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Book reviews

     

Truncated Newton method for sparse unconstrained optimization using automatic differentiation

When solving large complex optimization problems, the user is faced with three major problems. These are (i) the cost in human time in obtaining accurate expressions for the derivatives involved; (ii) the need to store second derivative information; and (iii), of lessening importance, the time taken to solve the problem on the computer. For many problems, a significant part of the latter can be attributed to solving Newton-like equations. In the algorithm described, the equations are solved using a conjugate direction method that only needs the Hessian at the current point when it is multiplied by a trial vector. In this paper, we present a method that finds this product using automatic differentiation while only requiring vector storage. The method takes advantage of any sparsity in the Hessian matrix and computes exact derivatives. It avoids the complexity of symbolic differentiation, the inaccuracy of numerical differentiation, the labor of finding analytic derivatives, and the need for matrix store. When far from a minimum, an accurate solution to the Newton equations is not justified, so an approximate solution is obtained by using a version of Dembo and Steihaug's truncated Newton algorithm (Ref. 1).This paper was presented at the SIAM National Meeting, Boston, Massachusetts, 1986.     

Exact soliton solutions of spinor Bose-Einstein condensates

We study matter-wave solitons in Bose-Einstein condensates of ultracold gaseous atoms with spin degrees of freedom and present a class of exact solutions based on the inverse scattering method. The one-soliton solutions are classified with respect to the spin states. We analyze collisional effects between solitons in the same or different spin state(s), which reveals a very interesting possibility: we can manipulate the spin dynamics by controlling the parameters of colliding solitons.     

3D-TOFSIMS characterization of black spots in polymer light emitting diodes

The occurrence and formation of black spots areas in PolyLED devices has been studied by time-of-flight SIMS (TOFSIMS). The composition, shape and position of the black spots is visualised by three-dimensional (3D)-TOFSIMS depth-profiling. It has been established that the formation of non-emissive spots is due to the growth of aluminium oxide clusters at the AlBa/polymer interface. Electron injection in the black spots is lost by the resulting local increase of the resistivity of the cathode.     

Specific features of photoisomerization of provitamin D 3 in a nematic liquid crystal

Photoisomerization of provitamin D ₃ (7-dehydrocholesterol) in a nematic liquid crystal (ZLI-1695, Merck) is investigated in detail by UV absorption spectroscopy. It is found that dissolution of chiral molecules of provitamin D ₃ induces the cholesteric phase in a nematic. The spectral kinetics of photoisomerization in this phase changes significantly from that in an ethanol solution. A sharp nonmonotonic dependence of the increase in accumulation of trans isomer tachysterol in a liquid crystal matrix with a decrease in the induced cholesteric pitch from 2200 to 25 μm is revealed.     

C- and N-Amidotrichloroethylation of Azoles

1H-Pyrazoles, triazoles, and imidazoles in reaction with ethoxycarbonylimine and arylsulfonylimines of chloral yield addition products, corresponding 1-(1-amidotrichloroethyl)azoles. Derivatives of 1-alkylpyrazoles and pyrazolones react with chloral 4-chlorophenylsulfonylimine to furnish products of C-amidotrichloroethylation into position 4 of the azole ring.     

Rehabilitation of the Gauss-Jordan algorithm

Summary In this paper a Gauss-Jordan algorithm with column interchanges is presented and analysed. We show that, in contrast with Gaussian elimination, the Gauss-Jordan algorithm has essentially differing properties when using column interchanges instead of row interchanges for improving the numerical stability. For solutions obtained by Gauss-Jordan with column interchanges, a more satisfactory bound for the residual norm can be given. The analysis gives theoretical evidence that the algorithm yields numerical solutions as good as those obtained by Gaussian elimination and that, in most practical situations, the residuals are equally small. This is confirmed by numerical experiments. Moreover, timing experiments on a Cyber 205 vector computer show that the algorithm presented has good vectorisation properties.