hyperfine.superconductivity.pippard.xi_Pippard

hyperfine.superconductivity.pippard.xi_Pippard(T: Annotated[float, slice(0, None, None)], T_c: Annotated[float, slice(0, None, None)], Delta_0: Annotated[float, slice(0, None, None)], l: Annotated[float, slice(0, None, None)], xi_0: Annotated[float, slice(0, None, None)], alpha: Annotated[float, slice(0, None, None)] = 1.0) → float

Evaluate the effective Pippard coherence length for a finite electron mean-free-path.

Parameters:

• T – Absolute temperature (K).

• T_c – Superconducting transition temperature (K).

• Delta_0 – Superconducting gap energy at 0 K (eV).

• l – electron mean-free-path (nm).

• xi_0 – Pippard coherence length at 0 K (nm).

• alpha – numerical constant on the order of unity.

Returns:

The effective Pippard coherence length (nm).

Example

import numpy as np
import matplotlib.pyplot as plt
from hyperfine.superconductivity import pippard

T = np.linspace(0.0, 1.0, 100)
args = (1.0, 1.43e-3, 200.0, 50.0)
xi = np.array([pippard.xi_Pippard(tt, *args) for tt in T])
plt.plot(T, xi, "-")
plt.xlabel("$T / T_{c}$")
plt.ylabel(r"$\xi_{0}(T)$ (nm)")
plt.show()

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