A system of static Hamilton-Jacobi PDEs plus an alternating fast-sweeping solver yields the mean-time-optimal UUV path under a weighted ensemble of ocean current forecasts.
Scattered light noise characterisation at the Virgo interferometer with tvf-EMD adaptive algorithm
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abstract
A methodology of adaptive time series analysis, based on Empirical Mode Decomposition (EMD), and on its time varying version tvf-EMD has been applied to strain data from the gravitational wave interferometer (IFO) Virgo in order to characterise scattered light noise affecting the sensitivity of the IFO in the detection frequency band. Data taken both during hardware injections, when a part of the IFO is put in oscillation for detector characterisation purposes, and during periods of science mode, when the IFO is fully locked and data are used for the detection of gravitational waves, were analysed. The adaptive nature of the EMD and tvf-EMD algorithms allows them to deal with nonlinear non-stationary data and hence they are particularly suited to characterise scattered light noise which is an intrinsically nonlinear and non-stationary noise. Obtained results show that tvf-EMD algorithm allows to obtain more precise results compared to the EMD algorithm, yielding higher cross-correlation values with the auxiliary channels that are the culprits of scattered light noise.
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math.OC 1years
2026 1verdicts
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Optimal mean-time path planning for unmanned underwater vehicles: a Hamilton-Jacobi approach
A system of static Hamilton-Jacobi PDEs plus an alternating fast-sweeping solver yields the mean-time-optimal UUV path under a weighted ensemble of ocean current forecasts.