pygsti.algorithms.germselection

pygsti.algorithms.germselection#

Functions for selecting a complete set of germs for a GST analysis.

Functions

clean_germ_list(model, circuit_cache[, ...])

compact_EVD(mat[, threshold, assume_hermitian])

Generate the compact eigenvalue decomposition of the input matrix.

compact_EVD_via_SVD(mat[, threshold])

Generate the compact eigenvalue decomposition of the input matrix.

compute_composite_germ_set_score(score_fn[, ...])

Compute the score for a germ set when it is not AC against a model.

compute_composite_germ_set_score_compactevd(...)

Compute the score for a germ set when it is not AC against a model.

compute_composite_germ_set_score_low_rank_trace(...)

Compute the score for a germ set when it is not AC against a model.

compute_composite_vector_set_score(...[, ...])

Compute the score for a germ set when it is not AC against a model.

compute_germ_set_score(germs[, ...])

Calculate the score of a germ set with respect to a model.

construct_update_cache(mat[, evd_tol])

Calculates the parts of the eigenvalue update loop algorithm that we can pre-compute and reuse throughout all of the potential updates.

construct_update_cache_rank_one(mat[, ...])

Calculates the parts of the pseudoinverse update loop algorithm that we can pre-compute and reuse throughout all of the potential updates.

create_circuit_cache(model, circuit_list)

Function for generating a cache of PTMs for the available fiducials.

drop_random_germs(candidate_list, rand_frac, ...)

Function for dropping a random fraction of the candidate germ list.

fast_kron(a, b)

find_germs(target_model[, randomize, ...])

Generate a germ set for doing GST with a given target model.

find_germs_breadthfirst(model_list, germs_list)

Greedy algorithm starting with 0 germs.

find_germs_breadthfirst_greedy(model_list, ...)

Greedy algorithm starting with 0 germs.

find_germs_depthfirst(model_list, germs_list)

Greedy germ selection algorithm starting with 0 germs.

find_germs_grasp(model_list, germs_list, alpha)

Use GRASP to find a high-performing germ set.

find_germs_integer_slack(model_list, germs_list)

Find a locally optimal subset of the germs in germs_list.

germ_set_spanning_vectors(target_model, ...)

minamide_style_inverse_trace(update, orig_e, ...)

This function performs a low-rank update to the components of the pseudo inverse of a matrix relevant to the calculation of that matrix's updated trace.

randomize_model_list(model_list, ...[, seed])

Applies random unitary perturbations to a model or list of models.

rank_one_inverse_trace_update(vector_update, ...)

Helper function for calculating rank-one updates to the trace of the pseudoinverse.

rank_one_psuedoinverse_update(vector_update, ...)

Helper function for calculating rank-one pseudoinverse updates.

stable_pinv(mat)

symmetric_low_rank_spectrum_update(update, ...)

This function performs a low-rank update to the spectrum of a matrix.

test_germ_set_finitel(model, germs_to_test, ...)

Test whether a set of germs is able to amplify all non-gauge parameters.

test_germ_set_infl(model, germs_to_test[, ...])

Test whether a set of germs is able to amplify all non-gauge parameters.

test_germs_list_completeness(model_list, ...)

Check to see if the germs_list is amplificationally complete (AC).