Complete Pick positivity and unitary invariance

The characteristic function for a contraction is a classical complete unitary invariant devised by Sz.-Nagy and Foias. Just as a contraction is related to the Szego kernel k(S) (z, w) = (1 - z (w) over tilde)(-1) for |z|, |w| < 1, by means of (1/k(S))(T,T*) >= 0, we consider an arbitrary open connected domain Omega in C-n, a complete Pick kernel k on Omega and a tuple T = (T-1, ..., T-n) of commuting bounded operators on a complex separable Hilbert space H such that (1/k)(T,T*) >= 0. For a complete Pick kernel the 1/k functional calculus makes sense in a beautiful way. It turns out that the model theory works very well and a characteristic function can be associated with T. Moreover, the characteristic function is then a complete unitary invariant for a suitable class of tuples T.

Thermal decomposition of ethylene diamine diperchlorate

Thermal decomposition of ethylene diamine diperchlorate (EDDP) has been studied by differential-thermal analysis (DTA), thermogravimetric analysis (TGA), isothermal weight-loss measurements and mass-spectrometric analysis of the decomposition products. It has been observed that EDDP decomposes in two temperature regions. The low-temperature decomposition stops at about 35 to 40 percent weight loss below 250°C. The reason for the low-temperature cessation may be the adsorption of excess ethylene diamine on the crystal surface of EDDP. An overall activation energy of 54 kcal per mole has been calculated for the thermal decomposition of EDDP. Mass-spectrometric analysis shows that the decomposition products are mainly CO2, H2O, HCl and N2. The following stoichiometry has been proposed for the thermal decomposition of EDDP: (−CH2NH3CIO4)2→2CO2O+2HCl+N2

Toward Effective Scalar Hardware for Highly Vectorizable Applications

The performance of a program will ultimately be limited by its serial (scalar) portion, as pointed out by Amdahl′s Law. Reported studies thus far of instruction-level parallelism have mixed data-parallel program portions with scalar program portions, often leading to contradictory and controversial results. We report an instruction-level behavioral characterization of scalar code containing minimal data-parallelism, extracted from highly vectorized programs of the PERFECT benchmark suite running on a Cray Y-MP system. We classify scalar basic blocks according to their instruction mix, characterize the data dependencies seen in each class, and, as a first step, measure the maximum intrablock instruction-level parallelism available. We observe skewed rather than balanced instruction distributions in scalar code and in individual basic block classes of scalar code; nonuniform distribution of parallelism across instruction classes; and, as expected, limited available intrablock parallelism. We identify frequently occurring data-dependence patterns and discuss new instructions to reduce latency. Toward effective scalar hardware, we study latency-pipelining trade-offs and restricted multiple instruction issue mechanisms.

Flat connections, geometric invariants and the symplectic nature of the fundamental group of surfaces

In this paper we associate a new geometric invariant to the space of fiat connections on a G (= SU(2))-bundle on a compact Riemann surface M and relate it tcr the symplectic structure on the space Hom(pi(1)(M), G)/G consisting of representations of the fundamental group pi(1)(M) Of M into G module the conjugate action of G on representations.