Search

Searching for periodic non-accelerated signals in the presence of ideal white noise using the fully phase-coherent fast-folding algorithm (FFA) is theoretically established as a more sensitive search method than the fast Fourier transform (FFT) search with incoherent harmonic summing. In this paper, we present a comparison of the performance of an FFA search implementation using RIPTIDE and an FFT search implementation using PRESTO, over a range of signal parameters with white noise and with real telescope noise from the Giant Meterwave Radio Telescope (GMRT) High Resolution Southern Sky (GHRSS) survey with the upgraded GMRT (uGMRT). We find that the FFA search with appropriate de-reddening of the time series performs better than the FFT search with spectral whitening for long-period pulsars under real GHRSS noise conditions. We describe an FFA-search pipeline implemented for the GHRSS survey looking for pulsars over a period of 0.1â€"100 s and up to a dispersion measure of 500 pc cmâˆ'3. We processed GHRSS survey data covering ∼1500 deg2 of the sky with this pipeline. We re-detected 43 known pulsars with a better signal-to-noise ratio in the FFA search than in the FFT search. We also report the discovery of two new pulsars, including a long-period pulsar with a short duty cycle, using this FFA-search pipeline. A population of long-period pulsars with periods of several seconds or higher could help constrain the pulsar death line. [ABSTRACT FROM AUTHOR]

Radio frequency interference (RFI) is a significant challenge faced by today's radio astronomers. While most past efforts were devoted to cleaning the RFI from the data, we develop a novel method for categorizing and cataloguing RFI for forensic purpose. We present a classifier that categorizes RFI into different types based on features extracted using Principal Component Analysis (PCA) and Fourier analysis. The classifier can identify narrowband non-periodic RFI above 2σ, narrowband periodic RFI above 3σ, and wideband impulsive RFI above 5σ with F1 scores [defined as F 1 = (2 · recall  × precision)/(recall + precision)] between 0.87 and 0.91 in simulation. This classifier could be used to identify the sources of RFI as well as to clean RFI contamination (particularly in pulsar search). In the long-term analysis of the categorized RFI, we found a special type of drifting periodic RFI that is detrimental to pulsar search. We also found pieces of evidence of an increased rate of impulsive RFI when the telescope is pointing towards the cities. These results demonstrate this classifier's potential as a forensic tool for RFI environment monitoring of radio telescopes. [ABSTRACT FROM AUTHOR]

We report the independent discovery of PSR J0026-1955 with the Murchison Widefield Array (MWA) in the ongoing Southern-sky MWA Rapid Two-metre pulsar survey. J0026-1955 has a period of ∼1.306 s, a dispersion measure of ∼20.869 pc cmâˆ'3, and a nulling fraction of ∼77%. This pulsar highlights the advantages of the survey's long dwell times (∼80 minutes), which, when fully searched, will be sensitive to the expected population of similarly bright, intermittent pulsars with long nulls. A single-pulse analysis in the MWA's 140â€"170 MHz band also reveals a complex subpulse drifting behavior, including both rapid changes of the drift rate characteristic of mode switching pulsars, as well as a slow, consistent evolution of the drift rate within modes. In some longer drift sequences, interruptions in the otherwise smooth drift rate evolution occur preferentially at a particular phase, typically lasting a few pulses. These properties make this pulsar an ideal test bed for prevailing models of drifting behavior such as the carousel model. [ABSTRACT FROM AUTHOR]

We present the results of an investigation of the giant radio pulse (GRP) generation rate from five radio pulsars (B0301+19, B0950+08, B1112+50, B1133+16, and B1237+25) and anomalous intensity pulse generation rate from B0809+74. All data used were obtained with the Large Phased Array radio telescope at the Pushchino Radio Astronomy Observatory at 111 MHz from 2012 to 2021. In addition to the analysis of the rate of generation of bright pulses, we analyse the distribution of bright pulses in the phase of the pulsar period and search for clusters of bright pulses – several bright pulses emitted in adjacent pulsar periods. It is found that pulsars B0301+19, B1112+50, B1133+16, and B1237+25 demonstrate different generation rates and generation of clusters. Pulsar B1112+50 generates GRP clusters more often than the other pulsars studied. The longest cluster of GRPs containing four single pulses is detected from this pulsar. GRPs from the pulsars studied are distributed along the longitudes of the main components of the average pulses of these pulsars. This distribution is 1.5–2 times narrower than the phase distribution of non-giant pulses. It is found that the distance between the components of the average GRP profile and the distance between the components of the average non-giant profile differ substantially for pulsars with multicomponent average profiles. [ABSTRACT FROM AUTHOR]

Using the MeerKAT radio telescope, a series of observations have been conducted to time the known pulsars and search for new pulsars in the globular cluster NGC 6440. As a result, two pulsars have been discovered, NGC 6440G and NGC 6440H, one of which is isolated and the other a non-eclipsing (at frequencies above 962 MHz) 'Black Widow', with a very low mass companion (M c > 0.006 M⊙). It joins the other binary pulsars discovered so far in this cluster that all have low companion masses (M c < 0.30 M⊙). We present the results of long-term timing solutions obtained using data from both Green Bank and MeerKAT telescopes for these two new pulsars and an analysis of the pulsars NGC 6440C and NGC 6440D. For the isolated pulsar NGC 6440C, we searched for planets using a Markov chain Monte Carlo technique. We find evidence for significant unmodelled variations but they cannot be well modelled as planets nor as part of a power-law red-noise process. Studies of the eclipses of the 'Redback' pulsar NGC 6440D at two different frequency bands reveal a frequency dependence with longer and asymmetric eclipses at lower frequencies (962–1283 MHz). [ABSTRACT FROM AUTHOR]

The observable population of double neutron star (DNS) systems in the Milky Way allow us to understand the nature of supernovae and binary stellar evolution. Until now, all DNS systems in wide orbits (P orb > 1 d) have been found to have orbital eccentricities, e > 0.1. In this paper, we report the discovery of pulsar PSR J1325−6253: a DNS system in a 1.81-d orbit with a surprisingly low eccentricity of just e  = 0.064. Through, 1.4 yr of dedicated timing with the Parkes radio telescope we have been able to measure its rate of advance of periastron, |$\dot{\omega }=0{_{.}^{\circ}}138\pm 0{_{.}^{\circ}}002\, \mathrm{yr}^{-1}$|⁠. If this induced |$\dot{\omega }$| is solely due to general relativity then the total mass of the system is, M sys = 2.57 ± 0.06 M⊙. Assuming an edge-on orbit the minimum companion mass is constrained to be M c, min > 0.98 M⊙ which implies the pulsar mass is M p, max < 1.59 M⊙. Its location in the P– |$\dot{P}$| diagram suggests that, like other DNS systems, PSR J1325−6253 is a recycled pulsar and if its mass is similar to the known examples (>1.3 M⊙), then the companion neutron star is probably less than ∼1.25 M⊙ and the system is inclined at about 50°–60°. The low eccentricity along with the wide orbit of the system strongly favours a formation scenario involving an ultra-stripped supernova explosion. [ABSTRACT FROM AUTHOR]

The document is a notice board from the Journal of the British Astronomical Association, providing information about upcoming meetings and events related to astronomy. It includes details about the National Astronomy Meeting 2024, hosted by the Royal Astronomical Society and the E.A. Milne Centre for Astrophysics. Other events mentioned include a BAA Meeting, a BAA Radio Astronomy Section Webinar, and a conference on John Herschel. The document also provides information on how to join mailing lists and purchase tickets for these events. [Extracted from the article]

A systematic, semi-automated search for pulsar glitches in the first UTMOST public data release is presented. The search is carried out using a hidden Markov model which incorporates both glitches and timing noise into the model of the assumed phase evolution of the pulsar. Glitches are detected through Bayesian model selection between models with and without glitches present with minimal human intervention. Nine glitches are detected among seven objects, all of which have been previously reported. No new glitches were detected. Injection studies are used to place 90 per cent frequentist upper limits on the size of undetected glitches in each of the 282 objects searched. The mean upper limit obtained is |$\Delta f^{90{{\%}}}/f = 1.9 \times 10^{-8}$|⁠ , with a range of |$4.1 \times 10^{-11} \le \Delta f^{90{{\%}}}/f \le 2.7 \times 10^{-7}$|⁠ , assuming step events with no post-glitch recoveries. It is demonstrated that including glitch recovery has a mild effect, in most cases increasing the upper limit by a factor of ≲5 conservatively assuming complete recovery on a time-scale of |$100\ \mathrm{d}$|⁠. [ABSTRACT FROM AUTHOR]

In 1967, then graduate student Jocelyn Bell identified pulsed radio waves signals, which later corroborated observationally the existence of neutron stars. In this paper, we develop a historical-epistemological study about the episode of detection of pulsars, based on narratives written by Jocelyn Bell Burnell and by her advisor, Antony Hewish, and on researches about this topic. In the epistemological analysis, we predominantly consider aspects of the philosophy of science by Thomas Kuhn and Norwood Hanson. The results draw attention to the role of serendipity in a scientific discovery and to the importance of collective work in a period of normal science, which in this case provided new theoretical and observational studies to understand this new astronomical object. We emphasize the discussion of serendipity and chance in the context of science teaching can contribute to demystifying mistaken ideas about this concept, supporting a better understanding of the nature of scientific knowledge. The paper also makes it possible to highlight the role of a woman scientist in an important scientific episode. [ABSTRACT FROM AUTHOR]

A search for pulse signals was carried out in a new sky area included in the monitoring program for the search for pulsars and transients. Processing of several months data recorded in six frequency channels with a total bandwidth of 2.5 MHz showed that, on average, 4 pulses per hour are observed in each of the 24 connected stationary beams. Of these pulses, 18.3% are similar to those of pulsars. They are visible in one or two neighboring beams and have a pronounced dispersion shift, that is, they are recorded first at a high and then at a low frequency, which indicates the possible passage of the signal through the interstellar medium. Almost 68% of such detected pulses belong to six known pulsars with dispersion measures from 9 to 141 pc/cm3, and almost all of the remaining pulses are either noise of an unknown nature or artifacts of the proposed pulse separation technique. An additional study of the selected array of 3650 obvious pulsar pulses revealed 13 pulses belonging to four rotating radio transients (RRATs). Their dispersion measures are in the range of 17–51 pc/cm3. A search for regular (periodic) RRAT emission was carried out using power spectra summed over 121 days. Periodic radiation was not detected, but for two RRATs, upper estimates of the periods were obtained from measurements of the time intervals between pulses. The upper estimates of the integrated flux density of the detected RRATs are in the range 2–4 mJy at the frequency 111 MHz. [ABSTRACT FROM AUTHOR]

The radiation energy of X-ray pulsars is mainly concentrated in the high-energy ray bands, so processing high-energy photon signals is helpful for discovering some young and active pulsars. To quickly and accurately detect effective pulsar signals from a large number of samples within a finite observation time, an automatic identification algorithm for pulsar candidates based on X-ray observations is developed in this paper. First, the autocorrelation operation is used to improve the signal-to-noise ratio of the profile and solve the initial phase misalignment problem. Then, the candidate frequency range is expanded, and the output signal is folded according to these frequencies to obtain a series of profiles. The six statistical features of these profiles are extracted to generate frequency-feature curves. Compared with the traditional epoch folding method, the frequency-feature curves show more consistent characteristics. To improve the classification accuracy, the frequency-feature curves are converted into two-dimensional images, and ConvNets are used for deep feature extraction and classification. A simulation method based on the nonhomogeneous Poisson process is utilized to create the training set, and generative adversarial networks are used for data augmentation to solve the class imbalance problem caused by limited pulsar samples. Finally, the RXTE observation data of PSR B0531+21, PSR B0540-69, and PSR B1509-58 are selected for testing. The experimental results show that the highest recall and precision reached 0.996 and 0.983, respectively. Demonstrating the considerable potential of this method for identifying pulsar candidates based on X-ray observations. [ABSTRACT FROM AUTHOR]

A modern pulsar survey generates a large number of pulsar candidates. Filtering these pulsar candidates in a large astronomical data set is an important step towards discovering new pulsars. In this paper, a novel adaptive boosting algorithm based on deep self normalized neural network (Adaboost-DSNN) is proposed to accurately classify pulsar and non-pulsar signals. To train the proposed method on a highly imbalanced data set, the Synthetic Minority Oversampling TEchnique (SMOTE) was initially employed for balancing the data set. Then, a deep ensemble network combined with a deep self-normalized neural network and adaptive boosting was developed to train and learn the processed pulsar data. The design of the proposed Adaboost-DSNN method significantly reduced the computational time when dealing with large astronomical data sets, while also improving the classification performance. The scaled exponential liner units activation function was used to normalize the data. Considering their neighbour information and the special dropout technique (α-dropout), Adaboost-DSNN displayed good pulsar classification performance, while preserving the data properties across subsequent layers. The proposed Adaboost-DSNN method was tested on the High Time Resolution Universe Survey data sets (HTRU-1 and HTRU-2). According to experimental results, Adaboost-DSNN outperform other state-of-the-art methods with respect to training time and F1-score. The training time of the Adaboost-DSNN model is 10x times faster compared to other models of this kind. [ABSTRACT FROM AUTHOR]

Relativistic binary pulsars orbiting white dwarfs and neutron stars have already provided excellent tests of gravity. However, despite observational efforts, a pulsar orbiting a black hole has remained elusive. One possible explanation is the extreme Doppler smearing caused by the pulsar's orbital motion which changes its apparent spin frequency during an observation. The classical solution to this problem has been to assume a constant acceleration/jerk for the entire observation. However, this assumption breaks down when the observation samples a large fraction of the orbit. This limits the length of search observations, and hence their sensitivity. This provides a strong motivation to develop techniques that can find compact binaries in longer observations. Here, we present a GPU-based radio pulsar search pipeline that can perform a coherent search for binary pulsars by directly searching over three or five Keplerian parameters using the template-bank algorithm. We compare the sensitivity obtained from our pipeline with acceleration and jerk search pipelines for simulated pulsar-stellar-mass black hole binaries and observations of PSR J0737−3039A. We also discuss the computational feasibility of our pipeline for untargeted pulsar surveys and targeted searches. Our benchmarks indicate that circular orbit searches for P-BH binaries with spin-period |$P{_\mathrm{{spin}}} \ge {20}\, \mathrm{m\, s}$| covering the 3–10  T obs regime are feasible for the High Time Resolution Universe pulsar survey. Additionally, an elliptical orbit search in Globular clusters for |$P{_\mathrm{{spin}}} \ge {20}\, \mathrm{m\, s}$| pulsars orbiting intermediate-mass black holes in the 5–10  T obs regime is feasible for observations shorter than 2 h with an eccentricity limit of 0.1. [ABSTRACT FROM AUTHOR]

We report on the latest results of a Parkes multibeam survey for pulsars and dispersed radio bursts in the Large Magellanic Cloud (LMC). We conducted both periodicity and single-pulse searches at a much larger range of trial dispersion measures (DMs) than previously searched. We detected 229 single pulses with signal-to-noise ratio (S/N) > 7 that were classified by the deep-learning network FETCH as being real (with >90% likelihood), of which nine were from the known giant-pulse-emitting pulsar PSR B0540âˆ'69. Two possibly repeating sources were detected with DMs suggesting that they lie within the LMC, but these require confirmation. Only three of the 220 unknown pulses had S/N > 8, and the DM distribution for these detected pulses follows an exponential falloff with increasing DM and does not show any excess of signals at DM values expected for the LMC. These features suggest that the detected pulses are not likely to be real, although they are visually compelling. We also report the discovery of a new pulsar (PSR J0556âˆ'67) in our periodicity search. This pulsar has a spin period of 791 ms, a DM of 71 cmâˆ'3 pc, an estimated 1400 MHz flux density of ∼0.12 mJy, and shows no evidence of binary motion. Future observations may be able to confirm whether any of the weak but promising candidates in our single-pulse and periodicity searches, including our two possible repeaters, are real or not. [ABSTRACT FROM AUTHOR]

In a search for short-time-scale astrophysical transients in time-domain data, radio-frequency interference (RFI) causes both large quantities of false positive candidates and a significant reduction in sensitivity if not correctly mitigated. Here, we propose an algorithm that infers a time-variable frequency channel mask directly from short-duration (∼1 s) data blocks: the method consists of computing a spectral statistic that correlates well with the presence of RFI, and then finding high outliers among the resulting values. For the latter task, we propose an outlier detection algorithm called Inter-Quartile Range Mitigation (IQRM), which is both non-parametric and robust to the presence of a trend in sequential data. The method requires no training and can, in principle, adapt to any telescope and RFI environment; its efficiency is shown on data from both the MeerKAT and Lovell 76-m radio telescopes. IQRM is fast enough to be used in a streaming search and has been integrated into the MeerTRAP real-time transient search pipeline. Open-source python and C++ implementations are also provided. [ABSTRACT FROM AUTHOR]

Fast and accurate identification of pulsar signals is important for X-ray pulsar-based navigation (XNAV). Traditional pulsar signal detection technology based on FFT search and epoch folding (EF) requires a very long time to obtain an appropriate signal-to-noise ratio (SNR) gain, especially for weak pulsar signals with low photon fluxes. This paper proposes an adaptive stochastic resonance (SR) method based on the grey wolf optimizer (GWO) algorithm for fast pulsar identification. The GWO algorithm can optimize the SR parameters to obtain the optimal SR output that matches the input signal. Meanwhile, the initial population of GWO is generated by Chebyshev chaotic maps, which guarantees the diversity of the initial population and enhances the global search capability of GWO. To further improve the performance of SR, we add an extra denoising process, including a high-pass filter and singular value decomposition (SVD) that determines the effective singular components through dispersion entropy (DE), to suppress the noise to a great extent. We use simulation data and Rossi X-ray Timing Explorer (RXTE) observation data to verify the proposed method. The output SNR is greatly improved, and the method can identify pulsars in a short time. The results indicated that the proposed method has great practical value in engineering. Further experiments reveal the importance of SVD, DE and the Chebyshev chaotic map for the algorithm. [ABSTRACT FROM AUTHOR]

Pulsar stars, usually neutron stars, are spherical and compact objects containing a large quantity of mass. Each pulsar star possesses a magnetic field and emits a slightly different pattern of electromagnetic radiation which is used to identify the potential candidates for a real pulsar star. Pulsar stars are considered an important cosmic phenomenon, and scientists use them to study nuclear physics, gravitational waves, and collisions between black holes. Defining the process of automatic detection of pulsar stars can accelerate the study of pulsar stars by scientists. This study contrives an accurate and efficient approach for true pulsar detection using supervised machine learning. For experiments, the high time-resolution (HTRU2) dataset is used in this study. To resolve the data imbalance problem and overcome model overfitting, a hybrid resampling approach is presented in this study. Experiments are performed with imbalanced and balanced datasets using well-known machine learning algorithms. Results demonstrate that the proposed hybrid resampling approach proves highly influential to avoid model overfitting and increase the prediction accuracy. With the proposed hybrid resampling approach, the extra tree classifier achieves a 0.993 accuracy score for true pulsar star prediction. [ABSTRACT FROM AUTHOR]

The high stellar density in the central parsecs around the Galactic Centre makes it a seemingly favourable environment for finding relativistic binary pulsars. These include pulsars orbiting other neutron stars, stellar-mass black holes, or the central supermassive black hole, Sagittarius A*. Here, we present multi-epoch pulsar searches of the Galactic Centre at four observing frequencies, |$4.85,\, 8.35,\, 14.6,\, 18.95\, {\rm GHz}$|⁠ , using the Effelsberg 100-m radio telescope. Observations were conducted 1 yr prior to the discovery of, and during monitoring observations of, the Galactic Centre magnetar PSR J1745−2900. Our data analysis features acceleration searches on progressively shorter time series to maintain sensitivity to relativistic binary pulsars. The multi-epoch observations increase the likelihood of discovering transient or nulling pulsars, or ensure orbital phases are observed at which acceleration search methods work optimally. In |${\sim}147\, {\rm h}$| of separate observations, no previously undiscovered pulsars have been detected. Through calibration observations, we conclude this might be due to insufficient instantaneous sensitivity, caused by the intense continuum emission from the Galactic Centre, its large distance, and, at higher frequencies, the aggregate effect of steep pulsar spectral indices and atmospheric contributions to the system temperature. Additionally, we find that for millisecond pulsars in wide circular orbits |$({\lesssim}800\, {\rm d})$| around Sagittarius A*, linear acceleration effects cannot be fully corrected in deep observations |$(9\, {\rm h})$| with existing software tools. Pulsar searches of the Galactic Centre with the next generation of radio telescopes – such as MeerKat, ngVLA, and SKA1-mid – will have improved chances of uncovering this elusive population. [ABSTRACT FROM AUTHOR]

Large-scale beamforming with radio interferometers has the potential to revolutionize the science done with pulsars and fast radio bursts by improving the survey efficiency for these sources. We describe a wide-field beamformer for the MeerKAT radio telescope and outline strategies to optimally design such surveys. For software implementation of these techniques, Mosaic is introduced and its application in the MeerKAT telescope is presented. We show initial results using the beamformer by observing a globular cluster to track several pulsars simultaneously and demonstrate the source localization capability of this observation. [ABSTRACT FROM AUTHOR]

The search for pulsar (periodic) radiation of five gamma-ray pulsars was carried out using the summed power spectra and summed periodograms. No harmonics corresponding to the known periods of the pulsars were found. An upper estimate was obtained for the integral flux density of pulsars J0357+3205 (<0.5 mJy), J0554+3107 (<0.5 mJy), J1958+2846 (<0.5 mJy), J2021+4026 (<0.4 mJy), and J2055+2539 (<0.55 mJy). [ABSTRACT FROM AUTHOR]

We report on a search for pulsars at the positions of eight low-mass white dwarfs and one higher mass white dwarf with the 100-m Effelsberg Radio Telescope. These systems have orbital parameters suggesting that their unseen companions are either massive white dwarfs or neutron stars (NSs). Our observations were performed at 1.36 GHz, reaching sensitivities of 0.1–0.2 mJy. We searched our data accounting for the possible acceleration and jerk of the pulsar signals due to orbital motion, but found no significant pulsar signals. Considering our result jointly with 20 non-detections of similar systems with the Greenbank Radio Telescope, we infer f NS ≤ 0.10, for the fraction of NSs orbiting these white dwarfs. We discuss the sensitivity of this result to the underlying assumptions and conclude with a brief discussion on the prospects of targeted surveys for discovering millisecond pulsars. [ABSTRACT FROM AUTHOR]

Machine learning methods are increasingly helping astronomers identify new radio pulsars. However, they require a large amount of labelled data, which is time consuming to produce and biased. Here, we describe a Semi-supervised generative adversarial network, which achieves better classification performance than the standard supervised algorithms using majority unlabelled data sets. We achieved an accuracy and mean F-Score of 94.9 per cent trained on only 100 labelled candidates and 5000 unlabelled candidates compared to our standard supervised baseline which scored at 81.1 per cent and 82.7 per cent, respectively. Our final model trained on a much larger labelled data set achieved an accuracy and mean F-score value of 99.2 per cent and a recall rate of 99.7 per cent. This technique allows for high-quality classification during the early stages of pulsar surveys on new instruments when limited labelled data are available. We open-source our work along with a new pulsar-candidate data set produced from the High Time Resolution Universe – South Low Latitude Survey. This data set has the largest number of pulsar detections of any public data set and we hope it will be a valuable tool for benchmarking future machine learning models. [ABSTRACT FROM AUTHOR]

As the next-generation radio astronomical telescopes continuously improve and develop, the pulsar survey will produce millions of pulsar candidates, which pose considerable challenges for pulsar identification and classification. The rapidly evolving artificial intelligence (AI) techniques are being used for pulsar identification and discovery of new pulsars. Using the pulsar data set observed with the Parkes telescope, namely the High Time Resolution Universe Survey (HTRUS), a 14-layer deep residual network has been designed (called the Residual Network, ResNet) for pulsar candidate classifications. In the HTRUS sample data, the number of non-pulsar candidates (i.e., negative samples) is much larger than that of pulsar candidates (i.e., positive samples). The imbalance between the positive and negative samples is prone to result in model misjudgement. By using the over-sampling technique to enhance the data of positive samples in the training set and adjusting the ratio of positive and negative samples, we have solved this imbalance problem. In the training process, the hyperparameters are adjusted by means of 5-fold cross validation to build the model. The test results indicate that the model can achieve a high precision (98%) and recall (100%), the F1-score can reach 99%, and that the implementation of each sample test needs only 7 ms, it has provided a feasible approach for the future big-data analysis of pulsars. [ABSTRACT FROM AUTHOR]

We report on the first pulsar and transient survey of the Galactic Center (GC) with the Atacama Large Millimeter/submillimeter Array (ALMA). The observations were conducted during the Global Millimeter VLBI Array campaign in 2017 and 2018. We carry out searches using time series of both total intensity and other polarization components in the form of Stokes parameters. We incorporate acceleration and its derivative in the pulsar search, and also search in segments of the entire observation to compensate for potential orbital motion of the pulsar. While no new pulsar is found, our observations yield the polarization profile of the GC magnetar PSR J1745−2900 at millimeter wavelength for the first time, which turns out to be nearly 100% linearly polarized. Additionally, we estimate the survey sensitivity placed by both system and red noise, and evaluate its capability of finding pulsars in orbital motion with either Sgr A* or a binary companion. We show that the survey is sensitive to only the most luminous pulsars in the known population and future observations with ALMA in Band-1 will deliver significantly deeper survey sensitivity on the GC pulsar population. [ABSTRACT FROM AUTHOR]

Radio pulsar signals are significantly perturbed by their propagation through the ionized interstellar medium. In addition to the frequency-dependent pulse times of arrival due to dispersion, pulse shapes are also distorted and shifted, having been scattered by the inhomogeneous interstellar plasma, affecting pulse arrival times. Understanding the degree to which scattering affects pulsar timing is important for gravitational-wave detection with pulsar timing arrays (PTAs), which depend on the reliability of pulsars as stable clocks with an uncertainty of ∼100 ns or less over ∼10 yr or more. Scattering can be described as a convolution of the intrinsic pulse shape with an impulse response function representing the effects of multipath propagation. In previous studies, the technique of cyclic spectroscopy has been applied to pulsar signals to deconvolve the effects of scattering from the original emitted signals, increasing the overall timing precision. We present an analysis of simulated data to test the quality of deconvolution using cyclic spectroscopy over a range of parameters characterizing interstellar scattering and pulsar signal-to-noise ratio (S/N). We show that cyclic spectroscopy is most effective for high S/N and/or highly scattered pulsars. We conclude that cyclic spectroscopy could play an important role in scattering correction to distant populations of highly scattered pulsars not currently included in PTAs. For future telescopes and for current instruments such as the Green Bank Telescope upgraded with the ultrawide bandwidth receiver, cyclic spectroscopy could potentially double the number of PTA-quality pulsars. [ABSTRACT FROM AUTHOR]

Highly accurate detection of pulsars is mandatory. With the application of machine learning (ML) algorithms, the detection of pulsars can certainly be improved if the dataset is balanced. In this paper, the publicly available dataset (HTRU2) is highly imbalanced so various balancing methods were applied. The balanced dataset was used in genetic programming symbolic classifier (GPSC) to obtain symbolic expressions (SEs) that can detect pulsars with high classification accuracy. To find the optimal combination of GPSC hyperparameters the random hyperparameter search (RHS) method was developed and applied. The GPSC was trained using 5-fold cross-validation so after each training a total of 5 SEs were obtained. The best set of SEs are selected based on their classification performance and all of them are applied on the original dataset. The best classification accuracy (ACC), the area under receiver operating characteristic (AUC), precision, recall, and f1-score were achieved in the case of the dataset balanced with the AllKNN method i.e. all mean evaluation metric values are equal to 0.995. The ensemble consisted of 25 SEs that achieved the A C C = 0. 978 , A U C = 0. 9452 , P r e c i s i o n = 0. 905 , R e c a l l = 0. 9963 , and F 1 − S c o r e = 0. 94877 , on the original dataset. [ABSTRACT FROM AUTHOR]

Using neural networks, we integrate the ability to account for Doppler smearing due to a pulsar's orbital motion with the pulsar population synthesis package psrpoppy to develop accurate modeling of the observed binary pulsar population. As a first application, we show that binary neutron star systems where the two components have highly unequal mass are, on average, easier to detect than systems that are symmetric in mass. We then investigate the population of ultracompact (1.5 minutes ≤ Pb ≤ 15 minutes) neutron star–white dwarf (NS–WD) and double neutron star (DNS) systems, which are promising sources for the Laser Interferometer Space Antenna gravitational-wave detector. Given the nondetection of these systems in radio surveys thus far, we estimate a 95% confidence upper limit of ∼1450 and ∼1100 ultracompact NS–WD and DNS systems in the Milky Way that are beaming toward the Earth, respectively. We also show that using survey integration times in the range 20 s–200 s with time-domain resampling will maximize the signal-to-noise ratio as well as the probability of detection of these ultracompact binary systems. Among all the large-scale radio pulsar surveys, those that are currently being carried out using archival data collected with the Arecibo radio telescope have a ∼50%–80% chance of detecting at least one of these systems using current integration integration times and ∼80%–95% using optimal integration times in the next several years. [ABSTRACT FROM AUTHOR]

We report detection of PSR B0656+14 with the Gran Telescopio Canarias in narrow optical F 657, F 754, F 802, and F 902 and near-infrared JHKs bands. The pulsar detection in the Ks band extends its spectrum to 2.2  |$\mu$| m and confirms its flux increase towards the infrared. We also present a thorough analysis of the optical spectrum obtained by us with the VLT. For a consistency check, we revised the pulsar near-infrared and narrow-band photometry obtained with the HST. We find no narrow spectral lines in the optical spectrum. We compile available near-infrared-optical-UV and archival 0.3–20 keV X-ray data and perform a self-consistent analysis of the rotation phase-integrated spectrum of the pulsar using unified spectral models. The spectrum is best fitted by the four-component model including two blackbodies, describing the thermal emission from the neutron star surface and its hot polar cap, the broken power law, originating from the pulsar magnetosphere, and an absorption line near ∼0.5 keV detected previously. The fit provides better constraints on the model parameters than using only a single spectral domain. The derived surface temperature is |$T_{NS}^{\infty } = 7.9(3)\times 10^5$|  K. The intrinsic radius (7.8–9.9 km) of the emitting region is smaller than a typical neutron star radius (13 km) and suggests a non-uniform temperature distribution over the star surface. In contrast, the derived radius of the hot polar cap is about twice as large as the 'canonical' one. The spectrum of the non-thermal emission steepens from the optical to X-rays and has a break near 0.1 keV. The X-ray data suggest the presence of another absorption line near 0.3 keV. [ABSTRACT FROM AUTHOR]

We present timing solutions for eight binary millisecond pulsars (MSPs) discovered by searching unidentified Fermi-Large Area Telescope (LAT) source positions with the 327 MHz receiver of the Arecibo 305 m radio telescope. Five of the pulsars are "spiders" with orbital periods shorter than 8.1 hr. Three of these are in "black widow" systems (with degenerate companions of 0.02–0.03 M⊙), one is in a "redback" system (with a non-degenerate companion of ≳0.3 M⊙), and one (J1908+2105) is an apparent middle-ground case between the two observational classes. The remaining three pulsars have white dwarf companions and longer orbital periods. With the initially derived radio timing solutions, we detected γ-ray pulsations from all MSPs and extended the timing solutions using photons from the full Fermi mission, thus confirming the identification of these MSPs with the Fermi-LAT sources. The radio emission of the redback is eclipsed during 50% of its orbital period, which is typical for this kind of system. Two of the black widows exhibit radio eclipses lasting for 10%–20% of the orbit, while J1908+2105 eclipses for 40% of the orbit. We investigate an apparent link between gamma-ray emission and a short orbital period among known binary MSPs in the Galactic disk, and conclude that selection effects cannot be ruled out as the cause. Based on this analysis we outline how the likelihood of new MSP discoveries can be improved in ongoing and future pulsar searches. [ABSTRACT FROM AUTHOR]

PSR J0636+5128 is a 2.87 ms binary millisecond pulsar (MSP) discovered by the Green Bank Northern Celestial Cap Pulsar Survey, and possesses the third shortest orbital period (P  = 1.6 h) among confirmed binary pulsars. Recent observations reported that this source is experiencing a rapid orbital expansion at a rate of |$\dot{P}=(1.89\pm 0.05)\times 10^{-12}\,\rm s\, s^{-1}$|⁠. The evaporation winds of the companion induced by the spin-down luminosity of the MSP may be responsible for such a positive orbital period derivative. However, our calculations show that the winds ejecting from the vicinity of the companion or the inner Lagrangian point cannot account for the observation due to an implausible evaporation efficiency. Assuming that the evaporation winds eject from the vicinity of the MSP in the form of asymmetric disc winds or outflows, the evaporation efficiency can be constrained to be ∼0.1. Therefore, the rapid orbital expansion detected in PSR J0636+5128 provides evidence of outflows and accretion disc around the MSP. [ABSTRACT FROM AUTHOR]

On the basis of the P sr P op P y software package, we developed an evolution model of population synthesis for isolated radio pulsars by incorporating the fan beam model, an alternative radio emission beam model to the widely used conal beam model. With proper choice of related models and parameters, we successfully reproduced the observational distributions of Galactic longitude (l) and latitude (b), spin period, period derivative, dispersion measure and 1.4 GHz flux density for the 1214 isolated pulsars discovered by the Parkes multibeam and Swinburne pulsar surveys. The size of the underlying population of radio-loud pulsars is found to be 2.27 × 106, which is larger than the underlying population of radio-loud pulsars simulated with the conal beam model. The model is used to estimate the number of isolated radio pulsars detected by the Galactic-plane pulsar survey with Five hundred-meter Aperture Spherical Telescope (FAST). Approximately 2700 and 240 new isolated pulsars are expected to be discovered in the inner galactic plane (20° < l < 90°, ∣b∣ < 10°) and the outer galactic plane (150° < l < 210°, ∣b∣ < 10°), respectively. These numbers are smaller than those estimated by the evolution models with conal beams and the snapshot models. [ABSTRACT FROM AUTHOR]

We report the first discovery of a fast radio burst (FRB), FRB 20200125A, by the Green Bank Northern Celestial Cap (GBNCC) Pulsar Survey conducted with the Green Bank Telescope at 350 MHz. FRB 20200125A was detected at a Galactic latitude of 58.°43 with a dispersion measure of 179 pc cm3, while electron density models predict a maximum Galactic contribution of 25 pc cm3 along this line of sight. Moreover, no apparent Galactic foreground sources of ionized gas that could account for the excess DM are visible in multiwavelength surveys of this region. This argues that the source is extragalactic. The maximum redshift for the host galaxy is zmax = 0.17, corresponding to a maximum comoving distance of approximately 750 Mpc. The measured peak flux density for FRB 20200125A is 0.37 Jy, and we measure a pulse width of 3.7 ms, consistent with the distribution of FRB widths observed at higher frequencies. Based on this detection and assuming a Euclidean flux density distribution of FRBs, we calculate an all-sky rate at 350 MHz of FRBs sky−1 day−1 above a peak flux density of 0.42 Jy for an unscattered pulse having an intrinsic width of 5 ms, consistent with rates reported at higher frequencies, albeit with large uncertainties. Given the recent improvements in our single-pulse search pipeline, we also revisit the GBNCC survey sensitivity to various burst properties. Finally, we find no evidence of strong interstellar scattering in FRB 20200125A, adding to the growing evidence that some FRBs have circumburst environments where free–free absorption and scattering are not significant. [ABSTRACT FROM AUTHOR]

Owing to its massive, dense core, Terzan 5 has the richest population of millisecond pulsars (MSPs) known among Galactic globular clusters. Here we report new deep 2–8 GHz radio continuum observations of Terzan 5 obtained with the Karl G. Jansky Very Large Array. We have identified a total of 24 sources within the cluster half-light radius, including 17 within the core radius. Nineteen are associated with previously studied MSPs and X-ray binaries. Three of the new radio sources have steep radio spectra and are located within the cluster core, as expected for MSPs. These three sources have hard X-ray photon indices (Γ = 1.3–1.5) and highly variable X-ray emission, suggesting they are binary MSPs belonging to the spider class. For the most X-ray luminous of these sources, the redback spider classification is confirmed by its X-ray light curve, which shows an orbital period of 12.32 hr and double-peaked structure around X-ray maximum. The likely discovery of bright binary MSPs in a well-studied cluster like Terzan 5 highlights how deep radio continuum imaging can complement pulsar search and timing observations in finding probable eclipsing systems. The other new radio source in the core has a flat radio spectrum and is X-ray faint (erg s−1) with a photon index Γ = 2.1 ± 0.5, consistent with the properties expected for a quiescent stellar-mass black hole X-ray binary. [ABSTRACT FROM AUTHOR]

We report the detection of pulsed gamma-ray emission from the Geminga pulsar (PSR J0633+1746) between 15 GeV and 75 GeV. This is the first time a middle-aged pulsar has been detected up to these energies. Observations were carried out with the MAGIC telescopes between 2017 and 2019 using the low-energy threshold Sum-Trigger-II system. After quality selection cuts, ∼80 h of observational data were used for this analysis. To compare with the emission at lower energies below the sensitivity range of MAGIC, 11 years of Fermi-LAT data above 100 MeV were also analysed. From the two pulses per rotation seen by Fermi-LAT, only the second one, P2, is detected in the MAGIC energy range, with a significance of 6.3σ. The spectrum measured by MAGIC is well-represented by a simple power law of spectral index Γ = 5.62 ± 0.54, which smoothly extends the Fermi-LAT spectrum. A joint fit to MAGIC and Fermi-LAT data rules out the existence of a sub-exponential cut-off in the combined energy range at the 3.6σ significance level. The power-law tail emission detected by MAGIC is interpreted as the transition from curvature radiation to Inverse Compton Scattering of particles accelerated in the northern outer gap. [ABSTRACT FROM AUTHOR]

Context. We investigate the use of saliency-map analysis to aid in searches for transient signals, such as fast radio bursts and individual pulses from radio pulsars. Aims. Our aim is to demonstrate that saliency maps provide the means to understand predictions from machine learning algorithms and can be implemented in pipelines used to search for transient events. Methods. We implemented a new deep learning methodology to predict whether any segment of the data contains a transient event. The algorithm was trained using real and simulated data sets. We demonstrate that the algorithm is able to identify such events. The output results are visually analysed via the use of saliency maps. Results. We find that saliency maps can produce an enhanced image of any transient feature without the need for de-dispersion or removal of radio frequency interference. The maps can be used to understand which features in the image were used in making the machine learning decision and to visualise the transient event. Even though the algorithm reported here was developed to demonstrate saliency-map analysis, we have detected a single burst event, in archival data, with dispersion measure of 41 cm−3 pc that is not associated with any currently known pulsar. [ABSTRACT FROM AUTHOR]

It is difficult to discover pulsars via their gamma-ray emission because current instruments typically detect fewer than one photon per million rotations. This creates a significant computing challenge for isolated pulsars, where the typical parameter search space spans wide ranges in four dimensions. It is even more demanding when the pulsar is in a binary system, where the orbital motion introduces several additional unknown parameters. Building on earlier work by Pletsch & Clark, we present optimal methods for such searches. These can also incorporate external constraints on the parameter space to be searched, for example, from optical observations of a presumed binary companion. The solution has two parts. The first is the construction of optimal search grids in parameter space via a parameter space metric, for initial semicoherent searches and subsequent fully coherent follow-ups. The second is a method to demodulate and detect the periodic pulsations. These methods have different sensitivity properties than traditional radio searches for binary pulsars and might unveil new populations of pulsars. [ABSTRACT FROM AUTHOR]

The direct detection of gravitational waves now provides a new channel for testing gravity theories. Despite that the parametrized post-Einsteinian framework is a powerful tool to quantitatively investigate the effects of modifications to gravity theory, the gravitational waveform in this framework is still extendable. One such extension is to take into account the gradual activation of dipole radiation due to massive fields, which are still only very weakly constrained if their mass $m$ is greater than $10^{-16}$ $\,$ eV from pulsar observations. Ground-based gravitational-wave detectors (LIGO, Virgo, and KAGRA) are sensitive to this activation in the mass range $10^{-14}$ $\,$ eV $\lesssim m \lesssim 10^{-13}$ $\,$ eV. Hence, we discuss a dedicated test for dipole radiation due to a massive field using the LIGO/Virgo collaboration's open data. In addition, assuming Einstein dilaton Gauss Bonnet (EdGB) type coupling, we combine the results of the analysis of binary black hole events to obtain 90% confidence level constraints on the coupling parameter $\alpha_{\rm EdGB}$ as $\sqrt{\alpha_{\rm EdGB}} \lesssim 2.47$ $\,$ km for any mass less than $6 \times 10^{-14}$ $\,$ eV for the first time, including $\sqrt{\alpha_{\rm EdGB}} \lesssim 1.85$ $\,$ km in the massless limit. [ABSTRACT FROM AUTHOR]

When galaxies merge, the supermassive black holes in their centers may form binaries and emit low-frequency gravitational radiation in the process. In this paper, we consider the galaxy 3C 66B, which was used as the target of the first multimessenger search for gravitational waves. Due to the observed periodicities present in the photometric and astrometric data of the source, it has been theorized to contain a supermassive black hole binary. Its apparent 1.05-year orbital period would place the gravitational-wave emission directly in the pulsar timing band. Since the first pulsar timing array study of 3C 66B, revised models of the source have been published, and timing array sensitivities and techniques have improved dramatically. With these advances, we further constrain the chirp mass of the potential supermassive black hole binary in 3C 66B to less than (1.65 ± 0.02) × 109 M⊙ using data from the NANOGrav 11-year data set. This upper limit provides a factor of 1.6 improvement over previous limits and a factor of 4.3 over the first search done. Nevertheless, the most recent orbital model for the source is still consistent with our limit from pulsar timing array data. In addition, we are able to quantify the improvement made by the inclusion of source properties gleaned from electromagnetic data over "blind" pulsar timing array searches. With these methods, it is apparent that it is not necessary to obtain exact a priori knowledge of the period of a binary to gain meaningful astrophysical inferences. [ABSTRACT FROM AUTHOR]

Pulsar detection using machine learning is a challenging problem as it involves extreme class imbalance and strong prioritization of high Recall. This paper is focused on automatic detection of astrophysical pulses in single-pulse searches, both within and across surveys. We use the output from the first stage of our previously developed two-stage Single-Pulse Event Group IDentification approach and focus on the second stage (i.e., classification of pulse candidates). Specifically, for the first time in time-domain single-pulse searches we (1) use boosting and deep learning algorithms for within-survey classification and (2) investigate cross-survey classification by using two transfer learning methods, trAdaBoost (instance-based) and fine-tuning (parameter-based). Our experimental results are based on two benchmark data sets, Green Bank Telescope Drift-scan (GBTDrift) and Pulsar Arecibo L-band Feed Array (PALFA)-extended, created from the GBTDrift survey and the PALFA survey. The main findings include: (1) Due to the emphasis on high Recall, F4 measure is more appropriate performance indicator than the balanced F1 measure. (2) For the GBTDrift benchmark, AdaBoost outperformed the other models with 98.5% Recall and F4 = 0.942. For the PALFA-extended benchmark, RandomForest performed the best, with 91.6% Recall and F4 = 0.890. (3) Models performance degraded significantly when they were used for pulsar classification across surveys. (4) Transfer learning improved cross-survey classification significantly when training data in the target data set were limited. When the GBTDrift benchmark was used as the target data set, fine-tuned SPEGnet models had the highest F4 measure, while trAdaBoost models had the highest F4 measure when PALFA-extended benchmark was used as the target data set. (5) Pulse classification was affected not only by the between-class imbalance (i.e., pulsar versus non-pulsar), but also by the within-class imbalance, which was more prominent in the case of the PALFA-extended benchmark due to the lack of labeled low signal-to-noise ratio pulsars. [ABSTRACT FROM AUTHOR]

We present timing solutions and analyses of 11 pulsars discovered by the Five-hundred-meter Aperture Spherical radio Telescope (FAST). These pulsars were discovered using an ultrawide bandwidth receiver in drift-scan observations made during the commissioning phase of FAST, and were then confirmed and timed using the 64-m Parkes Radio Telescope. Each pulsar has been observed over a span of at least one year. Highlighted discoveries include PSR J0344−0901, which displays mode-changing behaviour and may belong to the class of so-called swooshing pulsars (alongside PSRs B0919+06 and B1859+07); PSR J0803−0942, whose emission is almost completely linearly polarized; and PSRs J1900−0134 and J1945+1211, whose well-defined polarization angle curves place stringent constraints on their emission geometry. We further discuss the detectability of these pulsars by earlier surveys, and highlight lessons learned from our work in carrying out confirmation and monitoring observations of pulsars discovered by a highly sensitive telescope, many of which may be applicable to next-generation pulsar surveys. This paper marks one of the first major releases of FAST-discovered pulsars, and paves the way for future discoveries anticipated from the Commensal Radio Astronomy FAST Survey. [ABSTRACT FROM AUTHOR]

We present the first measurement of a non-zero magnetic field in the eclipsing material of a black widow pulsar. Black widows are millisecond pulsars which are ablating their companions; therefore they are often proposed as one potential source of isolated millisecond pulsars. PSR J2256–1024 is an eclipsing black widow discovered at radio wavelengths and later also observed in the X-ray and gamma parts of the spectrum. Here we present the radio timing solution for PSR J2256–1024; polarization profiles at 350, 820, and 1500 MHz; and an investigation of changes in the polarization profile due to eclipsing material in the system. In the latter we find evidence of Faraday rotation in the linear polarization shortly after eclipse, measuring a rotation measure of 0.44(6) rad m−2 and a corresponding line-of-sight magnetic field of ∼1.11(16) mG. [ABSTRACT FROM AUTHOR]

Pulsar timing experiments typically generate a phase-connected timing solution from a sequence of times of arrival (TOAs) by absolute pulse numbering, i.e., by fitting an integer number of pulses between TOAs in order to minimize the residuals with respect to a parameterized phase model. In this observing mode, rotational glitches are discovered, when the residuals of the no-glitch phase model diverge after some epoch, and glitch parameters are refined by Bayesian follow-up. Here, we present an alternative, complementary approach which tracks the pulse frequency f and its time derivative with a hidden Markov model (HMM), whose dynamics include stochastic spin wandering (timing noise) and impulsive jumps in f and (glitches). The HMM tracks spin wandering explicitly, as a specific realization of a discrete-time Markov chain. It discovers glitches by comparing the Bayes factor for glitch and no-glitch models. It ingests standard TOAs for convenience, and being fully automated, allows performance bounds to be calculated quickly via Monte Carlo simulations. Practical, user-oriented plots of the false-alarm probability and detection threshold (e.g., minimum resolvable glitch size) versus observational scheduling parameters (e.g., TOA uncertainty, mean delay between TOAs) and glitch parameters (e.g., transient and permanent jump sizes, exponential recovery timescale) are presented. The HMM is also applied to ∼1 yr of real data bracketing the 2016 December 12 glitch in PSR J0835−4510 as a proof of principle. It detects the known glitch and confirms that no other glitch exists in the same data with size ≳10−7f. [ABSTRACT FROM AUTHOR]

During five years of daily observations, the search for new pulsars using the BSA LPI radio telescope in 96 spatial beams covering 17 000 square degrees was conducted. Five new pulsars were identified. Candidate pulsars were selected in summed power spectra. A noise generator was used to renormalize data and total the power spectra for individual directions correctly. As a result, the sensitivity increased by a factor of 10–20 relative to that in individual observational sessions. The sensitivity for pulsars with pulses longer than 100 ms at declinations +30° < δ < +40° was 1.2 and 0.4 mJy in and out of the galaxy plane, respectively. [ABSTRACT FROM AUTHOR]

Pulsar searching is essential for the scientific research in the field of physics and astrophysics. With the development of the radio telescope, the exploding volume and growth speed of candidates have brought about several challenges. Therefore, there is an urgent demand for developing an automatic, accurate, and efficient pulsar candidate selection method. To meet this need, this work designed a Concat Convolutional Neural Network (CCNN) to identify the candidates collected from the Five-hundred-meter Aperture Spherical Telescope (FAST) data. The CCNN extracts some 'pulsar-like' patterns from the diagnostic subplots using Convolutional Neural Network (CNN) and combines these CNN features by a concatenate layer. Therefore, the CCNN is an end-to-end learning model without any need for any intermediate labels, which makes CCNN suitable for the online learning pipeline of pulsar candidate selection. Experimental results on FAST data show that the CCNN outperforms the available state-of-the-art models in a similar scenario. In total, it misses only 4 real pulsars out of 326. [ABSTRACT FROM AUTHOR]

We obtain a new exact analytical solution to the Einstein–Maxwell field equations with anisotropic matter. The solution describes the interior of anisotropic, electrically charged strange quark stars with a non-linear equation-of-state. We show the behavior of the solution graphically, and we determine the properties of the star (radius, mass, electric charge and compactness) for specific numerical values of the parameters involved. Finally, we check that causality is not violated, and that the energy conditions, the upper bound on the compactness of the stars, and constraints on the mass of the objects coming from observed massive pulsars and direct detection of gravitational waves are all fulfilled. [ABSTRACT FROM AUTHOR]

We model the present-day, observable, normal radio pulsar population of the Small Magellanic Cloud (SMC). The pulsars are generated with SeBa , a binary population synthesis code that evolves binaries and the constituent stellar objects up to remnant formation and beyond. We define radio pulsars by selecting neutron stars (NSs) that satisfy a selection of criteria defined by Galactic pulsars, and apply the detection thresholds of previous and future SMC pulsar surveys. The number of synthesized and recovered pulsars is exceptionally sensitive to the assumed star formation history and applied radio luminosity model, but is not affected extensively by the assumed common-envelope model, metallicity, and NS kick velocity distribution. We estimate that the SMC formed (1.6 ± 0.3) ×104 normal pulsars during the last 100 Myr. We study which pulsars could have been observed by the Parkes multibeam survey of the SMC, by applying the survey's specific selection effects, and recover 4.0 ± 0.8 synthetic pulsars. This is in agreement with their five observed pulsars. We also apply a proposed MeerKAT configuration for the upcoming SMC survey, and predict that the MeerKAT survey will detect 17.2 ± 2.5 pulsars. [ABSTRACT FROM AUTHOR]

While pulsars possess exceptional rotational stability, large-scale timing studies have revealed at least two distinct types of irregularities in their rotation: red timing noise and glitches. Using modern Bayesian techniques, we investigated the timing noise properties of 300 bright southern-sky radio pulsars that have been observed over 1.0–4.8 yr by the upgraded Molonglo Observatory Synthesis Telescope (MOST). We reanalysed the spin and spin-down changes associated with nine previously reported pulsar glitches, report the discovery of three new glitches and four unusual glitch-like events in the rotational evolution of PSR J1825−0935. We develop a refined Bayesian framework for determining how red noise strength scales with pulsar spin frequency (ν) and spin-down frequency (⁠|$\dot{\nu }$|⁠), which we apply to a sample of 280 non-recycled pulsars. With this new method and a simple power-law scaling relation, we show that red noise strength scales across the non-recycled pulsar population as |$\nu ^{a} |\dot{\nu }|^{b}$|⁠ , where |$a = -0.84^{+0.47}_{-0.49}$| and |$b = 0.97^{+0.16}_{-0.19}$|⁠. This method can be easily adapted to utilize more complex, astrophysically motivated red noise models. Lastly, we highlight our timing of the double neutron star PSR J0737−3039, and the rediscovery of a bright radio pulsar originally found during the first Molonglo pulsar surveys with an incorrectly catalogued position. [ABSTRACT FROM AUTHOR]

Using a 16.2-h radio observation by the Australia Telescope Compact Array and archival Chandra data, we found >5σ radio counterparts to four known and three new X-ray sources within the half-light radius (r h) of the Galactic globular cluster NGC 6397. The previously suggested millisecond pulsar (MSP) candidate, U18, is a steep-spectrum (S ν ∝ να; |$\alpha =-2.0^{+0.4}_{-0.5}$|⁠) radio source with a 5.5-GHz flux density of 54.7 ± 4.3  |$\mu \mathrm{ Jy}$|⁠. We argue that U18 is most likely a 'hidden' MSP that is continuously hidden by plasma shocked at the collision between the winds from the pulsar and companion star. The non-detection of radio pulsations so far is probably the result of enhanced scattering in this shocked wind. On the other hand, we observed the 5.5-GHz flux of the known MSP PSR J1740−5340 (U12) to decrease by a factor of >2.8 during epochs of 1.4-GHz eclipse, indicating that the radio flux is absorbed in its shocked wind. If U18 is indeed a pulsar whose pulsations are scattered, we note the contrast with U12's flux decreases in eclipse, which argues for two different eclipse mechanisms at the same radio frequency. In addition to U12 and U18, we also found radio associations for five other Chandra X-ray sources, four of which are likely background galaxies. The last, U97, which shows strong H α variability, is mysterious; it may be either a quiescent black hole low-mass X-ray binary or something more unusual. [ABSTRACT FROM AUTHOR]

It is an active topic to investigate the schemes based on machine learning (ML) methods for detecting pulsars as the data volume growing exponentially in modern surveys. To improve the detection performance, input features into an ML model should be investigated specifically. In the existing pulsar detection researches based on ML methods, there are mainly two kinds of feature designs: the empirical features and statistical features. Due to the combinational effects from multiple features, however, there exist some redundancies and even irrelevant components in the available features, which can reduce the accuracy of a pulsar detection model. Therefore, it is essential to select a subset of relevant features from a set of available candidate features and known as feature selection. In this work, two feature selection algorithms – Grid Search (GS) and Recursive Feature Elimination (RFE) – are proposed to improve the detection performance by removing the redundant and irrelevant features. The algorithms were evaluated on the Southern High Time Resolution University survey (HTRU-S) with five pulsar detection models. The experimental results verify the effectiveness and efficiency of our proposed feature selection algorithms. By the GS, a model with only two features reach a recall rate as high as 99 per cent and a false positive rate (FPR) as low as 0.65 per cent; by the RFE, another model with only three features achieves a recall rate of 99 per cent and an FPR of 0.16 per cent in pulsar candidates classification. Furthermore, this work investigated the number of features required as well as the misclassified pulsars by our models. [ABSTRACT FROM AUTHOR]