Can we see pulsars around Sgr A*? - The latest searches with the Effelsberg telescope

Radio pulsars in relativistic binary systems are unique tools to study the curved space-time around massive compact objects. The discovery of a pulsar closely orbiting the super-massive black hole at the centre of our Galaxy, Sgr A*, would provide a superb test-bed for gravitational physics. To date, the absence of any radio pulsar discoveries within a few arc minutes of Sgr A* has been explained by one principal factor: extreme scattering of radio waves caused by inhomogeneities in the ionized component of the interstellar medium in the central 100 pc around Sgr A*. Scattering, which causes temporal broadening of pulses, can only be mitigated by observing at higher frequencies. Here we describe recent searches of the Galactic centre region performed at a frequency of 18.95 GHz with the Effelsberg radio telescope.Comment: 3 pages, 2 figures, Proceedings of IAUS 291 "Neutron Stars and Pulsars: Challenges and Opportunities after 80 years", 201

Application of the Gaussian mixture model in pulsar astronomy -- pulsar classification and candidates ranking for {\it Fermi} 2FGL catalog

Machine learning, algorithms to extract empirical knowledge from data, can be used to classify data, which is one of the most common tasks in observational astronomy. In this paper, we focus on Bayesian data classification algorithms using the Gaussian mixture model and show two applications in pulsar astronomy. After reviewing the Gaussian mixture model and the related Expectation-Maximization algorithm, we present a data classification method using the Neyman-Pearson test. To demonstrate the method, we apply the algorithm to two classification problems. Firstly, it is applied to the well known period-period derivative diagram, where we find that the pulsar distribution can be modeled with six Gaussian clusters, with two clusters for millisecond pulsars (recycled pulsars) and the rest for normal pulsars. From this distribution, we derive an empirical definition for millisecond pulsars as $\frac{\dot{P}}{10^{-17}} \leq3.23(\frac{P}{100 \textrm{ms}})^{-2.34}$. The two millisecond pulsar clusters may have different evolutionary origins, since the companion stars to these pulsars in the two clusters show different chemical composition. Four clusters are found for normal pulsars. Possible implications for these clusters are also discussed. Our second example is to calculate the likelihood of unidentified \textit{Fermi} point sources being pulsars and rank them accordingly. In the ranked point source list, the top 5% sources contain 50% known pulsars, the top 50% contain 99% known pulsars, and no known active galaxy (the other major population) appears in the top 6%. Such a ranked list can be used to help the future follow-up observations for finding pulsars in unidentified \textit{Fermi} point sources.Comment: 9 pages, 4 figures, accepted by MNRA

Apportionment of primary and secondary organic aerosols in Southern California during the 2005 Study of Organic Aerosols in Riverside (SOAR-1)

Ambient sampling was conducted in Riverside, California during the 2005 Study of Organic Aerosols in Riverside to characterize the composition and sources of organic aerosol using a variety of state-of-the-art instrumentation and source apportionment techniques. The secondary organic aerosol (SOA) mass is estimated by elemental carbon and carbon monoxide tracer methods, water soluble organic carbon content, chemical mass balance of organic molecular markers, and positive matrix factorization of high-resolution aerosol mass spectrometer data. Estimates obtained from each of these methods indicate that the organic fraction in ambient aerosol is overwhelmingly secondary in nature during a period of several weeks with moderate ozone concentrations and that SOA is the single largest component of PM1 aerosol in Riverside. Average SOA/OA contributions of 70−90% were observed during midday periods, whereas minimum SOA contributions of ~45% were observed during peak morning traffic periods. These results are contrary to previous estimates of SOA throughout the Los Angeles Basin which reported that, other than during severe photochemical smog episodes, SOA was lower than primary OA. Possible reasons for these differences are discussed

A Cosmic Census of Radio Pulsars with the SKA

The Square Kilometre Array (SKA) will make ground breaking discoveries in pulsar science. In this chapter we outline the SKA surveys for new pulsars, as well as how we will perform the necessary follow-up timing observations. The SKA's wide field-of-view, high sensitivity, multi-beaming and sub-arraying capabilities, coupled with advanced pulsar search backends, will result in the discovery of a large population of pulsars. These will enable the SKA's pulsar science goals (tests of General Relativity with pulsar binary systems, investigating black hole theorems with pulsar-black hole binaries, and direct detection of gravitational waves in a pulsar timing array). Using SKA1-MID and SKA1-LOW we will survey the Milky Way to unprecedented depth, increasing the number of known pulsars by more than an order of magnitude. SKA2 will potentially find all the Galactic radio-emitting pulsars in the SKA sky which are beamed in our direction. This will give a clear picture of the birth properties of pulsars and of the gravitational potential, magnetic field structure and interstellar matter content of the Galaxy. Targeted searches will enable detection of exotic systems, such as the ~1000 pulsars we infer to be closely orbiting Sgr A*, the supermassive black hole in the Galactic Centre. In addition, the SKA's sensitivity will be sufficient to detect pulsars in local group galaxies. To derive the spin characteristics of the discoveries we will perform live searches, and use sub-arraying and dynamic scheduling to time pulsars as soon as they are discovered, while simultaneously continuing survey observations. The large projected number of discoveries suggests that we will uncover currently unknown rare systems that can be exploited to push the boundaries of our understanding of astrophysics and provide tools for testing physics, as has been done by the pulsar community in the past.Comment: 20 pages, 7 figures, to be published in: "Advancing Astrophysics with the Square Kilometre Array", Proceedings of Science, PoS(AASKA14)04

The High Time Resolution Universe Pulsar Survey I: System configuration and initial discoveries

We have embarked on a survey for pulsars and fast transients using the 13-beam Multibeam receiver on the Parkes radio telescope. Installation of a digital backend allows us to record 400 MHz of bandwidth for each beam, split into 1024 channels and sampled every 64 us. Limits of the receiver package restrict us to a 340 MHz observing band centred at 1352 MHz. The factor of eight improvement in frequency resolution over previous multibeam surveys allows us to probe deeper into the Galactic plane for short duration signals such as the pulses from millisecond pulsars. We plan to survey the entire southern sky in 42641 pointings, split into low, mid and high Galactic latitude regions, with integration times of 4200, 540 and 270 s respectively. Simulations suggest that we will discover 400 pulsars, of which 75 will be millisecond pulsars. With ~30% of the mid-latitude survey complete, we have re-detected 223 previously known pulsars and discovered 27 pulsars, 5 of which are millisecond pulsars. The newly discovered millisecond pulsars tend to have larger dispersion measures than those discovered in previous surveys, as expected from the improved time and frequency resolution of our instrument.Comment: Updated author list. 10 pages, 7 figures. For publication in MNRA

The High Time Resolution Universe Survey VI: An Artificial Neural Network and Timing of 75 Pulsars

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 are in binaries. Two display particularly interesting behaviour; PSR J1054-5944 is found to be an intermittent pulsar, and PSR J1809-0119 has glitched twice since its discovery. In the second half of the paper we discuss the development and application of an artificial neural network in the data-processing pipeline for the survey. We discuss the tests that were used to generate scores and find that our neural network was able to reject over 99% of the candidates produced in the data processing, and able to blindly detect 85% of pulsars. We suggest that improvements to the accuracy should be possible if further care is taken when training an artificial neural network; for example ensuring that a representative sample of the pulsar population is used during the training process, or the use of different artificial neural networks for the detection of different types of pulsars.Comment: 15 pages, 8 figure