Process | HEX: Excitation |
Data type | cross section | uploaded on 2022-11-11 |
Comment | Fit function in set IA scaled with relation from setIIA based on WUtte et al. |
Method | semi-empirical |
Frame | Target |
Columns |
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Threshold | 0.190 eV |
Ref |
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Data | Download (data from fit) |
Fit Function Details |
\[\begin{align} & \sigma_p^{exc}(E_p) = \sigma_e^{exc}(E_e) = \frac{5.984 \times 10^{-16}}{E} \Bigg[\frac{E- I}{E} \Bigg]^{A_6} \Bigg[ \sum_{j=1}^{4}\frac{A_j}{(E/I)^{j-1}} + A_5\ln\bigg( \frac{E}{I} \bigg) \Bigg] \\ & \quad E_p(keV/amu) = 0.918E_e(eV)\Bigg[1 - \frac{dE(eV)}{1.15E_e(eV)} + \sqrt{\bigg(1- \frac{dE(eV)}{E_e(eV)}\bigg)} \Bigg] \\ \end{align}\] | ||||||||||||||
Python | def li_hex_wutte(E, A1, A2, A3, A4, A5, A6, I): """ This function calculates proton impact excitation cross sections (in cm2) of Li. param E: requested electron-impact energy in eV type E: float, np.ndarray param Ai: fit coefficient type Ai: float param I: threshold energy in eV type I: float """ energy = np.logspace(np.log10(I), 5, num=500) sigma_e = 5.984e-16/E * ((energy-I)/energy)**A6 * (A1/((energy/I)**0) + A2/((energy/I)**1) + A3/((energy/I)**2) + A4/((energy/I)**3) + A5*np.log(energy/I)) ref_E = 0.918*energy*(1-I/(1.15*energy) + np.sqrt(1-I/energy)) sigma_p = sp.interpolate.interp1d(ref_E, sigma_e, kind='linear', fill_value='extrapolate') return sigma_p(E) |
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Fit Precision | 2.0 % | ||||||||||||||
Fit Coefficients |
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x-range | 0.022750434782608683 – |