arXiv subjects

Shaon Ghosh

Publications and source records attributed to Shaon Ghosh.

At least 19 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↗

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

What to expect: kilonova light curve predictions via equation of state marginalization

Efficient multi-messenger observations of gravitational-wave candidates from compact binary coalescence candidate events rely on data products reported in low-latency by the International Gravitational-wave Network (IGWN). While data products such as $\texttt{HasNS}$, the probability of at least one neutron star, and $\texttt{HasRemnant}$, the probability of remnant matter forming after merger, exist, these are not direct observables for a potential kilonova. Here, we present new kilonova light curve and ejecta mass data products derived from merger quantities measured in low latency, by marginalizing over our uncertainty in our understanding of the neutron star equation of state and using measurements of the source properties of the merger, including masses and spins. Two additional types of data products are proposed. The first is the probability of a candidate event having mass ejecta ($m_{\mathrm{ej}}$) greater than $10^{-3} M_\odot$, which we denote as $\texttt{HasEjecta}$. The second are $m_{\mathrm{ej}}$ estimates and accompanying $\texttt{ugrizy}$ and $\texttt{HJK}$ kilonova light curves predictions produced from a surrogate model trained on a grid of kilonova light curves from $\texttt{POSSIS}$, a time-dependent, three-dimensional Monte Carlo radiative transfer code. We are developing these data products in the context of the IGWN low-latency alert infrastructure, and will be advocating for their use and release for future detections.

astro-ph.HE↗

arXiv2024

GWSkyNet II : a refined machine learning pipeline for real-time classification of public gravitational wave alerts

Electromagnetic follow-up observations of gravitational wave events offer critical insights and provide significant scientific gain from this new class of astrophysical transients. Accurate identification of gravitational wave candidates and rapid release of sky localization information are crucial for the success of these electromagnetic follow-up observations. However, searches for gravitational wave candidates in real time suffer a non-negligible false alarm rate. By leveraging the sky localization information and other metadata associated with gravitational wave candidates, GWSkyNet, a machine learning classifier developed by Cabero et al. (2020), demonstrated promising accuracy for the identification of the origin of event candidates. We improve the performance of the classifier for LIGO-Virgo-KAGRA's fourth observing run by reviewing and updating the architecture and features used as inputs by the algorithm. We also retrain and fine-tune the classifier with data from the third observing run. To improve the prospect of electromagnetic follow-up observations, we incorporate GWSkyNet into LIGO-Virgo-KAGRA's low-latency infrastructure as an automatic pipeline for the evaluation of gravitational wave alerts in real time. We test the readiness of the algorithm on a LIGO-Virgo-KAGRA mock data challenge campaign. The results show that by thresholding on the GWSkyNet score, noise masquerading as astrophysical sources can be rejected efficiently and the majority of true astrophysical signals correctly identified.

astro-ph.IM↗

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↗

arXiv2023

QoQ: a Q-transform based test for Gravitational Wave transient events

The observation of transient gravitational waves is hindered by the presence of transient noise, colloquially referred to as glitches. These glitches can often be misidentified as gravitational waves by searches for unmodeled transients using the excess-power type of methods and sometimes even excite template waveforms for compact binary coalescences while using matched filter techniques. They thus create a significant background in the searches. This background is more critical in getting identified promptly and efficiently within the context of real-time searches for gravitational-wave transients. Such searches are the ones that have enabled multi-messenger astrophysics with the start of the Advanced LIGO and Advanced Virgo data taking in 2015 and they will continue to enable the field for further discoveries. With this work we propose and demonstrate the use of a signal-based test that quantifies the fidelity of the time-frequency decomposition of the putative signal based on first principles on how astrophysical transients are expected to be registered in the detectors and empirically measuring the instrumental noise. It is based on the Q-transform and a measure of the occupancy of the corresponding time-frequency pixels over select time-frequency volumes; we call it ``QoQ''. Our method shows a 40% reduction in the number of retraction of public alerts that were issued by the LIGO-Virgo-KAGRA collaborations during the third observing run with negligible loss in sensitivity. Receiver Operator Characteristic measurements suggest the method can be used in online and offline searches for transients, reducing their background significantly.

gr-qc↗

arXiv2022

Rapid Hierarchical Inference of Neutron Star Equation of State from multiple Gravitational Wave Observations of Binary Neutron Star Coalescences

Bayesian hierarchical inference of phenomenological parameterized neutron star equations of state (EoS) from multiple gravitational wave observations of binary neutron star mergers is of fundamental importance in improving our understanding of neutron star structure, the general properties of matter at supra nuclear densities and the strong nuclear force. However, such an analysis is computationally costly as it is unable to re-use single-event EoS agnostic parameter estimation runs that are carried out regardless for generating gravitational wave transient catalogs. With the number of events expected to be observable during the 4th observing run (O4) of LIGO/Virgo/KAGRA, this problem can only be expected to worsen. We develop a novel and robust algorithm for rapid and computationally cheap hierarchical inference of parameterized EoSs from gravitational wave data which re-uses single event EoS agnostic parameter estimation samples to significantly reduce computational cost. We efficiently include a priori knowledge of neutron star physics as Bayesian priors on the EoS parameters. The high speed and low computational cost of our method allow for efficient re-computation of EoS inference every time a new binary neutron star event is discovered or whenever new observations and theoretical discoveries change the prior on EoS parameters. We test our method on both real and simulated gravitational wave data to demonstrate its accuracy. We show that our computationally cheap method produces EoS constraints that are completely consistent with existing analysis for real data, the chosen fiducial EoS for simulated data. Armed with our fast analysis scheme, we also study the variability of EoS constraints with binary neutron star properties for sets of simulated events drawn in different signal-to-noise ratio and mass ranges.

gr-qc↗

arXiv2022

In search of short gamma-ray burst optical counterpart with the Zwicky Transient Facility

The Fermi Gamma-ray Burst Monitor (GBM) triggers on-board in response to $\sim$ 40 short gamma-ray bursts (SGRBs) per year; however, their large localization regions have made the search for optical counterparts a challenging endeavour. We have developed and executed an extensive program with the wide field of view of the Zwicky Transient Facility (ZTF) camera, mounted on the Palomar 48 inch Oschin telescope (P48), to perform target-of-opportunity (ToO) observations on 10 Fermi-GBM SGRBs during 2018 and 2020-2021. Bridging the large sky areas with small field of view optical telescopes in order to track the evolution of potential candidates, we look for the elusive SGRB afterglows and kilonovae (KNe) associated with these high-energy events. No counterpart has yet been found, even though more than 10 ground based telescopes, part of the Global Relay of Observatories Watching Transients Happen (GROWTH) network, have taken part in these efforts. The candidate selection procedure and the follow-up strategy have shown that ZTF is an efficient instrument for searching for poorly localized SGRBs, retrieving a reasonable number of candidates to follow-up and showing promising capabilities as the community approaches the multi-messenger era. Based on the median limiting magnitude of ZTF, our searches would have been able to retrieve a GW170817-like event up to $\sim$ 200 Mpc and SGRB afterglows to z = 0.16 or 0.4, depending on the assumed underlying energy model. Future ToOs will expand the horizon to z = 0.2 and 0.7 respectively.

astro-ph.HE↗

arXiv2021

Rapid model comparison of equations of state from gravitational wave observation of binary neutron star coalescences

The discovery of the coalescence of binary neutron star GW170817 was a watershed moment in the field of gravitational wave astronomy. Among the rich variety of information that we were able to uncover from this discovery was the first non-electromagnetic measurement of the neutron star radius, and the cold nuclear equation of state. It also led to a large equation of state model-selection study from gravitational-wave data. In those studies Bayesian nested sampling runs were conducted for each candidate equation of state model to compute their evidence in the gravitational-wave data. Such studies, though invaluable, are computationally expensive and require repeated, redundant, computation for any new models. We present a novel technique to conduct model-selection of equation of state in an extremely rapid fashion (~minutes) on any arbitrary model. We test this technique against the results of a nested-sampling model-selection technique published earlier by the LIGO/Virgo collaboration, and show that the results are in good agreement with a median fractional error in Bayes factor of about 10%, where we assume that the true Bayes factor is calculated in the aforementioned nested sampling runs. We found that the highest fractional error occurs for equation of state models that have very little support in the posterior distribution, thus resulting in large statistical uncertainty. We then used this method to combine multiple binary neutron star mergers to compute a joint-Bayes factor between equation of state models. This is achieved by stacking the evidence of the individual events and computing the Bayes factor from these stacked evidences for each pairs of equation of state.

gr-qc↗

arXiv2021

First demonstration of early warning gravitational wave alerts

Gravitational-wave observations became commonplace in Advanced LIGO-Virgo's recently concluded third observing run. 56 non-retracted candidates were identified and publicly announced in near real time. Gravitational waves from binary neutron star mergers, however, remain of special interest since they can be precursors to high-energy astrophysical phenomena like $\gamma$-ray bursts and kilonovae. While late-time electromagnetic emissions provide important information about the astrophysical processes within, the prompt emission along with gravitational waves uniquely reveals the extreme matter and gravity during - and in the seconds following - merger. Rapid communication of source location and properties from the gravitational-wave data is crucial to facilitate multi-messenger follow-up of such sources. This is especially enabled if the partner facilities are forewarned via an early-warning (pre-merger) alert. Here we describe the commissioning and performance of such a low-latency infrastructure within LIGO-Virgo. We present results from an end-to-end mock data challenge that detects binary neutron star mergers and alerts partner facilities before merger. We set expectations for these alerts in future observing runs.

astro-ph.HE↗

arXiv2020

Kilonova Luminosity Function Constraints based on Zwicky Transient Facility Searches for 13 Neutron Star Mergers

We present a systematic search for optical counterparts to 13 gravitational wave (GW) triggers involving at least one neutron star during LIGO/Virgo's third observing run. We searched binary neutron star (BNS) and neutron star black hole (NSBH) merger localizations with the Zwicky Transient Facility (ZTF) and undertook follow-up with the Global Relay of Observatories Watching Transients Happen (GROWTH) collaboration. The GW triggers had a median localization of 4480 deg^2, median distance of 267 Mpc and false alarm rates ranging from 1.5 to 1e-25 per yr. The ZTF coverage had a median enclosed probability of 39%, median depth of 20.8mag, and median response time of 1.5 hr. The O3 follow-up by the GROWTH team comprised 340 UVOIR photometric points, 64 OIR spectra, and 3 radio. We find no promising kilonova (radioactivity-powered counterpart) and we convert the upper limits to constrain the underlying kilonova luminosity function. Assuming that all kilonovae are at least as luminous as GW170817 at discovery (-16.1mag), we calculate our joint probability of detecting zero kilonovae is only 4.2%. If we assume that all kilonovae are brighter than -16.6mag (extrapolated peak magnitude of GW170817) and fade at 1 mag/day (similar to GW170817), the joint probability of zero detections is 7%. If we separate the NSBH and BNS populations, the joint probability of zero detections, assuming all kilonovae are brighter than -16.6mag, is 9.7% for NSBH and 7.9% for BNS mergers. Moreover, <57% (<89%) of putative kilonovae could be brighter than -16.6mag assuming flat (fading) evolution, at 90% confidence. If we further account for the online terrestrial probability for each GW trigger, we find that <68% of putative kilonovae could be brighter than -16.6mag. Comparing to model grids, we find that some kilonovae must have Mej < 0.03 Msun or Xlan>1e-4 or phi>30deg to be consistent with our limits. (Abridged)

astro-ph.HE↗

arXiv2020

Enhancing Gravitational-Wave Science with Machine Learning

Machine learning has emerged as a popular and powerful approach for solving problems in astrophysics. We review applications of machine learning techniques for the analysis of ground-based gravitational-wave detector data. Examples include techniques for improving the sensitivity of Advanced LIGO and Advanced Virgo gravitational-wave searches, methods for fast measurements of the astrophysical parameters of gravitational-wave sources, and algorithms for reduction and characterization of non-astrophysical detector noise. These applications demonstrate how machine learning techniques may be harnessed to enhance the science that is possible with current and future gravitational-wave detectors.

astro-ph.HE↗

arXiv2020

A Machine Learning Based Source Property Inference for Compact Binary Mergers

The detection of the binary neutron star (BNS) merger, GW170817, was the first success story of multi-messenger observations of compact binary mergers. The inferred merger rate along with the increased sensitivity of the ground-based gravitational-wave (GW) network in the present LIGO/Virgo, and future LIGO/Virgo/KAGRA observing runs, strongly hints at detection of binaries which could potentially have an electromagnetic (EM) counterpart. A rapid assessment of properties that could lead to a counterpart is essential to aid time-sensitive follow-up operations, especially robotic telescopes. At minimum, the possibility of counterparts require a neutron star (NS). Also, the tidal disruption physics is important to determine the remnant matter post merger, the dynamics of which could result in the counterparts. The main challenge, however, is that the binary system parameters such as masses and spins estimated from the real time, GW template-based searches are often dominated by statistical and systematic errors. Here, we present an approach that uses supervised machine-learning to mitigate such selection effects to report possibility of counterparts based on presence of a NS component, and presence of remnant matter post merger in real time.

astro-ph.IM↗

arXiv2019

GROWTH on S190425z: Searching thousands of square degrees to identify an optical or infrared counterpart to a binary neutron star merger with the Zwicky Transient Facility and Palomar Gattini IR

The third observing run by LVC has brought the discovery of many compact binary coalescences. Following the detection of the first binary neutron star merger in this run (LIGO/Virgo S190425z), we performed a dedicated follow-up campaign with the Zwicky Transient Facility (ZTF) and Palomar Gattini-IR telescopes. The initial skymap of this single-detector gravitational wave (GW) trigger spanned most of the sky observable from Palomar Observatory. Covering 8000 deg$^2$ of the initial skymap over the next two nights, corresponding to 46\% integrated probability, ZTF system achieved a depth of $\approx$\,21 $m_\textrm{AB}$ in $g$- and $r$-bands. Palomar Gattini-IR covered 2200 square degrees in $J$-band to a depth of 15.5\,mag, including 32\% integrated probability based on the initial sky map. The revised skymap issued the following day reduced these numbers to 21\% for the Zwicky Transient Facility and 19\% for Palomar Gattini-IR. We narrowed 338,646 ZTF transient "alerts" over the first two nights of observations to 15 candidate counterparts. Two candidates, ZTF19aarykkb and ZTF19aarzaod, were particularly compelling given that their location, distance, and age were consistent with the GW event, and their early optical lightcurves were photometrically consistent with that of kilonovae. These two candidates were spectroscopically classified as young core-collapse supernovae. The remaining candidates were ruled-out as supernovae. Palomar Gattini-IR did not identify any viable candidates with multiple detections only after merger time. We demonstrate that even with single-detector GW events localized to thousands of square degrees, systematic kilonova discovery is feasible.

astro-ph.HE↗

arXiv2019

The Zwicky Transient Facility: Science Objectives

The Zwicky Transient Facility (ZTF), a public-private enterprise, is a new time domain survey employing a dedicated camera on the Palomar 48-inch Schmidt telescope with a 47 deg$^2$ field of view and 8 second readout time. It is well positioned in the development of time domain astronomy, offering operations at 10% of the scale and style of the Large Synoptic Survey Telescope (LSST) with a single 1-m class survey telescope. The public surveys will cover the observable northern sky every three nights in g and r filters and the visible Galactic plane every night in g and r. Alerts generated by these surveys are sent in real time to brokers. A consortium of universities which provided funding ("partnership") are undertaking several boutique surveys. The combination of these surveys producing one million alerts per night allows for exploration of transient and variable astrophysical phenomena brighter than r $\sim$ 20.5 on timescales of minutes to years. We describe the primary science objectives driving ZTF including the physics of supernovae and relativistic explosions, multi-messenger astrophysics, supernova cosmology, active galactic nuclei and tidal disruption events, stellar variability, and Solar System objects.

astro-ph.IM↗

arXiv2019

2900 square degree search for the optical counterpart of short gamma-ray burst GRB 180523B with the Zwicky Transient Facility

There is significant interest in the models for production of short gamma-ray bursts. Until now, the number of known short gamma-ray bursts with multi-wavelength afterglows has been small. While the {\it Fermi} Gamma-Ray Burst Monitor detects many gamma-ray bursts relative to the Neil Gehrels {\it Swift} Observatory, the large localization regions makes the search for counterparts difficult. With the Zwicky Transient Facility recently achieving first light, it is now fruitful to use its combination of depth ($m_\textrm{AB} \sim 20.6$), field of view ($\approx$ 47 square degrees), and survey cadence (every $\sim 3$ days) to perform Target of Opportunity observations. We demonstrate this capability on GRB 180523B, which was recently announced by the {\it Fermi} Gamma-Ray Burst Monitor as a short gamma-ray burst. ZTF imaged $\approx$ 2900\,square degrees of the localization region, resulting in the coverage of 61.6\,\% of the enclosed probability over 2 nights to a depth of $m_\textrm{AB} \sim 20.5$. We characterized 14 previously unidentified transients, and none were found to be consistent with a short gamma-ray burst counterpart. This search with the Zwicky Transient Facility shows it is an efficient camera for searching for coarsely-localized short gamma-ray burst and gravitational-wave counterparts, allowing for a sensitive search with minimal interruption to its nominal cadence.

astro-ph.HE↗

arXiv2018

Systematic effects from black hole-neutron star waveform model uncertainties on the neutron star equation of state

We identify various contributors of systematic effects in the measurement of the neutron star (NS) tidal deformability and quantify their magnitude for several types of neutron star - black hole (NSBH) binaries. Gravitational waves from NSBH mergers contain information about the components' masses and spins as well as the NS equation of state. Extracting this information requires comparison of the signal in noisy detector data with theoretical templates derived from some combination of post-Newtonian (PN) approximants, effective one-body (EOB) models and %analytic fits to numerical relativity (NR) simulations. The accuracy of these templates is limited by errors in the NR simulations, by the approximate nature of the PN/EOB waveforms, and by the hybridization procedure used to combine them. In this paper, we estimate the impact of these errors by constructing and comparing a set of PN-NR hybrid waveforms, for the first time with NR waveforms from two different codes, namely, SpEC and SACRA, for such systems. We then attempt to recover the parameters of the binary using two non-precessing template approximants. We find that systematic errors are too large for tidal effects to be accurately characterized for any realistic NS equation of state model. We conclude that NSBH waveform models must be significantly improved if they are to be useful for the extraction of NS equation of state information or even for distinguishing NSBH systems from binary black holes.

gr-qc↗

arXiv2018

Optimizing searches for electromagnetic counterparts of gravitational wave triggers

With the detection of a binary neutron star system and its corresponding electromagnetic counterparts, a new window of transient astronomy has opened. Due to the size of the error regions, which can span hundreds to thousands of square degrees, there are significant benefits to optimizing tilings for these large sky areas. The rich science promised by gravitational-wave astronomy has led to the proposal for a variety of tiling and time allocation schemes, and for the first time, we make a systematic comparison of some of these methods. We find that differences of a factor of 2 or more in efficiency are possible, depending on the algorithm employed. For this reason, for future surveys searching for electromagnetic counterparts, care should be taken when selecting tiling, time allocation, and scheduling algorithms to maximize the probability of counterpart detection.

astro-ph.IM↗