Tuning the dipolar interaction in quantum gases

We have studied the tunability of the interaction between permanent dipoles in Bose-Einstein condensates. Based on time-dependent control of the anisotropy of the dipolar interaction, we show that even the very weak magnetic dipole coupling in alkali gases can be used to excite collective modes. Furthermore, we discuss how the effective dipolar coupling in a Bose-Einstein condensate can be tuned from positive to negative values and even switched off completely by fast rotation of the orientation of the dipoles.Comment: 4 pages, 3 figures. Submitted to PRL. (v3: Figure 3 replaced

Signatures of gravitational fixed points at the LHC

We study quantum-gravitational signatures at the CERN Large Hadron Collider (LHC) in the context of theories with extra spatial dimensions and a low fundamental Planck scale in the TeV range. Implications of a gravitational fixed point at high energies are worked out using Wilson¿s renormalization group. We find that relevant cross sections involving virtual gravitons become finite. Based on gravitational lepton pair production we conclude that the LHC is sensitive to a fundamental Planck scale of up to 6 TeV

Blurred Lines Between Competition and Parasitism

Accurately describing the ecological relationships between species is more than mere semantics-doing so has profound practical and applied implications, not the least of which is that inaccurate descriptions can lead to fundamentally incorrect predicted outcomes of community composition and functioning. Accurate ecological classifications are particularly important in the context of global change, where species interactions can change rapidly following shifts in species composition. Here, we argue that many common ecological interactions-particularly competition and parasitism-can be easily confused and that we often lack empirical evidence for the full reciprocal interaction among species. To make our case and to propose a theoretical framework for addressing this problem, we use the interactions between lianas and trees, whose outcomes have myriad implications for the ecology and conservation of tropical forests (e.g., Schnitzer et al. 2015)

Nitrate- and silicate-competition among antarctic phytoplankton

Natural phytoplankton from antarctic waters in the Drake Passage were used for competition experiments in semicontinuous cultures. The outcome of interspecific competition for silicate and nitrate was studied at a range of Si:N ratios (from 2.6:1 to 425:1) and at three different dilution rates. For five species Monod kinetics of silicate-and nitrate-limited growth has been established. Comparison between theoretical predictions derived from Monod kinetics and the outcome of competition experiments showed only minor deviations. Contrary to literature data, considerable depletion of nitrate was found in antarctic seawater. Both the concentrations of soluble silicate and of nitrate were too low to support maximum growth rates of some of the diatom species under investigation

Asymptotic safety and Kaluza-Klein gravitons at the LHC

We study Drell-Yan production at the LHC in low-scale quantum gravity models with extra dimensions. Asymptotic safety implies that the ultra-violet behavior of gravity is dictated by a fixed point. We show how the energy dependence of Newton's coupling regularizes the gravitational amplitude using a renormalization group improvement. We study LHC predictions and find that Kaluza-Klein graviton signals are well above Standard Model backgrounds. This leaves a significant sensitivity to the energy scale Lambda_T where the gravitational couplings cross over from classical to fixed point scaling.Comment: 25 pages, 14 figure

Hybrid apparatus for Bose-Einstein condensation and cavity quantum electrodynamics: Single atom detection in quantum degenerate gases

We present and characterize an experimental system in which we achieve the integration of an ultrahigh finesse optical cavity with a Bose-Einstein condensate (BEC). The conceptually novel design of the apparatus for the production of BECs features nested vacuum chambers and an in-vacuo magnetic transport configuration. It grants large scale spatial access to the BEC for samples and probes via a modular and exchangeable "science platform". We are able to produce \87Rb condensates of five million atoms and to output couple continuous atom lasers. The cavity is mounted on the science platform on top of a vibration isolation system. The optical cavity works in the strong coupling regime of cavity quantum electrodynamics and serves as a quantum optical detector for single atoms. This system enables us to study atom optics on a single particle level and to further develop the field of quantum atom optics. We describe the technological modules and the operation of the combined BEC cavity apparatus. Its performance is characterized by single atom detection measurements for thermal and quantum degenerate atomic beams. The atom laser provides a fast and controllable supply of atoms coupling with the cavity mode and allows for an efficient study of atom field interactions in the strong coupling regime. Moreover, the high detection efficiency for quantum degenerate atoms distinguishes the cavity as a sensitive and weakly invasive probe for cold atomic clouds

Bayesian Inference and Data Augmentation Schemes for Spatial, Spatiotemporal and Multivariate Log-Gaussian Cox Processes in R

Log-Gaussian Cox processes are an important class of models for spatial and spatiotemporal point-pattern data. Delivering robust Bayesian inference for this class of models presents a substantial challenge, since Markov chain Monte Carlo (MCMC) algorithms require careful tuning in order to work well. To address this issue, we describe recent advances in MCMC methods for these models and their implementation in the R package lgcp. Our suite of R functions provides an extensible framework for inferring covariate effects as well as the parameters of the latent field. We also present methods for Bayesian inference in two further classes of model based on the log-Gaussian Cox process. The first of these concerns the case where we wish to fit a point process model to data consisting of event-counts aggregated to a set of spatial regions: we demonstrate how this can be achieved using data-augmentation. The second concerns Bayesian inference for a class of marked-point processes specified via a multivariate log-Gaussian Cox process model. For both of these extensions, we give details of their implementation in R