diff --git a/calculations/PMM.py b/calculations/PMM.py
index 4123a7e..db5559d 100644
--- a/calculations/PMM.py
+++ b/calculations/PMM.py
@@ -17,7 +17,7 @@ train_ks = torch.tensor(train_data['k'].to_numpy(), dtype=torch.complex128)
 
 #%%
 # hyperparameters
-N = 9
+N = 5
 
 # initialize random Hamiltonians
 H0 = torch.randn(N, N, dtype=torch.complex128)
@@ -29,11 +29,11 @@ H1 = (H1 + torch.transpose(H1, 0, 1)).requires_grad_() # symmetric
 # training
 
 # generate a set of c values to follow by subdividing the training cs
-subdivisions = 3
+subdivisions = 2
 c_steps = np.concatenate([np.linspace(start, stop, subdivisions, endpoint=False) for (start, stop) in zip(train_cs, train_cs[1:])])
 c_steps = np.append(c_steps, train_cs[-1])
 
-lr = 0.05
+lr = 0.01
 epochs = 100000
 for epoch in range(epochs):
     ks = torch.empty(len(train_data), dtype=torch.complex128)