# This code is part of Qiskit. # # (C) Copyright IBM 2017, 2018. # # This code is licensed under the Apache License, Version 2.0. You may # obtain a copy of this license in the LICENSE.txt file in the root directory # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. # # Any modifications or derivative works of this code must retain this # copyright notice, and modified files need to carry a notice indicating # that they have been altered from the originals. """Backend Configuration Classes.""" import re import copy import numbers from typing import Dict, List, Any, Iterable, Tuple, Union from collections import defaultdict from qiskit.exceptions import QiskitError from qiskit.providers.exceptions import BackendConfigurationError from qiskit.pulse.channels import ( AcquireChannel, Channel, ControlChannel, DriveChannel, MeasureChannel, ) from qiskit.utils import deprecate_func class GateConfig: """Class representing a Gate Configuration Attributes: name: the gate name as it will be referred to in OpenQASM. parameters: variable names for the gate parameters (if any). qasm_def: definition of this gate in terms of OpenQASM 2 primitives U and CX. """ @deprecate_func( since="1.2", removal_timeline="in the 2.0 release", additional_msg="The models in ``qiskit.providers.models`` are part " "of the deprecated `BackendV1` workflow and no longer necessary for `BackendV2`. If a user " "workflow requires these representations it likely relies on deprecated functionality and " "should be updated to use `BackendV2`.", stacklevel=3, ) def __init__( self, name, parameters, qasm_def, coupling_map=None, latency_map=None, conditional=None, description=None, ): """Initialize a GateConfig object Args: name (str): the gate name as it will be referred to in OpenQASM. parameters (list): variable names for the gate parameters (if any) as a list of strings. qasm_def (str): definition of this gate in terms of OpenQASM 2 primitives U and CX. coupling_map (list): An optional coupling map for the gate. In the form of a list of lists of integers representing the qubit groupings which are coupled by this gate. latency_map (list): An optional map of latency for the gate. In the the form of a list of lists of integers of either 0 or 1 representing an array of dimension len(coupling_map) X n_registers that specifies the register latency (1: fast, 0: slow) conditional operations on the gate conditional (bool): Optionally specify whether this gate supports conditional operations (true/false). If this is not specified, then the gate inherits the conditional property of the backend. description (str): Description of the gate operation """ self.name = name self.parameters = parameters self.qasm_def = qasm_def # coupling_map with length 0 is invalid if coupling_map: self.coupling_map = coupling_map # latency_map with length 0 is invalid if latency_map: self.latency_map = latency_map if conditional is not None: self.conditional = conditional if description is not None: self.description = description @classmethod def from_dict(cls, data): """Create a new GateConfig object from a dictionary. Args: data (dict): A dictionary representing the GateConfig to create. It will be in the same format as output by :func:`to_dict`. Returns: GateConfig: The GateConfig from the input dictionary. """ return cls(**data) def to_dict(self): """Return a dictionary format representation of the GateConfig. Returns: dict: The dictionary form of the GateConfig. """ out_dict = { "name": self.name, "parameters": self.parameters, "qasm_def": self.qasm_def, } if hasattr(self, "coupling_map"): out_dict["coupling_map"] = self.coupling_map if hasattr(self, "latency_map"): out_dict["latency_map"] = self.latency_map if hasattr(self, "conditional"): out_dict["conditional"] = self.conditional if hasattr(self, "description"): out_dict["description"] = self.description return out_dict def __eq__(self, other): if isinstance(other, GateConfig): if self.to_dict() == other.to_dict(): return True return False def __repr__(self): out_str = f"GateConfig({self.name}, {self.parameters}, {self.qasm_def}" for i in ["coupling_map", "latency_map", "conditional", "description"]: if hasattr(self, i): out_str += ", " + repr(getattr(self, i)) out_str += ")" return out_str class UchannelLO: """Class representing a U Channel LO Attributes: q: Qubit that scale corresponds too. scale: Scale factor for qubit frequency. """ @deprecate_func( since="1.2", removal_timeline="in the 2.0 release", additional_msg="The models in ``qiskit.providers.models`` are part " "of the deprecated `BackendV1` workflow and no longer necessary for `BackendV2`. If a user " "workflow requires these representations it likely relies on deprecated functionality and " "should be updated to use `BackendV2`.", ) def __init__(self, q, scale): """Initialize a UchannelLOSchema object Args: q (int): Qubit that scale corresponds too. Must be >= 0. scale (complex): Scale factor for qubit frequency. Raises: QiskitError: If q is < 0 """ if q < 0: raise QiskitError("q must be >=0") self.q = q self.scale = scale @classmethod def from_dict(cls, data): """Create a new UchannelLO object from a dictionary. Args: data (dict): A dictionary representing the UChannelLO to create. It will be in the same format as output by :func:`to_dict`. Returns: UchannelLO: The UchannelLO from the input dictionary. """ return cls(**data) def to_dict(self): """Return a dictionary format representation of the UChannelLO. Returns: dict: The dictionary form of the UChannelLO. """ out_dict = { "q": self.q, "scale": self.scale, } return out_dict def __eq__(self, other): if isinstance(other, UchannelLO): if self.to_dict() == other.to_dict(): return True return False def __repr__(self): return f"UchannelLO({self.q}, {self.scale})" class QasmBackendConfiguration: """Class representing an OpenQASM 2.0 Backend Configuration. Attributes: backend_name: backend name. backend_version: backend version in the form X.Y.Z. n_qubits: number of qubits. basis_gates: list of basis gates names on the backend. gates: list of basis gates on the backend. local: backend is local or remote. simulator: backend is a simulator. conditional: backend supports conditional operations. open_pulse: backend supports open pulse. memory: backend supports memory. max_shots: maximum number of shots supported. """ _data = {} @deprecate_func( since="1.2", removal_timeline="in the 2.0 release", additional_msg="The models in ``qiskit.providers.models`` are part " "of the deprecated `BackendV1` workflow and no longer necessary for `BackendV2`. If a user " "workflow requires these representations it likely relies on deprecated functionality and " "should be updated to use `BackendV2`.", stacklevel=3, ) def __init__( self, backend_name, backend_version, n_qubits, basis_gates, gates, local, simulator, conditional, open_pulse, memory, max_shots, coupling_map, supported_instructions=None, dynamic_reprate_enabled=False, rep_delay_range=None, default_rep_delay=None, max_experiments=None, sample_name=None, n_registers=None, register_map=None, configurable=None, credits_required=None, online_date=None, display_name=None, description=None, tags=None, dt=None, dtm=None, processor_type=None, parametric_pulses=None, **kwargs, ): """Initialize a QasmBackendConfiguration Object Args: backend_name (str): The backend name backend_version (str): The backend version in the form X.Y.Z n_qubits (int): the number of qubits for the backend basis_gates (list): The list of strings for the basis gates of the backends gates (list): The list of GateConfig objects for the basis gates of the backend local (bool): True if the backend is local or False if remote simulator (bool): True if the backend is a simulator conditional (bool): True if the backend supports conditional operations open_pulse (bool): True if the backend supports OpenPulse memory (bool): True if the backend supports memory max_shots (int): The maximum number of shots allowed on the backend coupling_map (list): The coupling map for the device supported_instructions (List[str]): Instructions supported by the backend. dynamic_reprate_enabled (bool): whether delay between programs can be set dynamically (ie via ``rep_delay``). Defaults to False. rep_delay_range (List[float]): 2d list defining supported range of repetition delays for backend in μs. First entry is lower end of the range, second entry is higher end of the range. Optional, but will be specified when ``dynamic_reprate_enabled=True``. default_rep_delay (float): Value of ``rep_delay`` if not specified by user and ``dynamic_reprate_enabled=True``. max_experiments (int): The maximum number of experiments per job sample_name (str): Sample name for the backend n_registers (int): Number of register slots available for feedback (if conditional is True) register_map (list): An array of dimension n_qubits X n_registers that specifies whether a qubit can store a measurement in a certain register slot. configurable (bool): True if the backend is configurable, if the backend is a simulator credits_required (bool): True if backend requires credits to run a job. online_date (datetime.datetime): The date that the device went online display_name (str): Alternate name field for the backend description (str): A description for the backend tags (list): A list of string tags to describe the backend dt (float): Qubit drive channel timestep in nanoseconds. dtm (float): Measurement drive channel timestep in nanoseconds. processor_type (dict): Processor type for this backend. A dictionary of the form ``{"family": , "revision": , segment: }`` such as ``{"family": "Canary", "revision": "1.0", segment: "A"}``. - family: Processor family of this backend. - revision: Revision version of this processor. - segment: Segment this processor belongs to within a larger chip. parametric_pulses (list): A list of pulse shapes which are supported on the backend. For example: ``['gaussian', 'constant']`` **kwargs: optional fields """ self._data = {} self.backend_name = backend_name self.backend_version = backend_version self.n_qubits = n_qubits self.basis_gates = basis_gates self.gates = gates self.local = local self.simulator = simulator self.conditional = conditional self.open_pulse = open_pulse self.memory = memory self.max_shots = max_shots self.coupling_map = coupling_map if supported_instructions: self.supported_instructions = supported_instructions self.dynamic_reprate_enabled = dynamic_reprate_enabled if rep_delay_range: self.rep_delay_range = [_rd * 1e-6 for _rd in rep_delay_range] # convert to sec if default_rep_delay is not None: self.default_rep_delay = default_rep_delay * 1e-6 # convert to sec # max_experiments must be >=1 if max_experiments: self.max_experiments = max_experiments if sample_name is not None: self.sample_name = sample_name # n_registers must be >=1 if n_registers: self.n_registers = 1 # register_map must have at least 1 entry if register_map: self.register_map = register_map if configurable is not None: self.configurable = configurable if credits_required is not None: self.credits_required = credits_required if online_date is not None: self.online_date = online_date if display_name is not None: self.display_name = display_name if description is not None: self.description = description if tags is not None: self.tags = tags # Add pulse properties here because some backends do not # fit within the Qasm / Pulse backend partitioning in Qiskit if dt is not None: self.dt = dt * 1e-9 if dtm is not None: self.dtm = dtm * 1e-9 if processor_type is not None: self.processor_type = processor_type if parametric_pulses is not None: self.parametric_pulses = parametric_pulses # convert lo range from GHz to Hz if "qubit_lo_range" in kwargs: kwargs["qubit_lo_range"] = [ [min_range * 1e9, max_range * 1e9] for (min_range, max_range) in kwargs["qubit_lo_range"] ] if "meas_lo_range" in kwargs: kwargs["meas_lo_range"] = [ [min_range * 1e9, max_range * 1e9] for (min_range, max_range) in kwargs["meas_lo_range"] ] # convert rep_times from μs to sec if "rep_times" in kwargs: kwargs["rep_times"] = [_rt * 1e-6 for _rt in kwargs["rep_times"]] self._data.update(kwargs) def __getattr__(self, name): try: return self._data[name] except KeyError as ex: raise AttributeError(f"Attribute {name} is not defined") from ex @classmethod def from_dict(cls, data): """Create a new GateConfig object from a dictionary. Args: data (dict): A dictionary representing the GateConfig to create. It will be in the same format as output by :func:`to_dict`. Returns: GateConfig: The GateConfig from the input dictionary. """ in_data = copy.copy(data) gates = [GateConfig.from_dict(x) for x in in_data.pop("gates")] in_data["gates"] = gates return cls(**in_data) def to_dict(self): """Return a dictionary format representation of the GateConfig. Returns: dict: The dictionary form of the GateConfig. """ out_dict = { "backend_name": self.backend_name, "backend_version": self.backend_version, "n_qubits": self.n_qubits, "basis_gates": self.basis_gates, "gates": [x.to_dict() for x in self.gates], "local": self.local, "simulator": self.simulator, "conditional": self.conditional, "open_pulse": self.open_pulse, "memory": self.memory, "max_shots": self.max_shots, "coupling_map": self.coupling_map, "dynamic_reprate_enabled": self.dynamic_reprate_enabled, } if hasattr(self, "supported_instructions"): out_dict["supported_instructions"] = self.supported_instructions if hasattr(self, "rep_delay_range"): out_dict["rep_delay_range"] = [_rd * 1e6 for _rd in self.rep_delay_range] if hasattr(self, "default_rep_delay"): out_dict["default_rep_delay"] = self.default_rep_delay * 1e6 for kwarg in [ "max_experiments", "sample_name", "n_registers", "register_map", "configurable", "credits_required", "online_date", "display_name", "description", "tags", "dt", "dtm", "processor_type", "parametric_pulses", ]: if hasattr(self, kwarg): out_dict[kwarg] = getattr(self, kwarg) out_dict.update(self._data) if "dt" in out_dict: out_dict["dt"] *= 1e9 if "dtm" in out_dict: out_dict["dtm"] *= 1e9 # Use GHz in dict if "qubit_lo_range" in out_dict: out_dict["qubit_lo_range"] = [ [min_range * 1e-9, max_range * 1e-9] for (min_range, max_range) in out_dict["qubit_lo_range"] ] if "meas_lo_range" in out_dict: out_dict["meas_lo_range"] = [ [min_range * 1e-9, max_range * 1e-9] for (min_range, max_range) in out_dict["meas_lo_range"] ] return out_dict @property def num_qubits(self): """Returns the number of qubits. In future, `n_qubits` should be replaced in favor of `num_qubits` for consistent use throughout Qiskit. Until this is properly refactored, this property serves as intermediate solution. """ return self.n_qubits def __eq__(self, other): if isinstance(other, QasmBackendConfiguration): if self.to_dict() == other.to_dict(): return True return False def __contains__(self, item): return item in self.__dict__ class BackendConfiguration(QasmBackendConfiguration): """Backwards compatibility shim representing an abstract backend configuration.""" @deprecate_func( since="1.2", removal_timeline="in the 2.0 release", additional_msg="The models in ``qiskit.providers.models`` are part " "of the deprecated `BackendV1` workflow and no longer necessary for `BackendV2`. If a user " "workflow requires these representations it likely relies on deprecated functionality and " "should be updated to use `BackendV2`.", stacklevel=3, ) def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) class PulseBackendConfiguration(QasmBackendConfiguration): """Static configuration state for an OpenPulse enabled backend. This contains information about the set up of the device which can be useful for building Pulse programs. """ @deprecate_func( since="1.2", removal_timeline="in the 2.0 release", additional_msg="The models in ``qiskit.providers.models`` are part " "of the deprecated `BackendV1` workflow and no longer necessary for `BackendV2`. If a user " "workflow requires these representations it likely relies on deprecated functionality and " "should be updated to use `BackendV2`.", stacklevel=3, ) def __init__( self, backend_name: str, backend_version: str, n_qubits: int, basis_gates: List[str], gates: GateConfig, local: bool, simulator: bool, conditional: bool, open_pulse: bool, memory: bool, max_shots: int, coupling_map, n_uchannels: int, u_channel_lo: List[List[UchannelLO]], meas_levels: List[int], qubit_lo_range: List[List[float]], meas_lo_range: List[List[float]], dt: float, dtm: float, rep_times: List[float], meas_kernels: List[str], discriminators: List[str], hamiltonian: Dict[str, Any] = None, channel_bandwidth=None, acquisition_latency=None, conditional_latency=None, meas_map=None, max_experiments=None, sample_name=None, n_registers=None, register_map=None, configurable=None, credits_required=None, online_date=None, display_name=None, description=None, tags=None, channels: Dict[str, Any] = None, **kwargs, ): """ Initialize a backend configuration that contains all the extra configuration that is made available for OpenPulse backends. Args: backend_name: backend name. backend_version: backend version in the form X.Y.Z. n_qubits: number of qubits. basis_gates: list of basis gates names on the backend. gates: list of basis gates on the backend. local: backend is local or remote. simulator: backend is a simulator. conditional: backend supports conditional operations. open_pulse: backend supports open pulse. memory: backend supports memory. max_shots: maximum number of shots supported. coupling_map (list): The coupling map for the device n_uchannels: Number of u-channels. u_channel_lo: U-channel relationship on device los. meas_levels: Supported measurement levels. qubit_lo_range: Qubit lo ranges for each qubit with form (min, max) in GHz. meas_lo_range: Measurement lo ranges for each qubit with form (min, max) in GHz. dt: Qubit drive channel timestep in nanoseconds. dtm: Measurement drive channel timestep in nanoseconds. rep_times: Supported repetition times (program execution time) for backend in μs. meas_kernels: Supported measurement kernels. discriminators: Supported discriminators. hamiltonian: An optional dictionary with fields characterizing the system hamiltonian. channel_bandwidth (list): Bandwidth of all channels (qubit, measurement, and U) acquisition_latency (list): Array of dimension n_qubits x n_registers. Latency (in units of dt) to write a measurement result from qubit n into register slot m. conditional_latency (list): Array of dimension n_channels [d->u->m] x n_registers. Latency (in units of dt) to do a conditional operation on channel n from register slot m meas_map (list): Grouping of measurement which are multiplexed max_experiments (int): The maximum number of experiments per job sample_name (str): Sample name for the backend n_registers (int): Number of register slots available for feedback (if conditional is True) register_map (list): An array of dimension n_qubits X n_registers that specifies whether a qubit can store a measurement in a certain register slot. configurable (bool): True if the backend is configurable, if the backend is a simulator credits_required (bool): True if backend requires credits to run a job. online_date (datetime.datetime): The date that the device went online display_name (str): Alternate name field for the backend description (str): A description for the backend tags (list): A list of string tags to describe the backend channels: An optional dictionary containing information of each channel -- their purpose, type, and qubits operated on. **kwargs: Optional fields. """ self.n_uchannels = n_uchannels self.u_channel_lo = u_channel_lo self.meas_levels = meas_levels # convert from GHz to Hz self.qubit_lo_range = [ [min_range * 1e9, max_range * 1e9] for (min_range, max_range) in qubit_lo_range ] self.meas_lo_range = [ [min_range * 1e9, max_range * 1e9] for (min_range, max_range) in meas_lo_range ] self.meas_kernels = meas_kernels self.discriminators = discriminators self.hamiltonian = hamiltonian if hamiltonian is not None: self.hamiltonian = dict(hamiltonian) self.hamiltonian["vars"] = { k: v * 1e9 if isinstance(v, numbers.Number) else v for k, v in self.hamiltonian["vars"].items() } self.rep_times = [_rt * 1e-6 for _rt in rep_times] # convert to sec self.dt = dt * 1e-9 self.dtm = dtm * 1e-9 if channels is not None: self.channels = channels ( self._qubit_channel_map, self._channel_qubit_map, self._control_channels, ) = self._parse_channels(channels=channels) else: self._control_channels = defaultdict(list) if channel_bandwidth is not None: self.channel_bandwidth = [ [min_range * 1e9, max_range * 1e9] for (min_range, max_range) in channel_bandwidth ] if acquisition_latency is not None: self.acquisition_latency = acquisition_latency if conditional_latency is not None: self.conditional_latency = conditional_latency if meas_map is not None: self.meas_map = meas_map super().__init__( backend_name=backend_name, backend_version=backend_version, n_qubits=n_qubits, basis_gates=basis_gates, gates=gates, local=local, simulator=simulator, conditional=conditional, open_pulse=open_pulse, memory=memory, max_shots=max_shots, coupling_map=coupling_map, max_experiments=max_experiments, sample_name=sample_name, n_registers=n_registers, register_map=register_map, configurable=configurable, credits_required=credits_required, online_date=online_date, display_name=display_name, description=description, tags=tags, **kwargs, ) @classmethod def from_dict(cls, data): """Create a new GateConfig object from a dictionary. Args: data (dict): A dictionary representing the GateConfig to create. It will be in the same format as output by :func:`to_dict`. Returns: GateConfig: The GateConfig from the input dictionary. """ in_data = copy.copy(data) gates = [GateConfig.from_dict(x) for x in in_data.pop("gates")] in_data["gates"] = gates input_uchannels = in_data.pop("u_channel_lo") u_channels = [] for channel in input_uchannels: u_channels.append([UchannelLO.from_dict(x) for x in channel]) in_data["u_channel_lo"] = u_channels return cls(**in_data) def to_dict(self): """Return a dictionary format representation of the GateConfig. Returns: dict: The dictionary form of the GateConfig. """ out_dict = super().to_dict() u_channel_lo = [] for x in self.u_channel_lo: channel = [] for y in x: channel.append(y.to_dict()) u_channel_lo.append(channel) out_dict.update( { "n_uchannels": self.n_uchannels, "u_channel_lo": u_channel_lo, "meas_levels": self.meas_levels, "qubit_lo_range": self.qubit_lo_range, "meas_lo_range": self.meas_lo_range, "meas_kernels": self.meas_kernels, "discriminators": self.discriminators, "rep_times": self.rep_times, "dt": self.dt, "dtm": self.dtm, } ) if hasattr(self, "channel_bandwidth"): out_dict["channel_bandwidth"] = self.channel_bandwidth if hasattr(self, "meas_map"): out_dict["meas_map"] = self.meas_map if hasattr(self, "acquisition_latency"): out_dict["acquisition_latency"] = self.acquisition_latency if hasattr(self, "conditional_latency"): out_dict["conditional_latency"] = self.conditional_latency if "channels" in out_dict: out_dict.pop("_qubit_channel_map") out_dict.pop("_channel_qubit_map") out_dict.pop("_control_channels") # Use GHz in dict if self.qubit_lo_range: out_dict["qubit_lo_range"] = [ [min_range * 1e-9, max_range * 1e-9] for (min_range, max_range) in self.qubit_lo_range ] if self.meas_lo_range: out_dict["meas_lo_range"] = [ [min_range * 1e-9, max_range * 1e-9] for (min_range, max_range) in self.meas_lo_range ] if self.rep_times: out_dict["rep_times"] = [_rt * 1e6 for _rt in self.rep_times] out_dict["dt"] *= 1e9 out_dict["dtm"] *= 1e9 if hasattr(self, "channel_bandwidth"): out_dict["channel_bandwidth"] = [ [min_range * 1e-9, max_range * 1e-9] for (min_range, max_range) in self.channel_bandwidth ] if self.hamiltonian: hamiltonian = copy.deepcopy(self.hamiltonian) hamiltonian["vars"] = { k: v * 1e-9 if isinstance(v, numbers.Number) else v for k, v in hamiltonian["vars"].items() } out_dict["hamiltonian"] = hamiltonian if hasattr(self, "channels"): out_dict["channels"] = self.channels return out_dict def __eq__(self, other): if isinstance(other, QasmBackendConfiguration): if self.to_dict() == other.to_dict(): return True return False @property def sample_rate(self) -> float: """Sample rate of the signal channels in Hz (1/dt).""" return 1.0 / self.dt @property def control_channels(self) -> Dict[Tuple[int, ...], List]: """Return the control channels""" return self._control_channels def drive(self, qubit: int) -> DriveChannel: """ Return the drive channel for the given qubit. Raises: BackendConfigurationError: If the qubit is not a part of the system. Returns: Qubit drive channel. """ if not 0 <= qubit < self.n_qubits: raise BackendConfigurationError(f"Invalid index for {qubit}-qubit system.") return DriveChannel(qubit) def measure(self, qubit: int) -> MeasureChannel: """ Return the measure stimulus channel for the given qubit. Raises: BackendConfigurationError: If the qubit is not a part of the system. Returns: Qubit measurement stimulus line. """ if not 0 <= qubit < self.n_qubits: raise BackendConfigurationError(f"Invalid index for {qubit}-qubit system.") return MeasureChannel(qubit) def acquire(self, qubit: int) -> AcquireChannel: """ Return the acquisition channel for the given qubit. Raises: BackendConfigurationError: If the qubit is not a part of the system. Returns: Qubit measurement acquisition line. """ if not 0 <= qubit < self.n_qubits: raise BackendConfigurationError(f"Invalid index for {qubit}-qubit systems.") return AcquireChannel(qubit) def control(self, qubits: Iterable[int] = None) -> List[ControlChannel]: """ Return the secondary drive channel for the given qubit -- typically utilized for controlling multiqubit interactions. This channel is derived from other channels. Args: qubits: Tuple or list of qubits of the form `(control_qubit, target_qubit)`. Raises: BackendConfigurationError: If the ``qubits`` is not a part of the system or if the backend does not provide `channels` information in its configuration. Returns: List of control channels. """ try: if isinstance(qubits, list): qubits = tuple(qubits) return self._control_channels[qubits] except KeyError as ex: raise BackendConfigurationError( f"Couldn't find the ControlChannel operating on qubits {qubits} on " f"{self.n_qubits}-qubit system. The ControlChannel information is retrieved " "from the backend." ) from ex except AttributeError as ex: raise BackendConfigurationError( f"This backend - '{self.backend_name}' does not provide channel information." ) from ex def get_channel_qubits(self, channel: Channel) -> List[int]: """ Return a list of indices for qubits which are operated on directly by the given ``channel``. Raises: BackendConfigurationError: If ``channel`` is not a found or if the backend does not provide `channels` information in its configuration. Returns: List of qubits operated on my the given ``channel``. """ try: return self._channel_qubit_map[channel] except KeyError as ex: raise BackendConfigurationError(f"Couldn't find the Channel - {channel}") from ex except AttributeError as ex: raise BackendConfigurationError( f"This backend - '{self.backend_name}' does not provide channel information." ) from ex def get_qubit_channels(self, qubit: Union[int, Iterable[int]]) -> List[Channel]: r"""Return a list of channels which operate on the given ``qubit``. Raises: BackendConfigurationError: If ``qubit`` is not a found or if the backend does not provide `channels` information in its configuration. Returns: List of ``Channel``\s operated on my the given ``qubit``. """ channels = set() try: if isinstance(qubit, int): for key, value in self._qubit_channel_map.items(): if qubit in key: channels.update(value) if len(channels) == 0: raise KeyError elif isinstance(qubit, list): qubit = tuple(qubit) channels.update(self._qubit_channel_map[qubit]) elif isinstance(qubit, tuple): channels.update(self._qubit_channel_map[qubit]) return list(channels) except KeyError as ex: raise BackendConfigurationError(f"Couldn't find the qubit - {qubit}") from ex except AttributeError as ex: raise BackendConfigurationError( f"This backend - '{self.backend_name}' does not provide channel information." ) from ex def describe(self, channel: ControlChannel) -> Dict[DriveChannel, complex]: """ Return a basic description of the channel dependency. Derived channels are given weights which describe how their frames are linked to other frames. For instance, the backend could be configured with this setting:: u_channel_lo = [ [UchannelLO(q=0, scale=1. + 0.j)], [UchannelLO(q=0, scale=-1. + 0.j), UchannelLO(q=1, scale=1. + 0.j)] ] Then, this method can be used as follows:: backend.configuration().describe(ControlChannel(1)) >>> {DriveChannel(0): -1, DriveChannel(1): 1} Args: channel: The derived channel to describe. Raises: BackendConfigurationError: If channel is not a ControlChannel. Returns: Control channel derivations. """ if not isinstance(channel, ControlChannel): raise BackendConfigurationError("Can only describe ControlChannels.") result = {} for u_chan_lo in self.u_channel_lo[channel.index]: result[DriveChannel(u_chan_lo.q)] = u_chan_lo.scale return result def _parse_channels(self, channels: Dict[set, Any]) -> Dict[Any, Any]: r""" Generates a dictionaries of ``Channel``\s, and tuple of qubit(s) they operate on. Args: channels: An optional dictionary containing information of each channel -- their purpose, type, and qubits operated on. Returns: qubit_channel_map: Dictionary mapping tuple of qubit(s) to list of ``Channel``\s. channel_qubit_map: Dictionary mapping ``Channel`` to list of qubit(s). control_channels: Dictionary mapping tuple of qubit(s), to list of ``ControlChannel``\s. """ qubit_channel_map = defaultdict(list) channel_qubit_map = defaultdict(list) control_channels = defaultdict(list) channels_dict = { DriveChannel.prefix: DriveChannel, ControlChannel.prefix: ControlChannel, MeasureChannel.prefix: MeasureChannel, "acquire": AcquireChannel, } for channel, config in channels.items(): channel_prefix, index = self._get_channel_prefix_index(channel) channel_type = channels_dict[channel_prefix] qubits = tuple(config["operates"]["qubits"]) if channel_prefix in channels_dict: qubit_channel_map[qubits].append(channel_type(index)) channel_qubit_map[(channel_type(index))].extend(list(qubits)) if channel_prefix == ControlChannel.prefix: control_channels[qubits].append(channel_type(index)) return dict(qubit_channel_map), dict(channel_qubit_map), dict(control_channels) def _get_channel_prefix_index(self, channel: str) -> str: """Return channel prefix and index from the given ``channel``. Args: channel: Name of channel. Raises: BackendConfigurationError: If invalid channel name is found. Return: Channel name and index. For example, if ``channel=acquire0``, this method returns ``acquire`` and ``0``. """ channel_prefix = re.match(r"(?P[a-z]+)(?P[0-9]+)", channel) try: return channel_prefix.group("channel"), int(channel_prefix.group("index")) except AttributeError as ex: raise BackendConfigurationError(f"Invalid channel name - '{channel}' found.") from ex