Python API

The session class

The session class provides a way to set up the experiment table.

You can use the experiment table to run a list of quantum circuits under different conditions, such as number of measurement shots, backends, parameters, etc.

class core.session

property acc

acc:

Valid settings: aer | tnqvm

Select a back-end simulator. The single setting applies globally to all infiles, all instrings, and random circuits.

accs:

Valid settings: [[aer|tnqvm, …], [aer|tnqvm, …]]

The lead dimension’s element 0 matches the vector of infiles, element 1 matches the vector of instrings, element 2 matches the vector of random depths.

property accs

acc:

Valid settings: aer | tnqvm

Select a back-end simulator. The single setting applies globally to all infiles, all instrings, and random circuits.

accs:

Valid settings: [[aer|tnqvm, …], [aer|tnqvm, …]]

The lead dimension’s element 0 matches the vector of infiles, element 1 matches the vector of instrings, element 2 matches the vector of random depths.

property aer_sim_type

aer_sim_type:

Valid settings: statevector | density_matrix | matrix_product_state

Selects a simulation method for the AER simulator.

aer_sim_types:

A 1d-array (list) version of aer_sim_type.

property aer_sim_types

aer_sim_type:

Valid settings: statevector | density_matrix | matrix_product_state

Selects a simulation method for the AER simulator.

aer_sim_types:

A 1d-array (list) version of aer_sim_type.

aws_setup(self: core.session, arg0: int, arg1: int, arg2: int) → None: AWS Braket Setup

property beta: Warning

This property is currently unused.

property betas: Warning

This property is currently unused.

bitstring_index(self: core.session, arg0: str, arg1: int, arg2: int) → int: Get the (base-10) integer index for the counts/probabilities list, corresponding to a bitstring for the quantum experiment at (ii, jj).

property calc_jacobian

calc_jacobian:

Valid settings: True | False

Setting this to True will calculate gradients for the circuit when session.run() is evoked. The single setting applies globally. The gradients calculated will be a jacobian of the output probabilities with respect to the input parameters, i.e. d_probs/d_params.

calc_jacobians:

Valid settings: [[True|False, …], [True|False, …]]

A 1d-array (list) version of calc_jacobian.

property calc_jacobians

calc_jacobian:

Valid settings: True | False

Setting this to True will calculate gradients for the circuit when session.run() is evoked. The single setting applies globally. The gradients calculated will be a jacobian of the output probabilities with respect to the input parameters, i.e. d_probs/d_params.

calc_jacobians:

Valid settings: [[True|False, …], [True|False, …]]

A 1d-array (list) version of calc_jacobian.

property circuit_optimization

circuit_optimization:

List of circuit optimization passes.

circuit_optimizations:

A 1d-array (list) version of circuit_optimization.

property circuit_optimizations

circuit_optimization:

List of circuit optimization passes.

circuit_optimizations:

A 1d-array (list) version of circuit_optimization.

property debug

debug:

Valid settings: True | False

When set to True, extra debugging information will be printed.

divergence(self: core.session) → None: Calculate Jensen-Shannon divergence

property include_qb

include_qb:

A file that contains OpenQASM format gate definitions for custom Quantum Brilliance gates.

include_qbs:

Valid settings: [include_qb, …]

A 1d-array (list) version of session.include_qb.

property include_qbs

include_qb:

A file that contains OpenQASM format gate definitions for custom Quantum Brilliance gates.

include_qbs:

Valid settings: [include_qb, …]

A 1d-array (list) version of session.include_qb.

property infile

infile:

Name of a file containing (default: OpenQASM format) a quantum circuit.

infiles:

Valid settings: [infile, …]

A 1d-array (list) version of session.infile.

property infiles

infile:

Name of a file containing (default: OpenQASM format) a quantum circuit.

infiles:

Valid settings: [infile, …]

A 1d-array (list) version of session.infile.

property initial_bond_dimension

initial_bond_dimension:

Set the initial bond dimension (MPS simulator). The single setting applies globally.

initial_bond_dimensions:

A 1d-array (list) version of initial_bond_dimension.

Note

This is only needed if using the “tnqvm” backend accelerator.

property initial_bond_dimensions

initial_bond_dimension:

Set the initial bond dimension (MPS simulator). The single setting applies globally.

initial_bond_dimensions:

A 1d-array (list) version of initial_bond_dimension.

Note

This is only needed if using the “tnqvm” backend accelerator.

property initial_kraus_dimension

initial_kraus_dimension:

Set the initial kraus dimension (MPS simulator). The single setting applies globally.

initial_kraus_dimensions:

A 1d-array (list) version of initial_kraus_dimension.

Note

This is only needed if using the “tnqvm” backend accelerator.

property initial_kraus_dimensions

initial_kraus_dimension:

Set the initial kraus dimension (MPS simulator). The single setting applies globally.

initial_kraus_dimensions:

A 1d-array (list) version of initial_kraus_dimension.

Note

This is only needed if using the “tnqvm” backend accelerator.

property instring

instring:

A string that defines a circuit in OpenQASM format. Simple example:

__qpu__ void QBCIRCUIT(qreg q) {
        OPENQASM 2.0;
        include "qelib1.inc;"
        creg c0[1];
        creg c1[1];
        h q[0];
        cx q[0],q[1];
        measure q[0] -> c0[0];
        measure q[1] -> c1[0];
}

instrings:

Valid settings: [instring, …]

A 1d-array (list) version of session.instring.

property instrings

instring:

A string that defines a circuit in OpenQASM format. Simple example:

__qpu__ void QBCIRCUIT(qreg q) {
        OPENQASM 2.0;
        include "qelib1.inc;"
        creg c0[1];
        creg c1[1];
        h q[0];
        cx q[0],q[1];
        measure q[0] -> c0[0];
        measure q[1] -> c1[0];
}

instrings:

Valid settings: [instring, …]

A 1d-array (list) version of session.instring.

property ir_target

ir_target:

Input quantum circuit (core.Circuit).

ir_targets:

A 1d-array (list) version of ir_target.

property ir_targets

ir_target:

Input quantum circuit (core.Circuit).

ir_targets:

A 1d-array (list) version of ir_target.

property log_enabled

Warning

This property is currently unused.

log_enabled:

Setting this to True to enable logging to file. The single setting applies globally.

Valid settings: True | False

log_enableds:

Valid settings: [[True|False, …], [True|False, …]]

A 1d-array (list) version of log_enabled.

property log_enableds

Warning

This property is currently unused.

log_enabled:

Setting this to True to enable logging to file. The single setting applies globally.

Valid settings: True | False

log_enableds:

Valid settings: [[True|False, …], [True|False, …]]

A 1d-array (list) version of log_enabled.

property max_bond_dimension

max_bond_dimension:

Set the maximum bond dimension (MPS simulator). The single setting applies globally.

max_bond_dimensions:

A 1d-array (list) version of max_bond_dimension.

Note

This is only needed if using the “tnqvm” backend accelerator.

property max_bond_dimensions

max_bond_dimension:

Set the maximum bond dimension (MPS simulator). The single setting applies globally.

max_bond_dimensions:

A 1d-array (list) version of max_bond_dimension.

Note

This is only needed if using the “tnqvm” backend accelerator.

property max_kraus_dimension

max_kraus_dimension:

Set the maximum kraus dimension (MPS simulator). The single setting applies globally.

max_kraus_dimensions:

A 1d-array (list) version of max_kraus_dimension.

Note

This is only needed if using the “tnqvm” backend accelerator.

property max_kraus_dimensions

max_kraus_dimension:

Set the maximum kraus dimension (MPS simulator). The single setting applies globally.

max_kraus_dimensions:

A 1d-array (list) version of max_kraus_dimension.

Note

This is only needed if using the “tnqvm” backend accelerator.

property measure_sample_sequential

measure_sample_sequential:

Set the measurement sampling method (QB emulator tensor network simulator). The single setting applies globally.

measure_sample_sequentials:

A 1d-array (list) version of measure_sample_sequential.

Note

This is only needed if using the emulator tensor network accelerators.

property measure_sample_sequentials

measure_sample_sequential:

Set the measurement sampling method (QB emulator tensor network simulator). The single setting applies globally.

measure_sample_sequentials:

A 1d-array (list) version of measure_sample_sequential.

Note

This is only needed if using the emulator tensor network accelerators.

property noise

noise:

Valid settings: True | False

Setting this to True to enable noisy simulation (if supported by the acc backend). The single setting applies globally.

noises:

Valid settings: [[True|False, …], [True|False, …]]

A 1d-array (list) version of noise.

property noise_mitigation

noise_mitigation:

Select a noise mitigation module.

noise_mitigations:

A 1d-array (list) version of noise_mitigation.

property noise_mitigations

noise_mitigation:

Select a noise mitigation module.

noise_mitigations:

A 1d-array (list) version of noise_mitigation.

property noise_model

noise_model:

Set the noise model to be used in subsequent simulations.

Note

Requires setting: noise = True (to have effect)

The default (built in) model is a simple depolarizing noise model on all qubits.

Users may make their own instances of the NoiseModel class (or make an instance of the default and modify it), and then assign that model to this property. See examples/python/noise_model*.py.

If the Qristal Emulator is installed, the following additional models are available and can be accessed by specifying the relevant model name as a string passed to the constructor of the NoiseModel class:

“qb-nm1” : 4x4 NV centres in x-y grid, 3 qubits per NV centre

“qb-nm2” : 8x8 NV centres in x-y grid, 1 qubit per NV centre, nearest x and nearest y connectivity

“qb-nm3” : 48 NV centres in a 1-dimensional grid with linear qubit index, 1 qubits per NV centre

“qb-qdk1” : 1 NV centre with 2 qubits, fidelities tuned to match deployed device

“qb-dqc2” : 1 NV centre with 2 qubits, fidelities tuned to match lab-based device

noise_models:

A 1d-array (list) version of noise_model.

property noise_models