pygsti.tools.errgenproptools

Tools for the propagation of error generators through circuits.

Functions

acom(P1, P2)
alpha(errorgen, tableau, desired_bitstring)	First-order error generator sensitivity function for probability.
alpha_numerical(errorgen, tableau, ...)	First-order error generator sensitivity function for probability.
alpha_pauli(errorgen, tableau, pauli)	First-order error generator sensitivity function for pauli expectations.
alpha_pauli_numerical(errorgen, tableau, pauli)	First-order error generator sensitivity function for pauli expectations.
amplitude_of_state(tableau, desired_state, ...)	Get the amplitude of a particular computational basis state for given stabilizer state.
approximate_stabilizer_pauli_expectation(...)	Calculate the approximate probability of a desired bit string using a first-order approximation.
approximate_stabilizer_pauli_expectation_numerical(...)	Calculate the approximate probability of a desired bit string using a first-order approximation.
approximate_stabilizer_probabilities(...[, ...])	Calculate the approximate probability distribution over all bitstrings using a first-order approximation.
approximate_stabilizer_probability(...[, ...])	Calculate the approximate probability of a desired bit string using an nth-order taylor series approximation.
bch_approximation(errgen_layer_1, errgen_layer_2)	Apply the BCH approximation at the given order to combine the input dictionaries of error generator rates.
bch_numerical(propagated_errorgen_layers, ...)	Iteratively compute effective error generator layer produced by applying the BCH approximation to the list of input error generator matrices.
bitstring_to_tableau(bitstring)	Map a computational basis bit string into a corresponding Tableau which maps the all zero state into that state.
bulk_alpha(errorgens, tableau, ...)	First-order error generator sensitivity function for probability.
bulk_alpha_pauli(errorgens, tableau, paulis)	First-order error generator sensitivity function for pauli expectations.
bulk_amplitude_of_state(tableau, ...)	Get the amplitudes particular computational basis state fors given stabilizer state.
bulk_phi(tableau, desired_bitstring, Ps, Qs)	Computes the phi function for multiple (P, Q) pairs at once while caching and reusing intermediate values computed via pauli_phase_update_all_zeros and amplitude_of_state.
com(P1, P2)
compute_phase_reference(tableau)	Compute a canonical state, corresponding to the smallest state with non-zero amplitude, to use as a phase reference in computing the phases of components of this stabilizer state.
errgen_coeff_label_to_stim_pauli_strs(...)	Converts an input GlobalElementaryErrorgenLabel to a tuple of stim.PauliString objects, padded with an appropriate number of identities.
error_generator_commutator(errorgen_1, ...)	Returns the commutator of two error generators.
error_generator_commutator_numerical(...[, ...])	Numerically compute the commutator of the two specified elementary error generators.
error_generator_composition(errorgen_1, ...)	Returns the composition of two error generators.
error_generator_composition_numerical(...[, ...])	Numerically compute the composition of the two specified elementary error generators.
error_generator_taylor_expansion(errorgen_dict)	Compute the nth-order taylor expansion for the exponentiation of the error generator described by the input error generator dictionary.
error_generator_taylor_expansion_numerical(...)	Compute the nth-order taylor expansion for the exponentiation of the error generator described by the input error generator dictionary.
errorgen_layer_to_matrix(errorgen_layer, ...)	Converts an iterable over error generator coefficients and rates into the corresponding dense numpy array representation.
errorgen_pauli_action(errorgen, pauli)	Apply the specified error generator to a given Pauli operator.
errorgen_pauli_action_numerical(errorgen, pauli)	Apply the specified error generator to a given Pauli operator.
in_stabilizer_support(tableau, desired_state)	Return whether or not the desired bitstring is in the support of the stabilizer state corresponding to the input tableau.
iterative_error_generator_composition(...)	Iteratively compute error generator compositions.
iterative_error_generator_composition_numerical(...)	Iteratively compute error generator compositions.
magnus_expansion(errorgen_layers[, ...])	Function for computing the nth-order magnus expansion for a set of error generator layers.
magnus_numerical(propagated_errorgen_layers, ...)	Compute effective error generator layer produced by applying the magnus expansions to the list of input error generator matrices.
pairwise_bch_numerical(mat1, mat2[, order])	Helper function for doing the numerical BCH in a pairwise fashion.
pauli_phase_update(pauli, bitstring[, dual])	Takes as input a pauli and a bit string and computes the output bitstring and the overall phase that bit string accumulates.
pauli_phase_update_all_zeros(pauli[, dual])	Specialized version of pauli_phase_update for the case of the all-zeros bitstring which is more computationally efficient.
pauli_product(P1, P2)
phi(tableau, desired_bitstring, P, Q)	This function computes a quantity whose value is used in expression for the sensitivity of probabilities to error generators.
phi_numerical(tableau, desired_bitstring, P, Q)	This function computes a quantity whose value is used in expression for the sensitivity of probabilities to error generators.
random_support(tableau[, return_support])	Compute the number of bits over which the stabilizer state corresponding to this stim tableau would have measurement outcomes which are random.
slow_amplitude_of_state(tableau, ...)	Get the amplitude of a particular computational basis state for given stabilizer state.
slow_bulk_alpha(errorgens, tableau, ...)	First-order error generator sensitivity function for probability.
slow_bulk_alpha_pauli(errorgens, tableau, paulis)	First-order error generator sensitivity function for pauli expectations.
slow_bulk_amplitude_of_state(tableau, ...)	Get the amplitudes particular computational basis state fors given stabilizer state.
slow_bulk_phi(tableau, desired_bitstring, Ps, Qs)	Computes the phi function for multiple (P, Q) pairs at once while caching and reusing intermediate values computed via pauli_phase_update_all_zeros and amplitude_of_state.
slow_pauli_phase_update(pauli, bitstring[, dual])	Takes as input a pauli and a bit string and computes the output bitstring and the overall phase that bit string accumulates.
slow_pauli_phase_update_all_zeros(pauli[, dual])	Specialized version of pauli_phase_update for the case of the all-zeros bitstring which is more computationally efficient.
stabilizer_pauli_expectation(tableau, pauli)	Calculate the output probability for the specified output bitstring.
stabilizer_pauli_expectation_correction(...)	Compute the kth-order correction to the expectation value of the specified pauli.
stabilizer_pauli_expectation_correction_numerical(...)	Compute the kth-order correction to the expectation value of the specified pauli.
stabilizer_probability(tableau, ...)	Calculate the output probability for the specified output bitstring.
stabilizer_probability_correction(...[, ...])	Compute the kth-order correction to the probability of the specified bit string.
stim_pauli_string_less_than(pauli1, pauli2)	Returns true if pauli1 is less than pauli lexicographically.
tableau_fidelity(tableau1, tableau2)	Calculate the fidelity between the stabilizer states corresponding to the given stim tableaus.
zassenhaus_formula(errorgen_groups[, ...])	Function for computing the nth-order Zassenhaus formula for a set of error generators.
zassenhaus_formula_numerical(...[, ...])	Function for numerically computing the nth-order Zassenhaus formula for a set of error generators.