Transport-driven toroidal rotation in the tokamak edge

The interaction of passing-ion drift orbits with spatially-inhomogeneous but purely diffusive radial transport is demonstrated to cause spontaneous toroidal spin-up to experimentally-relevant values in the tokamak edge. Physically, major-radial orbit shifts cause orbit-averaged diffusivities to depend on parallel velocity, including its sign, leading to residual stress. The resulting intrinsic rotation scales with ion temperature over poloidal magnetic field strength, resembling typical experimental scalings. Additionally, an inboard (outboard) X-point is expected to enhance co- (counter-) current rotation

Fits to SO(10) Grand Unified Models

We perform numerical fits of Grand Unified Models based on SO(10), using various combinations of 10-, 120- and 126-dimensional Higgs representations. Both the supersymmetric and non-supersymmetric versions are fitted, as well as both possible neutrino mass orderings. In contrast to most previous works, we perform the fits at the weak scale, i.e. we use RG evolution from the GUT scale, at which the GUT-relations between the various Yukawa coupling matrices hold, down to the weak scale. In addition, the right-handed neutrinos of the seesaw mechanism are integrated out one by one in the RG running. Other new features are the inclusion of recent results on the reactor neutrino mixing angle and the Higgs mass (in the non-SUSY case). As expected from vacuum stability considerations, the low Higgs mass and the large top-quark Yukawa coupling cause some pressure on the fits. A lower top-quark mass, as sometimes argued to be the result of a more consistent extraction from experimental results, can relieve this pressure and improve the fits. We give predictions for neutrino masses, including the effective one for neutrinoless double beta decay, as well as the atmospheric neutrino mixing angle and the leptonic CP phase for neutrino oscillations.Comment: 40 pages, 2 figures. Published versio

Graphical Modeling for Multivariate Hawkes Processes with Nonparametric Link Functions

Hawkes (1971) introduced a powerful multivariate point process model of mutually exciting processes to explain causal structure in data. In this paper it is shown that the Granger causality structure of such processes is fully encoded in the corresponding link functions of the model. A new nonparametric estimator of the link functions based on a time-discretized version of the point process is introduced by using an infinite order autoregression. Consistency of the new estimator is derived. The estimator is applied to simulated data and to neural spike train data from the spinal dorsal horn of a rat.Comment: 20 pages, 4 figure

Normal Toric Ideals of Low Codimension

Every normal toric ideal of codimension two is minimally generated by a Grobner basis with squarefree initial monomials. A polynomial time algorithm is presented for checking whether a toric ideal of fixed codimension is normal

On Leptonic Unitary Triangles and Boomerangs

We review the idea of leptonic unitary triangles and extend the concept of the recently proposed unitary boomerangs to the lepton sector. Using a convenient parameterization of the lepton mixing, we provide approximate expressions for the side lengths and the angles of the six different triangles and give examples of leptonic unitary boomerangs. Possible applications of the leptonic unitary boomerangs are also briefly discussed.Comment: 11 pages, 3 figure

The affinely invariant distance correlation

Sz\'{e}kely, Rizzo and Bakirov (Ann. Statist. 35 (2007) 2769-2794) and Sz\'{e}kely and Rizzo (Ann. Appl. Statist. 3 (2009) 1236-1265), in two seminal papers, introduced the powerful concept of distance correlation as a measure of dependence between sets of random variables. We study in this paper an affinely invariant version of the distance correlation and an empirical version of that distance correlation, and we establish the consistency of the empirical quantity. In the case of subvectors of a multivariate normally distributed random vector, we provide exact expressions for the affinely invariant distance correlation in both finite-dimensional and asymptotic settings, and in the finite-dimensional case we find that the affinely invariant distance correlation is a function of the canonical correlation coefficients. To illustrate our results, we consider time series of wind vectors at the Stateline wind energy center in Oregon and Washington, and we derive the empirical auto and cross distance correlation functions between wind vectors at distinct meteorological stations.Comment: Published in at http://dx.doi.org/10.3150/13-BEJ558 the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm