精密超冷光谱的遗传拟合技术
Genetic fitting techniques for precision ultracold spectroscopy
摘要：
我们提出了一种遗传算法的发展，用于拟合双原子分子的势能曲线的实验数据。我们的方法不涉及任何函数形式的拟合，这使得它成为一个通用的拟合过程。特别是，它需要一个猜测的潜力，也许从一个$ab \ initio$计算，随着振动结合能，转动常数的实验测量，以及它们的实验不确定性。拟合过程能够修改猜测电位，直到它收敛到优于1%的不确定性，如由$\barχ^2$测量的。我们提出了这种技术的细节，以及通过我们的遗传算法和最先进的拟合技术的基础上的$X \ ^1Σ^+$和$C \ ^1Σ^+$潜力的锂铷的反演微扰方法计算的潜力的比较。
英文摘要：
We present development of a genetic algorithm for fitting potential energy curves of diatomic molecules to experimental data. Our approach does not involve any functional form for fitting, which makes it a general fitting procedure. In particular, it takes in a guess potential, perhaps from an $ab \ initio$ calculation, along with experimental measurements of vibrational binding energies, rotational constants, and their experimental uncertainties. The fitting procedure is able to modify the guess potential until it converges to better than 1% uncertainty, as measured by $\barχ^2$. We present the details of this technique along with a comparison of potentials calculated by our genetic algorithm and the state of the art fitting techniques based on inverted perturbation approach for the $X \ ^1Σ^+$ and $C \ ^1Σ^+$ potentials of lithium-rubidium.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
