Esempio n. 1
0
    # Input pulse: pulse duration [ps]
    tFWHM = 0.050
    t0 = tFWHM / 2 / np.sqrt(np.log(2))  # for dispersive length calculation

    # 3rd order soliton conditions
    ###########################################################################
    # Dispersive length
    LD = t0 ** 2 / np.abs(betas[0])
    # Non-linear length for 1st order soliton
    LNL = LD / (1 ** 2)
    # Input pulse: peak power [W]
    power = 1 / (LNL * setup.nonlinearity)
    # Fiber length [m]
    setup.fiber_length = 10 * LD
    # Type of pulse:  gaussian
    setup.pulse_model = gnlse.GaussianEnvelope(power, tFWHM)
    # 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
Esempio n. 2
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    # 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)
        gnlse.plot_wavelength_vs_distance(solution, WL_range=[400, 1400])
Esempio n. 3
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"""
Runs a simple simulation, saves it to disk and loads it back for plotting.
"""

import os
import gnlse

if __name__ == '__main__':
    setup = gnlse.GNLSESetup()
    setup.resolution = 2**13
    setup.time_window = 12.5  # ps
    setup.z_saves = 200
    setup.fiber_length = 0.15  # m
    setup.wavelength = 835  # nm
    setup.impulse_model = gnlse.GaussianEnvelope(1, 0.1)

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

    path = 'test.mat'

    solution.to_file(path)
    solution = gnlse.Solution()
    solution.from_file(path)

    gnlse.quick_plot(solution)

    os.remove(path)
Esempio n. 4
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import numpy as np
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)