arXiv subjects

Richard Dodson

Publications and source records attributed to Richard Dodson.

At least 37 records · Page 2Linked to original sources

arXiv2025

First frequency phase transfer from the 3 mm to the 1 mm band on an Earth-sized baseline

Frequency Phase Transfer (FPT) is a technique designed to increase coherence and sensitivity in radio interferometry by making use of the non-dispersive nature of the troposphere to calibrate high-frequency data using solutions derived at a lower frequency. While the Korean VLBI Network has pioneered the use of simultaneous multi-band systems for routine FPT up to an observing frequency of 130 GHz, this technique remains largely untested in the (sub)millimeter regime. A recent effort has been made to outfit dual-band systems at (sub)millimeter observatories participating in the Event Horizon Telescope (EHT) and to test the feasibility and performance of FPT up to the observing frequencies of the EHT. We present the results of simultaneous dual-frequency observations conducted in January 2024 on an Earth-sized baseline between the IRAM 30-m in Spain and the JCMT and SMA in Hawai`i. We performed simultaneous observations at 86 and 215 GHz on the bright sources J0958+6533 and OJ287, with strong detections obtained at both frequencies. We observe a strong correlation between the interferometric phases at the two frequencies, matching the trend expected for atmospheric fluctuations and demonstrating for the first time the viability of FPT for VLBI at a wavelength of $\sim$1 millimeter. We show that the application of FPT systematically increases the 215 GHz coherence on all averaging timescales. In addition, the use of the co-located JCMT and SMA as a single dual-frequency station demonstrates the feasibility of paired-antenna FPT for VLBI for the first time, with implications for future array capabilities (e.g., ALMA sub-arraying and ngVLA calibration strategies).

astro-ph.IM↗

arXiv2024

Supervised Radio Frequency Interference Detection with SNNs

Radio Frequency Interference (RFI) poses a significant challenge in radio astronomy, arising from terrestrial and celestial sources, disrupting observations conducted by radio telescopes. Addressing RFI involves intricate heuristic algorithms, manual examination, and, increasingly, machine learning methods. Given the dynamic and temporal nature of radio astronomy observations, Spiking Neural Networks (SNNs) emerge as a promising approach. In this study, we cast RFI detection as a supervised multi-variate time-series segmentation problem. Notably, our investigation explores the encoding of radio astronomy visibility data for SNN inference, considering six encoding schemes: rate, latency, delta-modulation, and three variations of the step-forward algorithm. We train a small twolayer fully connected SNN on simulated data derived from the Hydrogen Epoch of Reionization Array (HERA) telescope and perform extensive hyper-parameter optimization. Results reveal that latency encoding exhibits superior performance, achieving a per-pixel accuracy of 98.8% and an f1-score of 0.761. Remarkably, these metrics approach those of contemporary RFI detection algorithms, notwithstanding the simplicity and compactness of our proposed network architecture. This study underscores the potential of RFI detection as a benchmark problem for SNN researchers, emphasizing the efficacy of SNNs in addressing complex time-series segmentation tasks in radio astronomy.

cs.NE↗

arXiv2024

DEVILS/MIGHTEE/GAMA/DINGO: The Impact of SFR Timescales on the SFR-Radio Luminosity Correlation

The tight relationship between infrared luminosity (L$_\mathrm{TIR}$) and 1.4 GHz radio continuum luminosity (L$_\mathrm{1.4GHz}$) has proven useful for understanding star formation free from dust obscuration. Infrared emission in star-forming galaxies typically arises from recently formed, dust-enshrouded stars, whereas radio synchrotron emission is expected from subsequent supernovae. By leveraging the wealth of ancillary far-ultraviolet - far-infrared photometry from the Deep Extragalactic VIsible Legacy Survey (DEVILS) and Galaxy and Mass Assembly (GAMA) surveys, combined with 1.4 GHz observations from the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) survey and Deep Investigation of Neutral Gas Origins (DINGO) projects, we investigate the impact of timescale differences between far-ultraviolet - far-infrared and radio-derived star formation rate (SFR) tracers. We examine how the SED-derived star formation histories (SFH) of galaxies can be used to explain discrepancies in these SFR tracers, which are sensitive to different timescales. Galaxies exhibiting an increasing SFH have systematically higher L$_\mathrm{TIR}$ and SED-derived SFRs than predicted from their 1.4 GHz radio luminosity. This indicates that insufficient time has passed for subsequent supernovae-driven radio emission to accumulate. We show that backtracking the SFR(t) of galaxies along their SED-derived SFHs to a time several hundred megayears prior to their observed epoch will both linearise the SFR-L$_\mathrm{1.4GHz}$ relation and reduce the overall scatter. The minimum scatter in the SFR(t)-L$_\mathrm{1.4GHz}$ is reached at 200 - 300 Myr prior, consistent with theoretical predictions for the timescales required to disperse the cosmic ray electrons responsible for the synchrotron emission.

astro-ph.GA↗

arXiv2024

RFI Detection with Spiking Neural Networks

Detecting and mitigating Radio Frequency Interference (RFI) is critical for enabling and maximising the scientific output of radio telescopes. The emergence of machine learning methods has led to their application in radio astronomy, and in RFI detection. Spiking Neural Networks (SNNs), inspired by biological systems, are well-suited for processing spatio-temporal data. This study introduces the first exploratory application of SNNs to an astronomical data-processing task, specifically RFI detection. We adapt the nearest-latent-neighbours (NLN) algorithm and auto-encoder architecture proposed by previous authors to SNN execution by direct ANN2SNN conversion, enabling simplified downstream RFI detection by sampling the naturally varying latent space from the internal spiking neurons. Our subsequent evaluation aims to determine whether SNNs are viable for future RFI detection schemes. We evaluate detection performance with the simulated HERA telescope and hand-labelled LOFAR observation dataset the original authors provided. We additionally evaluate detection performance with a new MeerKAT-inspired simulation dataset that provides a technical challenge for machine-learnt RFI detection methods. This dataset focuses on satellite-based RFI, an increasingly important class of RFI and is an additional contribution. Our approach remains competitive with existing methods in AUROC, AUPRC and F1 scores for the HERA dataset but exhibits difficulty in the LOFAR and Tabascal datasets. Our method maintains this accuracy while completely removing the compute and memory-intense latent sampling step found in NLN. This work demonstrates the viability of SNNs as a promising avenue for machine-learning-based RFI detection in radio telescopes by establishing a minimal performance baseline on traditional and nascent satellite-based RFI sources and is the first work to our knowledge to apply SNNs in astronomy.

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arXiv2023

Radio Astronomy with Multiband Receivers and Frequency Phase Transfer: Scientific Perspectives

The technique of frequency phase transfer (FPT), enabled by multiband receivers with shared optical path (SOP), is set to become a true backbone of VLBI operations at frequencies above 22 GHz. The FPT has been successfully implemented at the Korean VLBI Network (KVN), while gaining ever more prominent attention worldwide. Over the next few years, FPT VLBI at 22/43/86 GHz will become feasible at more than ten telescopes in Eurasia and Australia. This development would bring order of magnitude improvements of sensitivity and dynamic range of VLBI imaging at 86 GHz and deliver astrometric measurements with an accuracy of one microsecond of arc. The resulting exceptional discovery potential would strongly impact a number of scientific fields ranging from fundamental cosmology and black hole physics to stellar astrophysics and studies of transient phenomena. It is now the right moment for establishing a Science Working Group and a Technical Working Group for FPT VLBI in order to actively focus and coordinate the relevant activities at all stakeholder institutes and ultimately to realize the first global FPT VLBI instrument operating at 22/43/86 GHz.

astro-ph.IM↗

arXiv2023

Inverse MultiView II: Microarcsecond Trigonometric Parallaxes for Southern Hemisphere 6.7~GHz Methanol Masers G232.62+00.99 and G323.74$-$00.26

We present the first results from the Southern Hemisphere Parallax Interferometric Radio Astrometry Legacy Survey (\spirals): $10μ$as-accurate parallaxes and proper motions for two southern hemisphere 6.7 GHz methanol masers obtained using the inverse MultiView calibration method. Using an array of radio telescopes in Australia and New Zealand, we measured the trigonometric parallax and proper motions for the masers associated with the star formation region G232.62+00.99 of $π= 0.610\pm0.011$~mas, $μ_x=-2.266\pm0.021$~mas~y$^{-1}$ and $μ_y=2.249\pm0.049$~mas~y$^{-1}$, which implies its distance to be $d=1.637\pm0.029$~kpc. These measurements represent an improvement in accuracy by more than a factor of 3 over the previous measurements obtained through Very Long Baseline Array observations of the 12~GHz methanol masers associated with this region. We also measure the trigonometric parallax and proper motion for G323.74--00.26 as $π= 0.364\pm0.009$~mas, $μ_x=-3.239\pm0.025$~mas~y$^{-1}$ and $μ_y=-3.976\pm0.039$~mas~y$^{-1}$, which implies a distance of $d=2.747\pm0.068$~kpc. These are the most accurate measurements of trigonometric parallax obtained for 6.7~GHz class II methanol masers to date. We confirm that G232.62+00.99 is in the Local arm and find that G323.74--00.26 is in the Scutum-Centaurus arm. We also investigate the structure and internal dynamics of both masers.

astro-ph.GA↗

arXiv2023

The Readiness of EVN Telescopes for the SKA-VLBI Era

The application of VLBI to scientific problems has undergone a relentless expansion since its conception, yet the potential for further expansion is still large. We are on the cusp of revolutionary progress given the arrival of a host of next-generation instruments. Over the last few years the community has been working hard to ensure the SKA design includes the capability to enable multiple simultaneous tied-array beams, which is a crucial technology to deliver ultra-precise astrometry and improve survey speed capabilities. However, to reach the full potential requires that the network of antennas is upgraded to match the SKA capabilities. We identify multiple-pixel technology, on large telescopes and connected arrays, as a crucial missing component and here will make recommendations for the upgrade path of the partner EVN (and other network) telescopes. Our feasibility studies on SKA-VLBI suggest an order of magnitude improvement in the precision and also in the frequency range at which astrometry can be performed today, if the full network has the required capabilities.

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arXiv2023

Key Science Goals for the Next-Generation Event Horizon Telescope

The Event Horizon Telescope (EHT) has led to the first images of a supermassive black hole, revealing the central compact objects in the elliptical galaxy M87 and the Milky Way. Proposed upgrades to this array through the next-generation EHT (ngEHT) program would sharply improve the angular resolution, dynamic range, and temporal coverage of the existing EHT observations. These improvements will uniquely enable a wealth of transformative new discoveries related to black hole science, extending from event-horizon-scale studies of strong gravity to studies of explosive transients to the cosmological growth and influence of supermassive black holes. Here, we present the key science goals for the ngEHT and their associated instrument requirements, both of which have been formulated through a multi-year international effort involving hundreds of scientists worldwide.

astro-ph.HE↗

arXiv2023

A Bibliometric Review of Neuromorphic Computing and Spiking Neural Networks

Neuromorphic computing and spiking neural networks aim to leverage biological inspiration to achieve greater energy efficiency and computational power beyond traditional von Neumann architectured machines. In particular, spiking neural networks hold the potential to advance artificial intelligence as the basis of third-generation neural networks. Aided by developments in memristive and compute-in-memory technologies, neuromorphic computing hardware is transitioning from laboratory prototype devices to commercial chipsets; ushering in an era of low-power computing. As a nexus of biological, computing, and material sciences, the literature surrounding these concepts is vast, varied, and somewhat distinct from artificial neural network sources. This article uses bibliometric analysis to survey the last 22 years of literature, seeking to establish trends in publication and citation volumes (III-A); analyze impactful authors, journals and institutions (III-B); generate an introductory reading list (III-C); survey collaborations between countries, institutes and authors (III-D), and to analyze changes in research topics over the years (III-E). We analyze literature data from the Clarivate Web of Science using standard bibliometric methods. By briefly introducing the most impactful literature in this field from the last two decades, we encourage AI practitioners and researchers to look beyond contemporary technologies toward a potentially spiking future of computing.

cs.NE↗

arXiv2023

The Transformational Power of Frequency Phase Transfer Methods for ngEHT

(Sub) mm VLBI observations are strongly hindered by limited sensitivity, with the fast tropospheric fluctuations being the dominant culprit. We predict great benefits from applying next-generation frequency phase transfer calibration techniques for the next generation Event Horizon Telescope, using simultaneous multi-frequency observations. We present comparative simulation studies to characterise its performance, the optimum configurations, and highlight the benefits of including observations at 85\,GHz along with the 230 and 340\,GHz bands. The results show a transformational impact on the ngEHT array capabilities, with orders of magnitude improved sensitivity, observations routinely possible over the whole year, and ability to carry out micro-arcsecond astrometry measurements at the highest frequencies, amongst others. This will enable the addressing of a host of innovative open scientific questions in astrophysics. We present a solution for highly scatter-broadened sources such as SgrA*, a prime ngEHT target. We conclude that adding the 85\,GHz band provides a pathway to an optimum and robust performance for ngEHT in sub-millimeter VLBI, and strongly recommmend its inclusion in the simultaneous multi-frequency receiver design.

astro-ph.IM↗

arXiv2023

Inverse Multview I: Multi-Calibrator inverse phase referencing for Microarcsecond VLBI Astrometry

Very Long Baseline Interferometry (VLBI) astrometry is a well established technique for achieving $\pm10~μ$as parallax accuracies at frequencies well above 10~GHz. At lower frequencies, uncompensated interferometer delays associated with the ionosphere play the dominant role in limiting the astrometric accuracy. Multiview is a novel VLBI calibration method, which uses observations of multiple quasars to accurately model and remove time-variable, directional-dependent changes to the interferometer delay. Here we extend the Multiview technique by phase referencing data to the target source ("inverse Multiview") and test its performance. Multiple observations with a four-antenna VLBI array operating at 8.3~GHz show single-epoch astrometric accuracies near $20~μ$as for target-reference quasar separations up to about 7 degrees. This represents an improvement in astrometric accuracy by up to an order of magnitude compared to standard phase referencing.

astro-ph.IM↗

arXiv2023

Enabling Transformational ngEHT Science via the Inclusion of 86 GHz Capabilities

We present a case for significantly enhancing the utility and efficiency of the ngEHT by incorporating an additional 86 GHz observing band. In contrast to 230 or 345 GHz, weather conditions at the ngEHT sites are reliably good enough for 86 GHz to enable year-round observations. Multi-frequency imaging that incorporates 86 GHz observations would sufficiently augment the ($u,v$) coverage at 230 and 345 GHz to permit detection of the M87 jet structure without requiring EHT stations to join the array. The general calibration and sensitivity of the ngEHT would also be enhanced by leveraging frequency phase transfer techniques, whereby simultaneous observations at 86 GHz and higher-frequency bands have the potential to increase the effective coherence times from a few seconds to tens of minutes. When observation at the higher frequencies is not possible, there are opportunities for standalone 86 GHz science, such as studies of black hole jets and spectral lines. Finally, the addition of 86 GHz capabilities to the ngEHT would enable it to integrate into a community of other VLBI facilities $-$ such as the GMVA and ngVLA $-$ that are expected to operate at 86 GHz but not at the higher ngEHT observing frequencies.

astro-ph.IM↗

arXiv2022

Applications of the source-frequency phase-referencing technique for ngEHT observations

The source-frequency phase-referencing (SFPR) technique has been demonstrated to have great advantages for mm-VLBI observations. By implementing simultaneous multi-frequency receiving systems on the next generation Event Horizon Telescope (ngEHT) antennas, it is feasible to carry out a frequency phase transfer (FPT) which could calibrate the non-dispersive propagation errors and significantly increase the phase coherence in the visibility data. Such increase offers an efficient approach for weak source or structure detection. SFPR also makes it possible for high precision astrometry, including the core-shift measurements up to sub-mm wavelengths for Sgr A* and M87* etc. We also briefly discuss the technical and scheduling considerations for future SFPR observations with the ngEHT.

astro-ph.IM↗

arXiv2022

Feed rotation corrections for antennas having beam waveguide mounts

We report on the development of new code to support the beam waveguide antenna mount types in AIPS, which will allow polarisation analysis of observations made using these antennas. Beam Wave-guide antennas in VLBI are common in communication antennas that have been repurposed (e.g. Warkworth, Yamaguchi). The mount type affects the differential phase between the left and the right hand circular polarisations (LHC and RHC) for different points on the sky. We demonstrate that the corrections for the Warkworth beam wave guide antenna can be applied.

astro-ph.IM↗

arXiv2022

Deep Investigation of Neutral Gas Origins (DINGO): HI stacking experiments with early science data

We present early science results from Deep Investigation of Neutral Gas Origins (DINGO), an HI survey using the Australian Square Kilometre Array Pathfinder (ASKAP). Using ASKAP sub-arrays available during its commissioning phase, DINGO early science data were taken over $\sim$ 60 deg$^{2}$ of the Galaxy And Mass Assembly (GAMA) 23 h region with 35.5 hr integration time. We make direct detections of six known and one new sources at $z < 0.01$. Using HI spectral stacking, we investigate the HI gas content of galaxies at $0.04 < z< 0.09$ for different galaxy colours. The results show that galaxy morphology based on optical colour is strongly linked to HI gas properties. To examine environmental impacts on the HI gas content of galaxies, three sub-samples are made based on the GAMA group catalogue. The average HI mass of group central galaxies is larger than those of satellite and isolated galaxies, but with a lower HI gas fraction. We derive a variety of HI scaling relations for physical properties of our sample, including stellar mass, stellar mass surface density, $NUV-r$ colour, specific star formation rate, and halo mass. We find that the derived HI scaling relations are comparable to other published results, with consistent trends also observed to $\sim$0.5 dex lower limits in stellar mass and stellar surface density. The cosmic HI densities derived from our data are consistent with other published values at similar redshifts. DINGO early science highlights the power of HI spectral stacking techniques with ASKAP.

astro-ph.GA↗

arXiv2022

Sciences with Thai National Radio Telescope

This White Paper summarises potential key science topics to be achieved with Thai National Radio Telescope (TNRT). The commissioning phase has started in mid 2022. The key science topics consist of "Pulsars and Fast Radio Bursts (FRBs)", "Star Forming Regions (SFRs)", "Galaxy and Active Galactic Nuclei (AGNs)", "Evolved Stars", "Radio Emission of Chemically Peculiar (CP) Stars", and "Geodesy", covering a wide range of observing frequencies in L/C/X/Ku/K/Q/W-bands (1-115 GHz). As a single-dish instrument, TNRT is a perfect tool to explore time domain astronomy with its agile observing systems and flexible operation. Due to its ideal geographical location, TNRT will significantly enhance Very Long Baseline Interferometry (VLBI) arrays, such as East Asian VLBI Network (EAVN), Australia Long Baseline Array (LBA), European VLBI Network (EVN), in particular via providing a unique coverage of the sky resulting in a better complete "uv" coverage, improving synthesized-beam and imaging quality with reducing side-lobes. This document highlights key science topics achievable with TNRT in single-dish mode and in collaboration with VLBI arrays.

astro-ph.IM↗

arXiv2022

The Astrometric Animation of Water Masers towards the Mira Variable BX Cam

We report VLBI monitoring observations of the 22 GHz water (H$_{2}$O) masers around the Mira variable BX Cam, which were carried out as a part of the EAVN Synthesis of Stellar Maser Animations (ESTEMA) project. Data of 37 epochs in total were obtained from 2018 May to 2021 June with a time interval of 3-4 weeks, spanning approximately three stellar pulsation periods ($P= \sim$440 d). In particular, the dual-beam system equipped on the VERA stations was used to measure the kinematics and parallaxes of the H$_{2}$O maser features. The measured parallax, $π=1.79\pm 0.08$ mas, is consistent with $Gaia$ EDR3 and previously measured VLBI parallaxes within a 1-$σ$ error level. The position of the central star was estimated, based on both the $Gaia$ EDR3 data and the center position of the ring-like 43 GHz silicon-monoxide (SiO) maser distribution imaged with the KVN. The three-dimensional H$_{2}$O maser kinematics indicates that the circumstellar envelope is expanding at a velocity of $13\pm4$ km s$^{-1}$, while there are asymmetries in both the spatial and velocity distributions of the maser features. Furthermore, the H$_{2}$O maser animation achieved by our dense monitoring program manifests the propagation of shock waves in the circumstellar envelope of BX Cam.

astro-ph.SR↗

arXiv2022

Radio Transient Detection with Closure Products and Machine Learning

For transient sources with timescales of 1-100 seconds, standardized imaging for all observations at each time step become impossible as large modern interferometers produce significantly large data volumes in this observation time frame. Here we propose a method based on machine learning and using interferometric closure products as input features to detect transient source candidates directly from the spatial frequency domain without imaging. We train a simple neural network classifier on a synthetic dataset of Noise/Transient/RFI events, which we construct to tackle the lack of labelled data. We also use the hyper-parameter dropout rate of the model to allow the model to approximate Bayesian inference, and select the optimal dropout rate to match the posterior prediction to the actual underlying probability distribution of the detected events. The overall F1-score of the classifier on the simulated dataset is greater than 85\%, with the signal-to-noise at 7$σ$. The performance of the trained neural network with Monte Carlo dropout is evaluated on semi-real data, which includes a simulated transient source and real noise. This classifier accurately identifies the presence of transient signals in the detectable signal-to-noise levels (above 4$σ$) with the optimal variance. Our findings suggest that a feasible radio transient classifier can be built up with only simulated data for applying to the prediction of real observation, even in the absence of annotated real samples for the purpose of training.

astro-ph.IM↗