EIGHT γ-RAY PULSARS DISCOVERED IN BLIND FREQUENCY SEARCHES OF<i>FERMI</i>LAT DATA

Parkinson, P. M. Saz; Dormody, M.; Ziegler, M.; Ray, Paul S.; Abdo, A. A.; Ballet, J.; Baring, Matthew G.; Belfiore, A.; Burnett, T. H.; Caliandro, G. A.; Camilo, F.; Caraveo, P. A.; Luca, A. De; Ferrara, E. C.; Freire, P. C. C.; Grove, J. E.; Gwon, C.; Harding, A. K.; Johnson, R. P.; Johnson, T. J.; Johnston, S.; Keith, Michael; Kerr, M.; Knödlseder, J.; Makeev, A.; Marelli, M.; Michelson, P. F.; Parent, D.; Ransom, S. M.; Reimer, O.; Romani, Roger W.; Smith, David A.; Thompson, D. J.; Watters, K.; Weltevrede, P.; Wolff, M. T.; Wood, K. S.

doi:10.1088/0004-637x/725/1/571

Cited by 166 publications

(169 citation statements)

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“…Among the earliest scientific results from the LAT was the discovery of a large population of radio-quiet gamma-ray pulsars (Abdo et al 2009b;Saz Parkinson et al 2010), using a new blind-search technique developed specifically for the very long time series expected with the LAT (Atwood et al 2006). These findings confirmed some predictions that many of the unidentified EGRET sources in the Galactic plane were pulsars(e.g., Yadigaroglu & Romani 1995), favoring outer gap pulsar models (Cheng et al 1986;Romani 1996Romani , 2014, where the gamma rays are generated in the outer magnetosphere, as opposed to polar cap models, where the emission comes from closer to the neutron star surface(e.g., Harding & Muslimov 1998).…”

Section: Introductionmentioning

confidence: 58%

Classification and Ranking of Fermi Lat Gamma-Ray Sources From the 3fgl Catalog Using Machine Learning Techniques

Parkinson

et al. 2016

ApJ

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We apply a number of statistical and machine learning techniques to classify and rank gamma-ray sources from the Third Fermi Large Area Telescope Source Catalog (3FGL), according to their likelihood of falling into the two major classes of gamma-ray emitters: pulsars (PSR) or active galactic nuclei (AGNs). Using 1904 3FGL sources that have been identified/associated with AGNs (1738) and PSR (166), we train (using 70% of our sample) and test (using 30%) our algorithms and find that the best overall accuracy (>96%) is obtained with the Random Forest (RF) technique, while using a logistic regression (LR) algorithm results in only marginally lower accuracy. We apply the same techniques on a subsample of 142 known gamma-ray pulsars to classify them into two major subcategories: young (YNG) and millisecond pulsars (MSP). Once more, the RF algorithm has the best overall accuracy (∼90%), while a boosted LR analysis comes a close second. We apply our two best models (RF and LR) to the entire 3FGL catalog, providing predictions on the likely nature of unassociated sources, including the likely type of pulsar (YNG or MSP). We also use our predictions to shed light on the possible nature of some gamma-ray sources with known associations (e.g., binaries, supernova remnants/pulsar wind nebulae). Finally, we provide a list of plausible X-ray counterparts for some pulsar candidates, obtained using Swift, Chandra, and XMM. The results of our study will be of interest both for in-depth follow-up searches (e.g., pulsar) at various wavelengths and for broader population studies.

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Section: Introductionmentioning

confidence: 58%

Classification and Ranking of Fermi Lat Gamma-Ray Sources From the 3fgl Catalog Using Machine Learning Techniques

Parkinson

et al. 2016

ApJ

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“…If the γ -ray pulsar is located beyond 6.0 kpc, the velocity of the pulsar required for escaping from the cluster has to be as large as 3000 km s −1 or more for a characteristic age of 4.6 kyr. Saz Parkinson et al (2010) and Ackermann et al (2011) therefore suggested the distance to be 1.8-2.4 kpc.…”

Section: Introductionmentioning

confidence: 99%

“…Fujita et al (2009b) argued that the shock front of an SNR occurred in the past may have accelerated CRs and emit the TeV γ -rays by the interaction with the molecular gas toward Wd 2. Recently, Fermi collaboration discovered a γ -ray pulsar PSR J1023−5746 near the peak position of the TeV γ -ray source (Saz Parkinson et al 2010). Ackermann et al (2011) suggested that HESS J1023−575 was an associated PWN.…”

Section: Introductionmentioning

confidence: 99%

THE JET AND ARC MOLECULAR CLOUDS TOWARD WESTERLUND 2, RCW 49, AND HESS J1023–575;¹²CO AND¹³CO (J= 2-1 andJ= 1-0) OBSERVATIONS WITH NANTEN2 AND MOPRA TELESCOPE

Furukawa

Ohama

Fukuda

et al. 2014

ApJ

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We have made new CO observations of two molecular clouds, which we call "jet" and "arc" clouds, toward the stellar cluster Westerlund 2 and the TeV γ -ray source HESS J1023−575. The jet cloud shows a linear structure from the position of Westerlund 2 on the east. In addition, we have found a new counter jet cloud on the west. The arc cloud shows a crescent shape in the west of HESS J1023−575. A sign of star formation is found at the edge of the jet cloud and gives a constraint on the age of the jet cloud to be ∼Myr. An analysis with the multi CO transitions gives temperature as high as 20 K in a few places of the jet cloud, suggesting that some additional heating may be operating locally. The new TeV γ -ray images by H.E.S.S. correspond to the jet and arc clouds spatially better than the giant molecular clouds associated with Westerlund 2. We suggest that the jet and arc clouds are not physically linked with Westerlund 2 but are located at a greater distance around 7.5 kpc. A microquasar with long-term activity may be able to offer a possible engine to form the jet and arc clouds and to produce the TeV γ -rays, although none of the known microquasars have a Myr age or steady TeV γ -rays. Alternatively, an anisotropic supernova explosion which occurred ∼Myr ago may be able to form the jet and arc clouds, whereas the TeV γ -ray emission requires a microquasar formed after the explosion.

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“…Among the extremes of the population of Fermi pulsars, PSR J2055+2539 (J2055 hereafter;Saz Parkinson et al 2010) is one of the best candidates. It is one of the 100 brightest γ-ray sources, with a γ-ray flux of (5.5 ± 0.1)×10 −7 erg cm −2 s −1 (Acero et al 2015).…”

Section: Introductionmentioning

confidence: 99%

The Tale of the Two Tails of the Oldish PSR J2055+2539

Marelli

Pizzocaro

Luca

et al. 2016

ApJ

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We analyzed a deep XMM-Newton observation of the radio-quiet γ-ray PSR J2055+2539. The spectrum of the X-ray counterpart is nonthermal, with a photon index of Γ=2.36±0.14 (1σ confidence). We detected X-ray pulsations with a pulsed fraction of 25% ± 3% and a sinusoidal shape. Taking into account considerations on the γ-ray efficiency of the pulsar and on its X-ray spectrum, we can infer a pulsar distance ranging from 450 to 750 pc. We found two different nebular features associated withPSR J2055+2539 and protruding from it. The angle between the two nebular main axes is ∼162°.8±0°.7. The main, brighter feature is 12′ long and <20″ thick, characterized by an asymmetry with respect to the main axis that evolves with the distance from the pulsar, possibly forming a helical pattern. The secondary feature is 250″×30″. Both nebulae present an almost flat brightness profile with a sudden decrease at the end. The nebulae can be fitted byeithera power-law model or a thermal bremsstrahlung model. A plausible interpretation of the brighter nebula is in terms of a collimated ballistic jet. The secondary nebula is most likely a classical synchrotron-emitting tail.

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EIGHT γ-RAY PULSARS DISCOVERED IN BLIND FREQUENCY SEARCHES OFFERMILAT DATA

Cited by 166 publications

References 39 publications

Classification and Ranking of Fermi Lat Gamma-Ray Sources From the 3fgl Catalog Using Machine Learning Techniques

Classification and Ranking of Fermi Lat Gamma-Ray Sources From the 3fgl Catalog Using Machine Learning Techniques

THE JET AND ARC MOLECULAR CLOUDS TOWARD WESTERLUND 2, RCW 49, AND HESS J1023–575;¹²CO AND¹³CO (J= 2-1 andJ= 1-0) OBSERVATIONS WITH NANTEN2 AND MOPRA TELESCOPE

The Tale of the Two Tails of the Oldish PSR J2055+2539

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EIGHT γ-RAY PULSARS DISCOVERED IN BLIND FREQUENCY SEARCHES OFFERMILAT DATA

Cited by 166 publications

References 39 publications

Classification and Ranking of Fermi Lat Gamma-Ray Sources From the 3fgl Catalog Using Machine Learning Techniques

Classification and Ranking of Fermi Lat Gamma-Ray Sources From the 3fgl Catalog Using Machine Learning Techniques

THE JET AND ARC MOLECULAR CLOUDS TOWARD WESTERLUND 2, RCW 49, AND HESS J1023–575;12CO AND13CO (J= 2-1 andJ= 1-0) OBSERVATIONS WITH NANTEN2 AND MOPRA TELESCOPE

The Tale of the Two Tails of the Oldish PSR J2055+2539

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THE JET AND ARC MOLECULAR CLOUDS TOWARD WESTERLUND 2, RCW 49, AND HESS J1023–575;¹²CO AND¹³CO (J= 2-1 andJ= 1-0) OBSERVATIONS WITH NANTEN2 AND MOPRA TELESCOPE