arXiv subjects

Jess McIver

Publications and source records attributed to Jess McIver.

31 records · Page 2Linked to original sources

arXiv2022

Report of the Instrumentation Frontier Working Group for Snowmass 2021

Detector instrumentation is at the heart of scientific discoveries. Cutting edge technologies enable US particle physics to play a leading role worldwide. This report summarizes the current status of instrumentation for High Energy Physics (HEP), the challenges and needs of future experiments and indicates high priority research areas. The Snowmass Instrumentation Frontier studies detector technologies and Research and Development (R&D) needed for future experiments in collider physics, neutrino physics, rare and precision physics and at the cosmic frontier. It is divided into more or less diagonal areas with some overlap among a few of them. We lay out five high-level key messages that are geared towards ensuring the health and competitiveness of the US detector instrumentation community, and thus the entire particle physics landscape.

hep-ex↗

arXiv2022

A Rosetta Stone for eccentric gravitational waveform models

Orbital eccentricity is a key signature of dynamical binary black hole formation. The gravitational waves from a coalescing binary contain information about its orbital eccentricity, which may be measured if the binary retains sufficient eccentricity near merger. Dedicated waveforms are required to measure eccentricity. Several models have been put forward, and show good agreement with numerical relativity at the level of a few percent or better. However, there are multiple ways to define eccentricity for inspiralling systems, and different models internally use different definitions of eccentricity, making it difficult to directly compare eccentricity measurements. In this work, we systematically compare two eccentric waveform models, $\texttt{SEOBNRE}$ and $\texttt{TEOBResumS}$, by developing a framework to translate between different definitions of eccentricity. This mapping is constructed by minimizing the relative mismatch between the two models over eccentricity and reference frequency, before evolving the eccentricity of one model to the same reference frequency as the other model. We show that for a given value of eccentricity passed to $\texttt{SEOBNRE}$, one must input a $20$-$50\%$ smaller value of eccentricity to $\texttt{TEOBResumS}$ in order to obtain a waveform with the same empirical eccentricity. We verify this mapping by repeating our analysis for eccentric numerical relativity simulations, demonstrating that $\texttt{TEOBResumS}$ reports a correspondingly smaller value of eccentricity than $\texttt{SEOBNRE}$.

gr-qc↗

arXiv2022

Impact of noise transients on low latency gravitational-wave event localisation

Gravitational-wave (GW) data contains non-Gaussian noise transients called "glitches". During the third LIGO-Virgo observing run about 24% of all gravitational-wave candidates were in the vicinity of a glitch, while even more events could be affected in future observing runs due to increasing detector sensitivity. This poses a problem since glitches can affect the estimation of GW source parameters, including sky localisation, which is crucial to identify an electromagnetic (EM) counterpart. In this paper we present a study that estimates how much sky localisation is affected by a nearby glitch in low latency. We injected binary black hole (BBH), binary neutron star (BNS) and neutron star-black hole (NSBH) signals into data containing three different classes of glitches: blips, thunderstorms and fast scatterings. The impact of these glitches was assessed by estimating the number of tile pointings that a telescope would need to search over until the true sky location of an event is observed. We found that blip glitches affect the localisation of BBH mergers the most; in the most extreme cases a BBH event is completely missed even by a 20 deg$^2$ field-of-view (FOV) telescope. Thunderstorm glitches have the biggest impact on BBH and NSBH events, especially if there is no third interferometer, while BNS events appear to be not affected. Fast scattering glitches impact low latency localisation only for NSBH signals. For two-interferometer network small (FOV=1 deg$^2$) and large (FOV=20 deg$^2$) telescopes are affected, whereas three-interferometer localisation bias is small enough not to affect large (FOV=20 deg$^2$) telescopes.

astro-ph.HE↗

arXiv2022

UniMAP: Model-free detection of unclassified noise transients in LIGO-Virgo data using the Temporal Outlier Factor

Data from current gravitational wave detectors contains a high rate of transient noise (glitches) that can trigger false detections and obscure true astrophysical events. Existing noise-detection algorithms largely rely on model-based methods that may miss noise transients unwitnessed by auxiliary sensors or with exotic morphologies. We propose the Unicorn Multi-window Anomaly-detection Pipeline (UniMAP): a model-free algorithm to identify and characterize transient noise leveraging the Temporal Outlier Factor (TOF) via a multi-window data-resampling scheme. We show this windowing scheme extends the anomaly detection capabilities of the TOF algorithm to resolve noise transients of arbitrary morphology and duration. We demonstrate the efficacy of this pipeline in detecting glitches during LIGO and Virgo's third observing run, and discuss potential applications.

gr-qc↗

arXiv2022

Prospects for measuring off-axis spins of binary black holes with Plus-era gravitational-wave detectors

The mass and spin properties of binary black holes (BBHs) inferred from their gravitational-wave signatures reveal important clues about how these systems form. BBHs originating from isolated binary evolution are expected to have spins preferentially aligned with their orbital angular momentum, whereas there is no such preference in binaries formed via dynamical assembly. The fidelity with which near-future gravitational-wave detectors can measure off-axis spins will have implications for the study of BBH formation channels. In this work, we examine the degree to which the Advanced LIGO Plus (A+) and Advanced Virgo Plus (AdV+) interferometric detectors can measure both aligned and misaligned spins. We compare spin resolution between the LIGO-Virgo network operating at either A+/AdV+ ("Plus") sensitivity or Advanced-era design ("Design") sensitivity using simulated BBH gravitational-wave signals injected into synthetic detector noise. The signals are distributed over the mass-spin parameter space of likely BBH systems, accounting for the effects of precession and higher-order modes. We find that the Plus upgrades yield significant improvements in spin estimation for systems with unequal masses and moderate or large spins. Using simulated signals modelled after different types of hierarchical BBH mergers, we also conclude that the Plus detector network will yield substantially improved spin estimates for 1G+2G binaries compared to the Design network.

gr-qc↗

arXiv2022

Prospects for reconstructing the gravitational-wave signals from core-collapse supernovae with Advanced LIGO-Virgo and the BayesWave algorithm

Our current understanding of the core-collapse supernova explosion mechanism is incomplete, with multiple viable models for how the initial shock wave might be energized enough to lead to a successful explosion. Detection of a gravitational-wave signal emitted in the initial few seconds after stellar core-collapse would provide unique and crucial insight into this process. With the Advanced LIGO and Advanced Virgo detectors expected to approach their design sensitivities soon, we could potentially detect this signal from a supernova within our galaxy. In anticipation of such a scenario, we study how well the BayesWave algorithm can recover the gravitational-wave signal from core-collapse supernova models in simulated advanced detector noise, and optimize its ability to accurately reconstruct the signal waveforms. We find that BayesWave can confidently reconstruct the signal from a range of supernova explosion models in Advanced LIGO-Virgo for network signal-to-noise ratios $\gtrsim 30$, reaching maximum reconstruction accuracies of $\sim 90\%$ at SNR $\sim 100$. For low SNR signals that are not confidently recovered, our optimization efforts result in gains in reconstruction accuracy of up to $20-40\%$, with typical gains of $\sim 10\%$.

astro-ph.HE↗

arXiv2022

Constraining Unmodeled Physics with Compact Binary Mergers from GWTC-1

We present a flexible model to describe the effects of generic deviations of observed gravitational wave signals from modeled waveforms in the LIGO and Virgo gravitational wave detectors. With the detection of 11 gravitational wave events from the GWTC-1 catalog, we are able to constrain possible deviations from our modeled waveforms. In this paper we present our coherent spline model that describes the deviations, then choose to validate our model on an example phenomenological and astrophysically motivated departure in waveforms based on extreme spontaneous scalarization. We find that the model is capable of recovering the simulated deviations. By performing model comparisons we observe that the spline model effectively describes the simulated departures better than a normal compact binary coalescence (CBC) model. We analyze the entire GWTC-1 catalog of events with our model and compare it to a normal CBC model, finding that there are no significant departures from the modeled template gravitational waveforms used.

gr-qc↗

arXiv2021

The Next Generation Global Gravitational Wave Observatory: The Science Book

The next generation of ground-based gravitational-wave detectors will observe coalescences of black holes and neutron stars throughout the cosmos, thousands of them with exceptional fidelity. The Science Book is the result of a 3-year effort to study the science capabilities of networks of next generation detectors. Such networks would make it possible to address unsolved problems in numerous areas of physics and astronomy, from Cosmology to Beyond the Standard Model of particle physics, and how they could provide insights into workings of strongly gravitating systems, astrophysics of compact objects and the nature of dense matter. It is inevitable that observatories of such depth and finesse will make new discoveries inaccessible to other windows of observation. In addition to laying out the rich science potential of the next generation of detectors, this report provides specific science targets in five different areas in physics and astronomy and the sensitivity requirements to accomplish those science goals. This report is the second in a six part series of reports by the GWIC 3G Subcommittee: i) Expanding the Reach of Gravitational Wave Observatories to the Edge of the Universe, ii) The Next Generation Global Gravitational Wave Observatory: The Science Book (this report), iii) 3G R&D: R&D for the Next Generation of Ground-based Gravitational Wave Detectors, iv) Gravitational Wave Data Analysis: Computing Challenges in the 3G Era, v) Future Ground-based Gravitational-wave Observatories: Synergies with Other Scientific Communities, and vi) An Exploration of Possible Governance Models for the Future Global Gravitational-Wave Observatory Network.

gr-qc↗

arXiv2021

GWSkyNet-Multi: A Machine Learning Multi-Class Classifier for LIGO-Virgo Public Alerts

Compact object mergers which produce both detectable gravitational waves and electromagnetic emission can provide valuable insights into the neutron star equation of state, the tension in the Hubble constant, and the origin of the r-process elements. However, electromagnetic follow-up of gravitational wave sources is complicated by false positive detections, sources which do not emit light, and the transient nature of the associated electromagnetic emission. GWSkyNet-Multi is a machine learning model that attempts to resolve these issues by providing real-time predictions of the source of a gravitational wave detection. The model uses information from Open Public Alerts (OPAs) released by LIGO-Virgo within minutes of a gravitational wave detection. GWSkyNet was first introduced in Cabero et al. (2020) as a binary classifier and uses the OPA skymaps to classify sources as either astrophysical or as glitches. In this paper, we introduce GWSkyNet-Multi, a new version of GWSkyNet which further distinguishes sources as binary black hole mergers, mergers involving a neutron star, or non-astrophysical glitches in the detectors. GWSkyNet-Multi is a sequence of three one-versus-all classifiers trained using a class-balanced and physically-motivated source mass distribution. Training on this data set, we obtain test set accuracies of 94% for BBH-versus-all, 94% for NS-versus-all, and 95% for glitch-versus-all. We obtain an overall accuracy of 93% using a hierarchical classification scheme. Furthermore, we correctly identify 36 of the 40 gravitational wave detections from the first half of LIGO-Virgo's third observing run (O3a) and present predictions for O3b sources. We also briefly discuss the interpretability of our models. As gravitational wave detections increase in number and frequency, GWSkyNet-Multi will be a powerful tool for prioritizing successful electromagnetic follow-up.

astro-ph.IM↗

arXiv2021

Parameterised population models of transient non-Gaussian noise in the LIGO gravitational-wave detectors

The two interferometric LIGO gravitational-wave observatories provide the most sensitive data to date to study the gravitational-wave Universe. As part of a global network, they have just completed their third observing run in which they observed many tens of signals from merging compact binary systems. It has long been known that a limiting factor in identifying transient gravitational-wave signals is the presence of transient non-Gaussian noise, which reduce the ability of astrophysical searches to detect signals confidently. Significant efforts are taken to identify and mitigate this noise at the source, but its presence persists, leading to the need for software solutions. Taking a set of transient noise artefacts categorised by the GravitySpy software during the O3a observing era, we produce parameterised population models of the noise projected into the space of astrophysical model parameters of merging binary systems. We compare the inferred population properties of transient noise artefacts with observed astrophysical systems from the GWTC2.1 catalogue. We find that while the population of astrophysical systems tend to have near equal masses and moderate spins, transient noise artefacts are typically characterised by extreme mass ratios and large spins. This work provides a new method to calculate the consistency of an observed candidate with a given class of noise artefacts. This approach could be used in assessing the consistency of candidates found by astrophysical searches (i.e. determining if they are consistent with a known glitch class). Furthermore, the approach could be incorporated into astrophysical searches directly, potentially improving the reach of the detectors, though only a detailed study would verify this.

gr-qc↗

arXiv2021

GWSkyNet: a real-time classifier for public gravitational-wave candidates

The rapid release of accurate sky localization for gravitational-wave candidates is crucial for multi-messenger observations. During the third observing run of Advanced LIGO and Advanced Virgo, automated gravitational-wave alerts were publicly released within minutes of detection. Subsequent inspection and analysis resulted in the eventual retraction of a fraction of the candidates. Updates could be delayed by up to several days, sometimes issued during or after exhaustive multi-messenger followup campaigns. We introduce GWSkyNet, a real-time framework to distinguish between astrophysical events and instrumental artefacts using only publicly available information from the LIGO-Virgo open public alerts. This framework consists of a non-sequential convolutional neural network involving sky maps and metadata. GWSkyNet achieves a prediction accuracy of 93.5% on a testing data set.

gr-qc↗

arXiv2020

New methods to assess and improve LIGO detector duty cycle

A network of three or more gravitational wave detectors simultaneously taking data is required to generate a well-localized sky map for gravitational wave sources, such as GW170817. Local seismic disturbances often cause the LIGO and Virgo detectors to lose light resonance in one or more of their component optic cavities, and the affected detector is unable to take data until resonance is recovered. In this paper, we use machine learning techniques to gain insight into the predictive behavior of the LIGO detector optic cavities during the second LIGO-Virgo observing run. We identify a minimal set of optic cavity control signals and data features which capture interferometer behavior leading to a loss of light resonance, or lockloss. We use these channels to accurately distinguish between lockloss events and quiet interferometer operating times via both supervised and unsupervised machine learning methods. This analysis yields new insights into how components of the LIGO detectors contribute to lockloss events, which could inform detector commissioning efforts to mitigate the associated loss of uptime. Particularly, we find that the state of the component optical cavities is a better predictor of loss of lock than ground motion trends. We report prediction accuracies of 98% for times just prior to lock loss, and 90% for times up to 30 seconds prior to lockloss, which shows promise for this method to be applied in near-real time to trigger preventative detector state changes. This method can be extended to target other auxiliary subsystems or times of interest, such as transient noise or loss in detector sensitivity. Application of these techniques during the third LIGO-Virgo observing run and beyond would maximize the potential of the global detector network for multi-messenger astronomy with gravitational waves.

astro-ph.IM↗

arXiv2019

Detecting Supermassive Black Hole-Induced Binary Eccentricity Oscillations with LISA

Stellar-mass black hole binaries (BHBs) near supermassive black holes (SMBH) in galactic nuclei undergo eccentricity oscillations due to gravitational perturbations from the SMBH. Previous works have shown that this channel can contribute to the overall BHB merger rate detected by the Laser Interferometer Gravitational-Wave Observatory (LIGO) and Virgo Interferometer. Significantly, the SMBH gravitational perturbations on the binary's orbit may produce eccentric BHBs which are expected to be visible using the upcoming Laser Interferometer Space Antenna (LISA) for a large fraction of their lifetime before they merge in the LIGO/Virgo band. For a proof-of-concept, we show that the eccentricity oscillations of these binaries can be detected with LISA for BHBs in the local universe up to a few Mpcs, with observation periods shorter than the mission lifetime, thereby disentangling this merger channel from others. The approach presented here is straightforward to apply to a wide variety of compact object binaries with a tertiary companion.

astro-ph.HE↗