XMM-Newton confirmation of a new intermediate polar: XMMU J185330.7-012815

We report the results from a detailed spectro-imaging and temporal analysis of an archival XMM-Newton observation of a new intermediate polar XMMU J185330.7-012815. Its X-ray spectrum can be well-described by a multi-temperature thermal plasma model with the K-lines of heavy elements clearly detected. Possible counterparts of XMMU J185330.7-012815 have been identified in optical and UV bands. The low value of the inferred X-ray-to-UV and X-ray-to-optical flux ratios help to safely rule out the possibility as an isolated neutron star. We confirm the X-ray periodicity of ~238 s, but different from the previous preliminary result, we do not find any convincing evidence of phase-shift in this observation. We further investigate its properties through an energy-resolved temporal analysis and find the pulsed fraction monotonically increases with energy.Comment: 9 pages, 4 figures, 1 table, accepted for publication in MNRA

The High Time Resolution Universe Survey - V: Single-pulse energetics and modulation properties of 315 pulsars

We report on the pulse-to-pulse energy distributions and phase-resolved modulation properties for catalogued pulsars in the southern High Time Resolution Universe intermediate-latitude survey. We selected the 315 pulsars detected in a single-pulse search of this survey, allowing a large sample unbiased regarding any rotational parameters of neutron stars. We found that the energy distribution of many pulsars is well-described by a log-normal distribution, with few deviating from a small range in log-normal scale and location parameters. Some pulsars exhibited multiple energy states corresponding to mode changes, and implying that some observed "nulling" may actually be a mode-change effect. PSRJ1900-2600 was found to emit weakly in its previously-identified "null" state. We found evidence for another state-change effect in two pulsars, which show bimodality in their nulling time scales; that is, they switch between a continuous-emission state and a single-pulse-emitting state. Large modulation occurs in many pulsars across the full integrated profile, with increased sporadic bursts at leading and trailing sub-beam edges. Some of these high-energy outbursts may indicate the presence of "giant pulse" phenomena. We found no correlation with modulation and pulsar period, age, or other parameters. Finally, the deviation of integrated pulse energy from its average value was generally quite small, despite the significant phase-resolved modulation in some pulsars; we interpret this as tenuous evidence of energy regulation between distinct pulsar sub-beams.Comment: Before full MNRAS publication, supplementary material is available temporarily at http://dl.dropbox.com/u/22076931/supplementary_material.pd

Advanced methods in automatic modulation classification for emerging technologies

Modulation classification (MC) is of large importance in both military and commercial communication applications. It is a challenging problem, especially in non-cooperative wireless environments, where channel fading and no prior knowledge on the incoming signal are major factors that deteriorate the reception performance. Although the average likelihood ratio test method can provide an optimal solution to the MC problem with unknown parameters, it suffers from high computational complexity and in some cases mathematical intractability. Instead, in this research, an array-based quasi-hybrid likelihood ratio test (qHLRT) algorithm is proposed, which depicts two major advantages. First, it is simple yet accurate enough parameter estimation with reduced complexity. Second the incorporation of antenna arrays offers an effective ability to combat fading. Furthermore, a practical array-based qHLRT classifier scheme is implemented, which applies maximal ratio combining (MRC) to increase the accuracy of both carrier frequency offset (CFO) estimation and likelihood function calculation in channel fading. In fact, double CFO estimations are executed in this classifier. With the first the unknown CFO, phase offsets and amplitudes are estimated as prerequisite for MRC operation. Then, MRC is performed using these estimates, followed by a second CFO estimator. Since the input of the second CFO estimator is the output of the MRC, fading effects on the incoming signals are removed significantly and signal-to-noise ratio (SNR) is augmented. As a result, a more accurate CFO estimate is obtained. Consequently, the overall classification performance is improved, especially in low SNR environment. Recently, many state-of-the-arts communication technologies, such as orthogonal frequency division multiplexing (OFDM) modulations, have been emerging. The need for distinguishing OFDM signal from single carrier has become obvious. Besides, some vital parameters of OFDM signals should be extracted for further processing. In comparison to the research on MC for single carrier single antenna transmission, much less attention has been paid to the MC for emerging modulation methods. A comprehensive classification system is proposed for recognizing the OFDM signal and extracting its parameters. An automatic OFDM modulation classifier is proposed, which is based on the goodness-of-fittest. Since OFDM signal is Gaussian, Cramer-von Mises technique, working on the empirical distribution function, has been applied to test the presence of the normality. Numerical results show that such approach can successfully identify OFDM signals from single carrier modulations over a wide SNR range. Moreover, the proposed scheme can provide the acceptable performance when frequency-selective fading is present. Correlation test is then applied to estimate OFDM cyclic prefix duration. A two-phase searching scheme, which is based on Fast Fourier Transform (FFT) as well as Gaussianity test, is devised to detect the number of subcarriers. In the first phase, a coarse search is carried out iteratively. The exact number of subcarriers is determined by the fine tune in the second phase. Both analytical work and numerical results are presented to verify the efficiency of the proposed scheme

An Overview on Application of Machine Learning Techniques in Optical Networks

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude the paper proposing new possible research directions

Multi-wavelength observations of 3FGL J2039.6-5618: a candidate redback millisecond pulsar

We present multi-wavelength observations of the unassociated gamma-ray source 3FGL J2039.6-5618 detected by the Fermi Large Area Telescope. The source gamma-ray properties suggest that it is a pulsar, most likely a millisecond pulsar, for which neither radio nor $\gamma$-ray pulsations have been detected yet. We observed 3FGL J2039.6-5618 with XMM-Newton and discovered several candidate X-ray counterparts within/close to the gamma-ray error box. The brightest of these X-ray sources is variable with a period of 0.2245$\pm$0.0081 d. Its X-ray spectrum can be described by a power law with photon index $\Gamma_X =1.36\pm0.09$, and hydrogen column density $N_{\rm H} < 4 \times 10^{20}$ cm$^{-2}$, which gives an unabsorbed 0.3--10 keV X-ray flux of $1.02 \times 10^{-13}$ erg cm$^{-2}$ s$^{-1}$. Observations with the Gamma-Ray Burst Optical/Near-Infrared Detector (GROND) discovered an optical counterpart to this X-ray source, with a time-average magnitude $g'\sim 19.5$. The counterpart features a flux modulation with a period of 0.22748$\pm$0.00043 d that coincides, within the errors, with that of the X-ray source, confirming the association based on the positional coincidence. We interpret the observed X-ray/optical periodicity as the orbital period of a close binary system where one of the two members is a neutron star. The light curve profile of the companion star, with two asymmetric peaks, suggests that the optical emission comes from two regions at different temperatures on its tidally-distorted surface. Based upon its X-ray and optical properties, we consider this source as the most likely X-ray counterpart to 3FGL J2039.6-5618, which we propose to be a new redback system.Comment: 35 pages, 8 figures, accepted for publication on Astrophysical Journa

Comparison of Signals from Gravitational Wave Detectors with Instantaneous Time-Frequency Maps

Gravitational wave astronomy relies on the use of multiple detectors, so that coincident detections may distinguish real signals from instrumental artifacts, and also so that relative timing of signals can provide the sky position of sources. We show that the comparison of instantaneous time-frequency and time- amplitude maps provided by the Hilbert-Huang Transform (HHT) can be used effectively for relative signal timing of common signals, to discriminate between the case of identical coincident signals and random noise coincidences, and to provide a classification of signals based on their time-frequency trajectories. The comparison is done with a chi-square goodness-of-fit method which includes contributions from both the instantaneous amplitude and frequency components of the HHT to match two signals in the time domain. This approach naturally allows the analysis of waveforms with strong frequency modulation.Comment: 13 pages, accepted for publication in CQ