Z-pole test of effective dark matter diboson interactions at the CEPC

In this paper we investigate the projected sensitivity to effective dark matter (DM) - diboson interaction during the high luminosity $Z$-pole and 240 GeV runs at the proposed Circular Electron Positron Collider (CEPC). The proposed runs at the 91.2 GeV $e^+e^-$ center of mass energy offers an interesting opportunity to probe effective dark matter couplings to the $Z$ boson, which can be less stringently tested in non-collider searches. We investigate the prospective sensitivity for dimension 6 and dimension 7 effective diboson operators to scalar and fermion dark matter. These diboson operators can generate semi-visible $Z$ boson decay, and high missing transverse momentum mono-photon signals that can be test efficiently at the CEPC, with a small and controllable Standard Model $\gamma\bar{\nu}\nu$ background. A projected sensitivity for effective $\gamma Z$ coupling efficient $\kappa_{\gamma Z}< (1030$ GeV$)^{-3}$, $(1970$ GeV$)^{-3}$ for scalar DM, $\kappa_{\gamma Z}< (360$ GeV$)^{-3}$, $(540$ GeV$)^{-3}$ for fermion DM are obtain for 25 fb$^{-1}$ and 2.5 ab$^{-1}$ $Z$-pole luminosities assuming the optimal low dark matter mass range. In comparison the effective DM-diphoton coupling sensitivity $\kappa_{\gamma \gamma}< (590$ GeV$)^{-3}$ for scalar DM, $\kappa_{\gamma \gamma}< (360$ GeV$)^{-3}$ for fermion DM are also obtained for a 5 ab$^{-1}$ 240 GeV Higgs run. We also compare the CEPC sensitivities to current direct and indirect search limits on these effective DM-diboson operators.Comment: 10 pages, 7 figures. Dimension-6 diboson operators include

Impacts of model calibration on high-latitude land-surface processes: PILPS 2(e) calibration/validation experiments

In the PILPS 2(e) experiment, the Snow Atmosphere Soil Transfer (SAST) land-surface scheme developed from the Biosphere-Atmosphere Transfer Scheme (BATS) showed difficulty in accurately simulating the patterns and quantities of runoff resulting from heavy snowmelt in the high-latitude Torne-Kalix River basin (shared by Sweden and Finland). This difficulty exposes the model deficiency in runoff formations. After representing subsurface runoff and calibrating the parameters, the accuracy of hydrograph prediction improved substantially. However, even with the accurate precipitation and runoff, the predicted soil moisture and its variation were highly "model-dependent". Knowledge obtained from the experiment is discussed. © 2003 Elsevier Science B.V. All rights reserved

Multiplicity Preserving Triangular Set Decomposition of Two Polynomials

In this paper, a multiplicity preserving triangular set decomposition algorithm is proposed for a system of two polynomials. The algorithm decomposes the variety defined by the polynomial system into unmixed components represented by triangular sets, which may have negative multiplicities. In the bivariate case, we give a complete algorithm to decompose the system into multiplicity preserving triangular sets with positive multiplicities. We also analyze the complexity of the algorithm in the bivariate case. We implement our algorithm and show the effectiveness of the method with extensive experiments.Comment: 18 page

2.5D multi-view gait recognition based on point cloud registration

This paper presents a method for modeling a 2.5-dimensional (2.5D) human body and extracting the gait features for identifying the human subject. To achieve view-invariant gait recognition, a multi-view synthesizing method based on point cloud registration (MVSM) to generate multi-view training galleries is proposed. The concept of a density and curvature-based Color Gait Curvature Image is introduced to map 2.5D data onto a 2D space to enable data dimension reduction by discrete cosine transform and 2D principle component analysis. Gait recognition is achieved via a 2.5D view-invariant gait recognition method based on point cloud registration. Experimental results on the in-house database captured by a Microsoft Kinect camera show a significant performance gain when using MVSM

Root Isolation of Zero-dimensional Polynomial Systems with Linear Univariate Representation

In this paper, a linear univariate representation for the roots of a zero-dimensional polynomial equation system is presented, where the roots of the equation system are represented as linear combinations of roots of several univariate polynomial equations. The main advantage of this representation is that the precision of the roots can be easily controlled. In fact, based on the linear univariate representation, we can give the exact precisions needed for roots of the univariate equations in order to obtain the roots of the equation system to a given precision. As a consequence, a root isolation algorithm for a zero-dimensional polynomial equation system can be easily derived from its linear univariate representation.Comment: 19 pages,2 figures; MM-Preprint of KLMM, Vol. 29, 92-111, Aug. 201