Ultracold molecules: new probes on the variation of fundamental constants

Ultracold molecules offer brand new opportunities to probe the variation of fundamental constants with unprecedented sensitivity. This paper summarizes theoretical background and current constraints on the variation of fine structure constant and electron-to-proton mass ratio, as well as proposals and experimental efforts to measure the variations based on ultracold molecules. In particular, we describe two novel spectroscopic schemes on ultracold molecules which have greatly enhanced sensitivity to fundamental constants: resonant scattering near Feshbach resonances and spectroscopy on close-lying energy levels of ultracold molecules

Guaranteed Cost Tracking for Uncertain Coupled Multi-agent Systems Using Consensus over a Directed Graph

This paper considers the leader-follower control problem for a linear multi-agent system with directed communication topology and linear nonidentical uncertain coupling subject to integral quadratic constraints (IQCs). A consensus-type control protocol is proposed based on each agent's states relative to its neighbors and leader's state relative to agents which observe the leader. A sufficient condition is obtained by overbounding the cost function. Based on this sufficient condition, a computational algorithm is introduced to minimize the proposed guaranteed bound on tracking performance, which yields a suboptimal bound on the system consensus control and tracking performance. The effectiveness of the proposed method is demonstrated using a simulation example.Comment: Accepted for presentation at the 2013 Australian Control conferenc

Gamma-ray bursts and the relevance of rotation-induced neutrino sterilization

A la Pontecorvo when one defines electroweak flavour states of neutrinos as a linear superposition of mass eigenstates one ignores the associated spin. If, however, there is a significant rotation between the neutrino source, and the detector, a negative helicity state emitted by the former acquires a non-zero probability amplitude to be perceived as a positive helicity state by the latter. Both of these states are still in the left-Weyl sector of the Lorentz group. The electroweak interaction cross sections for such helicity-flipped states are suppressed by a factor of $(m_\nu/E_\nu)^2$, where $m_\nu$ is the expectation value of the neutrino mass, and $E_\nu$ is the associated energy. Thus, if the detecting process is based on electroweak interactions, and the neutrino source is a highly rotating object, the rotation-induced helicity flip becomes very significant in interpreting the data. The effect immediately generalizes to anti-neutrinos. Motivated by these observations we present a generalization of the Pontecorvo formalism and discuss its relevance in the context of recent data obtained by the IceCube neutrino telescope.Comment: 4 page

Enhancement of variation of fundamental constants in ultracold atom and molecule systems near Feshbach resonances

Scattering length, which can be measured in Bose-Einstein condensate and Feshbach molecule experiments, is extremely sensitive to the variation of fundamental constants, in particular, the electron-to-proton mass ratio (m_e/m_p or m_e/Lambda_{QCD}, where Lambda_{QCD} is the QCD scale). Based on single- and two-channel scattering model, we show how the variation of the mass ratio propagates to the scattering length. Our results suggest that variation of m_e/m_p on the level of 10^{-11}~10^{-14} can be detected near a narrow magnetic or an optical Feshbach resonance by monitoring the scattering length on the 1% level. Derived formulae may also be used to estimate the isotopic shift of the scattering length

Structure of the electrospheres of bare strange stars

We consider a thin ($\sim 10^2-10^3$ fm) layer of electrons (the electrosphere) at the quark surface of a bare strange star, taking into account the surface effects at the boundary with the vacuum. The quark surface holds the electron layer by an extremely strong electric field, generated in the electrosphere to prevent the electrons from escaping to infinity by counterbalancing the degeneracy and thermal pressure. Because of the surface tension and depletion of $s$ quarks a very thin (a few fm) charged layer of quarks forms at the surface of the star. The formation of this layer modifies the structure of the electrosphere, by significantly changing the electric field and the density of the electrons, in comparison with the case when the surface effects are ignored. Some consequences of the modification of the electrosphere structure on the properties of strange stars are briefly discussed.Comment: 23 pages, 6 figures, to appear in Ap

EVALUATION WITHOUT BIAS: A METHODOLOGICAL PERSPECTIVE ON PERFORMANCE MEASURES FOR BUSINESS INCUBATORS

Business growth and formation are fundamental drivers of job crea-tion and economic growth. Business incubators provide a nurturing environment, through an array of business support resources and services, where entrepre-neurs, start-ups, and small businesses can commercially validate and transform their ideas and concepts into viable and tangible products and services. Despite growing attention to evaluate the performance and impact of business incuba-tors, the existing literature continues to suffer from methodological, theoretical, and empirical limitations. In particular, existing performance measures have inherent biases that lead them to underestimate the role of business incubators in entrepreneurship and economic development in economically distressed are-as, which typically face disadvantageous local economic conditions. The pur-pose of this paper is to explain the need for better performance measures and the difficulties in creating them.ECONOMICALLY DISTRESSED AREAS, BUSINESS START-UPS, BUSINESS INCUBATORS

Recognition of Microseismic and Blasting Signals in Mines Based on Convolutional Neural Network and Stockwell Transform

The microseismic monitoring signals which need to be determined in mines include those caused by both rock bursts and by blasting. The blasting signals must be separated from the microseismic signals in order to extract the information needed for the correct location of the source and for determining the blast mechanism. The use of a convolutional neural network (CNN) is a viable approach to extract these blast characteristic parameters automatically and to achieve the accuracy needed in the signal recognition. The Stockwell Transform (or S-Transform) has excellent two-dimensional time-frequency characteristics and thus to obtain the microseismic signal and blasting vibration signal separately, the microseismic signal has been converted in this work into a two-dimensional image format by use of the S-Transform, following which it is recognized by using the CNN. The sample data given in this paper are used for model training, where the training sample is an image containing three RGB color channels. The training time can be decreased by means of reducing the picture size and thus reducing the number of training steps used. The optimal combination of parameters can then be obtained after continuously updating the training parameters. When the image size is 180 × 140 pixels, it has been shown that the test accuracy can reach 96.15% and that it is feasible to classify separately the blasting signal and the microseismic signal based on using the S-Transform and the CNN model architecture, where the training parameters were designed by synthesizing LeNet-5 and AlexNet