Dual parameterization of generalized parton distributions and description of DVCS data

We discuss a new leading-order parameterization of generalized parton distributions of the proton, which is based on the idea of duality. In its minimal version, the parameterization is defined by the usual quark singlet parton distributions and the form factors of the energy-momentum tensor. We demonstrate that our parameterization describes very well the absolute value, the Q^2-dependence and the W-dependence of the HERA data on the total DVCS cross section and contains no free parameters in that kinematics. The parameterization suits especially well the low-x_{Bj} region, which allows us to advocate it as a better alternative to the frequently used double distribution parameterization of the GPDs.Comment: 13 pages, 2 figures, LaTeX. Revised version: equation for the DVCS cross section corrected; one reference added; numerical results did not chang

Flatness and Monge parameterization of two-input systems, control-affine with 4 states or general with 3 states

This paper studies Monge parameterization, or differential flatness, of control-affine systems with four states and twocontrols. Some of them are known to be flat, and this implies admitting a Monge parameterization. Focusing on systems outside this class, we describe the only possible structure of such a parameterization for these systems, and give a lower bound on the order of this parameterization, if it exists. This lower-bound is good enough to recover the known results about "(x,u)-flatness" of these systems, with much more elementary techniques

Parameterization Above a Multiplicative Guarantee

Parameterization above a guarantee is a successful paradigm in Parameterized Complexity. To the best of our knowledge, all fixed-parameter tractable problems in this paradigm share an additive form defined as follows. Given an instance (I,k) of some (parameterized) problem ? with a guarantee g(I), decide whether I admits a solution of size at least (at most) k+g(I). Here, g(I) is usually a lower bound (resp. upper bound) on the maximum (resp. minimum) size of a solution. Since its introduction in 1999 for Max SAT and Max Cut (with g(I) being half the number of clauses and half the number of edges, respectively, in the input), analysis of parameterization above a guarantee has become a very active and fruitful topic of research. We highlight a multiplicative form of parameterization above a guarantee: Given an instance (I,k) of some (parameterized) problem ? with a guarantee g(I), decide whether I admits a solution of size at least (resp. at most) k ? g(I). In particular, we study the Long Cycle problem with a multiplicative parameterization above the girth g(I) of the input graph, and provide a parameterized algorithm for this problem. Apart from being of independent interest, this exemplifies how parameterization above a multiplicative guarantee can arise naturally. We also show that, for any fixed constant ?>0, multiplicative parameterization above g(I)^(1+?) of Long Cycle yields para-NP-hardness, thus our parameterization is tight in this sense. We complement our main result with the design (or refutation of the existence) of algorithms for other problems parameterized multiplicatively above girth

A New Equation of State for Dark Energy Model

A new parameterization for the dark energy equation of state(EoS) is proposed and some of its cosmological consequences are also investigated. This new parameterization is the modification of Efstathiou' dark energy EoS parameterization. $w (z)$ is a well behaved function for $z\gg1$ and has same behavior in $z$ at low redshifts with Efstathiou' parameterization. In this parameterization there are two free parameter $w_0$ and $w_a$. We discuss the constraints on this model's parameters from current observational data. The best fit values of the cosmological parameters with $1\sigma$ confidence-level regions are: $\Omega_m=0.2735^{+0.0171}_{-0.0163}$, $w_0=-1.0537^{+0.1432}_{-0.1511}$ and $w_a=0.2738^{+0.8018}_{-0.8288}$.Comment: 5 pages, 3 figures.some statement is change

On the Computation Power of Name Parameterization in Higher-order Processes

Parameterization extends higher-order processes with the capability of abstraction (akin to that in lambda-calculus), and is known to be able to enhance the expressiveness. This paper focuses on the parameterization of names, i.e. a construct that maps a name to a process, in the higher-order setting. We provide two results concerning its computation capacity. First, name parameterization brings up a complete model, in the sense that it can express an elementary interactive model with built-in recursive functions. Second, we compare name parameterization with the well-known pi-calculus, and provide two encodings between them.Comment: In Proceedings ICE 2015, arXiv:1508.0459

A Linear Formulation for Disk Conformal Parameterization of Simply-Connected Open Surfaces

Surface parameterization is widely used in computer graphics and geometry processing. It simplifies challenging tasks such as surface registrations, morphing, remeshing and texture mapping. In this paper, we present an efficient algorithm for computing the disk conformal parameterization of simply-connected open surfaces. A double covering technique is used to turn a simply-connected open surface into a genus-0 closed surface, and then a fast algorithm for parameterization of genus-0 closed surfaces can be applied. The symmetry of the double covered surface preserves the efficiency of the computation. A planar parameterization can then be obtained with the aid of a M\"obius transformation and the stereographic projection. After that, a normalization step is applied to guarantee the circular boundary. Finally, we achieve a bijective disk conformal parameterization by a composition of quasi-conformal mappings. Experimental results demonstrate a significant improvement in the computational time by over 60%. At the same time, our proposed method retains comparable accuracy, bijectivity and robustness when compared with the state-of-the-art approaches. Applications to texture mapping are presented for illustrating the effectiveness of our proposed algorithm

New Constraints on Dispersive Form Factor Parameterizations from the Timelike Region

We generalize a recent model-independent form factor parameterization derived from rigorous dispersion relations to include constraints from data in the timelike region. These constraints dictate the convergence properties of the parameterization and appear as sum rules on the parameters. We further develop a new parameterization that takes into account finiteness and asymptotic conditions on the form factor, and use it to fit to the elastic \pi electromagnetic form factor. We find that the existing world sample of timelike data gives only loose bounds on the form factor in the spacelike region, but explain how the acquisition of additional timelike data or fits to other form factors are expected to give much better results. The same parameterization is seen to fit spacelike data extremely well.Comment: 24 pages, latex (revtex), 3 eps figure