pygsti.modelmembers.instruments

Sub-package holding model instrument objects.

Submodules

• pygsti.modelmembers.instruments.instrument
• pygsti.modelmembers.instruments.tpinstrument
• pygsti.modelmembers.instruments.tpinstrumentop

Package Contents

Classes

Instrument	A generalized quantum instrument.
TPInstrument	A trace-preservng quantum instrument.
TPInstrumentOp	An element of a TPInstrument.

Functions

instrument_type_from_op_type(op_type)	Decode an op type into an appropriate instrument type.
convert(instrument, to_type, basis[, ...])	TODO: update docstring

class pygsti.modelmembers.instruments.Instrument(member_ops, evotype=None, state_space=None, called_from_reduce=False, items=None)

Bases: pygsti.modelmembers.modelmember.ModelMember, collections.OrderedDict

A generalized quantum instrument.

Meant to correspond to a quantum instrument in theory, this class generalizes that notion slightly to include a collection of gates that may or may not have all of the properties associated by a mathematical quantum instrument.

Parameters

member_opsdict of LinearOperator objects

A dict (or list of key,value pairs) of the gates.

evotypeEvotype or str, optional

The evolution type. If None, the evotype is inferred from the first instrument member. If len(member_ops) == 0 in this case, an error is raised.

state_spaceStateSpace, optional

The state space for this POVM. If None, the space is inferred from the first instrument member. If len(member_ops) == 0 in this case, an error is raised.

itemslist or dict, optional

Initial values. This should only be used internally in de-serialization.

Initialize a new ModelMember

property parameter_labels

An array of labels (usually strings) describing this model member’s parameters.

property num_elements

Return the number of total gate elements in this instrument.

This is in general different from the number of parameters, which are the number of free variables used to generate all of the matrix elements.

Returns

int

property num_params

Get the number of independent parameters which specify this Instrument.

Returns

int

the number of independent parameters.

submembers()

Get the ModelMember-derived objects contained in this one.

Returns

list

to_memoized_dict(mmg_memo)

Create a serializable dict with references to other objects in the memo.

Parameters

mmg_memo: dict

Memo dict from a ModelMemberGraph, i.e. keys are object ids and values are ModelMemberGraphNodes (which contain the serialize_id). This is NOT the same as other memos in ModelMember (e.g. copy, allocate_gpindices, etc.).

Returns

mm_dict: dict

A dict representation of this ModelMember ready for serialization This must have at least the following fields: module, class, submembers, params, state_space, evotype Additional fields may be added by derived classes.

simplify_operations(prefix='')

Creates a dictionary of simplified instrument operations.

Returns a dictionary of operations that belong to the Instrument’s parent Model - that is, whose gpindices are set to all or a subset of this instruments’s gpindices. These are used internally within computations involving the parent Model.

Parameters

prefixstr

A string, usually identitying this instrument, which may be used to prefix the simplified gate keys.

Returns

OrderedDict of Gates

to_vector()

Extract a vector of the underlying gate parameters from this Instrument.

Returns

numpy array

a 1D numpy array with length == num_params().

from_vector(v, close=False, dirty_value=True)

Initialize the Instrument using a vector of its parameters.

Parameters

vnumpy array

The 1D vector of gate parameters. Length must == num_params().

closebool, optional

Whether v is close to this Instrument’s current set of parameters. Under some circumstances, when this is true this call can be completed more quickly.

dirty_valuebool, optional

The value to set this object’s “dirty flag” to before exiting this call. This is passed as an argument so it can be updated recursively. Leave this set to True unless you know what you’re doing.

Returns

None

transform_inplace(s)

Update each Instrument element matrix O with inv(s) * O * s.

Parameters

sGaugeGroupElement

A gauge group element which specifies the “s” matrix (and it’s inverse) used in the above similarity transform.

Returns

None

depolarize(amount)

Depolarize this Instrument by the given amount.

Parameters

amountfloat or tuple

The amount to depolarize by. If a tuple, it must have length equal to one less than the dimension of the gate. All but the first element of each spam vector (often corresponding to the identity element) are multiplied by amount (if a float) or the corresponding amount[i] (if a tuple).

Returns

None

rotate(amount, mx_basis='gm')

Rotate this instrument by the given amount.

Parameters

amounttuple of floats, optional

Specifies the rotation “coefficients” along each of the non-identity Pauli-product axes. The gate’s matrix G is composed with a rotation operation R (so G -> dot(R, G) ) where R is the unitary superoperator corresponding to the unitary operator U = exp( sum_k( i * rotate[k] / 2.0 * Pauli_k ) ). Here Pauli_k ranges over all of the non-identity un-normalized Pauli operators.

mx_basis{‘std’, ‘gm’, ‘pp’, ‘qt’} or Basis object

The source and destination basis, respectively. Allowed values are Matrix-unit (std), Gell-Mann (gm), Pauli-product (pp), and Qutrit (qt) (or a custom basis object).

Returns

None

acton(state)

Act with this instrument upon state

Parameters

stateState

The state to act on

Returns

OrderedDict

A dictionary whose keys are the outcome labels (strings) and whose values are (prob, normalized_state) tuples giving the probability of seeing the given outcome and the resulting state that would be obtained if and when that outcome is observed.

class pygsti.modelmembers.instruments.TPInstrument(op_matrices, evotype='default', state_space=None, called_from_reduce=False, items=None)

Bases: pygsti.modelmembers.modelmember.ModelMember, collections.OrderedDict

A trace-preservng quantum instrument.

This is essentially a collection of operations whose sum is a trace-preserving map. The instrument’s elements may or may not have all of the properties associated by a mathematical quantum instrument.

If M1,M2,…Mn are the elements of the instrument, then we parameterize

1. MT = (M1+M2+…Mn) as a TPParmeterizedGate

2. Di = Mi - MT for i = 1..(n-1) as FullyParameterizedGates

So to recover M1…Mn we compute: Mi = Di + MT for i = 1…(n-1) = -(n-2)*MT-sum(Di) = -(n-2)*MT-[(MT-Mi)-n*MT] for i == (n-1)

Parameters

op_matricesdict of numpy arrays

A dict (or list of key,value pairs) of the operation matrices whose sum must be a trace-preserving (TP) map.

evotypeEvotype or str, optional

The evolution type. The special value “default” is equivalent to specifying the value of pygsti.evotypes.Evotype.default_evotype.

state_spaceStateSpace, optional

The state space for this Instrument. If None, the space is inferred from the first effect vector. If len(effects) == 0 in this case, an error is raised.

itemslist or dict, optional

Initial values. This should only be used internally in de-serialization.

Initialize a new ModelMember

property parameter_labels

An array of labels (usually strings) describing this model member’s parameters.

property num_elements

Return the number of total gate elements in this instrument.

This is in general different from the number of parameters, which are the number of free variables used to generate all of the matrix elements.

Returns

int

property num_params

Get the number of independent parameters which specify this Instrument.

Returns

int

the number of independent parameters.

submembers()

Get the ModelMember-derived objects contained in this one.

Returns

list

to_memoized_dict(mmg_memo)

Create a serializable dict with references to other objects in the memo.

Parameters

mmg_memo: dict

Memo dict from a ModelMemberGraph, i.e. keys are object ids and values are ModelMemberGraphNodes (which contain the serialize_id). This is NOT the same as other memos in ModelMember (e.g. copy, allocate_gpindices, etc.).

Returns

mm_dict: dict

A dict representation of this ModelMember ready for serialization This must have at least the following fields: module, class, submembers, params, state_space, evotype Additional fields may be added by derived classes.

simplify_operations(prefix='')

Creates a dictionary of simplified instrument operations.

Returns a dictionary of operations that belong to the Instrument’s parent Model - that is, whose gpindices are set to all or a subset of this instruments’s gpindices. These are used internally within computations involving the parent Model.

Parameters

prefixstr

A string, usually identitying this instrument, which may be used to prefix the simplified gate keys.

Returns

OrderedDict of Gates

to_vector()

Extract a vector of the underlying gate parameters from this Instrument.

Returns

numpy array

a 1D numpy array with length == num_params().

from_vector(v, close=False, dirty_value=True)

Initialize the Instrument using a vector of its parameters.

Parameters

vnumpy array

The 1D vector of gate parameters. Length must == num_params().

closebool, optional

Whether v is close to this Instrument’s current set of parameters. Under some circumstances, when this is true this call can be completed more quickly.

dirty_valuebool, optional

The value to set this object’s “dirty flag” to before exiting this call. This is passed as an argument so it can be updated recursively. Leave this set to True unless you know what you’re doing.

Returns

None

transform_inplace(s)

Update each Instrument element matrix O with inv(s) * O * s.

Parameters

sGaugeGroupElement

A gauge group element which specifies the “s” matrix (and it’s inverse) used in the above similarity transform.

Returns

None

depolarize(amount)

Depolarize this Instrument by the given amount.

Parameters

amountfloat or tuple

The amount to depolarize by. If a tuple, it must have length equal to one less than the dimension of the gate. All but the first element of each spam vector (often corresponding to the identity element) are multiplied by amount (if a float) or the corresponding amount[i] (if a tuple).

Returns

None

rotate(amount, mx_basis='gm')

Rotate this instrument by the given amount.

Parameters

amounttuple of floats, optional

Specifies the rotation “coefficients” along each of the non-identity Pauli-product axes. The gate’s matrix G is composed with a rotation operation R (so G -> dot(R, G) ) where R is the unitary superoperator corresponding to the unitary operator U = exp( sum_k( i * rotate[k] / 2.0 * Pauli_k ) ). Here Pauli_k ranges over all of the non-identity un-normalized Pauli operators.

mx_basis{‘std’, ‘gm’, ‘pp’, ‘qt’} or Basis object

The source and destination basis, respectively. Allowed values are Matrix-unit (std), Gell-Mann (gm), Pauli-product (pp), and Qutrit (qt) (or a custom basis object).

Returns

None

class pygsti.modelmembers.instruments.TPInstrumentOp(param_ops, index, basis=None)

Bases: pygsti.modelmembers.operations.DenseOperator

An element of a TPInstrument.

A partial implementation of LinearOperator which encapsulates an element of a TPInstrument. Instances rely on their parent being a TPInstrument.

Parameters

param_opslist of LinearOperator objects

A list of the underlying operation objects which constitute a simple parameterization of a TPInstrument. Namely, this is the list of [MT,D1,D2,…Dn] operations which parameterize all of the TPInstrument’s elements.

indexint

The index indicating which element of the TPInstrument the constructed object is. Must be in the range [0,len(param_ops)-1].

basisBasis or {‘pp’,’gm’,’std’} or None

The basis used to construct the Hilbert-Schmidt space representation of this state as a super-operator. If None, certain functionality, such as access to Kraus operators, will be unavailable.

Initialize a new LinearOperator

property num_params

Get the number of independent parameters which specify this operation.

Returns

int

the number of independent parameters.

submembers()

Get the ModelMember-derived objects contained in this one.

Returns

list

to_memoized_dict(mmg_memo)

Create a serializable dict with references to other objects in the memo.

Parameters

mmg_memo: dict

Memo dict from a ModelMemberGraph, i.e. keys are object ids and values are ModelMemberGraphNodes (which contain the serialize_id). This is NOT the same as other memos in ModelMember (e.g. copy, allocate_gpindices, etc.).

Returns

mm_dict: dict

A dict representation of this ModelMember ready for serialization This must have at least the following fields: module, class, submembers, params, state_space, evotype Additional fields may be added by derived classes.

deriv_wrt_params(wrt_filter=None)

The element-wise derivative this operation.

Construct a matrix whose columns are the vectorized derivatives of the flattened operation matrix with respect to a single operation parameter. Thus, each column is of length op_dim^2 and there is one column per operation parameter. An empty 2D array in the StaticArbitraryOp case (num_params == 0).

Parameters

wrt_filterlist or numpy.ndarray

List of parameter indices to take derivative with respect to. (None means to use all the this operation’s parameters.)

Returns

numpy array

Array of derivatives with shape (dimension^2, num_params)

has_nonzero_hessian()

Whether this operation has a non-zero Hessian with respect to its parameters.

(i.e. whether it only depends linearly on its parameters or not)

Returns

bool

to_vector()

Get the operation parameters as an array of values.

Returns

numpy array

The operation parameters as a 1D array with length num_params().

from_vector(v, close=False, dirty_value=True)

Initialize the operation using a vector of parameters.

Parameters

vnumpy array

The 1D vector of operation parameters. Length must == num_params()

closebool, optional

Whether v is close to this operation’s current set of parameters. Under some circumstances, when this is true this call can be completed more quickly.

dirty_valuebool, optional

The value to set this object’s “dirty flag” to before exiting this call. This is passed as an argument so it can be updated recursively. Leave this set to True unless you know what you’re doing.

Returns

None

pygsti.modelmembers.instruments.instrument_type_from_op_type(op_type)

Decode an op type into an appropriate instrument type.

Parameters:

op_type: str or list of str

Operation parameterization type (or list of preferences)

Returns

instr_type_preferences: tuple of str

POVM parameterization types

pygsti.modelmembers.instruments.convert(instrument, to_type, basis, ideal_instrument=None, flatten_structure=False)

TODO: update docstring Convert intrument to a new type of parameterization.

This potentially creates a new object. Raises ValueError for invalid conversions.

Parameters

instrumentInstrument

Instrument to convert

to_type{“full”,”TP”,”static”,”static unitary”}

The type of parameterizaton to convert to. See Model.set_all_parameterizations() for more details.

basis{‘std’, ‘gm’, ‘pp’, ‘qt’} or Basis object

The basis for povm. Allowed values are Matrix-unit (std), Gell-Mann (gm), Pauli-product (pp), and Qutrit (qt) (or a custom basis object).

ideal_instrumentInstrument, optional

The ideal version of instrument, potentially used when converting to an error-generator type.

flatten_structurebool, optional

When False, the sub-members of composed and embedded operations are separately converted, leaving the original instrument’s structure unchanged. When True, composed and embedded operations are “flattened” into a single instrument of the requested to_type.

Returns

Instrument

The converted instrument, usually a distinct object from the object passed as input.