pygsti.modelmembers.operations.staticcliffordop

Defines the StaticCliffordOp class

Module Contents

Classes

StaticCliffordOp

A Clifford operation, represented via a symplectic matrix.

class pygsti.modelmembers.operations.staticcliffordop.StaticCliffordOp(unitary, symplecticrep=None, basis='pp', evotype='default', state_space=None)

Bases: pygsti.modelmembers.operations.linearop.LinearOperator, pygsti.modelmembers.errorgencontainer.NoErrorGeneratorInterface

A Clifford operation, represented via a symplectic matrix.

Parameters
  • unitary (numpy.ndarray) – The unitary action of the clifford operation.

  • symplecticrep (tuple, optional) – A (symplectic matrix, phase vector) 2-tuple specifying the pre- computed symplectic representation of unitary. If None, then this representation is computed automatically from unitary.

  • basis (Basis or {'pp','gm','std'}, optional) – The basis used to construct the Hilbert-Schmidt space representation of this state as a super-operator.

  • evotype (Evotype or str) – The evolution type. The special value “default” is equivalent to specifying the value of pygsti.evotypes.Evotype.default_evotype.

  • state_space (StateSpace, optional) – The state space for this operation. If None a default state space with the appropriate number of qubits is used.

__str__(self)

Return string representation

property smatrix(self)
property svector(self)
taylor_order_terms(self, order, max_polynomial_vars=100, return_coeff_polys=False)

Get the order-th order Taylor-expansion terms of this operation.

This function either constructs or returns a cached list of the terms at the given order. Each term is “rank-1”, meaning that its action on a density matrix rho can be written:

rho -> A rho B

The coefficients of these terms are typically polynomials of the operation’s parameters, where the polynomial’s variable indices index the global parameters of the operation’s parent (usually a Model), not the operation’s local parameter array (i.e. that returned from to_vector).

Parameters
  • order (int) – Which order terms (in a Taylor expansion of this LindbladOp) to retrieve.

  • max_polynomial_vars (int, optional) – maximum number of variables the created polynomials can have.

  • return_coeff_polys (bool) – Whether a parallel list of locally-indexed (using variable indices corresponding to this object’s parameters rather than its parent’s) polynomial coefficients should be returned as well.

Returns

  • terms (list) – A list of RankOneTerm objects.

  • coefficients (list) – Only present when return_coeff_polys == True. A list of compact polynomial objects, meaning that each element is a (vtape,ctape) 2-tuple formed by concatenating together the output of :method:`Polynomial.compact`.

property total_term_magnitude(self)

Get the total (sum) of the magnitudes of all this operator’s terms.

The magnitude of a term is the absolute value of its coefficient, so this function returns the number you’d get from summing up the absolute-coefficients of all the Taylor terms (at all orders!) you get from expanding this operator in a Taylor series.

Returns

float

property total_term_magnitude_deriv(self)

The derivative of the sum of all this operator’s terms.

Computes the derivative of the total (sum) of the magnitudes of all this operator’s terms with respect to the operators (local) parameters.

Returns

numpy array – An array of length self.num_params

to_dense(self, on_space='minimal')

Return the dense array used to represent this operation within its evolution type.

Note: for efficiency, this doesn’t copy the underlying data, so the caller should copy this data before modifying it.

Parameters

on_space ({'minimal', 'Hilbert', 'HilbertSchmidt'}) – The space that the returned dense operation acts upon. For unitary matrices and bra/ket vectors, use ‘Hilbert’. For superoperator matrices and super-bra/super-ket vectors use ‘HilbertSchmidt’. ‘minimal’ means that ‘Hilbert’ is used if possible given this operator’s evolution type, and otherwise ‘HilbertSchmidt’ is used.

Returns

numpy.ndarray

to_memoized_dict(self, 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.

classmethod _from_memoized_dict(cls, mm_dict, serial_memo)

For subclasses to implement. Submember-existence checks are performed, and the gpindices of the return value is set, by the non-underscored :method:`from_memoized_dict` implemented in this class.

_is_similar(self, other, rtol, atol)

Returns True if other model member (which it guaranteed to be the same type as self) has the same local structure, i.e., not considering parameter values or submembers