Related papers: SPINN: a straightforward machine learning solution…
Pulsar candidate sifting is an essential process for discovering new pulsars. It aims to search for the most promising pulsar candidates from an all-sky survey, such as High Time Resolution Universe (HTRU), Green Bank Northern Celestial Cap…
We present 75 pulsars discovered in the mid-latitude portion of the High Time Resolution Universe survey, 54 of which have full timing solutions. All the pulsars have spin periods greater than 100 ms, and none of those with timing solutions…
Pulsar searching with next-generation radio telescopes requires efficiently sifting through millions of candidates generated by search pipelines to identify the most promising ones. This challenge has motivated the utilization of Artificial…
The High Time Resolution Universe (HTRU) survey is an all-sky survey looking for pulsars and other radio transients. A new single-pulse (SP) search pipeline is presented, tailored to the northern part of the HTRU survey collected with the…
We present the results of processing an additional 44% of the High Time Resolution Universe South Low Latitude (HTRU-S LowLat) pulsar survey, the most sensitive blind pulsar survey of the southern Galactic plane to date. Our…
We have conducted a GPU accelerated reprocessing of $\sim 87\%$ of the archival data from the High Time Resolution Universe South Low Latitude (HTRU-S LowLat) pulsar survey by implementing a pulsar search pipeline that was previously used…
Modern radio pulsar surveys produce a large volume of prospective candidates, the majority of which are polluted by human-created radio frequency interference or other forms of noise. Typically, large numbers of candidates need to be…
Pulsar search is always the basis of pulsar navigation, gravitational wave detection and other research topics. Currently, the volume of pulsar candidates collected by Five-hundred-meter Aperture Spherical radio Telescope (FAST) shows an…
Pulsar search with time-domain observation is very computationally expensive and data volume will be enormous with the next generation telescopes such as the Square Kilometre Array. We apply artificial neural networks (ANNs), a machine…
We introduce a class of Sparse, Physics-based, and partially Interpretable Neural Networks (SPINN) for solving ordinary and partial differential equations (PDEs). By reinterpreting a traditional meshless representation of solutions of PDEs…
Pulsar searching is essential for the scientific research in the field of physics and astrophysics. As the development of the radio telescope, the exploding volume and it growth speed of candidates growth have brought about several…
We report on the discovery of four millisecond pulsars (MSPs) in the High Time Resolution Universe (HTRU) pulsar survey being conducted at the Parkes 64-m radio telescope. All four MSPs are in binary systems and are likely to have white…
We present initial results from the low-latitude Galactic plane region of the High Time Resolution Universe pulsar survey conducted at the Parkes 64-m radio telescope. We discuss the computational challenges arising from the processing of…
The Commensal Radio Astronomy Five-hundred-meter Aperture Spherical radio Telescope (FAST) Survey (CRAFTS) utilizes the novel drift-scan commensal survey mode of FAST and can generate billions of pulsar candidate signals. The human experts…
In this paper, we present a novel artificial intelligence (AI) program that identifies pulsars from recent surveys using image pattern recognition with deep neural nets---the PICS (Pulsar Image-based Classification System) AI. The AI mimics…
We propose a pulsar candidate cross matching algorithm to sift radio pulsar search candidates from repeated observations of the same sky location such as globular clusters, high energy sources, or supernova remnants. Our method uses both…
As a typical application of deep learning, physics-informed neural network (PINN) {has been} successfully used to find numerical solutions of partial differential equations (PDEs), but how to improve the limited accuracy is still a great…
As performance of dedicated facilities continually improved, massive pulsar candidates are being received, which makes selecting valuable pulsar signals from candidates challenging. In this paper, we designed a deep convolutional neural…
Improving survey specifications are causing an exponential rise in pulsar candidate numbers and data volumes. We study the candidate filters used to mitigate these problems during the past fifty years. We find that some existing methods…
The SKA pulsar search pipeline will be used for real time detection of pulsars. Modern radio telescopes such as SKA will be generating petabytes of data in their full scale of operation. Hence experience-based and data-driven algorithms…