Pulse Morphology of the Galactic Center Magnetar PSR J1745-2900

We present results from observations of the Galactic Center magnetar, PSR J1745-2900, at 2.3 and 8.4 GHz with the NASA Deep Space Network 70 m antenna, DSS-43. We study the magnetar's radio profile shape, flux density, radio spectrum, and single pulse behavior over a ~1 year period between MJDs 57233 and 57621. In particular, the magnetar exhibits a significantly negative average spectral index of $\langle\alpha\rangle$ = -1.86 $\pm$ 0.02 when the 8.4 GHz profile is single-peaked, which flattens considerably when the profile is double-peaked. We have carried out an analysis of single pulses at 8.4 GHz on MJD 57479 and find that giant pulses and pulses with multiple emission components are emitted during a significant number of rotations. The resulting single pulse flux density distribution is incompatible with a log-normal distribution. The typical pulse width of the components is ~1.8 ms, and the prevailing delay time between successive components is ~7.7 ms. Many of the single pulse emission components show significant frequency structure over bandwidths of ~100 MHz, which we believe is the first observation of such behavior from a radio magnetar. We report a characteristic single pulse broadening timescale of $\langle\tau_{d}\rangle$ = 6.9 $\pm$ 0.2 ms at 8.4 GHz. We find that the pulse broadening is highly variable between emission components and cannot be explained by a thin scattering screen at distances $\gtrsim$ 1 kpc. We discuss possible intrinsic and extrinsic mechanisms for the magnetar's emission and compare our results to other magnetars, high magnetic field pulsars, and fast radio bursts.Comment: 18 pages, 12 figures, Accepted for publication in ApJ on 2018 August 30. v2: Updated to match published versio

Observations of Radio Magnetars with the Deep Space Network

The Deep Space Network (DSN) is a worldwide array of radio telescopes that supports NASA's interplanetary spacecraft missions. When the DSN antennas are not communicating with spacecraft, they provide a valuable resource for performing observations of radio magnetars, searches for new pulsars at the Galactic Center, and additional pulsar-related studies. We describe the DSN's capabilities for carrying out these types of observations. We also present results from observations of three radio magnetars, PSR J1745-2900, PSR J1622-4950, and XTE J1810-197, and the transitional magnetar candidate, PSR J1119-6127, using the DSN radio telescopes near Canberra, Australia.Comment: 14 pages, 8 figures, Accepted for publication in Advances in Astronomy on 2019 January 27 (Invited paper for a special issue on magnetars

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

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

Statistical Studies of Giant Pulse Emission from the Crab Pulsar

We have observed the Crab pulsar with the Deep Space Network (DSN) Goldstone 70 m antenna at 1664 MHz during three observing epochs for a total of 4 hours. Our data analysis has detected more than 2500 giant pulses, with flux densities ranging from 0.1 kJy to 150 kJy and pulse widths from 125 ns (limited by our bandwidth) to as long as 100 microseconds, with median power amplitudes and widths of 1 kJy and 2 microseconds respectively. The most energetic pulses in our sample have energy fluxes of approximately 100 kJy-microsecond. We have used this large sample to investigate a number of giant-pulse emission properties in the Crab pulsar, including correlations among pulse flux density, width, energy flux, phase and time of arrival. We present a consistent accounting of the probability distributions and threshold cuts in order to reduce pulse-width biases. The excellent sensitivity obtained has allowed us to probe further into the population of giant pulses. We find that a significant portion, no less than 50%, of the overall pulsed energy flux at our observing frequency is emitted in the form of giant pulses.Comment: 19 pages, 17 figures; to be published in Astrophysical Journa

Observations of Radio Magnetars with the Deep Space Network

The Deep Space Network (DSN) is a worldwide array of radio telescopes which supports NASA’s interplanetary spacecraft missions. When the DSN antennas are not communicating with spacecraft, they provide a valuable resource for performing observations of radio magnetars, searches for new pulsars at the Galactic Center, and additional pulsar-related studies. We describe the DSN’s capabilities for carrying out these types of observations. We also present results from observations of three radio magnetars, PSR J1745–2900, PSR J1622–4950, and XTE J1810–197, and the transitional magnetar candidate, PSR J1119–6127, using the DSN radio telescopes near Canberra, Australia