arXiv subjects

Tommy Marshman

Publications and source records attributed to Tommy Marshman.

3 recordsLinked to original sources

arXiv2026

Characterising and mitigating Bluetooth and WiFi radio frequency interference at the Parkes Observatory

We present a detailed characterisation of radio frequency interference (RFI) in the 2.4 GHz band around Murriyang, CSIRO's Parkes radio telescope. The dominant sources of interference are Wi-Fi and Bluetooth transmissions. We quantify how the intensity and directionality of this RFI vary with time of day and document its evolution over several years. Although most observers currently discard data within this band, our analysis shows that the interference is confined in both timeand frequency and can be effectively mitigated. Using 10 seconds of 16-bit voltage data recorded during observations of the Vela Pulsar (PSR J0835-4510), we demonstrate that the majority of the channelised data remain unaffected by RFI. We compare three RFI detection and mitigation algorithms and evaluate their relative performance. All methods perform effectively, and any could be implemented in real time to enable productive use of this observing band. A real time implementation would allow the scientific use of this 128 MHz observing band to increase, from almost 70% of the band being completely unusable all of the time, to over 90% of becoming accessible for science. Given its simplicity and efficiency, a basic power-threshold approach offers a relatively straightforward solution.

astro-ph.IM↗

arXiv2022

Evaluating the prevalence of spurious correlations in pulsar timing array datasets

Pulsar timing array collaborations have recently reported evidence for a noise process with a common spectrum among the millisecond pulsars in the arrays. The spectral properties of this common-noise process are consistent with expectations for an isotropic gravitational-wave background (GWB) from inspiralling supermassive black-hole binaries. However, recent simulation analyses based on Parkes Pulsar Timing Array data indicate that such a detection may arise spuriously. In this paper, we use simulated pulsar timing array datasets to further test the robustness of the inference methods for spectral and spatial correlations from a GWB. Expanding on our previous results, we find strong support (Bayes factors exceeding $10^5$) for the presence of a common-spectrum noise process in datasets where no common process is present, under a wide range of timing noise prescriptions per pulsar. We show that these results are highly sensitive to the choice of Bayesian priors on timing noise parameters, with priors that more closely match the injected distributions of timing noise parameters resulting in diminished support for a common-spectrum noise process. These results emphasize shortcomings in current methods for inferring the presence of a common-spectrum process, and imply that the detection of a common process is not a reliable precursor to detection of the GWB. Future searches for the nanohertz GWB should remain focussed on detecting spatial correlations, and make use of more tailored specifications for a common-spectrum noise process.

astro-ph.HE↗

arXiv2022

Simulating high-time resolution radio-telescope observations

We describe a new software package for simulating channelised, high-time resolution data streams from radio telescopes. The software simulates data from the telescope and observing system taking into account the observation strategy, receiver system and digitisation. The signatures of pulsars, fast radio bursts and flare stars are modelled, including frequency-dependent effects such as scattering and scintillation. We also simulate more generic signals using spline curves and images. Models of radio frequency interference include signals from satellites, terrestrial transmitters and impulsive, broadband signals. The simulated signals can also be injected into real data sets. Uses of this software include the production of machine learning training data sets, development and testing of new algorithms to search for anomalous patterns and to characterise processing pipelines.

astro-ph.IM↗