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Source author record

David R. Thompson

David R. Thompson appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

ResearcherUnclaimed source record
astro-ph.IMastro-ph.COastro-ph.HEApplicationsDistributed, Parallel, and Cluster Computingeess.IVMachine Learningphysics.ao-ph

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Published work

9 published item(s)

preprint2026arXiv

Fully Automatic Trace Gas Plume Detection

Future imaging spectrometers will increase data volumes by orders of magnitude, requiring automated detection of trace gas point sources. We present a fully automated framework that combines machine learning-based morphological analysis with physics-based spectroscopic fitting to detect plumes without human participation. Applied to EMIT imaging spectrometer data, the system operates in two modes: "daily digest" that runs automatically on all downlinked data, flagging the largest events for immediate response, and a retrospective analysis that identifies plumes missed by prior human review. The daily digest demonstrates that a significant fraction of the largest plumes can be detected automatically with negligible false positives, while retrospective analysis suggests at least 25% of plumes may have been overlooked. In addition to the previously observed methane point sources, we extend detection to three understudied trace gases: NH3, NO2 and the first observations of carbon monoxide (CO) plume in EMIT imagery.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Fast and Accurate Retrieval of Methane Concentration from Imaging Spectrometer Data Using Sparsity Prior

The strong radiative forcing by atmospheric methane has stimulated interest in identifying natural and anthropogenic sources of this potent greenhouse gas. Point sources are important targets for quantification, and anthropogenic targets have potential for emissions reduction. Methane point source plume detection and concentration retrieval have been previously demonstrated using data from the Airborne Visible InfraRed Imaging Spectrometer Next Generation (AVIRIS-NG). Current quantitative methods have tradeoffs between computational requirements and retrieval accuracy, creating obstacles for processing real-time data or large datasets from flight campaigns. We present a new computationally efficient algorithm that applies sparsity and an albedo correction to matched filter retrieval of trace gas concentration-pathlength. The new algorithm was tested using AVIRIS-NG data acquired over several point source plumes in Ahmedabad, India. The algorithm was validated using simulated AVIRIS-NG data including synthetic plumes of known methane concentration. Sparsity and albedo correction together reduced the root mean squared error of retrieved methane concentration-pathlength enhancement by 60.7% compared with a previous robust matched filter method. Background noise was reduced by a factor of 2.64. The new algorithm was able to process the entire 300 flightline 2016 AVIRIS-NG India campaign in just over 8 hours on a desktop computer with GPU acceleration.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

A Machine Learning Classifier for Fast Radio Burst Detection at the VLBA

Time domain radio astronomy observing campaigns frequently generate large volumes of data. Our goal is to develop automated methods that can identify events of interest buried within the larger data stream. The V-FASTR fast transient system was designed to detect rare fast radio bursts (FRBs) within data collected by the Very Long Baseline Array. The resulting event candidates constitute a significant burden in terms of subsequent human reviewing time. We have trained and deployed a machine learning classifier that marks each candidate detection as a pulse from a known pulsar, an artifact due to radio frequency interference, or a potential new discovery. The classifier maintains high reliability by restricting its predictions to those with at least 90% confidence. We have also implemented several efficiency and usability improvements to the V-FASTR web-based candidate review system. Overall, we found that time spent reviewing decreased and the fraction of interesting candidates increased. The classifier now classifies (and therefore filters) 80-90% of the candidates, with an accuracy greater than 98%, leaving only the 10-20% most promising candidates to be reviewed by humans.

0 citations0 reviewsNo code linkedOpen access
preprint2016arXiv

Limits on Fast Radio Bursts from Four Years of the V-FASTR Experiment

The V-FASTR experiment on the Very Long Baseline Array was designed to detect dispersed pulses of milliseconds duration, such as fast radio bursts (FRBs). We use all V-FASTR data through February 2015 to report V-FASTR's upper limits on the rates of FRBs, and compare these with re-derived rates from Parkes FRB detection experiments. V-FASTR's operation at lambda=20 cm allows direct comparison with the 20 cm Parkes rate, and we derive a power-law limit of γ<-0.4 (95% confidence limit) on the index of FRB source counts, N(>S)\propto S^γ. Using the previously measured FRB rate and the unprecedented amount of survey time spent searching for FRBs at a large range of wavelengths (0.3 cm > λ> 90 cm), we also place frequency-dependent limits on the spectral distribution of FRBs. The most constraining frequencies place two-point spectral index limits of α_{20cm}^{4cm} < 5.8 and α_{90cm}^{20cm} > -7.6, where fluence F \propto f^αif we assume true the burst rate reported by Champion et al. (2016) of R(F~0.6 Jy ms) = 7 x 10^3 sky^{-1} day^{-1} (for bursts of ~3 ms duration). This upper limit on αsuggests that if FRBs are extragalactic but non-cosmological, that on average they are not experiencing excessive free-free absorption due to a medium with high optical depth (assuming temperature ~8,000 K), which excessively invert their low-frequency spectrum. This in turn implies that the dispersion of FRBs arises in either or both of the intergalactic medium or the host galaxy, rather than from the source itself.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

A framework for interpreting fast radio transients search experiments: application to the V-FASTR experiment

We define a framework for determining constraints on the detection rate of fast transient events from a population of underlying sources, with a view to incorporating beam shape, frequency effects, scattering effects, and detection efficiency into the metric. We then demonstrate a method for combining independent datasets into a single event rate constraint diagram, using a probabilistic approach to the limits on parameter space. We apply this new framework to present the latest results from the V-FASTR experiment, a commensal fast transients search using the Very Long Baseline Array (VLBA). In the 20 cm band, V-FASTR now has the ability to probe the regions of parameter space of importance for the observed Lorimer and Keane fast radio transient candidates, by combining the information from observations with differing bandwidths, and properly accounting for the source dispersion measure, VLBA antenna beam shape, experiment time sampling, and stochastic nature of events. We then apply the framework to combine the results of the V-FASTR and ATA Fly's Eye experiments, demonstrating their complementarity. Expectations for fast transients experiments for the SKA Phase I dish array are then computed, and the impact of large differential bandwidths is discussed.

0 citations0 reviewsNo code linkedOpen access
preprint2013arXiv

Real Time Event Detection in Astronomical Data Streams: Lessons from the VLBA

A new generation of observational science instruments is dramatically increasing collected data volumes in a range of fields. These instruments include the Square Kilometre Array (SKA), Large Synoptic Survey Telescope (LSST), terrestrial sensor networks, and NASA satellites participating in "decadal survey" missions. Their unprecedented coverage and sensitivity will likely reveal wholly new categories of unexpected and transient events. Commensal methods passively analyze these data streams, recognizing anomalous events of scientific interest and reacting in real time. We report on a case example: V-FASTR, an ongoing commensal experiment at the Very Long Baseline Array (VLBA) that uses online adaptive pattern recognition to search for anomalous fast radio transients. V-FASTR triages a millisecond-resolution stream of data and promotes candidate anomalies for further offline analysis. It tunes detection parameters in real time, injecting synthetic events to continually retrain itself for optimum performance. This self-tuning approach retains sensitivity to weak signals while adapting to changing instrument configurations and noise conditions. The system has operated since July 2011, making it the longest-running real time commensal radio transient experiment to date.

0 citations0 reviewsNo code linkedOpen access
preprint2012arXiv

Limits on the event rates of fast radio transients from the V-FASTR experiment

We present the first results from the V-FASTR experiment, a commensal search for fast transient radio bursts using the Very Long Baseline Array (VLBA). V-FASTR is unique in that the widely spaced VLBA antennas provide a discriminant against non-astronomical signals and a mechanism for the localization and identification of events that is not possible with single dishes or short baseline interferometers. Thus far V-FASTR has accumulated over 1300 hours of observation time with the VLBA, between 90 cm and 3 mm wavelength (327 MHz - 86 GHz), providing the first limits on fast transient event rates at high radio frequencies (>1.4 GHz). V-FASTR has blindly detected bright individual pulses from seven known pulsars but has not detected any single-pulse events that would indicate high redshift impulsive bursts of radio emission. At 1.4 GHz, V-FASTR puts limits on fast transient event rates comparable with the PALFA survey at the Arecibo telescope, but generally at lower sensitivities, and comparable to the "fly's eye" survey at the Allen Telescope Array, but with less sky coverage. We also illustrate the likely performance of the Phase 1 SKA dish array for an incoherent fast transient search fashioned on V-FASTR.

0 citations0 reviewsNo code linkedOpen access
preprint2011arXiv

Detection of fast radio transients with multiple stations: a case study using the Very Long Baseline Array

Recent investigations reveal an important new class of transient radio phenomena that occur on sub-millisecond timescales. Often transient surveys' data volumes are too large to archive exhaustively. Instead, an on-line automatic system must excise impulsive interference and detect candidate events in real-time. This work presents a case study using data from multiple geographically distributed stations to perform simultaneous interference excision and transient detection. We present several algorithms that incorporate dedispersed data from multiple sites, and report experiments with a commensal real-time transient detection system on the Very Long Baseline Array (VLBA). We test the system using observations of pulsar B0329+54. The multiple-station algorithms enhanced sensitivity for detection of individual pulses. These strategies could improve detection performance for a future generation of geographically distributed arrays such as the Australian Square Kilometre Array Pathfinder and the Square Kilometre Array.

0 citations0 reviewsNo code linkedOpen access
preprint2011arXiv

V-FASTR: The VLBA Fast Radio Transients Experiment

Recent discoveries of dispersed, non-periodic impulsive radio signals with single-dish radio telescopes have sparked significant interest in exploring the relatively uncharted space of fast transient radio signals. Here we describe V-FASTR, an experiment to perform a blind search for fast transient radio signals using the Very Long Baseline Array (VLBA). The experiment runs entirely in a commensal mode, alongside normal VLBA observations and operations. It is made possible by the features and flexibility of the DiFX software correlator that is used to process VLBA data. Using the VLBA for this type of experiment offers significant advantages over single-dish experiments, including a larger field of view, the ability to easily distinguish local radio-frequency interference from real signals and the possibility to localize detected events on the sky to milliarcsecond accuracy. We describe our software pipeline, which accepts short integration (~ms) spectrometer data from each antenna in real time during correlation and performs an incoherent dedispersion separately for each antenna, over a range of trial dispersion measures. The dedispersed data are processed by a sophisticated detector and candidate events are recorded. At the end of the correlation, small snippets of the raw data at the time of the events are stored for further analysis. We present the results of our event detection pipeline from some test observations of the pulsars B0329+54 and B0531+21 (the Crab pulsar).

0 citations0 reviewsNo code linkedOpen access