pygsti.models.oplessmodel

Defines the OplessModel class

Module Contents

Classes

OplessModel	A model that does not have independent component operations.
SuccessFailModel	An op-less model that always outputs 2 (success & failure) probabilities for each circuit.
ErrorRatesModel	A success-fail model based on per-gate error rates.
TwirledLayersModel	A model where twirled-layer error rates are computed and multiplied together to compute success probabilities.
TwirledGatesModel	A model where twirled-gate error rates are computed and multiplied together to compute success probabilities.
AnyErrorCausesFailureModel	A model where any gate failure causes a circuit failure.
AnyErrorCausesRandomOutputModel	A model where any gate error causes a random circuit output.

class pygsti.models.oplessmodel.OplessModel(state_space)

Bases: pygsti.models.model.Model

A model that does not have independent component operations.

OplessModel-derived classes often implement coarser models that predict the success or outcome probability of a circuit based on simple properties of the circuit and not detailed gate-level modeling.

Parameters

state_spaceStateSpace

The state space of this model.

property dim

property parameter_bounds

Upper and lower bounds on the values of each parameter, utilized by optimization routines

basis = 'None'

abstractmethod circuit_outcomes(circuit)

Get all the possible outcome labels produced by simulating this circuit.

Parameters

circuitCircuit

Circuit to get outcomes of.

Returns

tuple

abstractmethod probabilities(circuit, outcomes=None, time=None)

Construct a dictionary containing the outcome probabilities of circuit.

Parameters

circuitCircuit or tuple of operation labels

The sequence of operation labels specifying the circuit.

outcomeslist or tuple

A sequence of outcomes, which can themselves be either tuples (to include intermediate measurements) or simple strings, e.g. ‘010’.

timefloat, optional

The start time at which circuit is evaluated.

Returns

probsOutcomeLabelDict

A dictionary with keys equal to outcome labels and values equal to probabilities.

abstractmethod bulk_probabilities(circuits, clip_to=None, comm=None, mem_limit=None, smartc=None)

Construct a dictionary containing the probabilities for an entire list of circuits.

Parameters

circuits(list of Circuits) or CircuitOutcomeProbabilityArrayLayout

When a list, each element specifies a circuit to compute outcome probabilities for. A CircuitOutcomeProbabilityArrayLayout specifies the circuits along with an internal memory layout that reduces the time required by this function and can restrict the computed probabilities to those corresponding to only certain outcomes.

clip_to2-tuple, optional

(min,max) to clip return value if not None.

commmpi4py.MPI.Comm, optional

When not None, an MPI communicator for distributing the computation across multiple processors. Distribution is performed over subtrees of evalTree (if it is split).

mem_limitint, optional

A rough memory limit in bytes which is used to determine processor allocation.

smartcSmartCache, optional

A cache object to cache & use previously cached values inside this function.

Returns

probsdictionary

A dictionary such that probs[opstr] is an ordered dictionary of (outcome, p) tuples, where outcome is a tuple of labels and p is the corresponding probability.

class pygsti.models.oplessmodel.SuccessFailModel(state_space, use_cache=False)

Bases: OplessModel

An op-less model that always outputs 2 (success & failure) probabilities for each circuit.

Parameters

state_spaceStateSpace

The state space of this model.

use_cachebool, optional

Whether a cache should be used to increase performance.

property sim

Forward simulator for this model

use_cache = 'False'

circuit_outcomes(circuit)

Get all the possible outcome labels produced by simulating this circuit.

Parameters

circuitCircuit

Circuit to get outcomes of.

Returns

tuple

probabilities(circuit, outcomes=None, time=None)

Construct a dictionary containing the outcome probabilities of circuit.

Parameters

circuitCircuit or tuple of operation labels

The sequence of operation labels specifying the circuit.

outcomeslist or tuple

A sequence of outcomes, which can themselves be either tuples (to include intermediate measurements) or simple strings, e.g. ‘010’.

timefloat, optional

The start time at which circuit is evaluated.

Returns

probsOutcomeLabelDict

A dictionary with keys equal to outcome labels and values equal to probabilities.

bulk_probabilities(circuits, clip_to=None, comm=None, mem_limit=None, smartc=None)

Construct a dictionary containing the probabilities for an entire list of circuits.

Parameters

circuits(list of Circuits) or CircuitOutcomeProbabilityArrayLayout

When a list, each element specifies a circuit to compute outcome probabilities for. A CircuitOutcomeProbabilityArrayLayout specifies the circuits along with an internal memory layout that reduces the time required by this function and can restrict the computed probabilities to those corresponding to only certain outcomes.

clip_to2-tuple, optional

(min,max) to clip return value if not None.

commmpi4py.MPI.Comm, optional

When not None, an MPI communicator for distributing the computation across multiple processors. Distribution is performed over subtrees of evalTree (if it is split).

mem_limitint, optional

A rough memory limit in bytes which is used to determine processor allocation.

smartcSmartCache, optional

A cache object to cache & use previously cached values inside this function.

Returns

probsdictionary

A dictionary such that probs[opstr] is an ordered dictionary of (outcome, p) tuples, where outcome is a tuple of labels and p is the corresponding probability.

class pygsti.models.oplessmodel.ErrorRatesModel(error_rates, num_qubits, state_space_labels=None, alias_dict=None, idle_name='Gi')

Bases: SuccessFailModel

A success-fail model based on per-gate error rates.

Parameters

error_ratesdict

A dictionary with “gates” and “readout” keys, each of which corresponds to a dictionary of error-rates for gates or SPAM elements, respectively.

num_qubitsint

The number of qubits in the model.

state_space_labelsStateSpaceLabels or list or tuple

The decomposition (with labels) of (pure) state-space this model acts upon. Regardless of whether the model contains operators or superoperators, this argument describes the Hilbert space dimension and imposed structure. If a list or tuple is given, it must be of a from that can be passed to StateSpaceLabels.__init__.

alias_dictdict, optional

An alias dictionary mapping the gate labels in circuits to the keys of a (nested) error_rates dictionary. This allows, for instance, many gates’ error rates to be set by the same model parameter.

idle_namestr, optional

The gate name to be used for the 1-qubit idle gate (this should be set in error_rates to add idle errors.

property primitive_op_labels

property primitive_instrument_labels

to_dict()

Convert this model to a dictionary (for debugging or easy printing).

class pygsti.models.oplessmodel.TwirledLayersModel(error_rates, num_qubits, state_space_labels=None, alias_dict=None, idle_name='Gi')

Bases: ErrorRatesModel

A model where twirled-layer error rates are computed and multiplied together to compute success probabilities.

In this model, the success probability of a circuit is the product of 1.0 - alpha * pfail terms, one per layer of the circuit (including idles). The pfail of a circuit layer is given as 1 - prod(1 - error_rate_i), where i ranges over the gates in the layer. alpha is the constant 4^w / (4^w - 1) where w is the circuit width.

Parameters

error_ratesdict

A dictionary with “gates” and “readout” keys, each of which corresponds to a dictionary of error-rates for gates or SPAM elements, respectively.

num_qubitsint

The number of qubits in the model.

state_space_labelsStateSpaceLabels or list or tuple

The decomposition (with labels) of (pure) state-space this model acts upon. Regardless of whether the model contains operators or superoperators, this argument describes the Hilbert space dimension and imposed structure. If a list or tuple is given, it must be of a from that can be passed to StateSpaceLabels.__init__.

alias_dictdict, optional

An alias dictionary mapping the gate labels in circuits to the keys of a (nested) error_rates dictionary. This allows, for instance, many gates’ error rates to be set by the same model parameter.

idle_namestr, optional

The gate name to be used for the 1-qubit idle gate (this should be set in error_rates to add idle errors.

class pygsti.models.oplessmodel.TwirledGatesModel(error_rates, num_qubits, state_space_labels=None, alias_dict=None, idle_name='Gi')

Bases: ErrorRatesModel

A model where twirled-gate error rates are computed and multiplied together to compute success probabilities.

In this model, the success probability of a circuit is the product of 1.0 - alpha * pfail terms, one per gate of the circuit (including idles). The pfail of a gate is given as 1 - error_rate, and alpha is the constant 4^w / (4^w - 1) where w is the circuit width.

Parameters

error_ratesdict

A dictionary with “gates” and “readout” keys, each of which corresponds to a dictionary of error-rates for gates or SPAM elements, respectively.

num_qubitsint

The number of qubits in the model.

state_space_labelsStateSpaceLabels or list or tuple

The decomposition (with labels) of (pure) state-space this model acts upon. Regardless of whether the model contains operators or superoperators, this argument describes the Hilbert space dimension and imposed structure. If a list or tuple is given, it must be of a from that can be passed to StateSpaceLabels.__init__.

alias_dictdict, optional

An alias dictionary mapping the gate labels in circuits to the keys of a (nested) error_rates dictionary. This allows, for instance, many gates’ error rates to be set by the same model parameter.

idle_namestr, optional

The gate name to be used for the 1-qubit idle gate (this should be set in error_rates to add idle errors.

todo

class pygsti.models.oplessmodel.AnyErrorCausesFailureModel(error_rates, num_qubits, state_space_labels=None, alias_dict=None, idle_name='Gi')

Bases: ErrorRatesModel

A model where any gate failure causes a circuit failure.

Specifically, the success probability of a circuit is give by 1 - prod(1 - error_rate_i) where i ranges over all the gates in the circuit. That is, a circuit success probability is just the product of all its gate success probabilities. In this pessimistic model, any gate failure causes the circuit to fail.

Parameters

error_ratesdict

A dictionary with “gates” and “readout” keys, each of which corresponds to a dictionary of error-rates for gates or SPAM elements, respectively.

num_qubitsint

The number of qubits in the model.

state_space_labelsStateSpaceLabels or list or tuple

The decomposition (with labels) of (pure) state-space this model acts upon. Regardless of whether the model contains operators or superoperators, this argument describes the Hilbert space dimension and imposed structure. If a list or tuple is given, it must be of a from that can be passed to StateSpaceLabels.__init__.

alias_dictdict, optional

An alias dictionary mapping the gate labels in circuits to the keys of a (nested) error_rates dictionary. This allows, for instance, many gates’ error rates to be set by the same model parameter.

idle_namestr, optional

The gate name to be used for the 1-qubit idle gate (this should be set in error_rates to add idle errors.

class pygsti.models.oplessmodel.AnyErrorCausesRandomOutputModel(error_rates, num_qubits, state_space_labels=None, alias_dict=None, idle_name='Gi')

Bases: ErrorRatesModel

A model where any gate error causes a random circuit output.

Specifically, the success probability of a circuit is give by all_ok + (1 - all_ok) * 1 / 2^circuit_width where all_ok is the probability that all the gates succeed: all_ok = 1 - prod(1 - error_rate_i) with i ranging over all the gates in the circuit. In this model, any gate failure causes the circuit to produce a random output.

Parameters

error_ratesdict

A dictionary with “gates” and “readout” keys, each of which corresponds to a dictionary of error-rates for gates or SPAM elements, respectively.

num_qubitsint

The number of qubits in the model.

state_space_labelsStateSpaceLabels or list or tuple

The decomposition (with labels) of (pure) state-space this model acts upon. Regardless of whether the model contains operators or superoperators, this argument describes the Hilbert space dimension and imposed structure. If a list or tuple is given, it must be of a from that can be passed to StateSpaceLabels.__init__.

alias_dictdict, optional

An alias dictionary mapping the gate labels in circuits to the keys of a (nested) error_rates dictionary. This allows, for instance, many gates’ error rates to be set by the same model parameter.

idle_namestr, optional

The gate name to be used for the 1-qubit idle gate (this should be set in error_rates to add idle errors.