Status of the Zee-Babu model for neutrino mass and possible tests at a like-sign linear collider

We provide an updated scan of the allowed parameter space of the two-loop Zee-Babu model for neutrino mass. Taking into account most recent experimental data on $\mu\to e\gamma$ as well as the mixing angle $\theta_{13}$ we obtain lower bounds on the masses of the singly and doubly charged scalars of between 1 to 2 TeV, with some dependence on perturbativity and fine-tuning requirements. This makes the scalars difficult to observe at LHC with 14 TeV even with optimistic assumptions on the luminosity, and would require a multi-TeV linear collider to see the scalar resonances. We point out, however, that a sub-TeV linear collider in the like-sign mode may be able to observe lepton flavour violating processes such as $e^- e^- \to \mu^- \mu^-$ due to contact interactions induced by the doubly charged scalar with masses up to around 10 TeV. We investigate the possibility to distinguish the Zee-Babu model from the Higgs triplet model using such processes.Comment: 12 pages, 7 figure

Compensated isocurvature perturbations in the curvaton model

Primordial fluctuations in the relative number densities of particles, or isocurvature perturbations, are generally well constrained by cosmic microwave background (CMB) data. A less probed mode is the compensated isocurvature perturbation (CIP), a fluctuation in the relative number densities of cold dark matter and baryons. In the curvaton model, a subdominant field during inflation later sets the primordial curvature fluctuation $\zeta$. In some curvaton-decay scenarios, the baryon and cold dark matter isocurvature fluctuations nearly cancel, leaving a large CIP correlated with $\zeta$. This correlation can be used to probe these CIPs more sensitively than the uncorrelated CIPs considered in past work, essentially by measuring the squeezed bispectrum of the CMB for triangles whose shortest side is limited by the sound horizon. Here, the sensitivity of existing and future CMB experiments to correlated CIPs is assessed, with an eye towards testing specific curvaton-decay scenarios. The planned CMB Stage 4 experiment could detect the largest CIPs attainable in curvaton scenarios with more than 3$\sigma$ significance. The significance could improve if small-scale CMB polarization foregrounds can be effectively subtracted. As a result, future CMB observations could discriminate between some curvaton-decay scenarios in which baryon number and dark matter are produced during different epochs relative to curvaton decay. Independent of the specific motivation for the origin of a correlated CIP perturbation, cross-correlation of CIP reconstructions with the primary CMB can improve the signal-to-noise ratio of a CIP detection. For fully correlated CIPs the improvement is a factor of $\sim$2$-$3.Comment: 20 pages, 8 figures, minor changes matching publicatio

Lensing Bias to CMB Measurements of Compensated Isocurvature Perturbations

Compensated isocurvature perturbations (CIPs) are modes in which the baryon and dark matter density fluctuations cancel. They arise in the curvaton scenario as well as some models of baryogenesis. While they leave no observable effects on the cosmic microwave background (CMB) at linear order, they do spatially modulate two-point CMB statistics and can be reconstructed in a manner similar to gravitational lensing. Due to the similarity between the effects of CMB lensing and CIPs, lensing contributes nearly Gaussian random noise to the CIP estimator that approximately doubles the reconstruction noise power. Additionally, the cross correlation between lensing and the integrated Sachs-Wolfe (ISW) effect generates a correlation between the CIP estimator and the temperature field even in the absence of a correlated CIP signal. For cosmic-variance limited temperature measurements out to multipoles $l \leq 2500$, subtracting a fixed lensing bias degrades the detection threshold for CIPs by a factor of $1.3$, whether or not they are correlated with the adiabatic mode.Comment: 10 pages, 12 figures; one of the authors Chen He Heinrich was previously known as Chen H

Extraction and Classification of Diving Clips from Continuous Video Footage

Due to recent advances in technology, the recording and analysis of video data has become an increasingly common component of athlete training programmes. Today it is incredibly easy and affordable to set up a fixed camera and record athletes in a wide range of sports, such as diving, gymnastics, golf, tennis, etc. However, the manual analysis of the obtained footage is a time-consuming task which involves isolating actions of interest and categorizing them using domain-specific knowledge. In order to automate this kind of task, three challenging sub-problems are often encountered: 1) temporally cropping events/actions of interest from continuous video; 2) tracking the object of interest; and 3) classifying the events/actions of interest. Most previous work has focused on solving just one of the above sub-problems in isolation. In contrast, this paper provides a complete solution to the overall action monitoring task in the context of a challenging real-world exemplar. Specifically, we address the problem of diving classification. This is a challenging problem since the person (diver) of interest typically occupies fewer than 1% of the pixels in each frame. The model is required to learn the temporal boundaries of a dive, even though other divers and bystanders may be in view. Finally, the model must be sensitive to subtle changes in body pose over a large number of frames to determine the classification code. We provide effective solutions to each of the sub-problems which combine to provide a highly functional solution to the task as a whole. The techniques proposed can be easily generalized to video footage recorded from other sports.Comment: To appear at CVsports 201

Multipartite Entanglement Measure

In this paper, we generalize the residual entanglement to the case of multipartite states in arbitrary dimensions by making use of a new method. Through the introduction of a special entanglement measure, the residual entanglement of mixed states takes on a form that is more elegant than that in Ref.[7] (Phys.Rev.A 61 (2000) 052306) . The result obtained in this paper is different from the previous one given in Ref.[8] (Phys.Rev.A 63 (2000) 044301). Several examples demonstrate that our present result is a good measurement of the multipartite entanglement. Furthermore, the original residual entanglement is a special case of our result.Comment: 5 page

Adaptive Semi-supervised Learning for Cross-domain Sentiment Classification

We consider the cross-domain sentiment classification problem, where a sentiment classifier is to be learned from a source domain and to be generalized to a target domain. Our approach explicitly minimizes the distance between the source and the target instances in an embedded feature space. With the difference between source and target minimized, we then exploit additional information from the target domain by consolidating the idea of semi-supervised learning, for which, we jointly employ two regularizations -- entropy minimization and self-ensemble bootstrapping -- to incorporate the unlabeled target data for classifier refinement. Our experimental results demonstrate that the proposed approach can better leverage unlabeled data from the target domain and achieve substantial improvements over baseline methods in various experimental settings.Comment: Accepted to EMNLP201

Social media and sentiment in bioenergy consultation

Purpose: The push to widen participation in public consultation suggests social media as an additional mechanism through which to engage the public. Bioenergy companies need to build their capacity to communicate in these new media and to monitor the attitudes of the public and opposition organisations towards energy development projects. Design/methodology/approach: This short paper outlines the planning issues bioenergy developments face and the main methods of communication used in the public consultation process in the UK. The potential role of social media in communication with stakeholders is identified. The capacity of sentiment analysis to mine opinions from social media is summarised, and illustrated using a sample of tweets containing the term ‘bioenergy’ Findings: Social media have the potential to improve information flows between stakeholders and developers. Sentiment analysis is a viable methodology, which bioenergy companies should be using to measure public opinion in the consultation process. Preliminary analysis shows promising results. Research limitations/implications: Analysis is preliminary and based on a small dataset. It is intended only to illustrate the potential of sentiment analysis and not to draw general conclusions about the bioenergy sector. Originality/value: Opinion mining, though established in marketing and political analysis, is not yet systematically applied as a planning consultation tool. This is a missed opportunity