Пример #1
0
    # The dispersion model is built from a Taylor expansion with coefficients
    # given below.
    loss = 0
    betas = np.array([
        -0.024948815481502, 8.875391917212998e-05, -9.247462376518329e-08,
        1.508210856829677e-10
    ])
    setup.dispersion_model = gnlse.DispersionFiberFromTaylor(loss, betas)

    # Input impulse parameters
    power = 10000
    # pulse duration [ps]
    tfwhm = 0.05
    # hyperbolic secant
    setup.impulse_model = gnlse.SechEnvelope(power, tfwhm)

    # Simulation
    ###########################################################################
    # Type of dyspersion operator: build from Taylor expansion
    setup.dispersion = gnlse.DispersionFiberFromTaylor(loss, betas)
    solver = gnlse.GNLSE(setup)
    solution = solver.run()

    # Visualization
    ###########################################################################
    plt.figure(figsize=(10, 8))

    plt.subplot(2, 2, 1)
    plt.title("Results for Taylor expansion")
    gnlse.plot_wavelength_vs_distance(solution, WL_range=[400, 1400])
Пример #2
0
    setup = gnlse.GNLSESetup()

    # Numerical parameters
    setup.resolution = 2**14
    setup.time_window = 12.5  # ps
    setup.z_saves = 400

    # Input impulse parameters
    peak_power = 10000  # W
    duration = 0.050284  # ps

    # Physical parameters
    setup.wavelength = 835  # nm
    setup.fiber_length = 0.15  # m
    setup.nonlinearity = 0.11  # 1/W/m
    setup.impulse_model = gnlse.SechEnvelope(peak_power, duration)
    setup.self_steepening = True

    # The dispersion model is built from a Taylor expansion with coefficients
    # given below.
    loss = 0
    betas = np.array([
        -11.830e-3, 8.1038e-5, -9.5205e-8, 2.0737e-10, -5.3943e-13, 1.3486e-15,
        -2.5495e-18, 3.0524e-21, -1.7140e-24
    ])
    setup.dispersion_model = gnlse.DispersionFiberFromTaylor(loss, betas)

    # This example extends the original code with additional simulations for
    # three types of models of Raman response and no raman scattering case
    raman_models = {
        'Blow-Wood': gnlse.raman_blowwood,
Пример #3
0
    # The dispersion model is built from a Taylor expansion with coefficients
    # given below.
    loss = 0
    betas = np.array([
        -11.830e-3, 8.1038e-5, -9.5205e-8, 2.0737e-10, -5.3943e-13, 1.3486e-15,
        -2.5495e-18, 3.0524e-21, -1.7140e-24
    ])
    setup.dispersion_model = gnlse.DispersionFiberFromTaylor(loss, betas)

    # Input pulse parameters
    peak_power = 10000  # W
    duration = 0.050  # ps

    # This example extends the original code with additional simulations for
    pulse_models = [
        gnlse.SechEnvelope(peak_power, duration),
        gnlse.GaussianEnvelope(peak_power, duration),
        gnlse.LorentzianEnvelope(peak_power, duration)
    ]

    count = len(pulse_models)
    plt.figure(figsize=(14, 8), facecolor='w', edgecolor='k')
    for i, pulse_model in enumerate(pulse_models):
        print('%s...' % pulse_model.name)

        setup.pulse_model = pulse_model
        solver = gnlse.GNLSE(setup)
        solution = solver.run()

        plt.subplot(2, count, i + 1)
        plt.title(pulse_model.name)
Пример #4
0
    t0 = tFWHM / 2 / np.log(1 + np.sqrt(2))

    # 3rd order soliton conditions
    ###########################################################################
    # Dispersive length
    LD = t0 ** 2 / np.abs(betas[0])
    # Non-linear length for 3rd order soliton
    LNL = LD / (3 ** 2)
    # Input pulse: peak power [W]
    power = 1 / (LNL * setup.nonlinearity)
    # Length of soliton, in which it break dispersive characteristic
    Z0 = np.pi * LD / 2
    # Fiber length [m]
    setup.fiber_length = .5
    # Type of impulse:  hyperbolic secant
    setup.impulse_model = gnlse.SechEnvelope(power, 0.050)
    # Loss coefficient [dB/m]
    loss = 0
    # Type of dyspersion operator: build from Taylor expansion
    setup.dispersion_model = gnlse.DispersionFiberFromTaylor(loss, betas)

    # Type of Ramman scattering function: None (default)
    # Selftepening: not accounted
    setup.self_steepening = False

    # Simulation
    ###########################################################################
    solver = gnlse.gnlse.GNLSE(setup)
    solution = solver.run()

    # Visualization
Пример #5
0
import matplotlib.pyplot as plt
import gnlse

if __name__ == '__main__':

    # time full with half maximum of impulse
    FWHM = 2
    # Time grid [ps]
    T = np.linspace(-2 * FWHM, 2 * FWHM, 1000 * FWHM)
    # peak power [W]
    Pmax = 100

    # Amplitude envelope of gaussina impulse
    A1 = gnlse.GaussianEnvelope(Pmax, FWHM).A(T)
    # Amplitude envelope of hiperbolic secans impulse
    A2 = gnlse.SechEnvelope(Pmax, FWHM).A(T)
    # Amplitude envelope of lorentzian impulse
    A3 = gnlse.LorentzianEnvelope(Pmax, FWHM).A(T)

    plt.figure(figsize=(12, 8))
    plt.subplot(1, 2, 1)
    plt.plot(T, A1, label='gauss')
    plt.plot(T, A2, label='sech')
    plt.plot(T, A3, label='lorentz')
    plt.xlabel("Time [ps]")
    plt.ylabel("Amplitude [sqrt(W)]")
    plt.legend()

    plt.subplot(1, 2, 2)
    plt.plot(T, A1**2, label='gauss')
    plt.plot(T, A2**2, label='sech')