Source code for pycbc.waveform.nltides

""" Utilities for introducing nonlinear tidal effects into waveform approximants
import pycbc.conversions
import numpy
import lal

[docs]def nltides_fourier_phase_difference(f, delta_f, f0, amplitude, n, m1, m2): """Calculate the change to the Fourier phase change due to non-linear tides. Note that the Fourier phase Psi(f) is not the same as the gravitational-wave phase phi(f) and is computed by Delta Psi(f) = 2 \pi f Delta t(f) - Delta phi(f) Parameters ---------- f: numpy.array Array of frequency values to calculate the fourier phase difference delta_f: float Frequency resolution of f array f0: float Frequency that NL effects switch on amplitude: float Amplitude of effect n: float Growth dependence of effect m1: float Mass of component 1 m2: float Mass of component 2 Returns ------- delta_psi: numpy.array Fourier phase as a function of frequency """ kmin = int(f0/delta_f) kmax = len(f) f_ref, t_of_f_factor, phi_of_f_factor = \ pycbc.conversions.nltides_coefs(amplitude, n, m1, m2) # Fourier phase shift below f0 from \Delta \phi(f) delta_psi_f_le_f0 = numpy.ones(kmin) delta_psi_f_le_f0 *= - phi_of_f_factor * (f0/f_ref)**(n-3.) # Fourier phase shift above f0 from \Delta \phi(f) delta_psi_f_gt_f0 = - phi_of_f_factor * (f[kmin:kmax]/f_ref)**(n-3.) # Fourier phase shift below f0 from 2 pi f \Delta t(f) delta_psi_f_le_f0 += 2.0 * lal.lal.PI * f[0:kmin] * t_of_f_factor * \ (f0/f_ref)**(n-4.) # Fourier phase shift above f0 from 2 pi f \Delta t(f) delta_psi_f_gt_f0 += 2.0 * lal.lal.PI * f[kmin:kmax] * t_of_f_factor * \ (f[kmin:kmax]/f_ref)**(n-4.) # Return the shift to the Fourier phase return numpy.concatenate((delta_psi_f_le_f0, delta_psi_f_gt_f0), axis=0)
[docs]def nonlinear_tidal_spa(**kwds): """Generates a frequency-domain waveform that implements the TaylorF2+NL tide model described in """ from pycbc import waveform from pycbc.types import Array # We start with the standard TaylorF2 based waveform kwds.pop('approximant') hp, hc = waveform.get_fd_waveform(approximant="TaylorF2", **kwds) # Add the phasing difference from the nonlinear tides f = numpy.arange(len(hp)) * hp.delta_f pd = Array(numpy.exp(-1.0j * nltides_fourier_phase_difference(f, hp.delta_f, kwds['f0'], kwds['amplitude'], kwds['n'], kwds['mass1'], kwds['mass2'])), dtype=hp.dtype) hp *= pd hc *= pd return hp, hc