Direct searches for electroweak pair production of new particles at the LHC
are a difficult proposition, due to the large background and low signal cross
sections. We demonstrate how these searches can be improved by a combination of
new razor variables and shape analysis of signal and background kinematics. We
assume that the pair-produced particles decay to charged leptons and missing
energy, either directly or through a W boson. In both cases the final state is
a pair of opposite sign leptons plus missing transverse energy. We estimate
exclusion reach in terms of sleptons and charginos as realized in minimal
supersymmetry. We compare this super-razor approach in detail to analyses based
on other kinematic variables, showing how the super-razor uses more of the
relevant kinematic information while achieving higher selection efficiency on
signals, including cases with compressed spectra.

通过新的 Razor 变量和形态分析组合，本文研究了在 LHC 上直接搜索产生新粒子的难点，并假定这些粒子通过环境中的带荷轻子和失踪能量，最终得到一对随机符号轻子和失踪横向能量的状态下，比较超级 Razor 方法和其他动力学变量分析的优劣性，实现了在最小超对称性的情况下在睡眠子和带电荷粒子的排除程度方面的估计。

LHC 上的超级剃须刀和睡带粒子与带电胶子的搜索

Super-Razor and Searches for Sleptons and Charginos at the LHC

The use of Laplacian eigenbases has been shown to be fruitful in many
computer graphics applications. Today, state-of-the-art approaches to shape
analysis, synthesis, and correspondence rely on these natural harmonic bases
that allow using classical tools from harmonic analysis on manifolds. However,
many applications involving multiple shapes are obstacled by the fact that
Laplacian eigenbases computed independently on different shapes are often
incompatible with each other. In this paper, we propose the construction of
common approximate eigenbases for multiple shapes using approximate joint
diagonalization algorithms. We illustrate the benefits of the proposed approach
on tasks from shape editing, pose transfer, correspondence, and similarity.

本文提出了使用近似联合对角化算法构建多个形状的共同近似特征基，以解决独立计算不兼容导致的对多个形状的分析、综合和对应的难题，并以形状编辑、姿势传输、对应和相似性任务为例说明了所提出方法的优点。