![]() 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. The deep neural networks in this AI system grant it superior ability to recognize various more » types of pulsars as well as their harmonic signals. The AI takes these data from each candidate as its input and uses thousands of such candidates to train its ∼9000 neurons. The information from each pulsar candidate is synthesized in four diagnostic plots, which consist of image data with up to thousands of pixels. The training candidates are collected from the Pulsar Arecibo L-band Feed Array (PALFA) survey. 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 AI mimics human experts and distinguishes pulsars from noise and interference by looking for patterns from candidate plots. 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. Fortunately, computer scientists have developed powerful data-mining techniques that can be applied to various fields. This led the Arecibo Telescope to access only a part of the sky with a range of 40 degrees in declination directly overhead the telescope.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. The dish was so large and had to remain fixed on the ground, while the Gregorian dome could move in position with a limited capability. The Arecibo Telescope was one of the primary instruments in pulsar searching, leading to the discovery of many pulsars, including highly stable millisecond pulsars that were ideal for NANOGrav-type sciences. Due to its size, the timing observations of pulsars obtained with the Arecibo Telescope were more sensitive than those with the GBT. Given the enormous collecting area and the extensive observing frequency coverage, from 327 MHz to 10 GHz, with a 2-millimeter surface accuracy, the Arecibo Telescope was the most sensitive radio telescope in the world. The spherical aberration correction was done using its secondary optics in the Gregorian dome. The telescope had a 305-meter diameter spherical primary reflector, the size of 3 football fields, and could illuminate approximately 225 meters at a time. Gordon Telescope at the Arecibo Observatory in Puerto Rico was the second largest radio telescope in the world at the time of its collapse in December 2020. ![]() Roughly 5% of the total observing time of the Green Bank Telescope is reserved for monitoring the pulsars in our array. In addition to providing monthly timing observations of the millisecond pulsars in our array, the Green Bank Telescope is also used to search for possible new additions to our pulsar timing array through the Green Bank North Celestial Cap pulsar survey, among others. National Radio Quiet Zone, in which radio transmissions are regulated to limit the amount of interference that might adversely affect our observations. With its innovative design and location, the Green Bank Telescope can see 85% of the total sky, and is therefore critical to achieve the sky coverage necessary for our project. It also has an unblocked primary mirror, which allows it to detect more radio emission in a comparable time to telescopes with more traditional designs. With a 100 meter by 110 meter section of a 208 meter parabola, it has a reflecting surface of about 11,000 square meters and is thus the largest fully steerable telescope in the world. The Green Bank Telescope is located in Pocahontas County, West Virginia.
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