We report a method to determine the phase and amplitude of sinusoidally modulated event rates, binned into 4 bins per oscillation. The presented algorithm relies on a reconstruction of the unknown parameters. It omits a calculation intensive fitting procedure and avoids contrast reduction due to averaging effects. It allows the current data acquisition bottleneck to be relaxed by a factor of 4. Here, we explain the approach in detail and compare it to the established fitting procedures of time series having 4 and 16 time bins per oscillation. In addition we present the empirical estimates of the errors of the three methods and compare them to each other. We show that the reconstruction is unbiased, asymptotic, and efficient for estimating the phase. Reconstructing the contrast, which corresponds to the amplitude of the modulation, is roughly 10% less efficient than fitting 16 time binned oscillations. Finally, we give analytical equations to estimate the error for phase and contrast as a function of their initial values and counting statistics.
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