Residual test for the third gravitational-wave transient catalog

A spinning neutron star (NS) that is asymmetric with respect to its spin axis can emit continuous gravitational wave (GW) signals. The spin frequencies and their distribution of radio millisecond pulsars (MSPs) and accreting MSPs provide some evidences of GW radiation, and MSPs are ideal probes detecting high frequency GW signals. It is generally thought that MSPs originate from the recycled process, in which the NS accretes the material and angular momentum from the donor star. The accreted matter would be confined at the polar cap zone by an equatorial belt of compressed magnetic field fixed in the deep crust of the NS, and yields "magnetic mountain". Based on an assumption that the spin-down rates of three transitional MSPs including PSR J1023+0038 are the combinational contribution of the accretion torque, the propeller torque, and the GW radiation torque, in this work we attempt to constrain the ellipticities of MSPs with observed spin-down rates. Assuming some canonical parameters of NSs, the ellipticities of three transitional MSPs and ten redbacks are estimated to be $\epsilon=(0.9-23.4)\times 10^{-9}$. The electrical resistivities of three transitional MSPs are also derived to be in the range $\eta=(1.2-15.3)\times 10^{-31}~\rm s$, which display an ideal power law relation with the accretion rate. The characteristic strains ($h_{\rm c}=(0.6-2.5)\times10^{-27}$) of GW signals emitting by these sources are obviously beyond the sensitivity scope of the aLIGO. We expect that the third-generation GW detectors like the Einstein Telescope can seize the GW signals from these sources in the future.

In this work, we assess the sensitivity reach of pulsar timing array (PTA) measurements to probe pointlike primordial black holes (PBHs), with an extended mass distribution, which originate from collapsed Fermi balls that are formed through the aggregation of asymmetric U(1) dark fermions trapped within false vacuum bubbles during a dark first order phase transition (FOPT). The PBH formation scenario is mainly characterized by the dark asymmetry, strength of the FOPT, rate of FOPT, and the percolation temperature. Meanwhile, for PBH masses of interest lying within 10−10M⊙ − 102M⊙, the relevant signal for PTA measurements is the Doppler phase shift in the timing signal, due to the velocity change induced by transiting PBHs on pulsars. Taking the dark asymmetry parameter to be 10−4 and 10−5, we find that percolation temperatures within the 0.1 − 10 keV range, FOPT rates above 103 times the Hubble parameter at percolation, and FOPT strengths within 10−6 − 0.1 can give rise to PBHs that can be probed by an SKA-like PTA observation. On the other hand, the accompanying gravitational wave (GW) signal from the FOPT can be used as a complementary probe, assuming that the peak frequency lies within the \U0001d4aa(10−10) − \U0001d4aa(10−7) Hz range, and the peak GW abundance is above the peak-integrated sensitivity curves associated with pulsar timing observations that search for stochastic GWs. At the fundamental level, a quartic effective potential for a dark scalar field can trigger the FOPT. By performing a parameter scan, we obtained the class of effective potentials that lead to FOPT scenarios that can be probed by SKA through pulsar timing and GW observations.

We describe updates and improvements to the BayesWave gravitational wave transient analysis pipeline, and provide examples of how the algorithm is used to analyze data from ground-based gravitational wave detectors. BayesWave models gravitational wave signals in a morphology-independent manner through a sum of frame functions, such as Morlet-Gabor wavelets or chirplets. BayesWave models the instrument noise using a combination of a parametrized Gaussian noise component and nonstationary and non-Gaussian noise transients. Both the signal model and noise model employ trans-dimensional sampling, with the complexity of the model adapting to the requirements of the data. The flexibility of the algorithm makes it suitable for a variety of analyses, including reconstructing generic unmodeled signals; cross-checks against modeled analyses for compact binaries; as well as separating coherent signals from incoherent instrumental noise transients (glitches). The BayesWave model has been extended to account for gravitational wave signals with generic polarization content and the simultaneous presence of signals and glitches in the data. We describe updates in the BayesWave prior distributions, sampling proposals, and burn-in stage that provide significantly improved sampling efficiency. We present standard review checks indicating the robustness and convergence of the BayesWave trans-dimensional sampler.

We present gravitational wave (GW) signal predictions from four 3D multi-group neutrino hydrodynamics simulations of core-collapse supernovae of progenitors with 11.2 Msun, 20 Msun, and 27 Msun. GW emission in the pre-explosion phase strongly depends on whether the post-shock flow is dominated by the standing accretion shock instability (SASI) or convection and differs considerably from 2D models. SASI activity produces a strong signal component below 250 Hz through asymmetric mass motions in the gain layer and a non-resonant coupling to the proto-neutron star (PNS). Both convection- and SASI-dominated models show GW emission above 250 Hz, but with considerably lower amplitudes than in 2D. This is due to a different excitation mechanism for high-frequency l=2 motions in the PNS surface, which are predominantly excited by PNS convection in 3D. Resonant excitation of high-frequency surface g-modes in 3D by mass motions in the gain layer is suppressed compared to 2D because of smaller downflow velocities and a lack of high-frequency variability in the downflows. In the exploding 20 Msun model, shock revival results in enhanced low-frequency emission due to a change of the preferred scale of the convective eddies in the PNS convection zone. Estimates of the expected excess power in two frequency bands suggests that second-generation detectors will only be able to detect very nearby events, but that third-generation detectors could distinguish SASI- and convection-dominated models at distances of ~10 kpc.

The standard Cramer-von Mises and Anderson-Darling goodness-of-fit tests require continuous underlying distributions with known parameters. In this paper, tables of critical values are generated for both tests for Weibull distributions with unknown location and scale parameters and known shape parameters. The powers of the Cramer-von Mises, Anderson-Darling, Kolmogorov-Smirnov, and Chi-Square tests for this situation are investigated. The Cramer-von Mises test has most power when the shape is 1.0 and the Anderson-Darling test has most power when the shape is 3.5. Finally, a relation between critical value and inverse shape parameter is presented.

The Einstein Telescope is a third-generation gravitational wave detector which is expected to be an order of magnitude more sensitive than the current detectors. While the current detectors enabled various measurements which were first of their kind (such as the strong field test of general relativity, an independent measurement of the Hubble constant, probing the dense nuclear matter inside the neutron stars, and many more), the proposed third-generation detectors may not only bring about unprecedented accuracy and precision to these measurements but also enable new first-of-their-kind measurements which may be outside the reach of current detectors (the detection of primordial black holes or phase transitions in the neutron star matter, for example). While the improvement in the sensitivity is desirable, it also makes it more difficult to extract physics-related insights from data. Of particular concern are transient, instrumental noise sources (also known as glitches) overlapping with the gravitational wave signal(s). For the third-generation detectors, we expect many more glitches to overlap with the signals compared to the current scenario, making it crucial to develop a methodology which can reliably “de-glitch” the data without corrupting the underlying signal. To address this challenge, we develop a novel framework which can accurately remove glitches overlapping with gravitational wave signals. The framework is unique to the triangular geometry of the Einstein Telescope, i.e., it cannot be realised for other proposed geometries such as the two distant, mis-aligned L-shaped detectors. Exploiting the triangular geometry, our framework outperforms the traditional methodology of de-glitching the signals used for L-shaped detector networks, showcasing a clear edge of the triangle geometry over the geometries. In this context, our work stands to play an important role in the design studies related to the Einstein Telescope, underway at the time of writing of this thesis. Bayesian parameter inference plays a key role in the measurements of the source parameters (such as masses, spins, sky-location, and distance) of a gravitational wave signal. Increasing costs of Bayesian parameter inference is another challenge posed by the improved sensitivity of the detectors. To address this challenge, we develop a relative-binning based framework to reduce the cost of Bayesian inferences. We benchmark our methodology on a large number of real as well as simulated signals for the current and next generation detectors. We also test the validity of our rapid inference framework on overlapping signals and lensed gravitational wave signals. In addition, we perform simulation to demonstrate how gravitational lensing can help constrain gravitational wave propagation beyond general relativity.

The gravitational wave signals from coalescing Supermassive Black Hole Binaries are prime targets for the Laser Interferometer Space Antenna (LISA). With optimal data processing techniques, the LISA observatory should be able to detect black hole mergers anywhere in the Universe. The challenge is to find ways to dig the signals out of a combination of instrument noise and the large foreground from stellar mass binaries in our own galaxy. The standard procedure of matched filtering against a grid of templates can be computationally prohibitive, especially when the black holes are spinning or the mass ratio is large. Here we develop an alternative approach based on Metropolis-Hastings sampling and simulated annealing that is orders of magnitude cheaper than a grid search. For the first time, we show that it is possible to detect and characterize the signals from binary systems of Schwarzschild Black Holes that are embedded in instrument noise and a foreground containing millions of galactic binaries. Our technique is computationally efficient, robust, and applicable to both high and low signal-to-noise ratio systems.

To obtain the eigenfrequencies of a protoneutron star (PNS) in the postbounce phase of core-collapse supernovae (CCSNe), we perform a linear perturbation analysis of the angle-averaged PNS profiles using results from a general relativistic CCSN simulation of a $15 M_{\odot}$ star. In this work, we investigate how the choice of the outer boundary condition could affect the PNS oscillation modes in the linear analysis. By changing the density at the outer boundary of the PNS surface in a parametric manner, we show that the eigenfrequencies strongly depend on the surface density. By comparing with the gravitational wave (GW) signatures obtained in the hydrodynamics simulation, the so-called surface $g$-mode of the PNS can be well ascribed to the fundamental oscillations of the PNS. The frequency of the fundamental oscillations can be fitted by a function of the mass and radius of the PNS similar to the case of cold neutron stars. In the case that the position of the outer boundary is chosen to cover not only the PNS but also the surrounding postshock region, we obtain the eigenfrequencies close to the modulation frequencies of the standing accretion-shock instability (SASI). However, we point out that these oscillation modes are unlikely to have the same physical origin of the SASI modes seen in the hydrodynamics simulation. We discuss possible limitations of applying the angle-averaged, linear perturbation analysis to extract the full ingredients of the CCSN GW signatures.

UV inactivation and model of UV inactivation of foot-and-mouth disease viruses in suspension

We present axisymmetric hydrodynamical simulations of accretion-induced collapse (AIC) of dark matter (DM) admixed rotating white dwarfs (WD) and their burst gravitational-wave (GW) signals. For initial WD models with the same central baryon density, the admixed DM is found to delay the plunge and bounce phases of AIC, and decrease the central density and mass of the protoneutron star (PNS) produced. The bounce time, central density, and PNS mass generally depend on two parameters, the admixed DM mass M DM and the ratio between the rotational kinetic and gravitational energies of the inner core at bounce . The emitted GWs have generic waveform shapes and the variation of their amplitudes h + show a degeneracy on and M DM. We found that the ratios between the GW amplitude peaks around bounce allow breaking of the degeneracy and extraction of both and M DM. Even within the uncertainties of the nuclear matter equation of state, a DM core can be inferred if its mass is greater than 0.03 M ⊙. We also discuss possible DM effects on the GW signals emitted by PNS g-mode oscillations. GWs may boost the possibility for the detection of AIC, as well as open a new window into the indirect detection of DM.

We compare gravitational-wave (GW) signals from eight 3D simulations of core-collapse supernovae, using two different progenitors with zero-age main-sequence masses of 9 and 20 solar masses (M⊙). The collapse of each progenitor was simulated four times, at two different grid resolutions and with two different neutrino transport methods, using the aenus-alcar code. The main goal of this study is to assess the validity of recent concerns that the so-called ‘Ray-by-Ray+’ (RbR+) approximation is problematic in core-collapse simulations and can adversely affect theoretical GW predictions. Therefore, signals from simulations using RbR+ are compared to signals from corresponding simulations using a fully multidimensional (FMD) transport scheme. The 9 M⊙ progenitor successfully explodes, whereas the 20 M⊙ model does not. Both the standing accretion shock instability and hot-bubble convection develop in the post-shock layer of the non-exploding models. In the exploding models, neutrino-driven convection in the post-shock flow is established around 100 ms after core bounce and lasts until the onset of shock revival. We can, therefore, judge the impact of the numerical resolution and neutrino transport under all conditions typically seen in non-rotating core-collapse simulations. We find excellent qualitative agreement in all GW features. We find minor quantitative differences between simulations, but find no systematic differences between simulations using different transport schemes. Resolution-dependent differences in the hydrodynamic behaviour of low-resolution and high-resolution models have a greater impact on the GW signals than consequences of the different transport methods. Furthermore, increasing the resolution decreases the discrepancies between models with different neutrino transport.

Time delay interferometry combination with zero-response

Detecting imprints of orbital eccentricity in gravitational-wave (GW) signals promises to shed light on the formation mechanisms of binary black holes. To constrain the formation mechanisms, distributions of eccentricity derived from numerical simulations of astrophysical formation channels are compared to the estimates of eccentricity inferred from GW signals. We report that the definition of eccentricity typically used in astrophysical simulations is inconsistent with the one used while modeling GW signals, with the differences mainly arising due to the choice of reference frequency used in both cases. We also posit a prescription for calculating eccentricity from astrophysical simulations, by evolving ordinary differential equations obtained from post-Newtonian theory and using the dominant (ℓ = m = 2) mode’s frequency as the reference frequency; this ensures consistency in the definitions. On comparing the existing eccentricities of the binaries present in the Cluster Monte Carlo catalog of globular cluster simulations with the eccentricities calculated using the prescription presented here, we find a significant discrepancy at e ≳ 0.2; this discrepancy becomes worse with increasing eccentricity. We note the implications this discrepancy has for existing studies and recommend that care be taken when comparing data-driven constraints on eccentricity to expectations from astrophysical formation channels.

Five conventional tests (Shapiro-Wilk test, Kolmogorov-Smirnov test, Cramer-von Mises test, Anderson-Darling test and Chi-Square test) were carried out in this paper to learn the probability distribution of fracture energy of FRP-concrete interface under the environment of dry-wet cycling at high temperature. The relationship between interfacial fracture energy and the number of cycles was established through nonlinear regression analysis. Then the reliability index and the probability of deterioration of FRP-concrete interface that uses experimental data as design values were analyzed according to the reliability theory. It is shown that the optimum distribution of interfacial fracture energy is lognormal distribution, and the relationship between logarithmic mean value of interfacial fracture energy and number of cycles is subject to the exponential function. As the cycle number increases, reliability index decreases rapidly while the probability of deterioration the other way around in the beginning, yet both are stabilized at a certain level eventually. The probability of deterioration has reached a high value in a few cycles in experiments.

Exploring travel time distribution and variability patterns is essential for reliable route choices and sophisticated traffic management and control. State-of-the-art studies tend to treat different types of roads equally, which fails to provide more detailed analysis of travel time characteristics for each specific road type. In this study, based on a vast amount of probe vehicle data, 200 links inside the Third Ring Road of Beijing, China, were investigated. Four types of roads were covered including urban expressways, auxiliary roads of urban expressways, major roads, and secondary roads. The day-of-week distributions of unit distance travel time were first analyzed. Kolmogorov-Smirnov test, Anderson-Darling test, and chi-squared test were employed to test the goodness-of-fit of different distributions and the results showed lognormal distribution was best-fitted for different time periods and road types compared with normal, gamma, and Weibull distribution. In addition, four reliability measures, that is, unit distance travel time, coefficient of variation, buffer time index, and punctuality rate, were used to explore the day-of-week travel time variability patterns. The results indicated that urban expressways, auxiliary roads of urban expressways, and major roads have regular and distinct morning and afternoon peaks on weekdays. It is noteworthy that in daytime the travel times on auxiliary roads of urban expressways and major roads share similar variability patterns and appear relatively stable and reliable, while urban expressways have most reliable travel times at night. The results of analysis help enable a better understanding of the volatile travel time characteristics of each road type in urban network.