerance(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator, tol: float) → None

Set the tolerance for the DD package.

simulate(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator, shots: int) → dict[str, int]

Simulate the circuit and return the result as a dictionary of counts.

statistics(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator) → dict[str, str]

Get additional statistics provided by the simulator

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:

DD

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.

1. __init__(self: mqt.ddsim.pyddsim.PathCircuitSimulator, circ: object, config: mqt.ddsim.pyddsim.PathSimulatorConfiguration = { “mode”: “sequential” }) -> None

2. __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, path: list[tuple[int, int]], assume_correct_order: bool = False) → 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_3::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_3::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.

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

2. __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 StochasticNoiseSimulator

Bases: pybind11_object

__init__(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator, circ: object, approximation_step_fidelity: float = 1.0, approximation_steps: int = 1, approximation_strategy: str = 'fidelity', seed: int = -1, noise_effects: str = 'APD', noise_probability: float = 0.01, amp_damping_probability: float | None = 0.02, multi_qubit_gate_factor: float = 2) → None

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator, 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.StochasticNoiseSimulator, 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.StochasticNoiseSimulator) → 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.StochasticNoiseSimulator) → 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.StochasticNoiseSimulator) → 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.StochasticNoiseSimulator) → 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.StochasticNoiseSimulator) → str

Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator) → int

Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator) → float

Get the tolerance for the DD package.

get_vector(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator) → list[complex]

Get the state vector resulting from the simulation.

set_tolerance(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator, tol: float) → None

Set the tolerance for the DD package.

simulate(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator, shots: int) → dict[str, int]

Simulate the circuit and return the result as a dictionary of counts.

statistics(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator) → dict[str, str]

Get additional statistics provided by the simulator

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')

Bases: BackendV2

Python interface to MQT DDSIM.

static assign_parameters(quantum_circuits, parameter_values)

Return type:

list[QuantumCircuit]

property max_circuits: int | None

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

run(quantum_circuits, parameter_values=None, **options)

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 QuantumCircuit, ScheduleBlock, or Schedule objects to run on the backend.

• options (Any) – 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()

Return backend status.

Returns:

BackendStatus – the status of the backend.

property target: Target

A qiskit.transpiler.Target object for the backend.

Return type:

Target

ddsim.statevectorsimulator module

Backend for DDSIM.

class StatevectorSimulatorBackend

Bases: QasmSimulatorBackend

Python interface to MQT DDSIM.

property target: Target

A qiskit.transpiler.Target object for the backend.

Return type:

Target

ddsim.unitarysimulator module

Backend for DDSIM Unitary Simulator.

class UnitarySimulatorBackend

Bases: QasmSimulatorBackend

Decision diagram-based unitary simulator.

property target: Target

A qiskit.transpiler.Target object for the backend.

Return type:

Target

ddsim.primitives module

Module for Qiskit Primitives.

class Estimator(options=None, abelian_grouping=False)

Bases: Estimator

DDSIM implementation of qiskit’s sampler. Code adapted from Qiskit’s BackendEstimator class.

property preprocessed_circuits: tuple[list[QuantumCircuit], list[list[QuantumCircuit]]]

Generate quantum circuits for states and observables produced by preprocessing.

Returns: Tuple: A tuple containing two entries:

• List: Quantum circuits list entered in run() method.

• List: Quantum circuit representations of the observables.

class Sampler(*, options=None)

Bases: Sampler

property backend: QasmSimulatorBackend

property num_circuits: int

The number of circuits stored in the sampler.

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

Bases: ProviderV1

backends(name=None, filters=None, **kwargs)

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)

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 DeterministicNoiseSimulator

Bases: pybind11_object

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator, 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.DeterministicNoiseSimulator, 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.DeterministicNoiseSimulator) → 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.DeterministicNoiseSimulator) → 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.DeterministicNoiseSimulator) → 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.DeterministicNoiseSimulator) → 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.DeterministicNoiseSimulator) → str

Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator) → int

Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator) → float

Get the tolerance for the DD package.

get_vector(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator) → list[complex]

Get the state vector resulting from the simulation.

set_tolerance(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator, tol: float) → None

Set the tolerance for the DD package.

simulate(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator, shots: int) → dict[str, int]

Simulate the circuit and return the result as a dictionary of counts.

statistics(self: mqt.ddsim.pyddsim.DeterministicNoiseSimulator) → dict[str, str]

Get additional statistics provided by the simulator

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:

DD

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, path: list[tuple[int, int]], assume_correct_order: bool = False) → 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_3::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_3::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 StochasticNoiseSimulator

Bases: pybind11_object

export_dd_to_graphviz_file(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator, 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.StochasticNoiseSimulator, 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.StochasticNoiseSimulator) → 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.StochasticNoiseSimulator) → 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.StochasticNoiseSimulator) → 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.StochasticNoiseSimulator) → 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.StochasticNoiseSimulator) → str

Get the name of the simulator

get_number_of_qubits(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator) → int

Get the number of qubits

get_tolerance(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator) → float

Get the tolerance for the DD package.

get_vector(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator) → list[complex]

Get the state vector resulting from the simulation.

set_tolerance(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator, tol: float) → None

Set the tolerance for the DD package.

simulate(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator, shots: int) → dict[str, int]

Simulate the circuit and return the result as a dictionary of counts.

statistics(self: mqt.ddsim.pyddsim.StochasticNoiseSimulator) → dict[str, str]

Get additional statistics provided by the simulator

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