def test_etpa():
epp = Biphoton(0, 0.04 / au2ev, Te=10. / au2fs)
p = np.linspace(-4, 4, 256) / au2ev
q = p
epp.set_grid(p, q)
epp.get_jsa()
# epp.plt_jsa()
pump = np.linspace(0.5, 1.5, 100) / au2ev
signal = etpa(pump, mol, epp, [0], [1, 2, 3], [2, 3])
fig, ax = subplots()
ax.plot(pump * au2ev, np.abs(signal)**2)
plt.show()
return
# # ax.scatter(eigvals1.real, eigvals1.imag)
# ax.plot(omegas, -2 * la.imag)
# plt.show()
solver = Lindblad_solver(H, c_ops=[0.02 * sx])
# solver.liouvillian()
solver.eigenstates()
# print(solver.right_eigvecs)
times = np.linspace(0, 40) / au2fs
result = solver.evolve(rho0, tlist=times, e_ops=[sx, sz])
# cor = solver.correlation_2op_1t(rho0=rho0, ops=[sx, sx], tlist=times)
w = np.linspace(0.4, 2., 100) / au2ev
S = solver.correlation_3op_1w(rho0=rho0, ops=[sx, sx, sx], w=w)
fig, ax = subplots()
ax.plot(w * au2ev, S.real)
# print(cor)
# fig, ax = matplot(times, times, cor.real)
# cor = solver.correlation_3op_2t(ops=[sx, sx, sz], taulist=times, tlist=times, rho0=rho0, k=4)
# fig, ax = subplots()
# # # ax.scatter(eigvals1.real, eigvals1.imag)
# ax.plot(result.times, result.observables[:,1])
# plt.show()
# from lime.style import matplot
# fig, ax = matplot(times, times, cor.real)