57 research outputs found
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 = -1.86 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 = 6.9 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
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
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
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
Multiwavelength Radio Observations of Two Repeating Fast Radio Burst Sources: FRB 121102 and FRB 180916.J0158+65
The spectra of fast radio bursts (FRBs) encode valuable information about the source's local environment, underlying emission mechanism(s), and the intervening media along the line of sight. We present results from a long-term multiwavelength radio monitoring campaign of two repeating FRB sources, FRB 121102 and FRB 180916.J0158+65, with the NASA Deep Space Network (DSN) 70 m radio telescopes (DSS-63 and DSS-14). The observations of FRB 121102 were performed simultaneously at 2.3 and 8.4 GHz, and spanned a total of 27.3 hr between 2019 September 19 and 2020 February 11. We detected two radio bursts in the 2.3 GHz frequency band from FRB 121102, but no evidence of radio emission was found at 8.4 GHz during any of our observations. We observed FRB 180916.J0158+65 simultaneously at 2.3 and 8.4 GHz, and also separately in the 1.5 GHz frequency band, for a total of 101.8 hr between 2019 September 19 and 2020 May 14. Our observations of FRB 180916.J0158+65 spanned multiple activity cycles during which the source was known to be active and covered a wide range of activity phases. Several of our observations occurred during times when bursts were detected from the source between 400 and 800 MHz with the Canadian Hydrogen Intensity Mapping Experiment (CHIME) radio telescope. However, no radio bursts were detected from FRB 180916.J0158+65 at any of the frequencies used during our observations with the DSN radio telescopes. We find that FRB 180916.J0158+65's apparent activity is strongly frequency-dependent due to the narrowband nature of its radio bursts, which have less spectral occupancy at high radio frequencies (≳ 2 GHz). We also find that fewer or fainter bursts are emitted from the source at high radio frequencies. We discuss the implications of these results for possible progenitor models of repeating FRBs
- …