arXiv subjects

Alexander Pace

Publications and source records attributed to Alexander Pace.

14 recordsLinked to original sources

arXiv2026

Method to get Better Sky Maps in a GstLAL Low-Latency Analysis

Modeled gravitational wave searches correlate the strain data with a bank of gravitational wave template waveforms to make detections of gravitational wave candidates, and these results are processed by downstream tools to calculate the likely sky location and distance of the source of the candidates. This is crucial for multi-messenger efforts, since it informs astronomers where to point their telescopes to facilitate electromagnetic follow-up of the gravitational wave candidates. We present a novel method to improve the low-latency results of the GstLAL gravitational wave search pipeline, and thus improving sky location estimates of low-latency candidates. This method involves ingesting the GstLAL low-latency results, and performing a small targeted hierarchical search to recover the candidates with more accurate parameters, in a medium-latency timescale (few seconds to five minutes). To test our method, we perform a GstLAL low-latency analysis on forty days of data from the third observing run of LIGO, Virgo, and KAGRA, and show that our method improves the GstLAL results by 5.38% and the subsequent sky location results by 16.75% on average. In addition to this increase in precision, we also show that these results are more accurate as compared to the GstLAL results. This method has been adopted by GstLAL for the fourth observing run.

astro-ph.IM↗

arXiv2026

GstLAL O4 Online Results Paper

Gravitational-wave observations of merging binary neutron stars and black holes are now routinely made by detectors in the Advanced LIGO-Virgo-KAGRA network. Neutron star binary systems may also produce detectable electromagnetic and particle emission over times scales ranging from seconds to years. Real-time gravitational-wave searches play a central role in enabling time-critical electromagnetic and/or neutrino follow-up observations. During the fourth observing run (O4) of the Advanced LIGO-Virgo-KAGRA network, multiple real-time searches operated continuously to identify candidate gravitational-wave events and publicly disseminate information about these discoveries. Here, the performance and results of the GstLAL real-time analysis are reported. The analysis is designed to identify candidates with low latency, high detection efficiency, and sustained operational uptime over long observing periods. Across O4, it produced initial candidate uploads with a median latency of 15.8 s while maintaining an effective uptime of 98% during the first two parts of the observing run. During the run, the analysis contributed to 250 candidates classified as astrophysically plausible, provided the first upload for 222 of these, and was the sole contributor for 75. Among Gravitational-Wave Transient Catalog events with a false-alarm rate below one per year, 88% were identified as significant in low latency and promoted for expert vetting and public dissemination. The low-latency astrophysical classifications agreed with the final catalog classifications for 93% of the events considered.

gr-qc↗

arXiv2025

New Methods for Offline GstLAL Analyses

In this work, we present new methods implemented in the GstLAL offline gravitational wave search. These include a technique to reuse the matched filtering data products from a GstLAL online analysis, which hugely reduces the time and computational resources required to obtain offline results; a technique to combine these results with a separate search for heavier black hole mergers, enabling detections from a larger set of gravitational wave sources; changes to the likelihood ratio which increases the sensitivity of the analysis; and two separate changes to the background estimation, allowing more precise significance estimation of gravitational wave candidates. Some of these methods increase the sensitivity of the analysis, whereas others correct previous mis-estimations of sensitivity by eliminating false positives. These methods have been adopted for GstLAL's offline results during the fourth observing run of LIGO, Virgo, and KAGRA (O4). To test these new methods, we perform an offline analysis over one chunk of O3 data, lasting from May 12 19:36:42 UTC 2019 to May 21 14:45:08 UTC 2019, and compare it with previous GstLAL results over the same period of time. We show that cumulatively these methods afford around a 50% - 100% increase in sensitivity in the highest mass space, while simultaneously increasing the reliability of results, and making them more reusable and computationally cheaper.

gr-qc↗

arXiv2025

How Many Times Should We Matched Filter Gravitational Wave Data? A Comparison of GstLAL's Online and Offline Performance

Searches for gravitational waves from compact binary coalescences employ a process called matched filtering, in which gravitational wave strain data is cross-correlated against a bank of waveform templates. Data from every observing run of the LIGO, Virgo, and KAGRA collaboration is typically analyzed in this way twice, first in a low-latency mode in which gravitational wave candidates are identified in near-real time, and later in a high-latency mode. Such high-latency analyses have traditionally been considered more sensitive, since background data from the full observing run is available for assigning significance to all candidates, as well as more robust, since they do not need to worry about keeping up with live data. In this work, we present a novel technique to use the matched filtering data products from a low-latency analysis and re-process them by assigning significances in a high-latency way, effectively removing the need to perform matched filtering a second time. To demonstrate the efficacy of our method, we analyze 38 days of LIGO and Virgo data from the third observing run (O3) using the GstLAL pipeline, and show that our method is as sensitive and reliable as a traditional high-latency analysis. Since matched filtering represents the vast majority of computing time for a traditional analysis, our method greatly reduces the time and computational burden required to produce the same results as a traditional high-latency analysis. Consequently, it has already been adopted by GstLAL for the fourth observing run (O4) of the LIGO, Virgo, and KAGRA collaboration.

gr-qc↗

arXiv2024

Template bank for sub solar mass compact binary mergers in the fourth observing run of Advanced LIGO, Advanced Virgo, and KAGRA

Matched-filtering searches for gravitational-wave signals from compact binary mergers employ template banks which are a collection of modeled waveforms described by unique intrinsic parameters. We present two banks designed for low-latency and archive sub-solar mass (SSM) searches in data from the fourth observing run of LIGO-Virgo-KAGRA, and demonstrate the efficacy of the banks via simulated signals. Further, we introduce a set of modifications to the geometric, manifold algorithm that allow the method to work for exceedingly low component masses necessary for SSM bank production. The archive search bank contains a total of $3,452,006$ templates, and covers a mass parameter space of $0.2$ to $10\ M_\odot$ in the larger component and $0.2$ to $1.0\ M_\odot$ in the smaller component, the spin parameter space of $-0.9$ to $0.9$ for masses above $0.5$ $M_\odot$ and $-0.1$ to $0.1$ for masses below $0.5$ $M_\odot$, and the mass ratio parameter space of $1$ to $10$. The PSD used was from a week of the first half of the fourth observing run of Advanced LIGO, Advanced Virgo, and KAGRA, and the low frequency cutoff was set to $45$ Hz with a maximum waveform duration of $128$ seconds. The bank simulations performed using SBank have shown that the banks presented in this paper have sufficient efficacy for use in their respective searches.

gr-qc↗

arXiv2023

Low-latency gravitational wave alert products and their performance at the time of the fourth LIGO-Virgo-KAGRA observing run

Multi-messenger searches for BNS and NSBH mergers are currently one of the most exciting areas of astronomy. The search for joint electromagnetic and neutrino counterparts to GWs has resumed with O4. To support this effort, public semi-automated data products are sent in near real-time and include localization and source properties to guide complementary observations. In preparation for O4, we have conducted a study using a simulated population of compact binaries and a MDC in the form of a real-time replay to optimize and profile the software infrastructure and scientific deliverables. End-to-end performance was tested, including data ingestion, running online search pipelines, performing annotations, and issuing alerts to the astrophysics community. We present an overview of the low-latency infrastructure and the performance of the data products that are now being released during O4 based on the MDC. We report the expected median latency for the preliminary alert of full bandwidth searches (29.5s) and show consistency and accuracy of released data products using the MDC. For the first time, we report the expected median latency for triggers from early warning searches (-3.1s), which are new in O4 and target neutron star mergers during inspiral phase. This paper provides a performance overview for LVK low-latency alert infrastructure and data products using the MDC and serves as a useful reference for the interpretation of O4 detections.

astro-ph.HE↗

arXiv2021

Metric Assisted Stochastic Sampling (MASS) search for gravitational waves from binary black hole mergers

We present a novel gravitational wave detection algorithm that conducts a matched filter search stochastically across the compact binary parameter space rather than relying on a fixed bank of template waveforms. This technique is competitive with standard template-bank-driven pipelines in both computational cost and sensitivity. However, the complexity of the analysis is simpler allowing for easy configuration and horizontal scaling across heterogeneous grids of computers. To demonstrate the method we analyze approximately one month of public LIGO data from July 27 00:00 2017 UTC - Aug 25 22:00 2017 UTC and recover eight known confident gravitational wave candidates. We also inject simulated binary black hole (BBH) signals to demonstrate the sensitivity.

gr-qc↗

arXiv2020

Automating the Inclusion of Subthreshold Signal-to-Noise Ratios for Rapid Gravitational-Wave Localization

The accurate localization of gravitational-wave (GW) events in low-latency is a crucial element in the search for further multimessenger signals from these cataclysmic events. The localization of these events in low-latency uses signal-to-noise ratio (SNR) time-series from matched-filtered searches which identify candidate events. Here we report on an improvement to the GstLAL-based inspiral pipeline, the low-latency pipeline that identified GW170817 and GW190425, which automates the use of SNRs from all detectors in the network in rapid localization of GW events. This improvement was incorporated into the detection pipeline prior to the recent third observing run of the Advanced LIGO and Advanced Virgo detector network. Previously for this pipeline, manual intervention was required to use SNRs from all detectors if a candidate GW event was below an SNR threshold for any detector in the network. The use of SNRs from subthreshold events can meaningfully decrease the area of the 90% confidence region estimated by rapid localization. To demonstrate this, we present a study of the simulated detections of $\mathcal{O}(2\times10^4)$ binary neutron stars using a network mirroring the second observational run of the Advanced LIGO and Virgo detectors. When incorporating subthreshold SNRs in rapid localization, we find that the fraction of events that can be localized down to $100~\mathrm{deg}^2$ or smaller increases by a factor 1.18.

astro-ph.IM↗

arXiv2020

Incorporation of Statistical Data Quality Information into the GstLAL Search Analysis

We present updates to GstLAL, a matched filter gravitational-wave search pipeline, in Advanced LIGO and Virgo's third observing run. We discuss the incorporation of statistical data quality information into GstLAL's multi-dimensional likelihood ratio ranking statistic and additional improvements to search for gravitational wave candidates found in only one detector. Statistical data quality information is provided by iDQ, a data quality pipeline that infers the presence of short-duration transient noise in gravitational-wave data using the interferometer's auxiliary state, which has operated in near real-time since before LIGO's first observing run in 2015. We look at the performance and impact on noise rejection by the inclusion of iDQ information in GstLAL's ranking statistic, and discuss GstLAL results in the GWTC-2 catalog, focusing on two case studies; GW190424A, a single-detector gravitational-wave event found by GstLAL and a period of time in Livingston impacted by a thunderstorm.

gr-qc↗

arXiv2020

GstLAL: A software framework for gravitational wave discovery

The GstLAL library, derived from Gstreamer and the LIGO Algorithm Library, supports a stream-based approach to gravitational-wave data processing. Although GstLAL was primarily designed to search for gravitational-wave signatures of merging black holes and neutron stars, it has also contributed to other gravitational-wave searches, data calibration, and detector-characterization efforts. GstLAL has played an integral role in all of the LIGO-Virgo collaboration detections, and its low-latency configuration has enabled rapid electromagnetic follow-up for dozens of compact binary candidates.

astro-ph.IM↗

arXiv2020

Improving the background estimation technique in the GstLAL inspiral pipeline with the time-reversed template bank

Background estimation is important for determining the statistical significance of a gravitational-wave event. Currently, the background model is constructed numerically from the strain data using estimation techniques that insulate the strain data from any potential signals. However, as the observation of gravitational-wave signals become frequent, the effectiveness of such insulation will decrease. Contamination occurs when signals leak into the background model. In this work, we demonstrate an improved background estimation technique for the searches of gravitational waves (GWs) from binary neutron star coalescences by time-reversing the modeled GW waveforms. We found that the new method can robustly avoid signal contamination at a signal rate of about one per 20 seconds and retain a clean background model in the presence of signals.

astro-ph.IM↗

arXiv2020

An early warning system for electromagnetic follow-up of gravitational-wave events

Binary neutron stars (BNSs) will spend $\simeq 10$ -- 15 minutes in the band of Advanced LIGO and Virgo detectors at design sensitivity. Matched-filtering of gravitational-wave (GW) data could in principle accumulate enough signal-to-noise ratio (SNR) to identify a forthcoming event tens of seconds before the companions collide and merge. Here we report on the design and testing of an early warning gravitational-wave detection pipeline. Early warning alerts can be produced for sources that are at low enough redshift so that a large enough SNR accumulates $\sim 10 - 60\,\rm s$ before merger. We find that about 7% (respectively, 49%) of the total detectable BNS mergers will be detected $60\, \rm s$ ($10\, \rm s$) before the merger. About 2% of the total detectable BNS mergers will be detected before merger and localized to within $100\, \rm \text{deg}^2$ (90% credible interval). Coordinated observing by several wide-field telescopes could capture the event seconds before or after the merger. LIGO-Virgo detectors at design sensitivity could facilitate observing at least one event at the onset of merger.

astro-ph.HE↗

arXiv2019

Sub-threshold binary neutron star search in Advanced LIGO's first observing run

We present a search for gravitational waves from double neutron star binaries inspirals in Advanced LIGO's first observing run. The search considers a narrow range of binary chirp masses motivated by the population of known double neutron star binaries in the nearby universe. This search differs from previously published results by providing the most sensitive published survey of neutron stars in Advanced LIGO's first observing run within this narrow mass range and including times when only one of the two LIGO detectors was in operation in the analysis. The search was sensitive to binary neutron star inspirals to an average distance of ~85 Mpc over 93.2 days. We do not identify any unambiguous gravitational wave signals in our sample of 103 sub-threshold candidates with false-alarm-rates of less than one per day. However, given the expected binary neutron star merger rate of R = 100 - 4000 Gpc^(-3) yr^(-1), we expect O(1) gravitational wave events within our candidate list. This suggests the possibility that one or more of these candidates is in fact a binary neutron star merger. Although the contamination fraction in our candidate list is ~99%, it might be possible to correlate these events with other messengers to identify a potential multi-messenger signal. We provide an online candidate list with the times and sky locations for all events in order to enable multi-messenger searches.

gr-qc↗

arXiv2019

The GstLAL Search Analysis Methods for Compact Binary Mergers in Advanced LIGO's Second and Advanced Virgo's First Observing Runs

After their successful first observing run (September 12, 2015 - January 12, 2016), the Advanced LIGO detectors were upgraded to increase their sensitivity for the second observing run (November 30, 2016 - August 26, 2017). The Advanced Virgo detector joined the second observing run on August 1, 2017. We discuss the updates that happened during this period in the GstLAL-based inspiral pipeline, which is used to detect gravitational waves from the coalescence of compact binaries both in low latency and an offline configuration. These updates include deployment of a zero-latency whitening filter to reduce the over-all latency of the pipeline by up to 32 seconds, incorporation of the Virgo data stream in the analysis, introduction of a single-detector search to analyze data from the periods when only one of the detectors is running, addition of new parameters to the likelihood ratio ranking statistic, increase in the parameter space of the search, and introduction of a template mass-dependent glitch-excision thresholding method.

gr-qc↗