Remove the weight in the graph

[ahao27]

Change

• Removed weight matrices and weight parameters required when creating instances, as they are unnecessary for this example.
• Updated instance data generation in the MaxCut tutorial to address the incorrect usage reported in Issue The instance data generation in the maxcut tutorial is incorrect. #101.

Desciption

This PR addresses issue #101：

• The code now uses nx.to_numpy_array(G, nodelist=list(range(num_nodes))) instead of nx.to_numpy_array(G).
• Since all weights in this example are 1, weight parameters are removed from the example to simplify the code.

[Jacomichi]

I think you can erase this $w_{ij}$ in

Qamomile/docs/tutorial/maxcut.ipynb

Line 135 in 1d56854

" \\min \\quad -\\frac{1}{2} \\sum_{(i,j) \\in E} w_{i,j}(s_i s_j - 1) \n",

Moreover, you can change the problem as maximization for explanation.

[Jacomichi]

Can you change explanation a little bit?

[Jacomichi]

I think the jm.Problem is correct, however, this formula in LaTex is incorrect.
I think this should be max.