tensorcircuit.noisemodel#
General Noise Model Construction.
- class tensorcircuit.noisemodel.NoiseConf[source]#
Bases:
object
Noise Configuration
class.error1 = tc.channels.generaldepolarizingchannel(0.1, 1) error2 = tc.channels.thermalrelaxationchannel(300, 400, 100, "ByChoi", 0) readout_error = [[0.9, 0.75], [0.4, 0.7]] noise_conf = NoiseConf() noise_conf.add_noise("x", error1) noise_conf.add_noise("h", [error1, error2], [[0], [1]]) noise_conf.add_noise("readout", readout_error)
- add_noise(gate_name: str, kraus: Union[tensorcircuit.channels.KrausList, Sequence[tensorcircuit.channels.KrausList]], qubit: Optional[Sequence[Any]] = None) None [source]#
Add noise channels on specific gates and specific qubits in form of Kraus operators.
- Parameters
gate_name (str) – noisy gate
kraus (Sequence[Gate]) – noise channel
qubit (Optional[Sequence[Any]], optional) – the list of noisy qubit, defaults to None, indicating applying the noise channel on all qubits
- add_noise_by_condition(condition: Callable[[Dict[str, Any]], bool], kraus: tensorcircuit.channels.KrausList, name: Optional[Any] = 'custom') None [source]#
Add noise based on specified condition
- Parameters
condition (Callable[[Dict[str, Any]], bool]) – a function to decide if the noise should be added to the qir.
kraus (KrausList) – the error channel
name (Any) – the name of the condition. A metadata that does not affect the numerics.
- channel_count(c: tensorcircuit.circuit.Circuit) int [source]#
Count the total number of channels in a given circuit
- Parameters
c (Circuit) – the circuit to be counted
- Returns
the count
- Return type
int
- tensorcircuit.noisemodel.apply_qir_with_noise(c: Any, qir: List[Dict[str, Any]], noise_conf: tensorcircuit.noisemodel.NoiseConf, status: Optional[Any] = None) Any [source]#
- Parameters
c (AbstractCircuit) – A newly defined circuit
qir (List[Dict[str, Any]]) – The qir of the clean circuit
noise_conf (NoiseConf) – Noise Configuration
status (1D Tensor, optional) – The status for Monte Carlo sampling, defaults to None
- Returns
A newly constructed circuit with noise
- Return type
- tensorcircuit.noisemodel.circuit_with_noise(c: tensorcircuit.abstractcircuit.AbstractCircuit, noise_conf: tensorcircuit.noisemodel.NoiseConf, status: Optional[Any] = None) Any [source]#
Noisify a clean circuit.
- Parameters
c (AbstractCircuit) – A clean circuit
noise_conf (NoiseConf) – Noise Configuration
status (1D Tensor, optional) – The status for Monte Carlo sampling, defaults to None
- Returns
A newly constructed circuit with noise
- Return type
- tensorcircuit.noisemodel.expectation_noisfy(c: Any, *ops: Tuple[tensornetwork.network_components.Node, List[int]], noise_conf: Optional[tensorcircuit.noisemodel.NoiseConf] = None, nmc: int = 1000, status: Optional[Any] = None, **kws: Any) Any [source]#
Calculate expectation value with noise configuration.
- Parameters
c (Any) – The clean circuit
noise_conf (Optional[NoiseConf], optional) – Noise Configuration, defaults to None
nmc (int, optional) – repetition time for Monte Carlo sampling for noisfy calculation, defaults to 1000
status (Optional[Tensor], optional) – external randomness given by tensor uniformly from [0, 1], defaults to None, used for noisfy circuit sampling
- Returns
expectation value with noise
- Return type
Tensor
- tensorcircuit.noisemodel.sample_expectation_ps_noisfy(c: Any, x: Optional[Sequence[int]] = None, y: Optional[Sequence[int]] = None, z: Optional[Sequence[int]] = None, noise_conf: Optional[tensorcircuit.noisemodel.NoiseConf] = None, nmc: int = 1000, shots: Optional[int] = None, statusc: Optional[Any] = None, status: Optional[Any] = None, **kws: Any) Any [source]#
Calculate sample_expectation_ps with noise configuration.
- Parameters
c (Any) – The clean circuit
x (Optional[Sequence[int]], optional) – sites to apply X gate, defaults to None
y (Optional[Sequence[int]], optional) – sites to apply Y gate, defaults to None
z (Optional[Sequence[int]], optional) – sites to apply Z gate, defaults to None
noise_conf (Optional[NoiseConf], optional) – Noise Configuration, defaults to None
nmc (int, optional) – repetition time for Monte Carlo sampling for noisfy calculation, defaults to 1000
shots (Optional[int], optional) – number of measurement shots, defaults to None, indicating analytical result
statusc (Optional[Tensor], optional) – external randomness given by tensor uniformly from [0, 1], defaults to None, used for noisfy circuit sampling
status (Optional[Tensor], optional) – external randomness given by tensor uniformly from [0, 1], defaults to None, used for measurement sampling
- Returns
sample expectation value with noise
- Return type
Tensor