Looking for a gmic + python scripter to help me out here.

Well, about 4 hours. They canned a meeting on me. I’m imperfectly disappointed.
Here goes:
well image = quantum_torus_small.png 30,30,1,1
N = 30
No_points N*N = 900
increment 1/(N-1)^2 = 0.0011890606420927466
incrementValue -(N-1)^2 = -841.0
zeroV 4*(N-1)^2 = 3364.0

The diagonals offset from main diagonals have two values, 0 or -841. The main diagonal has a value of 3364. These values are consistent with those computed above.

The first non-zero pixels for the five diagonals are:

diagmN 73,103             (diagonal begins at 0,30. Initial interval of zero-valued pix: 73)
diagm1 73,74              (diagonal begins at 0,1.  Initial interval of zero-valued pix: 73) 
diag0  0, 0
diagp1 74,73              (diagonal begins at 1,0.  Initial interval of zero-valued pix: 73)
diagpN 103,73             (diagonal begins at 30,0. Initial interval of zero-valued pix: 73)

These are consistent with quantum_torus_small.png. It’s first two rows are black (60 pixels) the third row is black from zero to twelve (13) 30 + 30 + 13 = 73

The well image, the Hamiltonian generated with @weight_an’s script, and 30 rendered eigenvectors, also computed from his script, scaled from 30->128, normalized and mapped with rainbow.
hamneigs.zip sha256 hash 0d95f76775232a6aedb8a3a6463eadc6cb9fbb060987c39f164ab6ca88e5ad96
Have fun.
hamneigs.zip (434.5 KB)