Merge branch 'master' of gitlab.theory.iphy.ac.cn:codes/playwithgrad

test_grad.py

 '''
-Three different ways of computing gradient of infinite matrix product trace 
+Different ways of computing gradient of infinite matrix product trace 
 Z = Tr(T*T...*T)
 '''
 
@@ -34,5 +34,9 @@ loss = torch.log(w[-1])
 loss.backward()
 exact_grad = ((T.grad + T.grad.t())/2) # need to symmetrize since it is an upper triangular matrix
 
+# (4) use leading eigenvector of the transfer matrix $T$
+eigenvector_grad= torch.ger(v[:,-1], v[:, -1])/w[-1] # outer product of the leading eigenvector and its transpose
+
 print ((impurity_grad-exact_grad).abs().max().item())
 print ((lnZ_grad-exact_grad).abs().max().item())
+print ((eigenvector_grad-exact_grad).abs().max().item())