filter_function
Graph.filter_function(control_hamiltonian, noise_operator, frequencies, sample_count=100, projection_operator=None, *, name=None)
Evaluate the filter function for a control Hamiltonian and a noise operator at the given frequency elements.
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 filter function.
Return type
FilterFunction
SEE ALSO
Graph.frequency_domain_noise_operator
: Control-frame noise operator in the frequency domain.
Notes
The filter function is defined as 1:
F(f)=Tr(P)1Tr(PF{N~′(t)}(f)F{N~′(t)}(f)†P),with the control-frame noise operator in the frequency domain
F{N~′(t)}(f)=∫0τe−i2πftN~′(t)dt,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.