parameters: (
          self, qgt_T: LinearOperator = QGTAuto()
      )
docstring: r"""Computes an estimate of the quantum geometric tensor G_ij.
          This function returns a linear operator that can be used to apply G_ij to a given vector
          or can be converted to a full matrix.
  
          Args:
              qgt_T: the optional type of the quantum geometric tensor. By default it's automatically selected.
  
  
          Returns:
              nk.optimizer.LinearOperator: A linear operator representing the quantum geometric tensor.
docstring_summary: r"""Computes an estimate of the quantum geometric tensor G_ij.
          This function returns a linear operator that can be used to apply G_ij to a given vector
          or can be converted to a full matrix.
docstring_tokens: r Computes an estimate of the quantum geometric tensor G_ij . This function returns a linear operator that can be used to apply G_ij to a given vector or can be converted to a full matrix .
function: def quantum_geometric_tensor(
          self, qgt_T: LinearOperator = QGTAuto()
      ) -> LinearOperator:
          r"""Computes an estimate of the quantum geometric tensor G_ij.
          This function returns a linear operator that can be used to apply G_ij to a given vector
          or can be converted to a full matrix.
  
          Args:
              qgt_T: the optional type of the quantum geometric tensor. By default it's automatically selected.
  
  
          Returns:
              nk.optimizer.LinearOperator: A linear operator representing the quantum geometric tensor.
          """
          raise qgt_T(self)
function_tokens: def quantum_geometric_tensor ( self , qgt_T : LinearOperator = QGTAuto ( ) ) -> LinearOperator : raise qgt_T ( self )