arXiv subjects

Zong-Kuan Guo

Publications and source records attributed to Zong-Kuan Guo.

At least 73 records · Page 4Linked to original sources

arXiv2024

Phase transition catalyzed by primordial black holes

We investigate the first-order phase transition catalyzed by primordial black holes~(PBHs) in the early Universe. We find that super-horizon curvature perturbations generated in this scenario lead to the production of gravitational waves when the scalar modes re-enter the horizon. If PBHs with masses about $10^{-13}M_{\odot}$ constitute all dark matter, the first-order electroweak phase transition catalyzed by PBHs can explain the gravitational wave signal observed by pulsar timing array collaborations without the overproduction of PBHs.

astro-ph.CO↗

arXiv2024

Premerger detection of massive black hole binaries using deep learning

Coalescing massive black hole binaries (MBHBs) are one of primary sources for space-based gravitational wave (GW) observations. The mergers of these binaries are expected to give rise to detectable electromagnetic (EM) emissions with a narrow time window. The premerger detection of GW signals is vital for follow-up EM observations. The conventional approach for searching GW signals involves high computational costs. In this study, we present a deep learning model to search for GW signals from MBHBs. Our model is able to process 4.7 days of simulated data within 0.01 seconds and detect GW signals several hours to days before the final merger. The model provides the possibility of the coincident GW and EM detection of MBHBs.

astro-ph.IM↗

arXiv2024

Constraints on Einstein-dilaton Gauss-Bonnet gravity with Taiji

In the 2030s, space-based gravitational-wave (GW) detectors will exhibit unprecedented sensitivity in the millihertz frequency band, greatly expanding the potential for testing theories of gravity compared to ground-based GW detectors. Inspired by effective string theory, Einstein-dilaton Gauss-Bonnet (EdGB) gravity introduces an extra dilaton scalar field that is directly coupled to higher curvature terms. Here, we investigate the capability of Taiji to constrain the parameters of EdGB gravity by analyzing GWs from massive black hole binaries (MBHBs). We utilize the parameterized post-Einsteinian (ppE) waveform with the leading order EdGB corrections for the inspiral phase of MBHBs. The constraints on the coupling constants are obtained by performing Fisher matrix analysis. With different mass ratios and spins $χ_i$ at redshifts $z=2,3,4,5$, the $1σ$ bounds on the parameter $α$ have the same order of magnitude: $\sqrtα\sim 10^7$m.

gr-qc↗

arXiv2024

WaveFormer: transformer-based denoising method for gravitational-wave data

With the advent of gravitational-wave astronomy and the discovery of more compact binary coalescences, data quality improvement techniques are desired to handle the complex and overwhelming noise in gravitational wave (GW) observational data. Though recent machine learning-based studies have shown promising results for data denoising, they are unable to precisely recover both the GW signal amplitude and phase. To address such an issue, we develop a deep neural network centered workflow, WaveFormer, for significant noise suppression and signal recovery on observational data from the Laser Interferometer Gravitational-Wave Observatory (LIGO). The WaveFormer has a science-driven architecture design with hierarchical feature extraction across a broad frequency spectrum. As a result, the overall noise and glitch are decreased by more than one order of magnitude and the signal recovery error is roughly 1% and 7% for the phase and amplitude, respectively. Moreover, on 75 reported binary black hole (BBH) events of LIGO we obtain a significant improvement of inverse false alarm rate. Our work highlights the potential of large neural networks in gravitational wave data analysis and, while primarily demonstrated on LIGO data, its adaptable design indicates promise for broader application within the International Gravitational-Wave Observatories Network (IGWN) in future observational runs.

gr-qc↗

arXiv2024

Particle production during Inflation with a non-minimally coupled spectator scalar field

We study the inflationary model with a spectator scalar field $χ$ coupled to both the inflaton and Ricci scalar. The interaction between the $χ$ field and the gravity, denoted by $ξRχ^2$, can trigger the tachyonic instability of certain modes of the $χ$ field. As a result, the $χ$ field perturbations are amplified and serve as a gravitational wave (GW) source. When considering the backreaction of the $χ$ field, an upper bound on the coupling parameter $ξ$ must be imposed to ensure that inflation does not end prematurely. In this case, we find that the inflaton's evolution experiences a sudden slowdown due to the production of $χ$ particles, resulting in a unique oscillating structure in the power spectrum of curvature perturbations at specific scales. Moreover, the GW signal induced by the $χ$ field is more significant than primordial GWs at around its peak scale, leading to a noticeable bump in the overall energy spectrum of GWs. It's worth noting that this bump predicted in the slow-roll inflationary scenario is unlikely to be detected by LISA and Taiji, but there is a slim chance it might approach the detection limits of GW experiments like BBO and SKA if we devise distinctive inflatonary potentials.

gr-qc↗

arXiv2023

Enhanced curvature perturbations from spherical domain walls nucleated during inflation

We investigate spherical domain walls~(DWs) nucleated via quantum tunneling in multifield inflationary models and curvature perturbations induced by the inhomogeneous distribution of those DWs. We consider the case that the Euclidean action $S_{E}$ of DWs changes with time during inflation so that most of DWs nucleate when $S_{E}$ reaches the minimum value and the radii of DWs are almost the same. When the Hubble horizon scale exceeds the DW radius after inflation, DWs begin to annihilate and release their energy into background radiation. Because of the random nature of the nucleation process, the statistics of DWs is of the Poisson type and the power spectrum of curvature perturbations has a characteristic slope ${\cal P}_{\cal R}(k)\propto k^{3}$. The amplitude of ${\cal P}_{\cal R}(k)$ depends on the tension and abundance of DWs at the annihilation time while the peak mode depends on the mean separation of DWs. We also numerically obtain the energy spectra of scalar-induced gravitational waves from predicted curvature perturbations which are expected to be observed in multiband gravitational-wave detectors.

astro-ph.CO↗

arXiv2023

Taiji Data Challenge for Exploring Gravitational Wave Universe

The direct observation of gravitational waves (GWs) opens a new window for exploring new physics from quanta to cosmos and provides a new tool for probing the evolution of universe. GWs detection in space covers a broad spectrum ranging over more than four orders of magnitude and enables us to study rich physical and astronomical phenomena. Taiji is a proposed space-based GW detection mission that will be launched in the 2030s. Taiji will be exposed to numerous overlapping and persistent GW signals buried in the foreground and background, posing various data analysis challenges. In order to empower potential scientific discoveries, the Mock LISA Data Challenge and the LISA Data Challenge (LDC) were developed. While LDC provides a baseline framework, the first LDC needs to be updated with more realistic simulations and adjusted detector responses for Taiji's constellation. In this paper, we review the scientific objectives and the roadmap for Taiji, as well as the technical difficulties in data analysis and the data generation strategy, and present the associated data challenges. In contrast to LDC, we utilize second-order Keplerian orbit and second-generation time delay interferometry techniques. Additionally, we employ a new model for the extreme-mass-ratio inspiral waveform and stochastic GW background spectrum, which enables us to test general relativity and measure the non-Gaussianity of curvature perturbations. Furthermore, we present a comprehensive showcase of parameter estimation using a toy dataset. This showcase not only demonstrates the scientific potential of the Taiji Data Challenge but also serves to validate the effectiveness of the pipeline. As the first data challenge for Taiji, we aim to build an open ground for data analysis related to Taiji sources and sciences. More details can be found on the official website at http://taiji-tdc.ictp-ap.org.

gr-qc↗

arXiv2023

Parameter inference for coalescing massive black hole binaries using deep learning

In the 2030s, a new era of gravitational-wave (GW) observations will dawn as multiple space-based GW detectors, such as the Laser Interferometer Space Antenna, Taiji and TianQin, open the millihertz window for GW astronomy. These detectors are poised to detect a multitude of GW signals emitted by different sources. It is a challenging task for GW data analysis to recover the parameters of these sources at a low computational cost. Generally, the matched filtering approach entails exploring an extensive parameter space for all resolvable sources, incurring a substantial cost owing to the generation of GW waveform templates. To alleviate the challenge, we make an attempt to perform parameter inference for coalescing massive black hole binaries (MBHBs) using deep learning. The model trained in this work has the capability to produce 50,000 posterior samples for redshifted total mass, mass ratio, coalescence time and luminosity distance of a MBHB in about twenty seconds. Our model can serve as a potent data pre-processing tool, reducing the volume of parameter space by more than four orders of magnitude for MBHB signals with a signal-to-noise ratio larger than 100. Moreover, the model exhibits robustness when handling input data that contains multiple MBHB signals.

astro-ph.IM↗

arXiv2023

On networks of space-based gravitational-wave detectors

The space-based laser interferometers, LISA, Taiji and TianQin, are targeting to observe milliHz gravitational waves (GWs) in the 2030s. The joint observations from multiple space-based detectors yield significant advantages. In this work, we recap the studies and investigations for the joint space-based GW detector networks to highlight: 1) the high precision of sky localization for the massive binary black hole (BBH) coalescences and the GW sirens in the cosmological implication, 2) the effectiveness to test the parity violation in the stochastic GW background observations, 3) the efficiency of subtracting galactic foreground, 4) the improvement in stellar-mass BBH observations. We inspect alternative networks by trading off massive BBH observations and stochastic GW background observation.

gr-qc↗

arXiv2023

Rapid search for massive black hole binary coalescences using deep learning

The coalescences of massive black hole binaries are one of the main targets of space-based gravitational wave observatories. Such gravitational wave sources are expected to be accompanied by electromagnetic emissions. Low latency detection of the massive black hole mergers provides a start point for a global-fit analysis to explore the large parameter space of signals simultaneously being present in the data but at great computational cost. To alleviate this issue, we present a deep learning method for rapidly searching for signals of massive black hole binaries in gravitational wave data. Our model is capable of processing a year of data, simulated from the LISA data challenge, in only several seconds, while identifying all coalescences of massive black hole binaries with no false alarms. We further demonstrate that the model shows robust resistance to a wide range of generalization cases, including various waveform families and updated instrumental configurations. This method offers an effective approach that combines advances in artificial intelligence to open a new pathway for space-based gravitational wave observations.

astro-ph.IM↗

arXiv2023

Confusion noise from Galactic binaries for Taiji

Gravitational waves (GWs) from tens of millions of compact binaries in our Milky Way enter the milli-Hertz band of space-based detection. The majority of them cannot be resolved individually, resulting in a foreground confusion noise for Laser Interferometer Space Antenna (LISA). The concept of Taiji mission is similar to LISA's with slightly better sensitivity, which means that the galactic GW signals will also affect the detection with Taiji. Here we generate the GW signals from 29.8 million galactic binaries for Taiji and subtract the `resolvable' sources. The confusion noise is estimated and fitted in an analytic form with 6-month, 1-year, 2-year and 4-year observation time. We find that the full sensitivity curve is slightly lower for Taiji than for LISA at frequencies of $\leq 0.8$ mHz and around 2~mHz. For a 4-year lifetime, more than 29 thousand sources are resolvable with Taiji. Compared to LISA, Taiji can subtract $\sim 20 \%$ more sources and the distribution of them in our Milky Way is consistent with that of the resolvable sources with LISA. At frequencies around 2~mHz or with the chirp masses ranging from $0.2 M_\odot$ to $0.4 M_\odot$, more sources become resolvable with Taiji.

astro-ph.IM↗

arXiv2023

Constraints on ultra-slow-roll inflation from the third LIGO-Virgo observing run

The nonattractor evolution in ultra-slow-roll (USR) inflation results in the amplification of superhorizon curvature perturbations and then induces a strong and detectable stochastic gravitational wave background. In this letter, we search for such a stochastic gravitational wave background in data from the third LIGO-Virgo observing run and place constraints on the USR inflationary models. The $e$-folding number of the USR phase are constrained to be $ΔN \lesssim 2.9$ at the 95% confidence level and the power spectrum of curvature perturbations amplified during the USR phase is constrained to be $\log_{10}P_{R\mathrm{p}}<-1.7$ at the scales $2.9\times10^5 ~\mathrm{pc^{-1}} \lesssim k \lesssim 1.7\times10^{11}~\mathrm{pc^{-1}}$. Besides, we forecast the ability of future experiments to constrain USR inflation, and find $P_{R\mathrm{p}}\lesssim 10^{-3.6}$ for LISA and Taiji, $P_{R\mathrm{p}}\lesssim 10^{-3.3}$ for Cosmic Explore and Einstein Telescope, $P_{R\mathrm{p}}\lesssim 10^{-5.5}$ for DECIGO and Big Bang Observer and $P_{R\mathrm{p}}\lesssim 10^{-5.2}$ for Square Kilometre Array.

astro-ph.CO↗

arXiv2023

Testing primordial black hole and measuring the Hubble constant with multiband gravitational-wave observations

There exist two kinds of stochastic gravitational-wave backgrounds associated with the primordial curvature perturbations. One is called induced gravitational wave due to the nonlinear coupling of curvature perturbations to tensor perturbations, while the other is produced by coalescences of binary primordial black holes formed when the large amplitude curvature perturbations reenter the horizon in the radiation dominant era. In this paper we find a quite useful relation for the peak frequencies of these two stochastic gravitational-wave backgrounds. This relation can not only offer a smoking-gun criterion for the existence of primordial black holes, but also provide a method for measuring the Hubble constant $H_0$ by multiband observations of the stochastic gravitational-wave backgrounds.

astro-ph.CO↗

arXiv2022

MLGWSC-1: The first Machine Learning Gravitational-Wave Search Mock Data Challenge

We present the results of the first Machine Learning Gravitational-Wave Search Mock Data Challenge (MLGWSC-1). For this challenge, participating groups had to identify gravitational-wave signals from binary black hole mergers of increasing complexity and duration embedded in progressively more realistic noise. The final of the 4 provided datasets contained real noise from the O3a observing run and signals up to a duration of 20 seconds with the inclusion of precession effects and higher order modes. We present the average sensitivity distance and runtime for the 6 entered algorithms derived from 1 month of test data unknown to the participants prior to submission. Of these, 4 are machine learning algorithms. We find that the best machine learning based algorithms are able to achieve up to 95% of the sensitive distance of matched-filtering based production analyses for simulated Gaussian noise at a false-alarm rate (FAR) of one per month. In contrast, for real noise, the leading machine learning search achieved 70%. For higher FARs the differences in sensitive distance shrink to the point where select machine learning submissions outperform traditional search algorithms at FARs $\geq 200$ per month on some datasets. Our results show that current machine learning search algorithms may already be sensitive enough in limited parameter regions to be useful for some production settings. To improve the state-of-the-art, machine learning algorithms need to reduce the false-alarm rates at which they are capable of detecting signals and extend their validity to regions of parameter space where modeled searches are computationally expensive to run. Based on our findings we compile a list of research areas that we believe are the most important to elevate machine learning searches to an invaluable tool in gravitational-wave signal detection.

astro-ph.IM↗

arXiv2022

Generation of gravitational waves in dynamical Chern-Simons gravity

We investigate gravitational waves (GWs) generated in a two-field inflationary model with a non-canonical kinetic term, in which the gravitational Chern-Simons term is coupled to a heavy dynamical field. In such a model, primordial GWs experience a period of resonant amplification for some modes. In addition, isocurvature perturbations suffer from a temporary tachyonic instability due to an effective negative mass, which source curvature perturbations, resulting in large induced GWs. These two stochastic gravitational wave backgrounds correspond to different frequency bands, which are expected to be detected by future GW detectors such as SKA, LISA and Taiji.

gr-qc↗

arXiv2022

No-go guide for late-time solutions to the Hubble tension: Matter perturbations

The Hubble tension seems to be a crisis with $\sim5σ$ discrepancy between the most recent local distance ladder measurement from type Ia supernovae calibrated by Cepheids and the global fitting constraint from the cosmic microwave background data. To narrow down the possible late-time solutions to the Hubble tension, we have used in a recent study [Phys. Rev. D 105, L021301 (2022)] an improved inverse distance ladder method calibrated by the absolute measurements of the Hubble expansion rate at high redshifts from the cosmic chronometer data, and found no appealing evidence for new physics at the late time beyond the $Λ$CDM model characterized by a parametrization based on the cosmic age. In this paper, we further investigate the perspective of this improved inverse distance ladder method by including the late-time matter perturbation growth data. Independent of the dataset choices, model parametrizations, and diagnostic quantities ($S_8$ and $S_{12}$), the new physics at the late time beyond the $Λ$CDM model is strongly disfavored so that the previous late-time no-go guide for the Hubble tension is further strengthened.

astro-ph.CO↗

arXiv2022

Constraining first-order phase transitions with curvature perturbations

We investigate the curvature perturbations induced by the randomness of the quantum tunneling process during cosmological first-order phase transitions (PTs) and for the first time ultilize curvature perturbations to constrain the PT parameters. We find that the observations of the cosmic microwave background spectrum distortion and the ultracompact minihalo abundance can give strict constraints on the PTs below 100GeV, especially for the low-scale PTs and the weak PTs. The current constraint on the PT parameters is largely extended by the results in this work.

astro-ph.CO↗

arXiv2022

Primordial black hole production during first-order phase transitions

Primordial black holes (PBHs) produced in the early Universe have attracted wide interest for their ability to constitute dark matter and explain the compact binary coalescence. We propose a new mechanism of PBH production during first-order phase transitions (PTs) and find that PBHs are naturally produced during PTs model-independently. Because of the randomness of the quantum tunneling, there always exists some probability that the vacuum decay is postponed in a whole Hubble volume. Since the vacuum energy density remains constant while radiation is quickly redshifted in the expanding Universe, the postponed vacuum decay then results in overdense regions, which finally collapse into PBHs as indicated by numerical simulations. Utilizing this result one can obtain mutual predictions and constraints between PBHs and GWs from PTs. The predicted mass function of PBHs is nearly monochromatic. We investigate two typical cases and find that 1) PBHs from a PT constitute all dark matter and GWs peak at $1$Hz, 2) PBHs from a PT can explain the coalescence events observed by LIGO-Virgo collaboration, and meanwhile GWs can explain the common-spectrum process detected by NANOGrav collaboration.

astro-ph.CO↗