Verification
qiskit.ignis.verification
Quantum Volume
qv_circuits(qubit_lists[, ntrials, qr, cr, seed]) | Return a list of square quantum volume circuits (depth=width) |
QVFitter([backend_result, …]) | Class for fitters for quantum volume. |
Randomized Benchmarking
Randomization benchmarking (RB) is a well-known technique to measure average gate performance by running sequences of random Clifford gates that should return the qubits to the initial state. Qiskit Ignis has tools to generate one- and two-qubit gate Clifford RB sequences simultaneously, as well as performing interleaved RB, purity RB and RB on the non-Clifford CNOT-Dihedral group.
randomized_benchmarking_seq([nseeds, …]) | Generate generic randomized benchmarking (RB) sequences. |
RBFitter(backend_result, cliff_lengths[, …]) | Class for fitters for randomized benchmarking. |
InterleavedRBFitter(original_result, …[, …]) | Class for fitters for interleaved RB, derived from RBFitterBase class. |
PurityRBFitter(purity_result, npurity, …) | Class for fitter for purity RB. |
CNOTDihedralRBFitter(cnotdihedral_Z_result, …) | Class for fitters for non-Clifford CNOT-Dihedral RB. |
count_gates(qobj, basis, qubits) | Take a compiled qobj and output the number of gates in each circuit. |
gates_per_clifford(transpiled_circuits_list, …) | Take a list of transpiled QuantumCircuit and use these to calculate the number of gates per Clifford. |
calculate_1q_epg(gate_per_cliff, epc_1q, qubit) | Convert error per Clifford (EPC) into error per gates (EPGs) of single qubit basis gates. |
calculate_2q_epg(gate_per_cliff, epc_2q, …) | Convert error per Clifford (EPC) into error per gate (EPG) of two qubit cx gates. |
calculate_1q_epc(gate_per_cliff, epg_1q, qubit) | Convert error per gate (EPG) into error per Clifford (EPC) of single qubit basis gates. |
calculate_2q_epc(gate_per_cliff, epg_2q, …) | Convert error per gate (EPG) into error per Clifford (EPC) of two qubit cx gates. |
coherence_limit([nQ, T1_list, T2_list, gatelen]) | The error per gate (1-average_gate_fidelity) given by the T1,T2 limit. |
twoQ_clifford_error(ngates, gate_qubit, gate_err) | The two qubit Clifford gate error given measured errors in the primitive gates used to construct the Clifford (see arxiv:1712.06550). |
Tomography
state_tomography_circuits(circuit, …[, …]) | Return a list of quantum state tomography circuits. |
process_tomography_circuits(circuit, …[, …]) | Return a list of quantum process tomography circuits. |
gateset_tomography_circuits([…]) | Return a list of quantum gate set tomography (GST) circuits. |
basis | Quantum tomography basis |
StateTomographyFitter(result, circuits[, …]) | Maximum-Likelihood estimation state tomography fitter. |
ProcessTomographyFitter(result, circuits[, …]) | Maximum-Likelihood estimation process tomography fitter. |
GatesetTomographyFitter(result, circuits[, …]) | Initialize gateset tomography fitter with experimental data. |
TomographyFitter(result, circuits[, …]) | Base maximum-likelihood estimate tomography fitter class |
marginal_counts(counts[, meas_qubits, pad_zeros]) | Compute marginal counts from a counts dictionary. |
combine_counts(counts1, counts2) | Combine two counts dictionaries. |
expectation_counts(counts) | Converts count dict to an expectation counts dict. |
count_keys(num_qubits) | Return ordered count keys. |
Entanglement
BConfig(backend[, indicator]) | This class is used to create a GHZ circuit with parallellized CNOT gates to increase fidelity |
get_ghz_simple(n[, measure, full_measurement]) | Creates a linear GHZ state with the option of measurement |
get_ghz_mqc(n, delta[, full_measurement]) | This function creates an MQC circuit with n qubits, where the middle phase rotation around the z axis is by delta |
get_ghz_mqc_para(n[, full_measurement]) | This function creates an MQC circuit with n qubits, where the middle phase rotation around the z axis is parameterized |
get_ghz_po(n, delta) | This function creates an Parity Oscillation circuit with n qubits, where the middle superposition rotation around the x and y axes is by delta |
get_ghz_po_para(n) | This function creates a Parity Oscillation circuit with n qubits, where the middle superposition rotation around |
ordered_list_generator(counts_dictionary, qn) | For parity oscillations; just arranges dictionary of counts in bitwise binary order to compute dot products more easily |
composite_pauli_z(qn) | Generates n tensored pauli z matrix upon input of qubit number |
composite_pauli_z_expvalue(counts_dictionary, qn) | Generates expectation value of n tensored pauli matrix upon input of qubit number and composite pauli matrix |
Plotter(label) | Various plots of the ground state in MQC and PO experiments |
rho_to_fidelity(rho) | Get fidelity given rho :type rho: float :param rho: The density matrix |
Topological Codes
RepetitionCode(d[, T, xbasis, resets, delay]) | Implementation of a distance d repetition code, implemented over T syndrome measurement rounds. |
GraphDecoder(code[, S, brute]) | Class to construct the graph corresponding to the possible syndromes of a quantum error correction code, and then run suitable decoders. |
lookuptable_decoding(training_results, …) | Calculates the logical error probability using postselection decoding. |
postselection_decoding(results) | Calculates the logical error probability using postselection decoding. |
Accreditation
AccreditationCircuits(target_circ[, …]) | This class generates accreditation circuits from a target. |
AccreditationFitter() | Class for fitters for accreditation |
QOTP(circ, num[, two_qubit_gate, …]) | Performs a QOTP (or random compilation) on a generic circuit. |
QOTPCorrectCounts(qotp_counts, qotp_postp) | Corrects a dictionary of results, shifting the qotp |
QOTPCorrectString(qotp_string, qotp_postp) | Corrects a measurement string, shifting the qotp |
Was this page helpful?
Report a bug or request content on GitHub.