def hfc_zeroQuad(slow_spec, freqs, T):
    """
    Applies a correction factor to the spectrum of a slow-measured variable
    based on the response-time T. Quadrature must be analytically zero!

    Parameters
    -----------
    slow_spec: numpy.array or series
        the spectrum to be corrected (not cross-spectrum!)
    freqs: numpy.array
        frequencies
    T: float
        the response-time

    Returns
    --------
    spec: numpy.array
        the recovered array
    """
    import numpy as np
    assert len(slow_spec) == len(freqs)
    return slow_spec * (1.0 + 4.0 * np.pi ** 2.0 * freqs ** 2.0 * T ** 2.0)
