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Nikolaos Stergioulas

Publications and source records attributed to Nikolaos Stergioulas.

At least 37 records · Page 2Linked to original sources
arXiv2023

Exploring the Potential for Detecting Rotational Instabilities in Binary Neutron Star Merger Remnants with Gravitational Wave Detectors

We explore the potential for detecting rotational instabilities in the post-merger phase of binary neutron star mergers using different network configurations of upgraded and next-generation gravitational wave detectors. Our study employs numerically generated post-merger waveforms, which reveal the re-excitation of the $l=m=2$ $f$-mode at a time of $O(10{\rm})$ms after merger. We evaluate the detectability of these signals by injecting them into colored Gaussian noise and performing a reconstruction as a sum of wavelets using Bayesian inference. Computing the overlap between the reconstructed and injected signal, restricted to the instability part of the post-merger phase, we find that one could infer the presence of rotational instabilities with a network of planned 3rd-generation detectors, depending on the total mass and distance to the source. For a recently suggested high-frequency detector design, we find that the instability part would be detectable even at 200 Mpc, significantly increasing the anticipated detection rate. For a network consisting of the existing HLV detectors, but upgraded to twice the A+ sensitivity, we confirm that the peak frequency of the whole post-merger gravitational-wave emission could be detectable with a network signal-to-noise ratio of 8 at a distance of 40Mpc.

gr-qc↗
arXiv2023

Heavy-tailed likelihoods for robustness against data outliers: Applications to the analysis of gravitational wave data

In recent years, the field of Gravitational Wave Astronomy has flourished. With the advent of more sophisticated ground-based detectors and space-based observatories, it is anticipated that Gravitational Wave events will be detected at a much higher rate in the near future. One of the future data analysis challenges is performing robust statistical inference in the presence of detector noise transients or non-stationarities, as well as in the presence of stochastic Gravitational Wave signals of possible astrophysical and/or cosmological origin. The incomplete knowledge of the total noise of the observatory can introduce challenges in parameter estimation of detected sources. In this work, we propose a heavy-tailed, Hyperbolic likelihood, based on the Generalized Hyperbolic distribution. With the Hyperbolic likelihood we obtain a robust data analysis framework against data outliers, noise non-stationarities, and possible inaccurate modeling of the noise power spectral density. We apply this methodology to examples drawn from gravitational wave astronomy, and in particular to synthetic data sets from the planned LISA mission.

gr-qc↗
arXiv2023

Eryn : A multi-purpose sampler for Bayesian inference

In recent years, methods for Bayesian inference have been widely used in many different problems in physics where detection and characterization are necessary. Data analysis in gravitational-wave astronomy is a prime example of such a case. Bayesian inference has been very successful because this technique provides a representation of the parameters as a posterior probability distribution, with uncertainties informed by the precision of the experimental measurements. During the last couple of decades, many specific advances have been proposed and employed in order to solve a large variety of different problems. In this work, we present a Markov Chain Monte Carlo (MCMC) algorithm that integrates many of those concepts into a single MCMC package. For this purpose, we have built {\tt Eryn}, a user-friendly and multipurpose toolbox for Bayesian inference, which can be utilized for solving parameter estimation and model selection problems, ranging from simple inference questions, to those with large-scale model variation requiring trans-dimensional MCMC methods, like the LISA global fit problem. In this paper, we describe this sampler package and illustrate its capabilities on a variety of use cases.

astro-ph.IM↗
arXiv2023

The Laser Interferometer Space Antenna mission in Greece White Paper

The Laser Interferometer Space Antenna (LISA) mission, scheduled for launch in the mid-2030s, is a gravitational wave observatory in space designed to detect sources emitting in the millihertz band. LISA is an ESA flagship mission, currently entering the Phase B development phase. It is expected to help us improve our understanding about our Universe by measuring gravitational wave sources of different types, with some of the sources being at very high redshifts $z\sim 20$. On the 23rd of February 2022 we organized the 1$^\mathrm{st}$ {\it LISA in Greece Workshop}. This workshop aimed to inform the Greek scientific and tech industry community about the possibilities of participating in LISA science and LISA mission, with the support of the Hellenic Space Center (HSC). In this white paper, we summarize the outcome of the workshop, the most important aspect of it being the inclusion of $15$ Greek researchers to the LISA Consortium, raising our total number to $22$. At the same time, we present a road-map with the future steps and actions of the Greek Gravitational Wave community with respect to the future LISA mission.

gr-qc↗
arXiv2023

A Bayesian investigation of the neutron star equation-of-state vs. gravity degeneracy

Despite its elegance, the theory of General Relativity is subject to experimental, observational, and theoretical scrutiny to arrive at tighter constraints or an alternative, more preferred theory. In alternative gravity theories, the macroscopic properties of neutron stars, such as mass, radius, tidal deformability, etc. are modified. This creates a degeneracy between the uncertainties in the equation of state (EoS) and gravity since assuming a different EoS can be mimicked by changing to a different theory of gravity. We formulate a hierarchical Bayesian framework to simultaneously infer the EoS and gravity parameters by combining multiple astrophysical observations. We test this framework for a particular 4D Horndeski scalar-tensor theory originating from higher-dimensional Einstein-Gauss-Bonnet gravity and a set of 20 realistic EoS and place improved constraints on the coupling constant of the theory with current observations. Assuming a large number of observations with upgraded or third-generation detectors, we find that the $A+$ upgrade could place interesting bounds on the coupling constant of the theory, whereas with the LIGO Voyager upgrade or the third-generation detectors (Einstein Telescope and Cosmic Explorer), the degeneracy between EoS and gravity could be resolved with high confidence, even for small deviations from GR.

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arXiv2023

A neural-network-based surrogate model for the properties of neutron stars in 4D Einstein-Gauss-Bonnet gravity

Machine learning and artificial neural networks (ANNs) have increasingly become integral to data analysis research in astrophysics due to the growing demand for fast calculations resulting from the abundance of observational data. Simultaneously, neutron stars and black holes have been extensively examined within modified theories of gravity since they enable the exploration of the strong field regime of gravity. In this study, we employ ANNs to develop a surrogate model for a numerical iterative method to solve the structure equations of NSs within a specific 4D Einstein-Gauss-Bonnet gravity framework. We have trained highly accurate surrogate models, each corresponding to one of twenty realistic EoSs. The resulting ANN models predict the mass and radius of individual NS models between 10 and 100 times faster than the numerical solver. In the case of batch processing, we demonstrated that the speed up is several orders of magnitude higher. We have trained additional models where the radius is predicted for specific masses. Here, the speed up is considerably higher since the original numerical code that constructs the equilibrium models would have to do additional iterations to find a model with a specific mass. Our ANN models can be used to speed up Bayesian inference, where the mass and radius of equilibrium models in this theory of gravity are required.

gr-qc↗
arXiv2023

Deep Residual Error and Bag-of-Tricks Learning for Gravitational Wave Surrogate Modeling

Deep learning methods have been employed in gravitational-wave astronomy to accelerate the construction of surrogate waveforms for the inspiral of spin-aligned black hole binaries, among other applications. We face the challenge of modeling the residual error of an artificial neural network that models the coefficients of the surrogate waveform expansion (especially those of the phase of the waveform) which we demonstrate has sufficient structure to be learnable by a second network. Adding this second network, we were able to reduce the maximum mismatch for waveforms in a validation set by 13.4 times. We also explored several other ideas for improving the accuracy of the surrogate model, such as the exploitation of similarities between waveforms, the augmentation of the training set, the dissection of the input space, using dedicated networks per output coefficient and output augmentation. In several cases, small improvements can be observed, but the most significant improvement still comes from the addition of a second network that models the residual error. Since the residual error for more general surrogate waveform models (when e.g., eccentricity is included) may also have a specific structure, one can expect our method to be applicable to cases where the gain in accuracy could lead to significant gains in computational time.

astro-ph.IM↗
arXiv2023

Deep Residual Networks for Gravitational Wave Detection

Traditionally, gravitational waves are detected with techniques such as matched filtering or unmodeled searches based on wavelets. However, in the case of generic black hole binaries with non-aligned spins, if one wants to explore the whole parameter space, matched filtering can become impractical, which sets severe restrictions on the sensitivity and computational efficiency of gravitational-wave searches. Here, we use a novel combination of machine-learning algorithms and arrive at sensitive distances that surpass traditional techniques in a specific setting. Moreover, the computational cost is only a small fraction of the computational cost of matched filtering. The main ingredients are a 54-layer deep residual network (ResNet), a Deep Adaptive Input Normalization (DAIN), a dynamic dataset augmentation, and curriculum learning, based on an empirical relation for the signal-to-noise ratio. We compare the algorithm's sensitivity with two traditional algorithms on a dataset consisting of a large number of injected waveforms of non-aligned binary black hole mergers in real LIGO O3a noise samples. Our machine-learning algorithm can be used in upcoming rapid online searches of gravitational-wave events in a sizeable portion of the astrophysically interesting parameter space. We make our code, AResGW, and detailed results publicly available at https://github.com/vivinousi/gw-detection-deep-learning .

gr-qc↗
arXiv2023

Differentially rotating scalarized neutron stars with realistic post-merger profile

The merger remnant of a binary neutron star coalescence is initially strongly differentially rotating. Some properties of these remnants can be accurately modeled through building equilibrium neutron star models. In the present paper, we study how a modification of general relativity, namely scalar-tensor theory with a massive scalar field, will alter the picture. In contrast to previous studies, we implement a realistic phenomenological differential rotational law which allows for neutron star models to attain maximal angular velocity away from the center. We find that solutions with much higher masses and angular momenta exist in scalar-tensor theory compared to general relativity. They keep their quasi-spherical energy-density distribution for significantly higher values of the angular momentum before transitioning to quasi-toroidal models, in contrast to pure general relativity. Constructing such neutron star solutions is the first step to our final goal that is studying how scalarization alters the stability and gravitational wave emission of post-merger remnants.

gr-qc↗
arXiv2022

Gravitational Waves from Double White Dwarfs as probes of the Milky Way

Future gravitational wave detectors, such as the Laser Interferometer Space Antenna (\textit{LISA}), will be able to resolve a significant number of the ultra compact stellar-mass binaries in our own Galaxy and its neighborhood. These will be mostly double white dwarf (DWD) binaries, and their underlying population characteristics can be directly correlated to the different properties of the Galaxy. In particular, with \textit{LISA} we will be able to resolve $\sim\mathcal{O}(10^4)$ binaries, while the rest will generate a confusion foreground signal. Analogously to how the total electromagnetic radiation emitted by a galaxy can be related to the underlying total stellar mass, in this work we propose a framework to infer the same quantity by investigating the spectral shape and amplitude of the confusion foreground signal. For a fixed DWD evolution model, and thus a fixed binary fraction, we retrieve percentage-level relative errors on the total stellar mass, which improves for increasing values of the mass. At the same time, we find that variations in the Milky Way shape, at a fixed mass and at scale heights smaller than 500~pc, are not distinguishable based on the shape of stochastic signal alone. We perform this analysis on simulations of the LISA data, estimating the resolvable sources based on signal-to-noise criteria. Finally, we utilize the catalogue of resolvable sources to probe the characteristics of the underlying population of DWD binaries. We show that the DWD frequency, coalescence time and chirp mass (up to $<0.7\,$M$_\odot$) distributions can be reconstructed from \textit{LISA} data with no bias.

astro-ph.GA↗
arXiv2022

Thermonuclear and Electron-Capture Supernovae from Stripped-Envelope Stars

(abridged) When stripped from their hydrogen-rich envelopes, stars with initial masses between $\sim$7 and 11 M$_\odot$ develop massive degenerate cores and collapse. Depending on the final structure and composition, the outcome can range from a thermonuclear explosion, to the formation of a neutron star in an electron-capture supernova (ECSN). It has been recently demonstrated that stars in this mass range may initiate explosive oxygen burning when their central densities are still below $ρ_{\rm c} \lesssim 10^{9.6}$ g cm$^{-3}$. This makes them interesting candidates for type Ia supernovae -- which we call (C)ONe SNe Ia -- and might have broader implications for the formation of neutron stars via ECSNe. Here, we model the evolution of 252 helium stars with initial masses in the $0.8-3.5$ M$_\odot$ range, and metallicities between $Z=10^{-4}$ and $0.02$. We use these models to constrain the central densities, compositions and envelope masses at the time of explosive oxygen ignition. We further investigate the sensitivity of these properties to mass loss rate assumptions using additional models with varying wind efficiencies. We find that helium stars with masses between $\sim$1.8 and 2.7 M$_\odot$ evolve onto $1.35-1.37$ M$_\odot$ (C)ONe cores that initiate explosive burning at central densities between $\rm \log_{10}(ρ_c)\sim 9.3$ and 9.6. We constrain the amount of residual carbon retained after core carbon burning, and conclude that it plays a critical role in determining the final outcome: Chandrasekhar-mass degenerate cores that retain more than $\sim 0.005$ M$_\odot$ of carbon result in (C)ONe SNe Ia, while those with lower carbon mass become ECSNe. We find that (C)ONe SNe Ia are more likely to occur at high metallicities, whereas at low metallicities ECSNe dominate.

astro-ph.HE↗
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

Snowmass 2021 Cosmic Frontier White Paper: The Dense Matter Equation of State and QCD Phase Transitions

Our limited understanding of the physical properties of matter at ultra-high density, high proton/neutron number asymmetry, and low temperature is presently one of the major outstanding problems in physics. As matter in this extreme state is known to only exist stably in the cores of neutron stars (NSs), complementary measurements from electromagnetic and gravitational wave astrophysical observations of NSs, combined with terrestrial laboratory constraints and further theoretical investigations, hold the promise to provide important insight into the properties of matter in a region of the quantum chromodynamics phase space that is otherwise inaccessible. This multidisciplinary endeavor imposes the following requirements for facilities and resources in the upcoming decade and beyond: * A next generation of gravitational wave detectors to uncover more double NS and neutron star-black hole mergers; * Sensitive radio telescopes to find the most massive and fastest spinning NSs; * Large-area, high-time-resolution and/or high angular resolution X-ray telescopes to constrain the NS mass-radius relation; * Suitable laboratory facilities for nuclear physics experiments to constrain the dense matter equation of state; * Funding resources for theoretical studies of matter in this regime; * The availability of modern large-scale high performance computing infrastructure. The same facilities and resources would also enable significant advances in other high-profile fields of inquiry in modern physics such as the nature of dark matter, alternative theories of gravity, nucleon superfluidity and superconductivity, as well as an array of astrophysics, including but not limited to stellar evolution, nucleosynthesis, and primordial black holes.

astro-ph.HE↗
arXiv2022

Models of binary neutron star remnants with tabulated equations of state

The emergence of novel differential rotation laws that can reproduce the rotational profile of binary neutron star merger remnants has opened the way for the construction of equilibrium models with properties that resemble those of remnants in numerical simulations. We construct models of merger remnants, using a recently introduced 4-parameter differential rotation law and three tabulated, zero-temperature equations of state. The models have angular momenta that are determined by empirical relations, constructed through numerical simulations. After a systematic exploration of the parameter space of merger remnant equilibrium sequences, which includes the determination of turning points along constant angular momentum sequences, we find that a particular rotation law can reproduce the threshold mass to prompt collapse to a black hole with a relative difference of only $\sim 1\%$ with respect to numerical simulations, in all cases considered. Furthermore, our results indicate a possible correlation between the compactness of equilibrium models of remnants at the threshold mass and the compactness of maximum-mass nonrotating models. Another key prediction of binary neutron star merger simulations is a relatively slowly rotating inner region, where the angular velocity $Ω$ (as measured by an observer at infinity) is mostly due to the frame dragging angular velocity $ω$. In our investigation of the parameter space of the adopted differential rotation law, we naturally find quasi-spherical (Type A) remnant models with this property. Our investigation clarifies the impact of the differential rotation law and of the equation of state on key properties of binary neutron star remnants and lays the groundwork for including thermal effects in future studies.

astro-ph.HE↗
arXiv2022

New Horizons for Fundamental Physics with LISA

The Laser Interferometer Space Antenna (LISA) has the potential to reveal wonders about the fundamental theory of nature at play in the extreme gravity regime, where the gravitational interaction is both strong and dynamical. In this white paper, the Fundamental Physics Working Group of the LISA Consortium summarizes the current topics in fundamental physics where LISA observations of GWs can be expected to provide key input. We provide the briefest of reviews to then delineate avenues for future research directions and to discuss connections between this working group, other working groups and the consortium work package teams. These connections must be developed for LISA to live up to its science potential in these areas.

gr-qc↗
arXiv2022

Analytic models of the spectral properties of gravitational waves from neutron star merger remnants

We present a new analytic model describing gravitational wave emission in the post-merger phase of binary neutron star mergers. The model is described by a number of physical parameters that are related to various oscillation modes, quasi-linear combination tones or non-linear features that appear in the post-merger phase. The time evolution of the main post-merger frequency peak is taken into account and it is described by a two-segment linear expression. The effectiveness of the model, in terms of the fitting factor or, equivalently, the reduction in the detection rate, is evaluated along a sequence of equal-mass simulations of varying mass. We find that all parameters of the analytic model correlate with the total binary mass of the system. For high masses, we identify new spectral features originating from the non-linear coupling between the quasi-radial oscillation and the antipodal tidal deformation, the inclusion of which significantly improves the fitting factors achieved by the model. We can thus model the post-merger gravitational-wave emission with an analytic model that achieves high fitting factors for a wide range of total binary masses. Our model can be used for the detection and parameter estimation of the post-merger phase in upcoming searches with upgraded second-generation detectors, such as aLIGO+ and aVirgo+, with future, third-generation detectors (Einstein Telescope and Cosmic Explorer) or with dedicated, high-frequency detectors.

astro-ph.HE↗
arXiv2022

Astrophysical constraints on compact objects in 4D Einstein-Gauss-Bonnet gravity

We study the properties of compact objects in a particular 4D Horndeski theory originating from higher dimensional Einstein-Gauss-Bonnet gravity. Remarkably, an exact vacuum solution is known. This compact object differs from general relativity mostly in the strong field regime. We discuss some properties of black holes in this framework and investigate in detail the properties of neutron stars, both static and in slow rotation. We find that for relatively modest deviations from general relativity, the secondary object in GW190814 is compatible with being a slowly-rotating neutron star, without resorting to very stiff or exotic equations of state. Remarkably, the equilibrium sequence of neutron stars matches asymptotically to the black hole limit, completetly closing the mass gap between neutron stars and black holes of same radius, although the stability of equilibrium solutions has yet to be determined. As a consequence, there exists a universal endpoint for the neutron star sequence, independent of the equation of state. In light of our results and of current observational constraints, we discuss specific constraints on the coupling constant that parametrizes deviations from general relativity in this theory.

gr-qc↗
arXiv2022

Nonlinear dynamics of oscillating neutron stars in scalar-tensor gravity

The spectrum of oscillating compact objects can be considerably altered in alternative theories of gravity. In particular, it may be enriched by modes with no counterpart in general relativity, tied to the dynamics of additional degrees of freedom generically present in these theories. Detection of these modes, e.g. in the gravitational-wave signal from a binary compact object coalescence, could provide a powerful tool to probe the underlying theory of gravity. To access the potential of such a detection, it is crucial to understand the linear and nonlinear spectral features of dynamically formed, oscillating compact objects in alternative theories of gravity. As a step towards that goal, in this work we present a suite of 1+1 numerical relativity simulations of neutron stars in scalar-tensor theories, we carefully analyze the spectrum of stellar pulsations, and we compare results with expectations from linear perturbation theory. This allows us to build intuition for the case of binary neutron star mergers. Additionally, the models investigated in this work are representatives of two broad classes, in which the scalar field couples either strongly or weakly with the fluid. The distinct phenomenology of the nonlinear dynamics that we identify for each class of models, may find counterparts also in other alternative theories of gravity.

gr-qc↗