Experiment object links a
sample with an experimental probe.
The probe defines the Q values and the resolution of the individual
measurements, and returns the scattering factors associated with the
different materials in the sample.
Because our models allow representation based on composition, it is no longer trivial to compute the reflectivity from the model. We now have to look up the effective scattering density based on the probe type and probe energy. You’ve already seen this in Subclassing Layer: the render method for the layer requires the probe to look up the material scattering factors.
Rather than using
we can compute reflectivities directly with the functions in
refl1d.reflectivity. These routines provide the raw
calculation engines for the optical matrix formalism, converting
microslab models of the sample into complex reflectivity amplitudes,
and convolving the resulting reflectivity with the instrument resolution.
The following performs a complete calculation for a silicon substrate with 5 Å roughness using neutrons. The theory is sampled at intervals of 0.001, which is convolved with a 1% \(\Delta Q/Q\) resolution function to yield reflectivities at intervals of 0.01.
>>> from numpy import arange >>> from refl1d.reflectivity import reflectivity_amplitude as reflamp >>> from refl1d.reflectivity import convolve >>> Qin = arange(0,0.21,0.001) >>> w,rho,irho,sigma = zip((0,2.07,0,5),(0,0,0,0)) >>> # the last layer has no interface >>> r = reflamp(kz=Qin/2, depth=w, rho=rho, irho=irho, sigma=sigma[:-1]) >>> Rin = (r*r.conj()).real >>> Q = arange(0,0.2,0.01) >>> dQ = Q*0.01 # resolution dQ/Q = 0.01 >>> R = convolve(Qin, Rin, Q, dQ) >>> print("\n".join("Q: %.2f R: %.5e"%(Qi,Ri) for Qi,Ri in zip(Q,R))) Q: 0.00 R: 1.00000e+00 Q: 0.01 R: 3.11332e-02 Q: 0.02 R: 3.30684e-03 ... Q: 0.19 R: 2.10084e-07