NoisyResults

class pulser_simulation.simresults.NoisyResults(run_output, size, basis_name, sim_times, n_measures)

Bases: SimulationResults[SampledResult]

Results of a noisy simulation run of a pulse sequence.

Contrary to a CoherentResults object, this object contains a list of Counters describing the state distribution at the time it was created by using QutipEmulator.run() with a noisy simulation. Contains methods for studying the populations and extracting useful information from them.

Attributes

results	Probability distribution of the bitstrings.
states	Measured states as a list of diagonal qutip.Qobj.

Methods

count
expect	Returns the expectation values of operators in obs_list.
get_final_state	Get the final state of the simulation as a diagonal density matrix.
get_state	Gets the state at time t as a diagonal density matrix.
index	Raises ValueError if the value is not present.
plot	Plots the expectation value of a given operator op.
sample_final_state	Returns the result of multiple measurements of the final state.
sample_state	Returns the result of multiple measurements at time t.

Signatures

count(value) → integer -- return number of occurrences of value

expect(obs_list)

Returns the expectation values of operators in obs_list.

Parameters:

obs_list (Sequence[Qobj | ArrayLike]) – Input observable list. ArrayLike objects will be converted to qutip.Qobj.

Return type:

list[float | complex | ArrayLike]

Returns:

Expectation values of obs_list.

get_final_state()

Get the final state of the simulation as a diagonal density matrix.

Note

This is not the density matrix of the system, but is a convenient way of computing expectation values of observables.

Return type:

Qobj

Returns:

States probability distribution as a density matrix.

get_state(t, t_tol=0.001)

Gets the state at time t as a diagonal density matrix.

Note

This is not the density matrix of the system, but is a convenient way of computing expectation values of observables.

Parameters:

• t (float) – Time (in µs) at which to return the state.

• t_tol (float, default: 0.001) – Tolerance for the difference between t and closest time.

Return type:

Qobj

Returns:

States probability distribution as a diagonal density matrix.

index(value[, start[, stop]]) → integer -- return first index of value.

Raises ValueError if the value is not present.

Supporting start and stop arguments is optional, but recommended.

plot(op, fmt='.', label='', error_bars=True)

Plots the expectation value of a given operator op.

Note

The observable must be diagonal.

Parameters:

• op (Qobj) – Operator whose expectation value is wanted.

• fmt (str, default: '.') – Curve plot format.

• label (str, default: '') – y-Axis label.

• error_bars (bool, default: True) – Choose to display error bars.

Return type:

None

sample_final_state(N_samples=1000)

Returns the result of multiple measurements of the final state.

Parameters:

N_samples (int, default: 1000) – Number of samples to return.

Return type:

Counter

Returns:

Sample distribution of bitstrings corresponding to measured quantum states at the end of the simulation.

sample_state(t, n_samples=1000, t_tol=0.001)

Returns the result of multiple measurements at time t.

Parameters:

• t (float) – Time at which the state is sampled (in µs).

• n_samples (int, default: 1000) – Number of samples to return.

• t_tol (float, default: 0.001) – Tolerance for the difference between t and closest time.

Return type:

Counter

Returns:

Sample distribution of bitstrings corresponding to measured quantum states at time t.

property results: list[Counter]

Probability distribution of the bitstrings.

property states: list[Qobj]

Measured states as a list of diagonal qutip.Qobj.