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Block diagonalization

If only zero-order states from the same polyad are conpled together, this constitutes a fantastic simplification in the Flamiltonian. Enonnons compntational economies result in fitting spectra, becanse the spectroscopic Flamiltonian is block diagonal in the polyad nnmber. That is, only zero-order states within blocks with the same polyad number are coupled the resulting small matrix diagonalization problem is vastly simpler than diagonalizing a matrix with all the zero-order states conpled to each other. [Pg.66]

That is, in the basis rj.F.irjjthe Hamiltonian matrix is block diagonal in Fand and we can rewrite (equation A1.4.8) as... [Pg.139]

The Hamiltonian matrix will be block diagonal in this basis set. There will be one block for each irreducible representation of the synnnetry group. [Pg.140]

If we start with an t -dimensional representation of A consisting of the matrices M, M2, M3,. .., it may be that we can find a matrix V such that when it is used with ( equation A1.4.34) it produces an equivalent representation M, M 2, M 3,. .. each of whose matrices is in the same block diagonal form. For example, the nonvanishing elements of each of the matrices could fonn an upper-left-comer ... [Pg.151]

The value of the vanishing integral rule is that it allows the matrix H to be block diagonalized. This occurs if... [Pg.160]

Assuming that the diabatic space can be truncated to the same size as the adiabatic space, Eqs. (64) and (65) clearly define the relationship between the two representations, and methods have been developed to obtain the tians-formation matrices directly. These include the line integral method of Baer [53,54] and the block diagonalization method of Pacher et al. [179]. Failure of the truncation assumption, however, leads to possibly important nonremovable derivative couplings remaining in the diabatic basis [55,182]. [Pg.280]

IlyperChem supplies three types of optimi/ers or algorithms steepest descent, conjugate gradient (Fletcher-Reeves and Polak-Ribiere), and block diagonal (Newton-Raph son). [Pg.58]

Th c Newton-Raph son block dingotial method is a second order optim izer. It calculates both the first and second derivatives of potential energy with respect to Cartesian coordinates. I hese derivatives provide information ahont both the slope and curvature of lh e poten tial en ergy surface, Un like a full Newton -Raph son method, the block diagonal algorilh m calculates the second derivative matrix for one atom at a lime, avoiding the second derivatives with respect to two atoms. [Pg.60]

Unconstrained optimization methods [W. II. Press, et. ah, Numerical Recipes The An of Scieniific Compulime.. Cambridge University Press, 1 9H6. Chapter 101 can use values of only the objective function, or of first derivatives of the objective function. second derivatives of the objective function, etc. llyperChem uses first derivative information and, in the Block Diagonal Newton-Raphson case, second derivatives for one atom at a time. TlyperChem does not use optimizers that compute the full set of second derivatives (th e Hessian ) because it is im practical to store the Hessian for mac-romoleciiles with thousands of atoms. A future release may make explicit-Hessian meth oils available for smaller molecules but at this release only methods that store the first derivative information, or the second derivatives of a single atom, are used. [Pg.303]

A diva It MM3 wilh Ihe cumrnand mm3. Answer questions file etheiie.mm3, parameter file Enter (default) line number 1, option 2. The defaull parameter sel is Ihe MM3 parameler sel don t ehange il. The line number starts Ihe system reading on the first line of your input file, and option 2 is the block diagonal followed by full matrix minimi7 ation mentioned at the end of the section on the Hessian matrix. You will see intermediate atomic coordinates as the system minimises the geometry, followed by a final steiic eireigy, Kird with 0, output Enter, cooidinates Enter,... [Pg.155]

Note that every matrix in the four dimensional group representation labeled DN) has the so-called block diagonal form... [Pg.586]

These six matrices can be verified to multiply just as the symmetry operations do thus they form another three-dimensional representation of the group. We see that in the Ti basis the matrices are block diagonal. This means that the space spanned by the Tj functions, which is the same space as the Sj span, forms a reducible representation that can be decomposed into a one dimensional space and a two dimensional space (via formation of the Ti functions). Note that the characters (traces) of the matrices are not changed by the change in bases. [Pg.588]

Most ah initio calculations use symmetry-adapted molecular orbitals. Under this scheme, the Hamiltonian matrix is block diagonal. This means that every molecular orbital will have the symmetry properties of one of the irreducible representations of the point group. No orbitals will be described by mixing dilferent irreducible representations. [Pg.218]

The distance matrix A, which holds the relative distances (by whatever similarity measure) between the individual confonnations, is rarely informative by itself. For example, when sampling along a molecular dynamics trajectory, the A matrix can have a block diagonal form, indicating that the trajectory has moved from one conformational basin to another. Nonetheless, even in this case, the matrix in itself does not give reliable information about the size and shape of the respective basins. In general, the distance matrix requires further processing. [Pg.85]

The disappearance of matrix elements between the HF reference and singly excited states is known as Brillouins theorem. The HF reference state therefore only has nonzero matrix elements with doubly excited determinants, and the full Cl matrix acquires a block diagonal structure. [Pg.104]


See other pages where Block diagonalization is mentioned: [Pg.75]    [Pg.151]    [Pg.161]    [Pg.161]    [Pg.161]    [Pg.169]    [Pg.170]    [Pg.1502]    [Pg.2111]    [Pg.198]    [Pg.211]    [Pg.642]    [Pg.60]    [Pg.306]    [Pg.306]    [Pg.286]    [Pg.143]    [Pg.143]    [Pg.161]    [Pg.125]    [Pg.218]    [Pg.220]    [Pg.60]    [Pg.306]    [Pg.306]    [Pg.39]    [Pg.75]    [Pg.254]   


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Diagonal

Diagonalization

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