论文标题
循环积分评估和PysecDec的渐近扩展
Loop integral evaluation and asymptotic expansion with pySecDec
论文作者
论文摘要
对高环feynman积分的评估是降低理论预测不确定性并匹配LHC和Future Colliders的实验数据的核心。 PYSECDEC是一个基于扇区分解方法来评估此类积分的程序。它的新版本1.5引入了其性能的显着提高：对积分的加权总和（例如振幅）和运动比例的渐近扩展。在这里，我们简要审查这两者，说明了预期的绩效好处。
The evaluation of higher-loop Feynman integrals is at the core of the quest to reduce the uncertainty of theoretical predictions and match experimental data from the LHC and future colliders. pySecDec is a program to evaluate such integrals numerically based on the sector decomposition approach; its new release version 1.5 introduces features significantly improving its performance: automatic adaptive evaluation of weighted sums of integrals (e.g. amplitudes) and asymptotic expansion in kinematic ratios. Here we briefly review both, illustrating the expected performance benefits.
