ddsim package

Submodules

ddsim.error module

Exception for errors raised by DDSIM simulator.

exception DDSIMError(*message)

Bases: QiskitError

Class for errors raised by the DDSIM simulator.

ddsim.hybridqasmsimulator module

Backend for DDSIM Hybrid Schrodinger-Feynman Simulator.

class HybridQasmSimulatorBackend(configuration=None, provider=None)

Bases: BackendV1

Python interface to MQT DDSIM Hybrid Schrodinger-Feynman Simulator.

SHOW_STATE_VECTOR = False

run(quantum_circuits, **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 list) – An individual or a list of QuantumCircuit or Schedule objects to run on the backend. For legacy providers migrating to the new versioned providers, provider interface a QasmQobj or PulseQobj objects should probably be supported too (but deprecated) for backwards compatibility. Be sure to update the docstrings of subclasses implementing this method to document that. New provider implementations should not do this though as qiskit.qobj will be deprecated and removed along with the legacy providers interface.

• 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

run_experiment(qobj_experiment, **options)

status()

Return backend status.

Returns:

BackendStatus – the status of the backend.

ddsim.hybridstatevectorsimulator module

Backend for DDSIM Hybrid Schrodinger-Feynman Simulator.

class HybridStatevectorSimulatorBackend(configuration=None, provider=None)

Bases: HybridQasmSimulatorBackend

Python interface to MQT DDSIM Hybrid Schrodinger-Feynman Simulator.

SHOW_STATE_VECTOR = True

ddsim.job module

class DDSIMJob(backend, job_id, fn, qobj_experiment, **args)

Bases: JobV1

AerJob class.

_executor

executor to handle asynchronous jobs

Type:

futures.Executor

backend()

Return the instance of the backend used for this job.

cancel()

Attempt to cancel the job.

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:

• QobjValidationError – if the JSON serialization of the Qobj passed

• during construction does not validate against the Qobj schema. –

• JobError – if trying to re-submit the job.

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(configuration=None, provider=None)

Bases: BackendV1

Python interface to MQT DDSIM Simulation Path Framework.

SHOW_STATE_VECTOR = False

run(quantum_circuits, **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 list) – An individual or a list of QuantumCircuit or Schedule objects to run on the backend. For legacy providers migrating to the new versioned providers, provider interface a QasmQobj or PulseQobj objects should probably be supported too (but deprecated) for backwards compatibility. Be sure to update the docstrings of subclasses implementing this method to document that. New provider implementations should not do this though as qiskit.qobj will be deprecated and removed along with the legacy providers interface.

• 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

run_experiment(qobj_experiment, **options)

status()

Return backend status.

Returns:

BackendStatus – the status of the backend.

create_tensor_network(qc)

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

read_tensor_network_file(filename)

ddsim.pathstatevectorsimulator module

Backend for DDSIM.

class PathStatevectorSimulatorBackend(configuration=None, provider=None)

Bases: PathQasmSimulatorBackend

Python interface to MQT DDSIM Simulation Path Framework.

SHOW_STATE_VECTOR = True

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 used for filtering.

Returns:

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 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

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

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

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.

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 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.

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(configuration=None, provider=None)

Bases: BackendV1

Python interface to MQT DDSIM.

SHOW_STATE_VECTOR = False

run(quantum_circuits, **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 list) – An individual or a list of QuantumCircuit or Schedule objects to run on the backend. For legacy providers migrating to the new versioned providers, provider interface a QasmQobj or PulseQobj objects should probably be supported too (but deprecated) for backwards compatibility. Be sure to update the docstrings of subclasses implementing this method to document that. New provider implementations should not do this though as qiskit.qobj will be deprecated and removed along with the legacy providers interface.

• 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

run_experiment(qobj_experiment, **options)

Return type:

dict

status()

Return backend status.

Returns:

BackendStatus – the status of the backend.

ddsim.statevectorsimulator module

Backend for DDSIM.

class StatevectorSimulatorBackend(configuration=None, provider=None)

Bases: QasmSimulatorBackend

Python interface to MQT DDSIM.

SHOW_STATE_VECTOR = True

ddsim.unitarysimulator module

Backend for DDSIM Unitary Simulator.

class UnitarySimulatorBackend(configuration=None, provider=None, **fields)

Bases: BackendV1

Decision diagram-based unitary simulator.

run(quantum_circuits, **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 list) – An individual or a list of QuantumCircuit or Schedule objects to run on the backend. For legacy providers migrating to the new versioned providers, provider interface a QasmQobj or PulseQobj objects should probably be supported too (but deprecated) for backwards compatibility. Be sure to update the docstrings of subclasses implementing this method to document that. New provider implementations should not do this though as qiskit.qobj will be deprecated and removed along with the legacy providers interface.

• 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

run_experiment(qobj_experiment, **options)

Module contents

class CircuitSimulator

Bases: pybind11_object

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

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 used for filtering.

Returns:

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 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

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

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.

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