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9.2 Linear variation functions                237
                                                        X
                                                               2
                                             E ÿ E k ˆ      ja n j (E n ÿ E k )
                                                        n(>k)
                        from which it follows that
                                                        E > E k                            (9:7)
                        Thus, the quantity E is an upper bound to the energy E k corresponding to the
                        state ø k . For situations in which ö can be made orthogonal to each exact
                        eigenfunction ø 0 , ø 1 , ... , ø kÿ1 , the coef®cients a 0 , a 1 , ... , a kÿ1 vanish
                        according to equation (9.4) and the inequality (9.7) applies.
                          An example is a one-dimensional system for which the potential energy V(x)
                        is an even function of the position variable x. The eigenfunction ø 0 with the
                        lowest eigenvalue E 0 has no nodes and therefore must be an even function of x.
                        The eigenfunction ø 1 has one node, located at the origin, and therefore must
                        be an odd function of x. If we select for ö any odd function of x, then ö is
                        orthogonal to any even function of x, including ø 0 , and the coef®cient a 0
                                                          ^
                        vanishes. Thus, the integral E ˆhöjHjöi gives an upper bound to E 1 even
                        though the ground-state eigenfunction ø 0 may not be known.
                          When the exact eigenfunctions ø 0 , ø 1 , ... , ø kÿ1 are not known, they may
                        be approximated by trial functions ö 0 , ö 1 , ... , ö kÿ1 which successively give
                        upper bounds for E 0 , E 1 , ... , E kÿ1 , respectively. In this case, the function ö 1
                        is constructed to be orthogonal to ö 0 , ö 2 constructed orthogonal to both ö 0 and
                        ö 1 , and so forth. In general, this method is dif®cult to apply and gives
                        increasingly less accurate results with increasing n.



                                             9.2 Linear variation functions
                        A convenient and widely used form for the trial function ö is the linear
                        variation function
                                                           N
                                                          X
                                                      ö ˆ     c i ÷ i                      (9:8)
                                                           iˆ1
                        where ÷ 1 , ÷ 2 , ... , ÷ N are an incomplete set of linearly independent functions
                        which have the same variables and which satisfy the same boundary conditions
                        as the exact eigenfunctions ø n of equation (9.1). The functions ÷ i are selected
                        to be real and are not necessarily orthogonal to one another. Thus, the overlap
                        integral S ij , de®ned as
                                                      S ij  h÷ i j÷ j i                    (9:9)
                        is not generally equal to ä ij . The coef®cients c i are also restricted to real values
                        and are variation parameters to be determined by the minimization of the
                        variation integral E .
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