Self-consistent calculation of the superconducting gap

%matplotlib inline
from quant_met import geometry, mean_field

graphene_lattice = geometry.Graphene()
h = mean_field.EGXHamiltonian(
    hopping_gr=1,
    hopping_x=0.01,
    hopping_x_gr_a=1,
    lattice_constant=graphene_lattice.lattice_constant,
    chemical_potential=0.05,
    hubbard_int_x=1,
    hubbard_int_gr=1,
)
solved_h = mean_field.self_consistency_loop(h=h, number_of_k_points=100, epsilon=1e-9)

Old: [11.27451944 24.23568369 26.16494446]
New: [-0.4969519+7.6227480e-37j -0.4976627+7.8993718e-13j
 -0.4992918+1.0328691e-34j]
Difference [10.77756754 23.738021   25.66565266]
Old: [-0.4969519+7.6227480e-37j -0.4976627+7.8993718e-13j
 -0.4992918+1.0328691e-34j]
New: [0.13687669+5.7778435e-14j 0.26026246+1.6628001e-12j
 0.37336567+8.4846911e-14j]
Difference [0.36007524 0.23740023 0.12592614]
Old: [0.13687669+5.7778435e-14j 0.26026246+1.6628001e-12j
 0.37336567+8.4846911e-14j]
New: [-0.06337974+1.5729224e-13j -0.20659062+3.8311260e-12j
 -0.34990248+4.1175667e-13j]
Difference [0.07349695 0.05367184 0.02346319]
Old: [-0.06337974+1.5729224e-13j -0.20659062+3.8311260e-12j
 -0.34990248+4.1175667e-13j]
New: [0.04704691+3.9037041e-13j 0.19306026+1.8078214e-12j
 0.34554365+1.2781697e-12j]
Difference [0.01633283 0.01353036 0.00435883]
Old: [0.04704691+3.9037041e-13j 0.19306026+1.8078214e-12j
 0.34554365+1.2781697e-12j]
New: [-0.04327855+2.9163103e-13j -0.18962845-5.2329306e-14j
 -0.34477895+1.5615429e-12j]
Difference [0.00376837 0.00343181 0.0007647 ]
Old: [-0.04327855+2.9163103e-13j -0.18962845-5.2329306e-14j
 -0.34477895+1.5615429e-12j]
New: [0.04239125+1.2316775e-13j 0.18876444+7.3247989e-13j
 0.3446538 +1.3354658e-12j]
Difference [0.0008873  0.00086401 0.00012517]
Old: [0.04239125+1.2316775e-13j 0.18876444+7.3247989e-13j
 0.3446538 +1.3354658e-12j]
New: [-0.04217995+1.5742922e-13j -0.18854833+2.0858077e-12j
 -0.3446352 +1.3334361e-12j]
Difference [2.1129847e-04 2.1611154e-04 1.8596649e-05]
Old: [-0.04217995+1.5742922e-13j -0.18854833+2.0858077e-12j
 -0.3446352 +1.3334361e-12j]
New: [0.04212927+2.8586294e-13j 0.18849453-9.4710860e-13j
 0.3446329 +1.6773684e-12j]
Difference [5.0682575e-05 5.3793192e-05 2.2947788e-06]
Old: [0.04212927+2.8586294e-13j 0.18849453-9.4710860e-13j
 0.3446329 +1.6773684e-12j]
New: [-0.04211704+4.6911517e-14j -0.18848118+6.8316837e-12j
 -0.34463277+1.2084345e-12j]
Difference [1.22226775e-05 1.33514404e-05 1.19209290e-07]
Old: [-0.04211704+4.6911517e-14j -0.18848118+6.8316837e-12j
 -0.34463277+1.2084345e-12j]
New: [0.04211408+6.9561338e-13j 0.18847787+4.1522306e-12j
 0.34463283+2.7694667e-12j]
Difference [ 2.9616058e-06  3.3080578e-06 -5.9604645e-08]
Old: [0.04211408+6.9561338e-13j 0.18847787+4.1522306e-12j
 0.34463283+2.7694667e-12j]
New: [-0.04211336+6.3211296e-13j -0.18847707+1.0189978e-11j
 -0.34463283+3.4583877e-12j]
Difference [7.189810e-07 8.046627e-07 0.000000e+00]
Old: [-0.04211336+6.3211296e-13j -0.18847707+1.0189978e-11j
 -0.34463283+3.4583877e-12j]
New: [0.04211319+1.2107649e-12j 0.18847686+9.8746983e-12j
 0.34463286+5.5763983e-12j]
Difference [ 1.7508864e-07  2.0861626e-07 -2.9802322e-08]
Old: [0.04211319+1.2107649e-12j 0.18847686+9.8746983e-12j
 0.34463286+5.5763983e-12j]
New: [-0.04211315+1.3826809e-12j -0.18847682+1.5146823e-11j
 -0.34463286+7.3376444e-12j]
Difference [4.0978193e-08 4.4703484e-08 0.0000000e+00]
Old: [-0.04211315+1.3826809e-12j -0.18847682+1.5146823e-11j
 -0.34463286+7.3376444e-12j]
New: [0.04211314+1.9845386e-12j 0.1884768 +1.1023485e-11j
 0.34463286+1.0190397e-11j]
Difference [1.1175871e-08 1.4901161e-08 0.0000000e+00]
Old: [0.04211314+1.9845386e-12j 0.1884768 +1.1023485e-11j
 0.34463286+1.0190397e-11j]
New: [-0.04211313+1.8523048e-12j -0.1884768 +3.3645489e-12j
 -0.34463286+1.1614067e-11j]
Difference [3.7252903e-09 0.0000000e+00 0.0000000e+00]
Finished
[0.04211313+1.2110719e-12j 0.1884768 +3.3582211e-13j
 0.34463286+1.0879225e-11j]