quara.objects.mprocess module

class MProcess(c_sys, hss, shape=None, mode_sampling=False, random_seed_or_generator=None, is_physicality_required=True, is_estimation_object=True, on_para_eq_constraint=True, on_algo_eq_constraint=True, on_algo_ineq_constraint=True, mode_proj_order='eq_ineq', eps_proj_physical=None, eps_truncate_imaginary_part=None, eps_zero=1e-08)[source]

Bases: quara.objects.qoperation.QOperation

Constructor

Parameters

c_sys (CompositeSystem) – CompositeSystem of this QOperation.
is_physicality_required (bool, optional) – whether this QOperation is physicality required, by default True
is_estimation_object (bool, optional) – whether this QOperation is estimation object, by default True
on_para_eq_constraint (bool, optional) – whether this QOperation is on parameter equality constraint, by default True
on_algo_eq_constraint (bool, optional) – whether this QOperation is on algorithm equality constraint, by default True
on_algo_ineq_constraint (bool, optional) – whether this QOperation is on algorithm inequality constraint, by default True
mode_proj_order (str, optional) – the order in which the projections are performed, by default “eq_ineq”
eps_proj_physical (float, optional) – epsiron that is projection algorithm error threshold for being physical, by default get_atol() / 10.0
eps_truncate_imaginary_part (float, optional) – threshold to truncate imaginary part, by default get_atol()
hss (List[numpy.ndarray]) –
shape (Tuple[int]) –
mode_sampling (bool) –
random_seed_or_generator (Union[int, numpy.random._generator.Generator]) –
eps_zero (Union[float, numpy.float64]) –

Raises

ValueError – eps_proj_physical is negative.

calc_gradient(var_index)[source]

calculates gradient of QOperation.

this function must be implemented in the subclass.

Parameters: var_index (int) – index of variables to calculate gradient.
Returns: gradient of QOperation.
Return type: QOperation
Raises: NotImplementedError – this function does not be implemented in the subclass.

calc_proj_eq_constraint()[source]

calculates the projection of QOperation on equal constraint.

Returns: the projection of QOperation on equal constraint.
Return type: QOperation

static calc_proj_eq_constraint_with_var(c_sys, var, on_para_eq_constraint=True)[source]

Parameters

c_sys (quara.objects.composite_system.CompositeSystem) –
var (numpy.ndarray) –
on_para_eq_constraint (bool) –

Return type

numpy.ndarray

calc_proj_ineq_constraint()[source]

calculates the projection of QOperation on inequal constraint.

Returns: the projection of QOperation on inequal constraint.
Return type: QOperation

static calc_proj_ineq_constraint_with_var(c_sys, var, on_para_eq_constraint=True, eps_truncate_imaginary_part=None)[source]

Parameters

c_sys (quara.objects.composite_system.CompositeSystem) –
var (numpy.ndarray) –
on_para_eq_constraint (bool) –
eps_truncate_imaginary_part (Optional[float]) –

Return type

numpy.ndarray

convert_basis(other_basis)[source]

returns list of HS representations for other_basis. :param other_basis: basis. :type other_basis: MatrixBasis

Returns: list of HS representations for other_basis.
Return type: List[np.ndarray]
Parameters: other_basis (quara.objects.matrix_basis.SparseMatrixBasis) –

static convert_stacked_vector_to_var(c_sys, stacked_vector, on_para_eq_constraint=True)[source]

converts stacked vector of MProcess to variables of MProcess.

Parameters

c_sys (CompositeSystem) – CompositeSystem of this MProcess.
stacked_vector (np.ndarray) – stacked vector of MProcess.
on_para_eq_constraint (bool, optional) – uses equal constraints, by default True.

Returns

variables of MProcess.

Return type

np.ndarray

convert_to_comp_basis(mode='row_major')[source]

returns list of HS representations for computational basis. :param mode: specify whether the order of basis is “row_major” or “column_major”, by default “row_major”. :type mode: str, optional

Returns: list of HS representations for computational basis.
Return type: List[np.ndarray]
Parameters: mode (str) –

static convert_var_to_stacked_vector(c_sys, var, on_para_eq_constraint=True)[source]

converts variables of MProcess to stacked vector of MProcess.

Parameters

c_sys (CompositeSystem) – CompositeSystem of this MProcess.
var (np.ndarray) – variables of MProcess.
on_para_eq_constraint (bool, optional) – uses equal constraints, by default True.

Returns

stacked vector of MProcess.

Return type

np.ndarray

copy()[source]

returns copy of MProcess.

Returns: copy of MProcess.
Return type: MProcess

property dim

returns dim of gate.

Returns: dim of gate.
Return type: int

property eps_zero

generate_from_var(var, is_physicality_required=None, is_estimation_object=None, on_para_eq_constraint=None, on_algo_eq_constraint=None, on_algo_ineq_constraint=None, mode_proj_order='eq_ineq', eps_proj_physical=None, eps_truncate_imaginary_part=None)[source]

generates QOperation from variables.

Parameters

var (np.ndarray) – variables.
is_physicality_required (bool, optional) – whether this QOperation is physicality required, by default None. if this parameter is None, the value of this instance is set.
is_estimation_object (bool, optional) – whether this QOperation is estimation object, by default None. if this parameter is None, the value of this instance is set.
on_para_eq_constraint (bool, optional) – whether this QOperation is on parameter equality constraint, by default None. if this parameter is None, the value of this instance is set.
on_algo_eq_constraint (bool, optional) – whether this QOperation is on algorithm equality constraint, by default None. if this parameter is None, the value of this instance is set.
on_algo_ineq_constraint (bool, optional) – whether this QOperation is on algorithm inequality constraint, by default None. if this parameter is None, the value of this instance is set.
mode_proj_order (str, optional) – the order in which the projections are performed, by default “eq_ineq”.
eps_proj_physical (float, optional) – epsiron that is projection algorithm error threshold for being physical, by default None. if this parameter is None, the value of this instance is set.
eps_truncate_imaginary_part (float, optional) – threshold to truncate imaginary part, by default get_atol()

Returns

generated QOperation.

Return type

QOperation

generate_origin_obj()[source]

returns origin object of MProcess.

Returns: origin object of MProcess.
Return type: MProcess

generate_zero_obj()[source]

returns zero object of QOperation.

Returns: zero object of QOperation.
Return type: QOperation

get_basis()[source]

returns MatrixBasis of gate. :returns: MatrixBasis of gate. :rtype: MatrixBasis

Return type: quara.objects.matrix_basis.SparseMatrixBasis

hs(index)[source]

returns HS representations of MProcess by index.

Parameters

index (Union[int, Tuple[int]]) – index of HS of MProcess. If type is an int, access is one-dimensional. If type is tuple, access is multi-dimensional.

Returns

HS of MProcess by index.

Return type

np.ndarray

Raises

ValueError – length of tuple does not equal length of the list of HS.
IndexError – specified index does not exist in the list of HS.

property hss

returns HS representations of MProcess.

Returns: HS representations of MProcess.
Return type: np.ndarray

is_cp(atol=None)[source]

Parameters: atol (Optional[float]) –
Return type: bool

is_eq_constraint_satisfied(atol=None)[source]

Parameters: atol (Optional[float]) –
Return type: bool

is_ineq_constraint_satisfied(atol=None)[source]

Parameters: atol (Optional[float]) –
Return type: bool

is_sum_tp(atol=None)[source]

Parameters: atol (Optional[float]) –
Return type: bool

property mode_sampling: bool

returns the mode of sampling.

if mode_sampling is True, samples to determine one HS.

Returns: the mode of sampling.
Return type: bool

property num_outcomes: int

Property to get the number of HSs.

Returns: the number of HSs.
Return type: int

property random_seed_or_generator: Union[int, numpy.random._generator.Generator]

returns the random seed or state to sample HS.

Returns: the random seed or state to sample HS.
Return type: Union[int, np.random.Generator]

property random_state: numpy.random._generator.Generator

returns the random state to sample HS.

Returns: the random state to sample HS.
Return type: np.random.Generator

set_mode_sampling(mode_sampling, random_seed_or_generator=None)[source]

Parameters

mode_sampling (bool) –
random_seed_or_generator (Optional[Union[int, numpy.random._generator.Generator]]) –

Return type

None

set_zero()[source]

sets parameters to zero.

this function must be implemented in the subclass.

Raises: NotImplementedError – this function does not be implemented in the subclass.

property shape: Tuple[int]

returns shape.

Returns: the shape of MProcess.
Return type: Tuple[int]

to_choi_matrix(outcome)[source]

returns Choi matrix of gate.

Parameters: outcome (Union[int, Tuple[int]]) – index of HS of MProcess. If type is an int, access is one-dimensional. If type is tuple, access is multi-dimensional.
Returns: Choi matrix of gate.
Return type: np.ndarray

to_choi_matrix_with_dict(outcome)[source]

returns Choi matrix of gate.

Parameters: outcome (Union[int, Tuple[int]]) – index of HS of MProcess. If type is an int, access is one-dimensional. If type is tuple, access is multi-dimensional.
Returns: Choi matrix of gate.
Return type: np.ndarray

to_choi_matrix_with_sparsity(outcome)[source]

returns Choi matrix of gate.

Parameters: outcome (Union[int, Tuple[int]]) – index of HS of MProcess. If type is an int, access is one-dimensional. If type is tuple, access is multi-dimensional.
Returns: Choi matrix of gate.
Return type: np.ndarray

to_kraus_matrices(outcome)[source]

returns Kraus matrices of gate.

this function returns Kraus matrices as list of np.ndarray with dtype=np.complex128. the list is sorted large eigenvalue order. if HS of gate is not CP, then returns empty list because Kraus matrices does not exist.

Parameters: outcome (Union[int, Tuple[int]]) – index of HS of MProcess. If type is an int, access is one-dimensional. If type is tuple, access is multi-dimensional.
Returns: Kraus matrices of gate.
Return type: List[np.ndarray]

to_povm()[source]

Return type: quara.objects.povm.Povm

to_process_matrix(outcome)[source]

returns process matrix of gate.

Parameters: outcome (Union[int, Tuple[int]]) – index of HS of MProcess. If type is an int, access is one-dimensional. If type is tuple, access is multi-dimensional.
Returns: process matrix of gate.
Return type: np.ndarray

to_stacked_vector()[source]

converts QOperation to stacked vector.

this function must be implemented in the subclass.

Returns: stacked vector representation of QOperation.
Return type: np.ndarray
Raises: NotImplementedError – this function does not be implemented in the subclass.

to_var()[source]

converts QOperation to variables.

this function must be implemented in the subclass.

Returns: variable representation of QOperation.
Return type: np.ndarray
Raises: NotImplementedError – this function does not be implemented in the subclass.

calc_gradient_from_mprocess(c_sys, hss, var_index, shape=None, mode_sampling=False, random_seed_or_generator=None, is_estimation_object=True, on_para_eq_constraint=True, on_algo_eq_constraint=True, on_algo_ineq_constraint=True, mode_proj_order='eq_ineq', eps_proj_physical=None, eps_truncate_imaginary_part=None)[source]

calculates gradient from MProcess.

Parameters

c_sys (CompositeSystem) – CompositeSystem of this MProcess.
hss (List[np.ndarray]) – list of HS representation of this MProcess.
var_index (int) – variable index.
on_para_eq_constraint (bool, optional) – uses equal constraints, by default True.
shape (Optional[Tuple[int]]) –
mode_sampling (bool) –
random_seed_or_generator (Optional[Union[int, numpy.random._generator.Generator]]) –
is_estimation_object (bool) –
on_algo_eq_constraint (bool) –
on_algo_ineq_constraint (bool) –
mode_proj_order (str) –
eps_proj_physical (Optional[float]) –
eps_truncate_imaginary_part (Optional[float]) –

Returns

MProcess with gradient as hss.

Return type

MProcess

convert_hss_to_var(c_sys, hss, on_para_eq_constraint=True)[source]

converts hss of MProcess to variables.

Parameters

c_sys (CompositeSystem) – CompositeSystem of this MProcess.
hss (List[np.ndarray]) – list of HS representation of this MProcess.
on_para_eq_constraint (bool, optional) – uses equal constraints, by default True.

Returns

variables.

Return type

np.ndarray

convert_mprocess_index_to_var_index(c_sys, mprocess_index, hss, on_para_eq_constraint=True)[source]

converts MProcess index to variable index.

Parameters

c_sys (CompositeSystem) – CompositeSystem of this MProcess.
mprocess_index (Tuple[int, int, int]) – MProcess index. first value of tuple is index of list of HS representation of this MProcess. second value of tuple is row number of HS representation of this MProcess. third value of tuple is column number of HS representation of this MProcess.
hss (List[np.ndarray]) – list of HS representation.
on_para_eq_constraint (bool, optional) – uses equal constraints, by default True.

Returns

variable index.

Return type

int

convert_var_index_to_mprocess_index(c_sys, hss, var_index, on_para_eq_constraint=True)[source]

converts variable index to MProcess index.

Parameters

c_sys (CompositeSystem) – CompositeSystem of this MProcess.
hss (List[np.ndarray]) – list of HS representation.
var_index (int) – variable index.
on_para_eq_constraint (bool, optional) – uses equal constraints, by default True.

Returns

MProcess index. first value of tuple is index of list of HS representation of this MProcess. second value of tuple is row number of HS representation of this MProcess. third value of tuple is column number of HS representation of this MProcess.

Return type

Tuple[int, int, int]

convert_var_to_hss(c_sys, var, on_para_eq_constraint=True)[source]

converts variables of MProcess to list of HS representation.

Parameters

c_sys (CompositeSystem) – CompositeSystem of this MProcess.
var (np.ndarrayd@y) – variables of gate.
on_para_eq_constraint (bool, optional) – uses equal constraints, by default True.

Returns

list of HS representation of this MProcess.

Return type

List[np.ndarray]