Ejemplo n.º 1
0
    def test(self):
        # With initial condition y(1) = 2, solution is
        def exact(x):
            return np.power(x + x**2 * (0.5 * 2**(2. / 3.) - 1), -3)

        ystart = np.ones((1, ))
        ystart[:] = [2.0]

        rtol = 1.0e-13
        atol = 1.0e-13
        x0 = 1.0
        x1 = 4.0
        hmin = 0.0
        h1 = 0.01
        out = ode_solve.Output(1)

        a = ode_solve.ODEint(ystart, x0, x1, atol, rtol, h1,hmin, out,\
                 dopr853.StepperDopr853, integrand() )
        a.integrate()
        y_calc = a.out.ysave[a.out.count - 1]
        y_exct = exact(a.out.xsave[a.out.count - 1])
        self.assertAlmostEqual(y_calc, y_exct, delta=2 * atol * y_exct)
Ejemplo n.º 2
0
integrand = dfg_problem(pump_in,
                        sgnl_in,
                        idlr_in,
                        crystal,
                        disable_SPM=True,
                        waist=beamwaist)

# Set up integrator
rtol = 1.0e-6
atol = 1.0e-6
x0 = 0.0
x1 = crystallength
hmin = 0.0
h1 = 0.00001
out = ode_solve.Output(n_saves)

a = ode_solve.ODEint(integrand.ystart, x0, x1, atol, rtol, h1,hmin, out,\
         dopr853.StepperDopr853, integrand)
a.integrate()

print 'integrated!'

pump_out = a.out.ysave[0:a.out.count, 0:npoints].T
sgnl_out = a.out.ysave[0:a.out.count, npoints:2 * npoints].T
idlr_out = a.out.ysave[0:a.out.count, 2 * npoints:3 * npoints].T
z = a.out.xsave[0:a.out.count]

pump_power_in = np.round(
    1e3 * np.trapz(abs(IFFT_t(pump_out[:, 0]))**2, pump_in.T) * pump_in.frep,
    decimals=4)
Ejemplo n.º 3
0
        sigma = 10.0
        R = 28.0
        b = 8.0 / 3.0
        dydx[0] = sigma * (y[1] - y[0])
        dydx[1] = R * y[0] - y[1] - y[0] * y[2]
        dydx[2] = -b * y[2] + y[0] * y[1]


ystart = np.ones((3, ), dtype=np.complex128)
ystart[:] = [10.0, 1.0, 1.0]
dydxstart = np.ones((3, ), dtype=np.complex128)

xstart = np.zeros((1, ))

rtol = 1.0e-9
atol = 1.0e-9
x0 = 0.0
x1 = 250.0
hmin = 0.0
h1 = 0.01
out = ode_solve.Output(5000)

a = ode_solve.ODEint(ystart, x0, x1, atol, rtol, h1,hmin, out,\
         dopr853.StepperDopr853, integrand())
a.integrate()

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot(a.out.ysave[:a.out.count, 0], a.out.ysave[:a.out.count, 1],
        a.out.ysave[:a.out.count, 2])
plt.show()
Ejemplo n.º 4
0
    def test_fn(self):
        npoints = 2**6
        # Physical lengths are in meters
        crystallength = 0.010
        crystal = crystals.AgGaSe2()
        crystal = crystals.AgGaSe2(length=crystallength)

        n_saves = 10

        # Wavelengths are in nanometers
        pump_wl_nm = 1560. + 10.0 * np.random.rand()
        sgnl_wl_nm = 2200. + 10.0 * np.random.rand()
        theta, idlr_wl_nm = crystal.phasematch(pump_wl_nm,
                                               sgnl_wl_nm,
                                               None,
                                               return_wavelength=True)
        crystal.set_theta(theta)

        pump_power = (1 + np.random.rand()) * 5000.0
        sgnl_power = 0.10 * np.random.rand()
        twind = 25.
        beamwaist = 100e-3

        pump_in = CWPulse(pump_power,
                          pump_wl_nm,
                          NPTS=npoints,
                          time_window_ps=twind)
        sgnl_in = CWPulse(sgnl_power,
                          sgnl_wl_nm,
                          NPTS=npoints,
                          time_window_ps=twind)

        integrand = dfg_problem(pump_in,
                                sgnl_in,
                                crystal,
                                disable_SPM=True,
                                pump_waist=beamwaist,
                                apply_gouy_phase=True)

        # Set up integrator
        rtol = 1.0e-12
        atol = 1.0e-12
        x0 = 0.0
        x1 = crystallength
        hmin = 0.0
        h1 = 0.0000001
        out = ode_solve.Output(n_saves)

        # From Boyd section 2.8, also my One Note
        omega = lambda l_nm: 2.0 * np.pi * speed_of_light / (l_nm * 1.0e-9)
        w_1 = omega(sgnl_wl_nm)
        w_2 = omega(idlr_wl_nm)
        k_1 = np.mean(2 * np.pi * crystal.n(sgnl_wl_nm, 'o') /
                      (sgnl_wl_nm * 1.0e-9))
        k_2 = np.mean(2 * np.pi * crystal.n(idlr_wl_nm, 'o') /
                      (idlr_wl_nm * 1.0e-9))

        n_1 = crystal.n(sgnl_wl_nm, 'o')
        n_2 = crystal.n(idlr_wl_nm, 'o')
        n_3 = crystal.n(pump_wl_nm, 'mix')

        A_3 = np.sqrt(pump_power) * integrand.pump_beam.rtP_to_a(
            crystal.n(pump_wl_nm, 'mix'))
        A_1 = np.sqrt(sgnl_power) * integrand.sgnl_beam.rtP_to_a(
            crystal.n(sgnl_wl_nm, 'o'))

        kappa = np.mean(
            np.sqrt(4 * crystal.deff**2 * w_1**2 * w_2**2 /
                    (k_1 * k_2 * speed_of_light**4)) * A_3)

        a = ode_solve.ODEint(integrand.ystart, x0, x1, atol, rtol, h1,hmin, out,\
                 dopr853.StepperDopr853, integrand, dtype = np.complex128)
        a.integrate()

        pump_out = a.out.ysave[0:a.out.count, 0:npoints].T
        sgnl_out = a.out.ysave[0:a.out.count, npoints:2 * npoints].T
        idlr_out = a.out.ysave[0:a.out.count, 2 * npoints:3 * npoints].T
        z = a.out.xsave[0:a.out.count]

        pump_power_in = np.sum(np.abs(pump_out[:, 0]), axis=0)**2
        sgnl_power_in = np.sum(np.abs(sgnl_out[:, ])**2, axis=0)
        idlr_power_in = np.sum(np.abs(idlr_out[:, 0]), axis=0)**2

        pump_power_out = np.sum(np.abs(pump_out[:, -1]))**2
        sgnl_power_out = np.sum(np.abs(sgnl_out[:, -1]))**2
        idlr_power_out = np.sum(np.abs(idlr_out[:, -1]))**2

        # Compare integrated and analytic values for signal power
        numeric_sgnl = np.sum(np.abs(sgnl_out[:, :])**2, axis=0)
        analytic_sgnl = sgnl_power_in * np.cosh(kappa * z)**2
        self.assertLess(
            abs(
                np.sum(numeric_sgnl - analytic_sgnl) /
                np.sum(abs(analytic_sgnl))), 0.01)

        # Compare integrated and analytic values for idler power
        numeric_idlr = np.sum(np.abs(idlr_out[:, :])**2, axis=0)
        analytic_idlr = n_1 * w_2 / (n_2 * w_1) * sgnl_power_in * np.sinh(
            kappa * z)**2
        self.assertLess(
            abs(
                np.sum(numeric_idlr - analytic_idlr) /
                np.sum(abs(analytic_idlr))), 0.02)