The Invisible Axion and Neutrino Masses

We show that in any invisible axion model due to the effects of effective non-renormalizable interactions related to an energy scale near the Peccei-Quinn, grand unification or even the Planck scale, active neutrinos necessarily acquire masses in the sub-eV range. Moreover, if sterile neutrinos are also included and if appropriate cyclic $Z_N$ symmetries are imposed, it is possible that some of these neutrinos are heavy while others are light.Comment: An example included and new references added. To appear in PR

Human-agent collectives

We live in a world where a host of computer systems, distributed throughout our physical and information environments, are increasingly implicated in our everyday actions. Computer technologies impact all aspects of our lives and our relationship with the digital has fundamentally altered as computers have moved out of the workplace and away from the desktop. Networked computers, tablets, phones and personal devices are now commonplace, as are an increasingly diverse set of digital devices built into the world around us. Data and information is generated at unprecedented speeds and volumes from an increasingly diverse range of sources. It is then combined in unforeseen ways, limited only by human imagination. People’s activities and collaborations are becoming ever more dependent upon and intertwined with this ubiquitous information substrate. As these trends continue apace, it is becoming apparent that many endeavours involve the symbiotic interleaving of humans and computers. Moreover, the emergence of these close-knit partnerships is inducing profound change. Rather than issuing instructions to passive machines that wait until they are asked before doing anything, we will work in tandem with highly inter-connected computational components that act autonomously and intelligently (aka agents). As a consequence, greater attention needs to be given to the balance of control between people and machines. In many situations, humans will be in charge and agents will predominantly act in a supporting role. In other cases, however, the agents will be in control and humans will play the supporting role. We term this emerging class of systems human-agent collectives (HACs) to reflect the close partnership and the flexible social interactions between the humans and the computers. As well as exhibiting increased autonomy, such systems will be inherently open and social. This means the participants will need to continually and flexibly establish and manage a range of social relationships. Thus, depending on the task at hand, different constellations of people, resources, and information will need to come together, operate in a coordinated fashion, and then disband. The openness and presence of many distinct stakeholders means participation will be motivated by a broad range of incentives rather than diktat. This article outlines the key research challenges involved in developing a comprehensive understanding of HACs. To illuminate this agenda, a nascent application in the domain of disaster response is presented

Onset of Localization in Heterogeneous Interfacial Failure

We study numerically the failure of an interface joining two elastic materials under load using a fiber bundle model connected to an elastic half space. We find that the breakdown process follows the equal load sharing fiber bundle model without any detectable spatial correlations between the positions of the failing fibers until localization sets in. The onset of localization is an instability, not a phase transition. Depending on the elastic constant describing the elastic half space, localization sets in before or after the critical load causing the interface to fail completely, is reached. There is a crossover between failure due to localization or failure without spatial correlations when tuning the elastic constant, not a phase transition. Contrary to earlier claims based on models different from ours, we find that a finite fraction of fibers must fail before the critical load is attained, even in the extreme localization regime, i.e.\ for very small elastic constant. We furthermore find that the critical load remains finite for all values of the elastic constant in the limit of an infinitely large system.Comment: 4 pages, 5 figure

An SU(5)⊗\otimesZ_{13} Grand Unification Model

We propose an SU(5) grand unified model with an invisible axion and the unification of the three coupling constants which is in agreement with the values, at $M_Z$, of $\alpha$, $\alpha_s$, and $\sin^2\theta_W$. A discrete, anomalous, $Z_{13}$ symmetry implies that the Peccei-Quinn symmetry is an automatic symmetry of the classical Lagrangian protecting, at the same time, the invisible axion against possible semi-classical gravity effects. Although the unification scale is of the order of the Peccei-Quinn scale the proton is stabilized by the fact that in this model the standard model fields form the SU(5) multiplets completed by new exotic fields and, also, because it is protected by the $Z_{13}$ symmetry.Comment: 14 pages, more typos correcte

Bulk de novo mitogenome assembly from pooled total DNA elucidates the phylogeny of weevils (Coleoptera: Curculionoidea)

Complete mitochondrial genomes have been shown to be reliable markers for phylogeny reconstruction among diverse animal groups. However, the relative difficulty and high cost associated with obtaining de novo full mitogenomes have frequently led to conspicuously low taxon sampling in ensuing studies. Here, we report the successful use of an economical and accessible method for assembling complete or near-complete mitogenomes through shot-gun next-generation sequencing of a single library made from pooled total DNA extracts of numerous target species. To avoid the use of separate indexed libraries for each specimen, and an associated increase in cost, we incorporate standard polymerase chain reaction-based “bait” sequences to identify the assembled mitogenomes. The method was applied to study the higher level phylogenetic relationships in the weevils (Coleoptera: Curculionoidea), producing 92 newly assembled mitogenomes obtained in a single Illumina MiSeq run. The analysis supported a separate origin of wood-boring behavior by the subfamilies Scolytinae, Platypodinae, and Cossoninae. This finding contradicts morphological hypotheses proposing a close relationship between the first two of these but is congruent with previous molecular studies, reinforcing the utility of mitogenomes in phylogeny reconstruction. Our methodology provides a technically simple procedure for generating densely sampled trees from whole mitogenomes and is widely applicable to groups of animals for which bait sequences are the only required prior genome knowledge

One- and two-particle microrheology

We study the dynamics of rigid spheres embedded in viscoelastic media and address two questions of importance to microrheology. First we calculate the complete response to an external force of a single bead in a homogeneous elastic network viscously coupled to an incompressible fluid. From this response function we find the frequency range where the standard assumptions of microrheology are valid. Second we study fluctuations when embedded spheres perturb the media around them and show that mutual fluctuations of two separated spheres provide a more accurate determination of the complex shear modulus than do the fluctuations of a single sphere.Comment: 4 pages, 1 figur

EEG Classification based on Image Configuration in Social Anxiety Disorder

The problem of detecting the presence of Social Anxiety Disorder (SAD) using Electroencephalography (EEG) for classification has seen limited study and is addressed with a new approach that seeks to exploit the knowledge of EEG sensor spatial configuration. Two classification models, one which ignores the configuration (model 1) and one that exploits it with different interpolation methods (model 2), are studied. Performance of these two models is examined for analyzing 34 EEG data channels each consisting of five frequency bands and further decomposed with a filter bank. The data are collected from 64 subjects consisting of healthy controls and patients with SAD. Validity of our hypothesis that model 2 will significantly outperform model 1 is borne out in the results, with accuracy $6$--$7\%$ higher for model 2 for each machine learning algorithm we investigated. Convolutional Neural Networks (CNN) were found to provide much better performance than SVM and kNNs

Bayesian analysis of LIGO-Virgo mergers:Primordial vs. astrophysical black hole populations

We conduct a thorough Bayesian analysis of the possibility that the black hole merger events seen in gravitational waves are primordial black hole (PBH) mergers. Using the latest merger rate models for PBH binaries drawn from a lognormal mass function we compute posterior parameter constraints and Bayesian evidences using data from the first two observing runs of LIGO-Virgo. We account for theoretical uncertainty due to possible disruption of the binary by surrounding PBHs, which can suppress the merger rate significantly. We also consider simple astrophysically motivated models and find that these are favoured decisively over the PBH scenario, quantified by the Bayesian evidence ratio. Paying careful attention to the influence of the parameter priors and the quality of the model fits, we show that the evidence ratios can be understood by comparing the predicted chirp mass distribution to that of the data. We identify the posterior predictive distribution of chirp mass as a vital tool for discriminating between models. A model in which all mergers are PBH binaries is strongly disfavoured compared with astrophysical models, in part due to the over-prediction of heavy systems having $\mathcal{M}_{{\rm chirp}} \gtrsim 40 \, M_\odot$ and positive skewness over the range of observed masses which does not match the observations. We find that the fit is not significantly improved by adding a maximum mass cut-off, a bimodal mass function, or imposing that PBH binaries form at late times. We argue that a successful PBH model must either modify the lognormal shape of the initial mass function significantly or abandon the hypothesis that all observed merging binaries are primordial. We develop and apply techniques for analysing PBH models with gravitational wave data which will be necessary for robust statistical inference as the gravitational wave source sample size increases.Comment: 29+8 pages, 18 figures. Minor edits to match version published in Physical Review