frequency_domain_noise_operator
Graph.frequency_domain_noise_operator(control_hamiltonian, noise_operator, frequencies, sample_count=100, projection_operator=None, *, name=None)
Create a control-frame noise operator in the frequency domain for a control Hamiltonian and a noise operator at the given frequencies.
Parameters
- control_hamiltonian (Pwc) – The control Hamiltonian Hc(t).
- noise_operator (Pwc) – The noise operator N(t).
- frequencies (list or tuple or np.ndarray) – The elements in the frequency domain at which to return the values of the filter function.
- sample_count (int or None , optional) – The number of points in time, M, to sample the control-frame noise operator. These samples are used to calculate the approximate Fourier integral efficiently. If None the piecewise Fourier integral is calculated exactly. Defaults to 100.
- projection_operator (np.ndarray or None , optional) – The projection operator P. Defaults to the identity matrix.
- name (str or None , optional) – The name of the node.
Returns
The noise operator in the frequency domain.
Return type
SEE ALSO
Graph.filter_function
: The filter function.
Notes
The control-frame noise operator in the frequency domain is defined as the Fourier transform of the operator in the time domain 1:
\mathcal{F} \left\\{ \tilde N^\prime(t) \right\\}(f) = \int_0^\tau e^{-i 2\pi f t} \tilde N^\prime(t) \mathrm{d}t,where
N~′(t)=N~(t)−Tr(P)Tr(PN~(t)P)Iis the traceless control-frame noise operator in the time domain,
N~(t)=Uc†(t)N(t)Uc(t)is the control-frame noise operator in the time domain, and Uc(t) is the time evolution induced by the control Hamiltonian. If sample_count is set, the Fourier integral is approximated as
\mathcal{F} \left\\{ \tilde N^\prime(t) \right\\}(f) \approx \sum_{n=0}^{M-1} \frac{\tau}{M} e^{-i 2\pi f n \tau/M} \langle \tilde N^\prime (n\tau/M) \rangle,where τ is the duration of the control Hamiltonian.