论文标题

Maiani-Testa方法和反问题的变化

Variations on the Maiani-Testa approach and the inverse problem

论文作者

Bruno, Mattia, Hansen, Maxwell T.

论文摘要

我们通过将受调节的逆拉动式变换的方法与Maiani和Testa的工作相结合,讨论了一种构建欧几里得相关因子的Hadronic散射和衰减幅度的方法。重新审视原始结果,我们观察到,可以通过将相关器解释为光谱函数,$ρ(ω)$可以理解的关键观察,即只能在大分离下提取阈值散射信息,并与欧几里得内核,$ e^{ - ωt} $相处。因此,我们考虑了一种修改,在该修改中,将平滑的步长函数(等于目标能量上方等于目标能量)插入光谱分解中。这可以通过类似于backus-gilbert样方法或更直接地使用变分方法来实现。结果是转移的分辨率函数,使得大的$ t $限制项目限制在散射或衰减幅度高于阈值之上。该方法的实用性通过三点和四点功能的大型$ t $扩展突出显示,这些功能包括与目标可观察到的实际零件成正比的领先术语。这项工作还提出了与阈值下未修饰的相关器相关的新结果,包括从四点功能中提取$nπ$散射长度的表达方式,以及一种组织大型$ t $扩展的新策略,该策略比$ 1/t $的powers的扩展更好。

We discuss a method to construct hadronic scattering and decay amplitudes from Euclidean correlators, by combining the approach of a regulated inverse Laplace transform with the work of Maiani and Testa. Revisiting the original result, we observe that the key observation, i.e. that only threshold scattering information can be extracted at large separations, can be understood by interpreting the correlator as a spectral function, $ρ(ω)$, convoluted with the Euclidean kernel, $e^{- ωt}$, which is sharply peaked at threshold. We therefore consider a modification in which a smooth step function, equal to one above a target energy, is inserted in the spectral decomposition. This can be achieved either through Backus-Gilbert-like methods or more directly using the variational approach. The result is a shifted resolution function, such that the large $t$ limit projects onto scattering or decay amplitudes above threshold. The utility of this method is highlighted through large $t$ expansions of both three- and four-point functions that include leading terms proportional to the real and imaginary parts (separately) of the target observable. This work also presents new results relevant for the un-modified correlator at threshold, including expressions for extracting the $N π$ scattering length from four-point functions and a new strategy to organize the large $t$ expansion that exhibits better convergence than the expansion in powers of $1/t$.

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