Gluon jets from quarkonia

A detailed analysis is made within perturbative QCD of the decays into gluon jets of P-wave and S-wave quarkonia (J^PC = 0⁺⁺, 1⁺⁺, 2⁺⁺, 1^+? and 0^?+, 1^??). For all those states we compute to leading non-trivial order in α_s the conventional fraction f(?, δ) of the jet-like hadronic final states, characterized by the back-to-back cone of half angle δ, in which all but a small fraction ? of the total energy is emitted. To the same order we give also the average values of thrust momenta and spherocity distributions.     

The Lefschetz number of an involution on the space of harmonic cusp forms ofSL 3

Inventiones mathematicae -     

Whitham's dynamical principle for parabolic equations and its proof

A generalization of Whitham's asymptotic principle for parabolic equations is stated. An application of this principle to Fisher's one-dimensional nonlinear equation is considered.Translated from Zapiski Nauchnykh Seminarov Leningradskogo Otdeleniya Matematicheskogo Instituta im. V. A. Steklova, Vol. 179, pp. 46–51, 1989.     

Christoffel-Darboux-type formulae and a recurrence for biorthogonal polynomials

It is proved that biorthogonal polynomials obey two different kinds of Christoffel-Darboux-type formulae, one linking polynomials with a different parameter and one combining polynomials with different degrees. This is used to produce a mixed recurrence relation, which is valid for all biorthogonal polynomials. This recurrence relation establishes several results on interlacing property of zeros of successive biorthogonal polynomials and leads to a new result on the interlace of zeros of orthogonal polynomials (of equal degrees) with respect to two distributionsdψ(x) andx ^p dψ(x), 0<p≤1, with support in either [0, 1] or [1, ∞).     

A search technique for global optimization in a chaotic environment

We describe a new algorithm which uses the trajectories of a discrete dynamical system to sample the domain of an unconstrained objective function in search of global minima. The algorithm is unusually adept at avoiding nonoptimal local minima and successfully converging to a global minimum. Trajectories generated by the algorithm for objective functions with many local minima exhibit chaotic behavior, in the sense that they are extremely sensitive to changes in initial conditions and system parameters. In this context, chaos seems to have a beneficial effect: failure to converge to a global minimum from a given initial point can often be rectified by making arbitrarily small changes in the system parameters.