Engineering topics
Zhu, W. W.
Publications and source records attributed to Zhu, W. W..
The NANOGrav 11 Yr Data Set: Limits on Gravitational Waves from Individual Supermassive Black Hole Binaries
Observations indicate that nearly all galaxies contain supermassive black holes at their centers. When galaxies merge, their component black holes form SMBH binaries (SMBHBs), which emit low-frequency gravitational waves (GWs) that can be detected by pulsar timing arrays. We have searched the North American Nanohertz Observatory for Gravitational Waves 11 yr data set for GWs from individual SMBHBs in circular orbits. As we did not find strong evidence for GWs in our data, we placed 95% upper limits on the strength of GWs from such sources. At f(gw) = 8 nHz, we placed a sky-averaged upper limit of h(0) < 7.3(3) × 10(exp −15). We also developed a technique to determine the significance of a particular signal in each pulsar using "dropout" parameters as a way of identifying spurious signals. From these upper limits, we ruled out SMBHBs emitting GWs f(gw) = 8 nHz within 120 Mpc for M = 10(exp 9) Solar Mass, and within 5.5 Gpc for M= 10(exp 10) Solar Mass at our most sensitive sky location. We also determined that there are no SMBHBs with M > 1.6 x 10(exp 9) Solar Mass emitting GWs with f(gw) = 2.8–317.8 nHz in the Virgo Cluster. Finally, we compared our strain upper limits to simulated populations of SMBHBs, based on galaxies in the Two Micron All-Sky Survey and merger rates from the Illustris cosmological simulation project, and found that only 34 out of 75,000 realizations of the local universe contained a detectable source.
The NANOGrav 12.5 yr Data Set: The Frequency Dependence of Pulse Jitter in Precision Millisecond Pulsars
Low-frequency gravitational-wave experiments require the highest timing precision from an array of the moststable millisecond pulsars. Several known sources of noise on short timescales in single radio pulsar observationsare well described by a simple model of three components: template fitting from a finite signal-to-noise ratio, pulsephase/amplitude jitter from single-pulse stochasticity, and scintillation errors from short-timescale interstellarscattering variations. Currently template-fitting errors dominate, but as radio telescopes push toward higher signalto-noise ratios, jitter becomes the next dominant term for most millisecond pulsars. Understanding the statistics ofjitter becomes crucial for properly characterizing arrival time uncertainties. We characterize the radio frequencydependence of jitter using data on 48 pulsars in the North American Nanohertz Observatory for GravitationalWaves timing program. We detect significant jitter in 43 of the pulsars and test several functional forms for itsfrequency dependence; we find significant frequency dependence for 30 pulsars. We find moderate correlations ofrms jitter with pulse width (R = 0.62) and number of profile components (R = 0.40); the single-pulse rms jitter istypically 1% of pulse phase. The average frequency dependence for all pulsars using a power-law model hasindex 0.42. We investigate the jitter variations for the interpulse of PSR B1937+21 and find no significantdeviations from the main pulse rms jitter. We also test the time variation of jitter in two pulsars and find thatsystematics likely bias the results for high-precision pulsars. Pulsar timing array analyses must properly modeljitter as a significant component of the noise within the detector.
The NANOGrav 11 yr Data Set: Solar Wind Sounding through Pulsar Timing
The North American Nanohertz Observatory for Gravitational Waves (NANOGrav) has observed dozens ofmillisecond pulsars for over a decade. We have accrued a large collection of dispersion measure (DM)measurements sensitive to the total electron content between Earth and the pulsars at each observation. All lines ofsight cross through the solar wind (SW), which produces correlated DM fluctuations in all pulsars. We develop andapply techniques for extracting the imprint of the SW from the full collection of DM measurements in the recentlyreleased NANOGrav 11 yr data set. We filter out long-timescale DM fluctuations attributable to structure in theinterstellar medium and carry out a simultaneous analysis of all pulsars in our sample that can differentiate thecorrelated signature of the wind from signals unique to individual lines of sight. When treating the SW asspherically symmetric and constant in time, we find the electron number density at 1au to be 7.9 ± 0.2 cm(exp -3). Wefind our data to be insensitive to long-term variation in the density of the wind. We argue that our techniques pairedwith a high-cadence, low-radio-frequency observing campaign of near-ecliptic pulsars would be capable ofmapping out large-scale latitudinal structure in the wind.
The NANOGrav 11 Year Data Set: Pulsar-Timing Constraints on the Stochastic Gravitational-Wave Background
We search for an isotropic stochastic gravitational-wave background (GWB) in the newly released 11 year data set from the North American Nanohertz Observatory for Gravitational Waves (NANOGrav). While we find no evidence for a GWB, we place constraints on a population of inspiraling supermassive black hole (SMBH) binaries, a network of decaying cosmic strings, and a primordial GWB. For the first time, we find that the GWB constraints are sensitive to the solar system ephemeris (SSE) model used and that SSE errors can mimic a GWB signal. We developed an approach that bridges systematic SSE differences, producing the first pulsar-timing array (PTA) constraints that are robust against SSE errors. We thus place a 95% upper limit on the GW-strain amplitude of A (sub GWB) < 1.45 × 10 (exp -15) at a frequency of f=1 yr(exp -1) for a fiducial f (exp -2/3) power-law spectrum and with interpulsar correlations modeled. This is a factor of approximately 2 improvement over the NANOGrav nine-year limit calculated using the same procedure. Previous PTA upper limits on the GWB (as well as their astrophysical and cosmological interpretations) will need revision in light of SSE systematic errors. We use our constraints to characterize the combined influence on the GWB of the stellar mass density in galactic cores, the eccentricity of SMBH binaries, and SMBH-galactic-bulge scaling relationships. We constrain the cosmic-string tension using recent simulations, yielding an SSE-marginalized 95% upper limit of G (sub mu) < 5.3 × 10(exp -11) - a factor of approximately 2 better than the published NANOGrav nine-year constraints. Our SSE-marginalized 95% upper limit on the energy density of a primordial GWB (for a radiation-dominated post-inflation universe) is omega (sub GWB)(f) h (exp 2) < 3.4 × 10 (exp -10).
The Nanograv Nine-Year Data Set: Measurement and Analysis of Variations in Dispersion Measures
We analyze dispersion measure(DM) variations of 37 millisecond pulsars in the nine-year North American Nanohertz Observatory for Gravitational Waves (NANOGrav) data release and constrain the sources of these variations. DM variations can result from a changing distance between Earth and the pulsar, inhomogeneities in the interstellar medium, and solar effects. Variations are significant for nearly all pulsars, with characteristic timescales comparable to or even shorter than the average spacing between observations. Five pulsars have periodic annual variations, 14 pulsars have monotonically increasing or decreasing trends, and 14 pulsars show both effects. Of the four pulsars with linear trends that have line-of-sight velocity measurements, three are consistent with a changing distance and require an overdensity of free electrons local to the pulsar. Several pulsars show correlations between DM excesses and lines of sight that pass close to the Sun. Mapping of the DM variations as a function of the pulsar trajectory can identify localized interstellar medium features and, in one case, an upper limit to the size of the dispersing region of 4 au. Four pulsars show roughly Kolmogorov structure functions (SFs), and another four show SFs less steep than Kolmogorov. One pulsar has too large an uncertainty to allow comparisons. We discuss explanations for apparent departures from a Kolmogorov-like spectrum, and we show that the presence of other trends and localized features or gradients in the interstellar medium is the most likely cause.
The NANOGrav Nine-Year Data Set: Limits on the Isotropic Stochastic Gravitational Wave Background
We compute upper limits on the nanohertz-frequency isotropic stochastic gravitational wave background (GWB) using the 9 year data set from the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) collaboration. Well-tested Bayesian techniques are used to set upper limits on the dimensionless strain amplitude (at a frequency of 1 yr(exp -1) for a GWB from supermassive black hole binaries of A(sub gw) less than 1.5 x 10(exp -15). We also parameterize the GWB spectrum with a broken power-law model by placing priors on the strain amplitude derived from simulations of Sesana and McWilliams et al. Using Bayesian model selection we find that the data favor a broken power law to a pure power law with odds ratios of 2.2 and 22 to one for the Sesana and McWilliams prior models, respectively. Using the broken power-law analysis we construct posterior distributions on environmental factors that drive the binary to the GW-driven regime including the stellar mass density for stellar-scattering, mass accretion rate for circumbinary disk interaction, and orbital eccentricity for eccentric binaries, marking the first time that the shape of the GWB spectrum has been used to make astrophysical inferences. Returning to a power-law model, we place stringent limits on the energy density of relic GWs, OMEGA(sub gw) (f) h squared less than 4.2 x 10(exp -10). Our limit on the cosmic string GWB, OMEGA(sub gw) (f) h squared less than 2.2 x 10(exp -10), translates to a conservative limit on the cosmic string tension with G mu less than 3.3 x 10(exp -8), a factor of four better than the joint Planck and high-l‚ cosmic microwave background data from other experiments.
Arecibo pulsar survey using ALFA. IV. Mock spectrometer data analysis, survey sensitivity, and the discovery of 40 pulsars
The on-going Arecibo Pulsar-ALFA (PALFA) survey began in 2004 and is searching for radio pulsars in the Galactic plane at 1.4 GHz. Here we present a comprehensive description of one of its main data reduction pipelines that is based on the PRESTO software and includes new interference-excision algorithms and candidate selection heuristics. This pipeline has been used to discover 40 pulsars, bringing the survey’s discovery total to 144 pulsars. Of the new discoveries, eight are millisecond pulsars (MSPs; P<10 ms) and one is a Fast Radio Burst (FRB). This pipeline has also re-detected 188 previously known pulsars, 60 of them previously discovered by the other PALFA pipelines. We present a novel method for determining the survey sensitivity that accurately takes into account the effects of interference and red noise: we inject synthetic pulsar signals with various parameters into real survey observations and then attempt to recover them with our pipeline. We find that the PALFA survey achieves the sensitivity to MSPs predicted by theoretical models but suffers a degradation for P≳100 ms that gradually becomes up to ∼10 times worse for P>4 s at DM<150 pc cm{sup −3}. We estimate 33 ± 3% of the slower pulsars are missed, largely due to red noise. A population synthesis analysis using the sensitivity limits we measured suggests the PALFA survey should have found 224 ± 16 un-recycled pulsars in the data set analyzed, in agreement with the 241 actually detected. The reduced sensitivity could have implications on estimates of the number of long-period pulsars in the Galaxy.
Testing theories of gravitation using 21-year timing of pulsar binary J1713+0747
We report 21-year timing of one of the most precise pulsars: PSR J1713+0747. Its pulse times of arrival are well modeled by a comprehensive pulsar binary model including its three-dimensional orbit and a noise model that incorporates short- and long-timescale correlated noise such as jitter and red noise. Its timing residuals have weighted root mean square ∼92 ns. The new data set allows us to update and improve previous measurements of the system properties, including the masses of the neutron star (1.31 ± 0.11 M{sub ⊙}) and the companion white dwarf (0.286 ± 0.012 M{sub ⊙}) as well as their parallax distance 1.15 ± 0.03 kpc. We measured the intrinsic change in orbital period, P-dot {sub b}{sup Int}, is −0.20 ± 0.17 ps s{sup −1}, which is not distinguishable from zero. This result, combined with the measured P-dot {sub b}{sup Int} of other pulsars, can place a generic limit on potential changes in the gravitational constant G. We found that G-dot /G is consistent with zero [(−0.6 ± 1.1) × 10{sup −12} yr{sup −1}, 95% confidence] and changes at least a factor of 31 (99.7% confidence) more slowly than the average expansion rate of the universe. This is the best G-dot /G limit from pulsar binary systems. The P-dot {sub b}{sup Int} of pulsar binaries can also place limits on the putative coupling constant for dipole gravitational radiation κ{sub D}=(−0.9±3.3)×10{sup −4} (95% confidence). Finally, the nearly circular orbit of this pulsar binary allows us to constrain statistically the strong-field post-Newtonian parameters Δ, which describes the violation of strong equivalence principle, and α-hat {sub 3}, which describes a breaking of both Lorentz invariance in gravitation and conservation of momentum. We found, at 95% confidence, Δ<0.01 and α-hat {sub 3}<2×10{sup −20} based on PSR J1713+0747.
Searching for pulsars using image pattern recognition
In the modern era of big data, many fields of astronomy are generating huge volumes of data, the analysis of which can sometimes be the limiting factor in research. Fortunately, computer scientists have developed powerful data-mining techniques that can be applied to various fields. In this paper, we present a novel artificial intelligence (AI) program that identifies pulsars from recent surveys by using image pattern recognition with deep neural nets—the PICS (Pulsar Image-based Classification System) AI. The AI mimics human experts and distinguishes pulsars from noise and interference by looking for patterns from candidate plots. Different from other pulsar selection programs that search for expected patterns, the PICS AI is taught the salient features of different pulsars from a set of human-labeled candidates through machine learning. The training candidates are collected from the Pulsar Arecibo L-band Feed Array (PALFA) survey. The information from each pulsar candidate is synthesized in four diagnostic plots, which consist of image data with up to thousands of pixels. The AI takes these data from each candidate as its input and uses thousands of such candidates to train its ∼9000 neurons. The deep neural networks in this AI system grant it superior ability to recognize various types of pulsars as well as their harmonic signals. The trained AI's performance has been validated with a large set of candidates from a different pulsar survey, the Green Bank North Celestial Cap survey. In this completely independent test, the PICS ranked 264 out of 277 pulsar-related candidates, including all 56 previously known pulsars and 208 of their harmonics, in the top 961 (1%) of 90,008 test candidates, missing only 13 harmonics. The first non-pulsar candidate appears at rank 187, following 45 pulsars and 141 harmonics. In other words, 100% of the pulsars were ranked in the top 1% of all candidates, while 80% were ranked higher than any noise or interference. The performance of this system can be improved over time as more training data are accumulated. This AI system has been integrated into the PALFA survey pipeline and has discovered six new pulsars to date.
On the Extended Emission of the Anomalous X-ray Pulsar IE 1547.0-5408
We present an analysis of the extended emission around the anomalous X-ray pulsar IE 1547.0-5408 using four XMM-Newton observations taken with the source in varying states of outburst as well as in quiescence. We find that the extended emission flux is highly variable and strongly correlated with the flux of the magnetar. Based on this result, as well as on spectral and energetic considerations, we conclude that the extended emission is dominated by a dust-scattering halo and not a pulsar wind nebula (P-VVN), as has been previously argued. We obtain an upper limit on the 2-10 keV flux of a possible PWN of 4.7 x 10(exp -14) erg/s/sq cm, three times less than the previously claimed value, implying an efficiency for conversion of spin-down energy into nebular luminosity of <9 x 10(exp -4) .