Type Ia supernovae as speed sensors at intermediate redshifts

The application of large scale peculiar velocity (LSPV), as a crucial probe of dark matter, dark energy and gravity, is severely limited by measurement obstacles. We show that fluctuations in type Ia supernovae (SNe Ia) fluxes induced by LSPV offer a promising approach to measure LSPV at intermediate redshifts. In the 3D Fourier space, gravitational lensing, the dominant systematical error, is well suppressed, localized and can be further corrected effectively. Advance in SN observations can further significantly reduce shot noise induced by SN intrinsic fluctuations, which is the dominant statistical error. Robust mapping on the motion of the dark universe through SNe Ia is thus feasible to $z\sim 0.5$.Comment: 6 pages, 1 figure. v2: expanded discussions. Accepted to PRD. Also refer to the news report at Physics world http://physicsworld.com/cws/article/news/3509

Coherent Radio Emission from a Twisted Magnetosphere after a Magnetar-quake

Magnetars are a class of highly magnetized, slowly rotating neutron stars, only a small fraction of which exhibit radio emission. We propose that the coherent radio curvature emission is generated by net charge fluctuations from a twist-current-carrying bundle (the j-bundle) in the scenario of magnetar-quake. Two-photon pair production is triggered, which requires a threshold voltage not too much higher than 109 V in the current-carrying bundle, and which can be regarded as the open field lines of a magnetar. Continued untwisting of the magnetosphere maintains change fluctuations, and hence coherent radio emission, in the progressively shrinking j-bundle, which lasts for years until the radio beam is too small to be detected. The modeled peak flux of radio emission and the flat spectrum are generally consistent with the observations. We show that this time-dependent, conal-beam, radiative model can interpret the variable radio pulsation behaviors and the evolution of the X-ray hot spot of the radio-transient magnetar XTE J1810−197 and the high-B pulsar/anomalous X-ray pulsar PSR J1622−4950. Radio emission with luminosity of and high-frequency oscillations are expected to be detected for a magnetar after an X-ray outburst. Differences of radio emission between magnetars and ordinary pulsars are discussed

Contraints on radiative dark-matter decay from the cosmic microwave background

If dark matter decays to electromagnetically-interacting particles, it can inject energy into the baryonic gas and thus affect the processes of recombination and reionization. This leaves an imprint on the cosmic microwave background (CMB): the large-scale polarization is enhanced, and the small-scale temperature fluctuation is damped. We use the WMAP three-year data combined with galaxy surveys to constrain radiatively decaying dark matter. Our new limits to the dark-matter decay width are about ten times stronger than previous limits. For dark-matter lifetimes that exceed the age of the Universe, a limit of $\zeta \Gamma_{\chi} < 1.7 \times 10^{-25} s^{-1}$ (95% CL) is derived, where $\zeta$ is the efficiency of converting decay energy into ionization energy. Limits for lifetimes short compared with the age of the Universe are also derived. We forecast improvements expected from the Planck satellite.Comment: replaced with version published on PR

Leptonic dark matter annihilation in the evolving universe: constraints and implications

The cosmic electron and positron excesses have been explained as possible dark matter (DM) annihilation products. In this work we investigate the possible effects of such a DM annihilation scenario during the evolution history of the Universe. We first calculate the extragalactic $\gamma$-ray background (EGRB), which is produced through the final state radiation of DM annihilation to charged leptons and the inverse Compton scattering between electrons/positrons and the cosmic microwave background. The DM halo profile and the minimal halo mass, which are not yet well determined from the current N-body simulations, are constrained by the EGRB data from EGRET and Fermi telescopes. Then we discuss the impact of such leptonic DM models on cosmic evolution, such as the reionization and heating of intergalactic medium, neutral Hydrogen 21 cm signal and suppression of structure formation. We show that the impact on the Hydrogen 21 cm signal might show interesting signatures of DM annihilation, but the influence on star formation is not remarkable. Future observations of the 21 cm signals could be used to place new constraints on the properties of DM.Comment: 24 pages, 6 figures and 2 tables. Improved treatment of the energy deposition process, the suppression on structure formation is weaker. Accepted for publication by JCA

Studying top quark decay into the polarized W-boson in the TC2 model

We study the decay mode of top quark decaying into Wb in the TC2 model where the top quark is distinguished from other fermions by participating in a strong interaction. We find that the TC2 correction to the decay width $\Gamma (t \to b W)$ is generally several percent and maximum value can reach 8% for the currently allowed parameters. The magnitude of such correction is comparable with QCD correction and larger than that of minimal supersymmetric model. Such correction might be observable in the future colliders. We also study the TC2 correction to the branching ratio of top quark decay into the polarized W bosons and find the correction is below $1$. After considering the TC2 correction, we find that our theoretical predictions about the decay branching ratio are also consistent with the experimental data.Comment: 8 pages, 4 figure

The consistency test on the cosmic evolution

We propose a new and robust method to test the consistency of the cosmic evolution given by a cosmological model. It is realized by comparing the combined quantity r_d^CMB/D_V^SN, which is derived from the comoving sound horizon r_d from cosmic microwave background (CMB) measurements and the effective distance D_V derived from low-redshift Type-Ia supernovae (SNe Ia) data, with direct and independent r_d/D_V obtained by baryon acoustic oscillation (BAO) measurements at median redshifts. We apply this test method for the Lambda-CDM and wCDM models, and investigate the consistency of the derived value of r_d/D_V from Planck 2015 and the SN Ia data sets of Union2.1 and JLA (z<1.5), and the r_d/D_V directly given by BAO data from six-degree-field galaxy survey (6dFGS), Sloan Digital Sky Survey Data Release 7 Main Galaxy Survey (SDSS-DR7 MGS), DR11 of SDSS-III, WiggleZ and Ly-alpha forecast surveys from Baryon Oscillation Spectroscopic Data (BOSS) DR-11 over 0.1<z<2.36. We find that r_d^CMB/D_V^SN for both non-flat Lambda-CDM and flat wCDM models with Union2.1 and JLA data are well consistent with the BAO and CMB measurements within 1-sigma CL. Future surveys will further tight up the constraints significantly, and provide stronger test on the consistency.Comment: 11 pages, 5 figures, 4 tables. Version accepted by PR

COMPARISON OF BANKRUPTCY PREDICTION MODELS WITH PUBLIC RECORDS AND FIRMOGRAPHICS

Many business operations and strategies rely on bankruptcy prediction. In this paper, we aim to study the impacts of public records and firmographics and predict the bankruptcy in a 12-month-ahead period with using different classification models and adding values to traditionally used financial ratios. Univariate analysis shows the statistical association and significance of public records and firmographics indicators with the bankruptcy. Further, seven statistical models and machine learning methods were developed, including Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, Support Vector Machine, Bayesian Network, and Neural Network. The performance of models were evaluated and compared based on classification accuracy, Type I error, Type II error, and ROC curves on the hold-out dataset. Moreover, an experiment was set up to show the importance of oversampling for rare event prediction. The result also shows that Bayesian Network is comparatively more robust than other models without oversampling

Influence of the Event Rate on Discrimination Abilities of Bankruptcy Prediction Models

In bankruptcy prediction, the proportion of events is very low, which is often oversampled to eliminate this bias. In this paper, we study the influence of the event rate on discrimination abilities of bankruptcy prediction models. First the statistical association and significance of public records and firmographics indicators with the bankruptcy were explored. Then the event rate was oversampled from 0.12% to 10%, 20%, 30%, 40%, and 50%, respectively. Seven models were developed, including Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, Support Vector Machine, Bayesian Network, and Neural Network. Under different event rates, models were comprehensively evaluated and compared based on Kolmogorov-Smirnov Statistic, accuracy, F1 score, Type I error, Type II error, and ROC curve on the hold-out dataset with their best probability cut-offs. Results show that Bayesian Network is the most insensitive to the event rate, while Support Vector Machine is the most sensitive