qtcad.qubit.noise module
Class used to understand dynamics of two-level systems under the influence of noise.
- class qtcad.qubit.noise.Noise
Bases:
Noise
Class used to understand dynamics of two-level systems under the influence of noise.
- dynamics(H0, delta_V, omega, spectrum, T0, psi0, times, operator, vec_omega=None, num_runs=1, avg=True, seed=None)
Calculates the expectation value of an operator as a function of time.
- Parameters:
H0 (2D array) – Diagonalized system Hamiltonian.
delta_V (2D array) – Drive that can initiate transitions between eigenstates of H0.
omega (float) – Frequency of the drive and of the rotating frame.
spectrum (1D array) – Spectral density of the noise.
T0 (float) – Period of the noise process.
psi0 (qutip Qobj) – Initial state.
times (1D array) – Times at which to solve for the expectation value of the operator.
operator (2D array or qutip Qobj) – operator for which we want the expectation value as a function of time.
vec_omega (1D array) – The frequencies at which the spectral function is evaluated. If None, the noise spectral function is assumed to be evaluated at harmonics omega_k = 2*pi*k/T0.
num_runs (integer) – Number of runs to perform.
avg (boolean) – Whether or not the average of the runs should be computed.
seed (integer) – Default is None. If not None, the random processes will be initialized with the given seed.
- Returns:
numpy array – Array containing the expectation value of the operator for each run (if avg = False) or containing the average over all runs (if avg = True). In the former case the output is a 2D array and in the later it is a 1D array.
- gen_process(times, spectrum, wk, T0)
Generate one realization of a Gaussian random process.
- Parameters:
times (1d array) – Times at which the process is evaluated
spectrum (1d array) – Spectrum at harmonics omega_k = 2*pi*k/T0
T0 (float) – Period of the noise process.
- Returns:
1d array – random process at times specified in input
Note
T0 should be the largest timescale in the problem. Otherwise the noise process will repeat itself periodically.