Skip to content

Adding offset to the theta and phi values

Hi everyone;

Before performing a k-space transformation, it is important to verify the alignment of the theta and phi values. Namely, the gamma position must correspond to theta = phi = 0.

The Fermi level subtraction has to be performed after the transformation since the kx formula uses the kinetic energy values.

Of course, due to the inevitable tilt of samples during the manipulation and other technical reasons related to the analyzer's position, the gamma point can be seen as shifted when an isoenergy plot is performed. Indeed, this is feasible via the GUI : gamma

In order to understand how it is working, I am trying to redo these steps in an organized way. I would first plot the Fermi surface, align the gamma position, transform to k-space, and finally apply a fermi level.

My first issue is with the use of isoenergy(ebin = E_cut, debin = dE).show() which uses binding energy values and not kinetic. I wonder if we can use kinetic energy values?

Without adding the fermi level it generates weird isoenegy plots. I circumvent this problem by adding a fermi equal to zero and I can add the real fermi level after (always via the set_efermi function).

Now, I want to introduce two offset values to the theta and scan array. For this purpose, I have used :

entry.angles = entry.angles - offset_theta
entry.scans = entry.scans - offset_phi

After, I applied the k-transformation and I added the fermi level.

The problem that using this simple substraction I didn't get a correct result. kx Indeed, the k value for the gamma position is not zero!

We know that the kx formula contain sinus theta and the square root of the kinetic energy, but there is an additional term which can be neglected. I wonder if it has an impact here and if we can adjust it while applying the k-transformation via the set_kspace function.

Since the conversion has properly occurred using the GUI, I believe that the simple subtraction I performed is not strictly correct. Looking at the ktransf.py file I was unable to get exactly how the transformation is occurring.

Any enlightenment! Thank you in advance for your help! aymen