Evolution systems for non-linear perturbations of background geometries

The formulation of the initial value problem for the Einstein equations is at the heart of obtaining interesting new solutions using numerical relativity and still very much under theoretical and applied scrutiny. We develop a specialised background geometry approach, for systems where there is non-trivial a priori knowledge about the spacetime under study. The background three-geometry and associated connection are used to express the ADM evolution equations in terms of physical non-linear deviations from that background. Expressing the equations in first order form leads naturally to a system closely linked to the Einstein-Christoffel system, introduced by Anderson and York, and sharing its hyperbolicity properties. We illustrate the drastic alteration of the source structure of the equations, and discuss why this is likely to be numerically advantageous.Comment: 12 pages, 3 figures, Revtex v3.0. Revised version to appear in Physical Review

Using Rapidity Gaps to Distinguish Between Higgs Production by W and Gluon Fusion

The possibility of distinguishing between two higgs production mechanisms, W fusion and gluon fusion, is investigated using the Monte Carlo event generator PYTHIA. It is shown that, considering the designed CM energy and luminosity for the LHC, it is not possible to distinguish between the two higgs production processes as, for a given integrated luminosity, they lead to the same number of events containing a rapidity gap.Comment: uudecoded compressed tar file containing a tex file and 6 figure files. Two more figures, avaiable from the authors upon reques

Heterotic domain wall solutions and SU(3) structure manifolds

We examine compactifications of heterotic string theory on manifolds with SU(3) structure. In particular, we study N = 1/2 domain wall solutions which correspond to the perturbative vacua of the 4D, N =1 supersymmetric theories associated to these compactifications. We extend work which has appeared previously in the literature in two important regards. Firstly, we include two additional fluxes which have been, heretofore, omitted in the general analysis of this situation. This allows for solutions with more general torsion classes than have previously been found. Secondly, we provide explicit solutions for the fluxes as a function of the torsion classes. These solutions are particularly useful in deciding whether equations such as the Bianchi identities can be solved, in addition to the Killing spinor equations themselves. Our work can be used to straightforwardly decide whether any given SU(3) structure on a six-dimensional manifold is associated with a solution to heterotic string theory. To illustrate how to use these results, we discuss a number of examples taken from the literature.Comment: 34 pages, minor corrections in second versio

Sneutrino Mixing Phenomena

In any model with nonzero Majorana neutrino masses, the sneutrino and antisneutrino of the supersymmetric extended theory mix. We outline the conditions under which sneutrino-antisneutrino mixing is experimentally observable. The mass-splitting of the sneutrino mass eigenstates and sneutrino oscillation phenomena are considered.Comment: 12 pages, revtex + axodraw, 1 figure included. Minor change

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

Background: Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion: We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions: We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the detection of moderately irregularly shaped clusters. The multi-objective cohesion scan is most effective for the detection of highly irregularly shaped clusters

Spatial metallicity distribution statistics at ≲100\lesssim 100 pc scales in the AMUSING++ nearby galaxy sample

We analyse the spatial statistics of the 2D gas-phase oxygen abundance distributions in a sample of 219 local galaxies. We introduce a new adaptive binning technique to enhance the signal-to-noise ratio of weak lines, which we use to produce well-filled metallicity maps for these galaxies. We show that the two-point correlation functions computed from the metallicity distributions after removing radial gradients are in most cases well described by a simple injection-diffusion model. Fitting the data to this model yields the correlation length $l_{\rm corr}$, which describes the characteristic interstellar medium mixing length scale. We find typical correlation lengths $l_{\rm corr} \sim 1$ kpc, with a strong correlation between $l_{\rm corr}$ and stellar mass, star formation rate, and effective radius, a weak correlation with Hubble type, and significantly elevated values of $l_{\rm corr}$ in interacting or merging galaxies. We show that the trend with star formation rate can be reproduced by a simple transport+feedback model of interstellar medium turbulence at high star formation rate, and plausibly also at low star formation rate if dwarf galaxy winds have large mass-loading factors. We also report the first measurements of the injection width that describes the initial radii over which supernova remnants deposit metals. Inside this radius the metallicity correlation function is not purely the product of a competition between injection and diffusion. We show that this size scale is generally smaller than 60 pc.Comment: 18 pages, 18 figures, 1 table, submitted to MNRAS. Comments are welcom

Focus Points and Naturalness in Supersymmetry

We analyze focus points in supersymmetric theories, where a parameter's renormalization group trajectories meet for a family of ultraviolet boundary conditions. We show that in a class of models including minimal supergravity, the up-type Higgs mass has a focus point at the weak scale, where its value is highly insensitive to the universal scalar mass. As a result, scalar masses as large as 2 to 3 TeV are consistent with naturalness, and {\em all} squarks, sleptons and heavy Higgs scalars may be beyond the discovery reaches of the Large Hadron Collider and proposed linear colliders. Gaugino and Higgsino masses are, however, still constrained to be near the weak scale. The focus point behavior is remarkably robust, holding for both moderate and large \tan\beta, any weak scale gaugino masses and A parameters, variations in the top quark mass within experimental bounds, and for large variations in the boundary condition scale.Comment: 30 pages, 17 figure

Method to estimate ISCO and ring-down frequencies in binary systems and consequences for gravitational wave data analysis

Recent advances in the description of compact binary systems have produced gravitational waveforms that include inspiral, merger and ring-down phases. Comparing results from numerical simulations with those of post-Newtonian (PN), and related, expansions has provided motivation for employing PN waveforms in near merger epochs when searching for gravitational waves and has encouraged the development of analytic fits to full numerical waveforms. The models and simulations do not yet cover the full binary coalescence parameter space. For these yet un-simulated regions, data analysts can still conduct separate inspiral, merger and ring-down searches. Improved knowledge about the end of the inspiral phase, the beginning of the merger, and the ring-down frequencies could increase the efficiency of both coherent inspiral-merger-ring-down (IMR) searches and searches over each phase separately. Insight can be gained for all three cases through a recently presented theoretical calculation, which, corroborated by the numerical results, provides an implicit formula for the final spin of the merged black holes, accurate to within 10% over a large parameter space. Knowledge of the final spin allows one to predict the end of the inspiral phase and the quasinormal mode ring-down frequencies, and in turn provides information about the bandwidth and duration of the merger. In this work we will discuss a few of the implications of this calculation for data analysis.Comment: Added references to section 3 14 pages 5 figures. Submitted to Classical and Quantum Gravit

b→sγb\to s\gamma Constraints on the Minimal Supergravity Model with Large tan⁡β\tan\beta

In the minimal supergravity model (mSUGRA), as the parameter $\tan\beta$ increases, the charged Higgs boson and light bottom squark masses decrease, which can potentially increase contributions from $tH^\pm$, \tg\tb_j and \tz_i\tb_j loops in the decay $b\to s\gamma$. We update a previous QCD improved $b\to s\gamma$ decay calculation to include in addition the effects of gluino and neutralino loops. We find that in the mSUGRA model, loops involving charginos also increase, and dominate over $tW$, $tH^\pm$, \tg\tq and \tz_i\tq contributions for \tan\beta\agt 5-10. We find for large values of $\tan\beta \sim 35$ that most of the parameter space of the mSUGRA model for $\mu <0$ is ruled out due to too large a value of branching ratio $B(b\to s\gamma)$. For $\mu >0$ and large $\tan\beta$, most of parameter space is allowed, although the regions with the least fine-tuning (low $m_0$ and $m_{1/2}$) are ruled out due to too low a value of $B(b\to s\gamma)$. We compare the constraints from $b\to s\gamma$ to constraints from the neutralino relic density, and to expectations for sparticle discovery at LEP2 and the Fermilab Tevatron $p\bar p$ colliders. Finally, we show that non-universal GUT scale soft breaking squark mass terms can enhance gluino loop contributions to $b\to s\gamma$ decay rate even if these are diagonal.Comment: 14 page REVTEX file plus 6 PS figure

Behavioral Responses to a Repetitive Visual Threat Stimulus Express a Persistent State of Defensive Arousal in Drosophila

The neural circuit mechanisms underlying emotion states remain poorly understood. Drosophila offers powerful genetic approaches for dissecting neural circuit function, but whether flies exhibit emotion-like behaviors has not been clear. We recently proposed that model organisms may express internal states displaying “emotion primitives,” which are general characteristics common to different emotions, rather than specific anthropomorphic emotions such as “fear” or “anxiety.” These emotion primitives include scalability, persistence, valence, and generalization to multiple contexts. Here, we have applied this approach to determine whether flies’ defensive responses to moving overhead translational stimuli (“shadows”) are purely reflexive or may express underlying emotion states. We describe a new behavioral assay in which flies confined in an enclosed arena are repeatedly exposed to an overhead translational stimulus. Repetitive stimuli promoted graded (scalable) and persistent increases in locomotor velocity and hopping, and occasional freezing. The stimulus also dispersed feeding flies from a food resource, suggesting both negative valence and context generalization. Strikingly, there was a significant delay before the flies returned to the food following stimulus-induced dispersal, suggestive of a slowly decaying internal defensive state. The length of this delay was increased when more stimuli were delivered for initial dispersal. These responses can be mathematically modeled by assuming an internal state that behaves as a leaky integrator of stimulus exposure. Our results suggest that flies’ responses to repetitive visual threat stimuli express an internal state exhibiting canonical emotion primitives, possibly analogous to fear in mammals. The mechanistic basis of this state can now be investigated in a genetically tractable insect species