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Majid, Walid A.

Publications and source records attributed to Majid, Walid A..

9 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

POST-OUTBURST RADIO OBSERVATIONS OF THE HIGH MAGNETIC FIELD PULSAR PSR J1119-6127

We have carried out high-frequency radio observations of the high magnetic field pulsar PSR J1119-6127 following its recent X-ray outburst. While initial observations showed no evidence of significant radio emission, subsequent observations detected pulsed emission across a large frequency band. In this Letter, we report on the initial disappearance of the pulsed emission and its prompt reactivation and dramatic evolution over several months of observation. The periodic pulse profile at S -band (2.3 GHz) after reactivation exhibits a multi-component emission structure, while the simultaneous X -band (8.4 GHz) profile shows a single emission peak. Single pulses were also detected at S -band near the main emission peaks. We present measurements of the spectral index across a wide frequency bandwidth, which captures the underlying changes in the radio emission profile of the neutron star. The high-frequency radio detection, unusual emission profile, and observed variability suggest similarities with magnetars, which may independently link the high-energy outbursts to magnetar-like behavior.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

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 in duration, such as fast radio bursts (FRBs). We use all V-FASTR data through 2015 February to report V-FASTR’s upper limits on the rates of FRBs, and compare these with rederived rates from Parkes FRB detection experiments. V-FASTR’s operation at λ=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)∝S{sup 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{sub 20 cm}{sup 4 cm}<5.8 and α{sub 90 cm}{sup 20 cm}>−7.6, where fluence F∝f{sup α} if we assume that the burst rate reported by Champion et al. of R(F∼0.6 Jy ms)=7×10{sup 3} sky{sup −1} day{sup −1} is accurate (for bursts of ∼3 ms duration). This upper limit on α suggests that if FRBs are extragalactic but noncosmological, on average they are not experiencing excessive free–free absorption due to a medium with high optical depth (assuming temperature ∼8000 K), which excessively inverts 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.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

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 incorporate beam shape, frequency effects, scattering effects, and detection efficiency into the metric. We then demonstrate a method for combining independent data sets 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 Allen Telescope Array 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.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2011

Semi-Supervised Novelty Detection with Adaptive Eigenbases, and Application to Radio Transients

We present a semi-supervised online method for novelty detection and evaluate its performance for radio astronomy time series data. Our approach uses adaptive eigenbases to combine 1) prior knowledge about uninteresting signals with 2) online estimation of the current data properties to enable highly sensitive and precise detection of novel signals. We apply the method to the problem of detecting fast transient radio anomalies and compare it to current alternative algorithms. Tests based on observations from the Parkes Multibeam Survey show both effective detection of interesting rare events and robustness to known false alarm anomalies.

anomaly detection↗
NASA NTRS2011

Multiple-Beam Detection of Fast Transient Radio Sources

A method has been designed for using multiple independent stations to discriminate fast transient radio sources from local anomalies, such as antenna noise or radio frequency interference (RFI). This can improve the sensitivity of incoherent detection for geographically separated stations such as the very long baseline array (VLBA), the future square kilometer array (SKA), or any other coincident observations by multiple separated receivers. The transients are short, broadband pulses of radio energy, often just a few milliseconds long, emitted by a variety of exotic astronomical phenomena. They generally represent rare, high-energy events making them of great scientific value. For RFI-robust adaptive detection of transients, using multiple stations, a family of algorithms has been developed. The technique exploits the fact that the separated stations constitute statistically independent samples of the target. This can be used to adaptively ignore RFI events for superior sensitivity. If the antenna signals are independent and identically distributed (IID), then RFI events are simply outlier data points that can be removed through robust estimation such as a trimmed or Winsorized estimator. The alternative "trimmed" estimator is considered, which excises the strongest n signals from the list of short-beamed intensities. Because local RFI is independent at each antenna, this interference is unlikely to occur at many antennas on the same step. Trimming the strongest signals provides robustness to RFI that can theoretically outperform even the detection performance of the same number of antennas at a single site. This algorithm requires sorting the signals at each time step and dispersion measure, an operation that is computationally tractable for existing array sizes. An alternative uses the various stations to form an ensemble estimate of the conditional density function (CDF) evaluated at each time step. Both methods outperform standard detection strategies on a test sequence of VLBA data, and both are efficient enough for deployment in real-time, online transient detection applications.

Thompson, David R.↗
NASA NTRS2011

Feature Acquisition with Imbalanced Training Data

This work considers cost-sensitive feature acquisition that attempts to classify a candidate datapoint from incomplete information. In this task, an agent acquires features of the datapoint using one or more costly diagnostic tests, and eventually ascribes a classification label. A cost function describes both the penalties for feature acquisition, as well as misclassification errors. A common solution is a Cost Sensitive Decision Tree (CSDT), a branching sequence of tests with features acquired at interior decision points and class assignment at the leaves. CSDT's can incorporate a wide range of diagnostic tests and can reflect arbitrary cost structures. They are particularly useful for online applications due to their low computational overhead. In this innovation, CSDT's are applied to cost-sensitive feature acquisition where the goal is to recognize very rare or unique phenomena in real time. Example applications from this domain include four areas. In stream processing, one seeks unique events in a real time data stream that is too large to store. In fault protection, a system must adapt quickly to react to anticipated errors by triggering repair activities or follow- up diagnostics. With real-time sensor networks, one seeks to classify unique, new events as they occur. With observational sciences, a new generation of instrumentation seeks unique events through online analysis of large observational datasets. This work presents a solution based on transfer learning principles that permits principled CSDT learning while exploiting any prior knowledge of the designer to correct both between-class and withinclass imbalance. Training examples are adaptively reweighted based on a decomposition of the data attributes. The result is a new, nonparametric representation that matches the anticipated attribute distribution for the target events.

Thompson, David R.↗