Timeless path integral for relativistic quantum mechanics

Starting from the canonical formalism of relativistic (timeless) quantum mechanics, the formulation of timeless path integral is rigorously derived. The transition amplitude is reformulated as the sum, or functional integral, over all possible paths in the constraint surface specified by the (relativistic) Hamiltonian constraint, and each path contributes with a phase identical to the classical action divided by $\hbar$. The timeless path integral manifests the timeless feature as it is completely independent of the parametrization for paths. For the special case that the Hamiltonian constraint is a quadratic polynomial in momenta, the transition amplitude admits the timeless Feynman's path integral over the (relativistic) configuration space. Meanwhile, the difference between relativistic quantum mechanics and conventional nonrelativistic (with time) quantum mechanics is elaborated on in light of timeless path integral.Comment: 41 pages; more references and comments added; version to appear in CQ

High Spin Glueballs from the Lattice

We discuss the principles underlying higher spin glueball calculations on the lattice. For that purpose, we develop numerical techniques to rotate Wilson loops by arbitrary angles in lattice gauge theories close to the continuum. As a first application, we compute the glueball spectrum of the SU(2) gauge theory in 2+1 dimensions for both parities and for spins ranging from 0 up to 4 inclusive. We measure glueball angular wave functions directly, decomposing them in Fourier modes and extrapolating the Fourier coefficients to the continuum. This allows a reliable labelling of the continuum states and gives insight into the way rotation symmetry is recovered. As one of our results, we demonstrate that the D=2+1 SU(2) glueball conventionally labelled as J^P = 0^- is in fact 4^- and that the lightest ``J=1'' state has, in fact, spin 3.Comment: Minor changes in the text; the spin 4 glueball mass is taken further out in Euclidean time at higher beta values. 41 pages, 20 figure

Effective Field Theory of Nuclear Forces

The application of the effective field theory (EFT) method to nuclear systems is reviewed. The roles of degrees of freedom, QCD symmetries, power counting, renormalization, and potentials are discussed. EFTs are constructed for various energy regimes of relevance in nuclear physics, and are used in systematic expansions to derive nuclear forces in terms of a number of parameters that embody information about QCD dynamics. Two-, three-, and many-nucleon systems, including external probes, are considered.Comment: 83 pages, 20 figures, commissioned for Prog. Part. Nucl. Phy

Reconstruction subgrid models for nonpremixed combustion

Large-eddy simulation of combustion problems involves highly nonlinear terms that, when filtered, result in a contribution from subgrid fluctuations of scalars, Z, to the dynamics of the filtered value. This subgrid contribution requires modeling. Reconstruction models try to recover as much information as possible from the resolved field Z, based on a deconvolution procedure to obtain an intermediate field ZM. The approximate reconstruction using moments (ARM) method combines approximate reconstruction, a purely mathematical procedure, with additional physics-based information required to match specific scalar moments, in the simplest case, the Reynolds-averaged value of the subgrid variance. Here, results from the analysis of the ARM model in the case of a spatially evolving turbulent plane jet are presented. A priori and a posteriori evaluations using data from direct numerical simulation are carried out. The nonlinearities considered are representative of reacting flows: power functions, the dependence of the density on the mixture fraction (relevant for conserved scalar approaches) and the Arrhenius nonlinearity (very localized in Z space). Comparisons are made against the more popular beta probability density function (PDF) approach in the a priori analysis, trying to define ranges of validity for each approach. The results show that the ARM model is able to capture the subgrid part of the variance accurately over a wide range of filter sizes and performs well for the different nonlinearities, giving uniformly better predictions than the beta PDF for the polynomial case. In the case of the density and Arrhenius nonlinearities, the relative performance of the ARM and traditional PDF approaches depends on the size of the subgrid variance with respect to a characteristic scale of each function. Furthermore, the sources of error associated with the ARM method are considered and analytical bounds on that error are obtained