Engineering topics

Dartez, L. P.

Publications and source records attributed to Dartez, L. P..

3 records

DOE OSTI2019

The Green Bank North Celestial Cap Pulsar Survey. IV. Four New Timing Solutions

Here, we observe timing solutions for four pulsars discovered in the Green Bank Northern Celestial Cap survey. All four pulsars are isolated with spin periods between 0.26 and 1.84 s. PSR J0038₋2501 has a 0.26 s period and a period derivative of 7.6 × 10 ₋19 s s ₋1 , which is unusually low for isolated pulsars with similar periods. This low period derivative may be simply an extreme value for an isolated pulsar or it could indicate an unusual evolution path for PSR J0038₋2501, such as a disrupted recycled pulsar from a binary system or an orphaned central compact object (CCO). Correcting the observed spin-down rate for the Shklovskii effect suggests that this pulsar may have an unusually low space velocity, which is consistent with expectations for DRPs. There is no X-ray emission detected from PSR J0038₋2501 in an archival Swift observation, which suggests that it is not a young orphaned CCO. The high dispersion measure of PSR J1949+3426 suggests a distance of 12.3 kpc. This distance suggests that PSR J1949+3426 is among the most distant 7% of Galactic field pulsars, and is one of the most luminous pulsars.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

The green bank northern celestial cap pulsar survey. I. Survey description, data analysis, and initial results

We describe an ongoing search for pulsars and dispersed pulses of radio emission, such as those from rotating radio transients (RRATs) and fast radio bursts, at 350 MHz using the Green Bank Telescope. With the Green Bank Ultimate Pulsar Processing Instrument, we record 100 MHz of bandwidth divided into 4096 channels every 81.92 μs. This survey will cover the entire sky visible to the Green Bank Telescope (δ > –40°, or 82% of the sky) and outside of the Galactic Plane will be sensitive enough to detect slow pulsars and low dispersion measure (<30 pc cm{sup –3}) millisecond pulsars (MSPs) with a 0.08 duty cycle down to 1.1 mJy. For pulsars with a spectral index of –1.6, we will be 2.5 times more sensitive than previous and ongoing surveys over much of our survey region. Here we describe the survey, the data analysis pipeline, initial discovery parameters for 62 pulsars, and timing solutions for 5 new pulsars. PSR J0214+5222 is an MSP in a long-period (512 days) orbit and has an optical counterpart identified in archival data. PSR J0636+5129 is an MSP in a very short-period (96 minutes) orbit with a very low mass companion (8 M{sub J}). PSR J0645+5158 is an isolated MSP with a timing residual RMS of 500 ns and has been added to pulsar timing array experiments. PSR J1434+7257 is an isolated, intermediate-period pulsar that has been partially recycled. PSR J1816+4510 is an eclipsing MSP in a short-period orbit (8.7 hr) and may have recently completed its spin-up phase.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Searching for pulsars using image pattern recognition

In the modern era of big data, many fields of astronomy are generating huge volumes of data, the analysis of which can sometimes be the limiting factor in research. Fortunately, computer scientists have developed powerful data-mining techniques that can be applied to various fields. In this paper, we present a novel artificial intelligence (AI) program that identifies pulsars from recent surveys by using image pattern recognition with deep neural nets—the PICS (Pulsar Image-based Classification System) AI. The AI mimics human experts and distinguishes pulsars from noise and interference by looking for patterns from candidate plots. Different from other pulsar selection programs that search for expected patterns, the PICS AI is taught the salient features of different pulsars from a set of human-labeled candidates through machine learning. The training candidates are collected from the Pulsar Arecibo L-band Feed Array (PALFA) survey. The information from each pulsar candidate is synthesized in four diagnostic plots, which consist of image data with up to thousands of pixels. The AI takes these data from each candidate as its input and uses thousands of such candidates to train its ∼9000 neurons. The deep neural networks in this AI system grant it superior ability to recognize various types of pulsars as well as their harmonic signals. The trained AI's performance has been validated with a large set of candidates from a different pulsar survey, the Green Bank North Celestial Cap survey. In this completely independent test, the PICS ranked 264 out of 277 pulsar-related candidates, including all 56 previously known pulsars and 208 of their harmonics, in the top 961 (1%) of 90,008 test candidates, missing only 13 harmonics. The first non-pulsar candidate appears at rank 187, following 45 pulsars and 141 harmonics. In other words, 100% of the pulsars were ranked in the top 1% of all candidates, while 80% were ranked higher than any noise or interference. The performance of this system can be improved over time as more training data are accumulated. This AI system has been integrated into the PALFA survey pipeline and has discovered six new pulsars to date.

79 ASTRONOMY AND ASTROPHYSICS↗