amplify.client.ocean.DWaveSamplerClientQuantumSolverParametersOcean

class DWaveSamplerClientQuantumSolverParametersOcean

D-Wave solver parameters available in DWaveSamplerClient of Amplify SDK. For more information, see D-Wave Sampler Properties and Solver Parameters.

__init__(*args, **kwargs)

Methods

__init__(*args, **kwargs)

Attributes

anneal_offsets	Provides offsets to annealing paths, per qubit.
anneal_schedule	Introduces variations to the global anneal schedule.
annealing_time	Sets the duration, in microseconds, of quantum annealing time, per read.
answer_mode	Indicates how answers are returned from the solver.
auto_scale	Indicates whether \(-h\) and \(J\) values are rescaled.
beta	Provides a value for the Boltzmann distribution parameter.
chains	Defines which qubits represent the same logical variable.
flux_biases	List of flux-bias offset values with which to calibrate a chain.
flux_drift_compensation	Boolean flag indicating whether the D-Wave system compensates for flux drift.
h_gain_schedule	Sets a time-dependent gain for linear coefficients (qubit biases, see the h parameter) in the Hamiltonian.
initial_state	Initial state to which the system is set for reverse annealing.
max_answers	Specifies the maximum number of answers returned from the solver.
num_reads	Indicates the number of states (output solutions) to read from the solver.
num_spin_reversal_transforms	Specifies the number of spin-reversal transforms to perform.
postprocess	Defines what type of postprocessing the system runs online on raw solutions.
programming_thermalization	Sets the time, in microseconds, to wait after programming the QPU for it to cool back to base temperature.
readout_thermalization	Sets the time, in microseconds, to wait after each state is read from the QPU for it to cool back to base temperature.
reduce_intersample_correlation	Boolean flag indicating whether the system adds a delay between reads.
reinitialize_state	Boolean parameter to control reinitialization.

property anneal_offsets

Provides offsets to annealing paths, per qubit. Given by the list, where the indices and elements correspond to the qubit indices and their annealing offset values, respectively. For more information, see anneal_offsets.

Type:

list

Note

Modifying each element anneal_offsets by direct reference is not supported. If you need to replace one or more elements, the entire list needs to be redefined.

from amplify.client.ocean import DWaveSamplerClient

client = DWaveSamplerClient(token="XXXX-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
client.parameters.anneal_offsets = [0.1, 0.2]

>>> client.parameters.anneal_offsets
[0.1, 0.2]
>>> client.parameters.anneal_offsets[0] = 0.3 # List elements cannot be replaced by direct reference.
>>> client.parameters.anneal_offsets
[0.1, 0.2]
>>> client.parameters.anneal_offsets= [0.3, 0.4]  # Redefition of the entire list can replace list elements.
>>> client.parameters.anneal_offsets
[0.3, 0.4]

property anneal_schedule

Introduces variations to the global anneal schedule. For more information, see anneal_schedule.

Type:

list

Note

Modifying each list element of anneal_schedule by direct reference is not supported. If you need to replace one or more list elements, the entire two-dimensional list needs to be redefined.

from amplify.client.ocean import DWaveSamplerClient

client = DWaveSamplerClient(token="XXXX-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
client.parameters.anneal_schedule = [[0.0, 0.0], [2, 0.3], [5, 1.0]]

>>> client.parameters.anneal_schedule
[[0.0, 0.0], [2, 0.3], [5, 1.0]]
>>> client.parameters.anneal_schedule[1] = [3, 0.5]  # List elements cannot be replaced by direct reference.
>>> client.parameters.anneal_schedule
[[0.0, 0.0], [2, 0.3], [5, 1.0]]
>>> client.parameters.anneal_schedule = [[0.0, 0.0], [3, 0.5], [5, 1.0]]  # Redefition of the entire list can replace list elements.
>>> client.parameters.anneal_schedule
[[0.0, 0.0], [3, 0.5], [5, 1.0]]

property annealing_time

Sets the duration, in microseconds, of quantum annealing time, per read. For more information, see annealing_time.

Type:

int

property answer_mode

Indicates how answers are returned from the solver. Supported values are 'raw' and 'histogram'. For more information, see answer_mode.

Type:

str

property auto_scale

Indicates whether \(-h\) and \(J\) values are rescaled. For more information, see auto_scale.

Type:

bool

property beta

Provides a value for the Boltzmann distribution parameter. For more information, see beta. Not available for Advantage_system4.1 and Advantage_system6.3.

Type:

float

property chains

Defines which qubits represent the same logical variable. Given by the two-dimensional list, where each element in the list is a list of bits that form a chain. For more information, see chains. Not available for Advantage_system4.1 and Advantage_system6.3.

Type:

list

Note

Modifying each list element of chains by direct reference is not supported. If you need to replace one or more list elements, the entire two-dimensional list needs to be redefined.

from amplify.client.ocean import DWaveSamplerClient

client = DWaveSamplerClient(token="XXXX-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
client.parameters.chains = [[0, 1], [2, 3]]

>>> client.parameters.chains
[[0, 1], [2, 3]]
>>> client.parameters.chains[0] = [4, 5, 6]  # List elements cannot be replaced by direct reference.
>>> client.parameters.chains
[[0, 1], [2, 3]]
>>> client.parameters.chains = [[4, 5, 6], [7, 8]]  # Redefition of the entire list can replace list elements.
>>> client.parameters.chains
[[4, 5, 6], [7, 8]]

property flux_biases

List of flux-bias offset values with which to calibrate a chain. For more information, see flux_biases.

Type:

list

Note

Modifying each element of flux_biases by direct reference is not supported. If you need to replace one or more elements, the entire list needs to be redefined.

from amplify.client.ocean import DWaveSamplerClient

client = DWaveSamplerClient(token="XXXX-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
client.parameters.flux_biases = [0.001, 0.002]

>>> client.parameters.flux_biases
[0.001, 0.002]
>>> client.parameters.flux_biases[0] = 0.003 # List elements cannot be replaced by direct reference.
>>> client.parameters.flux_biases
[0.001, 0.002]
>>> client.parameters.flux_biases= [0.003, 0.004]  # Redefition of the entire list can replace list elements.
>>> client.parameters.flux_biases
[0.003, 0.004]

property flux_drift_compensation

Boolean flag indicating whether the D-Wave system compensates for flux drift. For more information, see flux_drift_compensation.

Type:

bool

property h_gain_schedule

Sets a time-dependent gain for linear coefficients (qubit biases, see the h parameter) in the Hamiltonian. For more information, see h_gain_schedule.

Type:

list

Note

Modifying each list element of h_gain_schedule by direct reference is not supported. If you need to replace one or more list elements, the entire two-dimensional list needs to be redefined.

from amplify.client.ocean import DWaveSamplerClient

client = DWaveSamplerClient(token="XXXX-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
client.parameters.h_gain_schedule = [[0.0, 0.0], [2, 0.3], [5, 1.0]]

>>> client.parameters.h_gain_schedule
[[0.0, 0.0], [2, 0.3], [5, 1.0]]
>>> client.parameters.h_gain_schedule[1] = [3, 0.5]  # List elements cannot be replaced by direct reference.
>>> client.parameters.h_gain_schedule
[[0.0, 0.0], [2, 0.3], [5, 1.0]]
>>> client.parameters.h_gain_schedule = [[0.0, 0.0], [3, 0.5], [5, 1.0]]  # Redefition of the entire list can replace list elements.
>>> client.parameters.h_gain_schedule
[[0.0, 0.0], [3, 0.5], [5, 1.0]]

property initial_state

Initial state to which the system is set for reverse annealing. Given by a list of tuples (or lists), where the first and second tuple elements correspond to the qubit index and its initial value, respectively. For more information, see initial_state.

Type:

list

Note

Modifying each list element of inital_state by direct reference is not supported. If you need to replace one or more list elements, the entire two-dimensional list needs to be redefined.

from amplify.client.ocean import DWaveSamplerClient

client = DWaveSamplerClient(token="XXXX-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx")
client.parameters.inital_state = [(5, 1), (10, 0)]

>>> client.parameters.inital_state
[(5, 1), (10, 0)]
>>> client.parameters.inital_state[0] = [5, 0]  # List elements cannot be replaced by direct reference.
>>> client.parameters.inital_state
[(5, 1), (10, 0)]
>>> client.parameters.inital_state = [(5, 0), (10, 1)]  # Redefition of the entire list can replace list elements.
>>> client.parameters.inital_state
[(5, 0), (10, 1)]

property max_answers

Specifies the maximum number of answers returned from the solver. For more information, see max_answers.

Type:

int

property num_reads

Indicates the number of states (output solutions) to read from the solver. For more information, see num_reads.

Type:

int

property num_spin_reversal_transforms

Specifies the number of spin-reversal transforms to perform. For more information, see num_spin_reversal_transforms.

Type:

int

property postprocess

Defines what type of postprocessing the system runs online on raw solutions. For more information, see postprocess. Not available for Advantage_system4.1 and Advantage_system6.3.

Type:

str

property programming_thermalization

Sets the time, in microseconds, to wait after programming the QPU for it to cool back to base temperature. For more information, see programming_thermalization.

Type:

int

property readout_thermalization

Sets the time, in microseconds, to wait after each state is read from the QPU for it to cool back to base temperature. For more information, see readout_thermalization.

Type:

int

property reduce_intersample_correlation

Boolean flag indicating whether the system adds a delay between reads. For more information, see reduce_intersample_correlation.

Type:

bool

property reinitialize_state

Boolean parameter to control reinitialization. For more information, see reinitialize_state.

Type:

bool