7,960 research outputs found
Navier-Stokes calculations for the vortex of a rotor in hover
An efficient finite-difference scheme for the solution of the incompressible Navier-Stokes equation is used to study the vortex wake of a rotor in hover. The solution Procedure uses a vorticity-stream function formulation and incorporates an asymptotic far-field boundary condition enabling the size of the computational domain to be reduced in comparison to other methods. The results from the present method are compared with experimental data obtained by smoke flow visualization and hot-wire measurements for several rotor blade configurations
Theory of minimum effort control
Optimum control theory formulations for solving problems in optimum guidance for interplanetary manned space flight mission
Uncertainties of predictions from parton distribution functions II: the Hessian method
We develop a general method to quantify the uncertainties of parton
distribution functions and their physical predictions, with emphasis on
incorporating all relevant experimental constraints. The method uses the
Hessian formalism to study an effective chi-squared function that quantifies
the fit between theory and experiment. Key ingredients are a recently developed
iterative procedure to calculate the Hessian matrix in the difficult global
analysis environment, and the use of parameters defined as components along
appropriately normalized eigenvectors. The result is a set of 2d Eigenvector
Basis parton distributions (where d=16 is the number of parton parameters) from
which the uncertainty on any physical quantity due to the uncertainty in parton
distributions can be calculated. We illustrate the method by applying it to
calculate uncertainties of gluon and quark distribution functions, W boson
rapidity distributions, and the correlation between W and Z production cross
sections.Comment: 30 pages, Latex. Reference added. Normalization of Hessian matrix
changed to HEP standar
Optimal Topological Test for Degeneracies of Real Hamiltonians
We consider adiabatic transport of eigenstates of real Hamiltonians around
loops in parameter space. It is demonstrated that loops that map to nontrivial
loops in the space of eigenbases must encircle degeneracies. Examples from
Jahn-Teller theory are presented to illustrate the test. We show furthermore
that the proposed test is optimal.Comment: Minor corrections, accepted in Phys. Rev. Let
Neutrino Dimuon Production and the Strangeness Asymmetry of the Nucleon
We have performed the first global QCD analysis to include the CCFR and NuTeV
dimuon data, which provide direct constraints on the strange and anti-strange
parton distributions, and . To explore the strangeness
sector, we adopt a general parametrization of the non-perturbative functions satisfying basic QCD requirements. We find that the
strangeness asymmetry, as represented by the momentum integral , is sensitive to the dimuon data provided the
theoretical QCD constraints are enforced. We use the Lagrange Multiplier method
to probe the quality of the global fit as a function of and find
. Representative parton distribution sets spanning this
range are given. Comparisons with previous work are made.Comment: 23 pages, 4 figures; expanded version for publicatio
Collider Inclusive Jet Data and the Gluon Distribution
Inclusive jet production data are important for constraining the gluon
distribution in the global QCD analysis of parton distribution functions. With
the addition of recent CDF and D0 Run II jet data, we study a number of issues
that play a role in determining the up-to-date gluon distribution and its
uncertainty, and produce a new set of parton distributions that make use of
that data. We present in detail the general procedures used to study the
compatibility between new data sets and the previous body of data used in a
global fit. We introduce a new method in which the Hessian matrix for
uncertainties is ``rediagonalized'' to obtain eigenvector sets that
conveniently characterize the uncertainty of a particular observable.Comment: Published versio
Multivariate Fitting and the Error Matrix in Global Analysis of Data
When a large body of data from diverse experiments is analyzed using a
theoretical model with many parameters, the standard error matrix method and
the general tools for evaluating errors may become inadequate. We present an
iterative method that significantly improves the reliability of the error
matrix calculation. To obtain even better estimates of the uncertainties on
predictions of physical observables, we also present a Lagrange multiplier
method that explores the entire parameter space and avoids the linear
approximations assumed in conventional error propagation calculations. These
methods are illustrated by an example from the global analysis of parton
distribution functions.Comment: 13 pages, 5 figures, Latex; minor clarifications, fortran program
made available; Normalization of Hessian matrix changed to HEP standar
- …