Long-Time Correlations in Single-Neutron Interferometry Data

TL;DR

This paper analyzes long-time correlations in single-neutron interferometry data, revealing non-stationary features and phase-dependent fluctuations that challenge standard quantum models of independent events.

Contribution

It demonstrates that neutron count data exhibit long-time correlations and non-stationary behavior, which can be modeled by a periodic phase shift variation over time.

Findings

Neutron count variance depends on phase-shifter setting.

Detection events show damped oscillations with a 2.8 s period.

Correlations can be simulated by a periodically varying phase shift.

Abstract

We present a detailed analysis of the time series of time-stamped neutron counts obtained by single-neutron interferometry. The neutron counting statistics display the usual Poissonian behavior, but the variance of the neutron counts does not. Instead, the variance is found to exhibit a dependence on the phase-shifter setting which can be explained by a probabilistic model that accounts for fluctuations of the phase shift. The time series of the detection events exhibit long-time correlations with amplitudes that also depend on the phase-shifter setting. These correlations appear as damped oscillations with a period of about 2.8 s. By simulation, we show that the correlations of the time differences observed in the experiment can be reproduced by assuming that, for a fixed setting of the phase shifter, the phase shift experienced by the neutrons varies periodically in time with a period of 2.8 s. The same simulations also reproduce the behavior of the variance. Our analysis of the experimental data suggests that time-stamped data of singleparticle interference experiments may exhibit transient features that require a description in terms of non-stationary processes, going beyond the standard quantum model of independent random events.