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Jade M. Ducharme

Publications and source records attributed to Jade M. Ducharme.

3 recordsLinked to original sources

Improved Modeling for Moving Sources of Radio Frequency Interference and Impact on Flagging Strategies

Radio frequency interference (RFI) is a major challenge for low-frequency radio experiments targeting the redshifted 21-cm signal from the Epoch of Reionization. Many important RFI sources, including aircraft and satellites, move across the sky during an observation. The averaging of visibilities for such moving sources over a finite correlator integration produces a distinct sinc-like pattern in the interferometric uv-plane, causing the RFI to appear bright on some baselines and strongly suppressed on others. Here, we develop an analytical model for this effect and validate its qualitative behavior against real MWA observations and numerical simulations. Controlled RFI injections into clean MWA data are then used to compare several flagging treatments in the context of EoR power spectrum recovery. These treatments explore the trade-off between per-baseline flagging, which can miss weak but potentially non-negligible contamination on baselines where the integration effect leads to strong suppression, and baseline-aggregated flagging, which removes more faint residual contamination but reduces the total number of usable uv-modes. We find that the preferred strategy depends on RFI brightness and occupancy, but that flagging all frequencies at contaminated time-steps most consistently minimizes excess power for bright or frequent events. However, none of the tested flagging treatments fully recovers the uncontaminated reference spectrum, motivating future work on direct modeling and subtraction of moving RFI sources.

astro-ph.IM↗

Interference Meets Inference: Bayesian Time-Series Modeling of Radio-Frequency Interference

Radio-frequency interference (RFI) remains a major challenge for modern radio astronomy experiments. In this work, we cast RFI detection as a one-dimensional time-series anomaly-detection problem and develop a probabilistic mixture-model framework for separating a smoothly varying astronomical background from anomalous contamination. The model jointly describes the clean and contaminated components and assigns each time sample a posterior probability of belonging to the RFI state, rather than relying solely on binary flags. This probabilistic formulation provides a measure of classification confidence, enables uncertainty propagation into derived downstream statistics, and offers additional information for investigating ambiguous events. We apply the framework to observations from the Murchison Widefield Array collected in 2014, producing "soft" classification labels and seasonal RFI trends. We perform a parallel analysis using the Sky-Subtracted Incoherent Noise Spectrum software pipeline (SSINS), which produces "hard" classification labels. Overall, the mixture model provides similar and in some cases superior classification results while providing a complementary probabilistic description of RFI contamination and its uncertainty.

astro-ph.IM↗

Altitude Estimation of Radio Frequency Interference Sources via Interferometric Near Field Corrections

Radio-frequency interference (RFI) presents a significant obstacle to current radio interferometry experiments aimed at the Epoch of Reionization. RFI contamination is often several orders of magnitude brighter than the astrophysical signals of interest, necessitating highly precise identification and flagging. Although existing RFI flagging tools have achieved some success, the pervasive nature of this contamination leads to the rejection of excessive data volumes. In this work, we present a way to estimate an RFI emitter's altitude using near-field corrections. Being able to obtain the precise location of such an emitter could shift the strategy from merely flagging to subtracting or peeling the RFI, allowing us to preserve a higher fraction of usable data. We conduct a preliminary study using a two-minute observation from the Murchison-Widefield Array (MWA) in which an unknown object briefly crosses the field of view, reflecting RFI signals into the array. By applying near-field corrections that bring the object into focus, we are able to estimate its approximate altitude and speed to be $11.7$ km and $792$ km/h, respectively. This allows us to confidently conclude that the object in question is in fact an airplane. We further validate our technique through the analysis of two additional RFI-containing MWA observations, where we are consistently able to identify airplanes as the source of the interference.

astro-ph.IM↗