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Barak Zackay

Publications and source records attributed to Barak Zackay.

At least 19 recordsLinked to original sources

Summary statistic for pulsar timing arrays

The timing residuals produced by gravitational-wave signals can be described as an incoherent (pulsar term) contribution and a coherent (Earth term) map on the sky, which PTAs measure at the locations of the timed pulsars. The observed Earth term map and the variance induced by the pulsar term contain all of the information about any GW signal available to a PTA (assuming pulsar distances are unknown). Furthermore, any type of signal produces on average the same angular correlation function, the Hellings and Downs curve, which decays steeply with multipole as $C_\ell \propto 1/[(\ell+2)(\ell+1)\ell(\ell-1)]$. This suggests that the signal is inherently low-dimensional and therefore only a small number of parameters are needed to fully characterize it. We present an expression for the PTA likelihood that makes the dependence on the Earth term map and pulsar term variance explicit, and show that only a few spherical harmonic coefficients are needed to capture most of the information about the signal. To quantify this in a realistic setting, we compute the Fisher matrix of the amplitude of a stochastic background or a deterministic point source assuming the noise properties and sky locations of the pulsars in the NANOGrav 15yr dataset. We find that $\ell_{\rm max}=2$ of the Earth term map and the monopole of the pulsar term variance retain $\sim 95\%$ of the information about the signal. For a point source, including the dipole of the pulsar term variance is important to achieve a similar fraction.

astro-ph.CO

Co-addition and Subtraction of Undersampled Images

In astronomical imaging surveys, repeated observations of the same sky patches are taken in order to obtain deeper images and detect new sources. This is the case in the search for many transient phenomena, such as supernovae, gravitational wave (GW) optical counterparts and other cataclysmic variables. In many such surveys some of the images are undersampled, meaning that the pixel size is too large, and the image suffers from aliasing. For undersampled images, both co-addition of the images and background subtraction are done in a non-optimal manner, which leads to reduced sensitivity and an increased rate of false alarms. We present a new method (named Linear Undersampled Transients \& Addition (LUTRA)) that performs both processes in a mathematically proven optimal way, which allows improved performance for many scientific applications. It also allows easy and direct performance of measurements such as photometry and astrometry in a simple manner, while providing results in super-resolution. We demonstrate the performance of the method on public ZTF data and show $\times 1.25$ higher SNR compared to current methods. We provide an open source Python implementation.

astro-ph.IM

Coherent Signal Detection with Pruning -- I. Finding Short-Period Binary Pulsars in Circular Orbits

Detecting pulsars in short-period binary systems, which are unparalleled laboratories for fundamental physics and tests of general relativity, is a prime objective of radio astronomy. Their rapid orbital motion, however, presents a formidable computational challenge. Conventional searches are therefore limited to simplified signal models (e.g., constant acceleration) that remain valid for only short integrations ($\lesssim 4$-$10$% of an orbital period). This fundamental limitation severely degrades search sensitivity, placing much of the faint, relativistic pulsar population beyond the reach of current surveys. We present a novel hierarchical search framework based on extreme pruning that overcomes these limitations by progressively eliminating improbable regions of parameter space across successive coherent integration stages. The algorithm achieves $>90$% detection probability at the sensitivity threshold, with near-unity recovery for stronger signals, while reducing the computational complexity of full circular-orbit searches by up to 10 orders of magnitude relative to an unpruned hierarchical baseline. The resulting efficiency enables, for the first time, fully coherent integration over an entire orbital period and beyond. Compared to conventional acceleration searches, the proposed method delivers a 3- to 5-fold improvement in sensitivity, dramatically increasing the discovery potential for high-value targets such as pulsar-black hole binaries.

astro-ph.HE

Expanding the Population of Short Gamma-Ray Transients with a Coherent Fermi/GBM Search. A 13-year catalog of short GRBs

In this paper, we present an archival search for short gamma-ray bursts (sGRBs) over 13 years (2013-2025) of Fermi/GBM data using a Poisson matched-filter pipeline that performs a fully coherent analysis across all detectors and energy channels, significantly improving sensitivity relative to the onboard triggering algorithms. A central component of the analysis is the empirical estimation of trigger significance using 'timeslided' data, allowing each candidate to be assigned a probability of astrophysical origin. We also developed a new parameter-estimation framework based on the Poisson matched filter, which uses the global structure of the detected event across spectral, temporal, and spatial parameter spaces. This enables us to systematically classify bursts and distinguish between GRBs, soft gamma repeaters, terrestrial gamma-ray flashes, and solar flares. We identify 568 new GRB candidates with $p_{\text{astro}}\geq0.9$ and thousands of magnetar bursts, significantly expanding the known short-transient population in GBM data. To further strengthen the significance of the GRB candidates, we performed a targeted follow-up search in Swift/BAT rate data. Applying the followup to all of our triggers - including triggers below the detection threshold yielded 1736 temporally coincident events with association probability above $90\%$. The resulting probabilistically ranked catalog substantially expands the population of short GRBs and magnetar flares detected in GBM data and provides a statistically robust framework for multimessenger searches.

astro-ph.HE

Discovery of Interpretable Surrogates via Agentic AI: Application to Gravitational Waves

Fast surrogate models for expensive simulations are now essential across the sciences, yet they typically operate as black boxes. We present \texttt{GWAgent}, a large language model (LLM)-based workflow that constructs interpretable analytic surrogates directly from simulation data. Surrogate modeling is well suited to agentic workflows because candidate models can be quantitatively validated against ground-truth simulations at each iteration. As a demonstration, we build a surrogate for gravitational waveforms from eccentric binary black hole mergers. We show that providing the agent with a physics-informed domain ansatz substantially improves output model accuracy. The resulting analytic surrogate attains a median Advanced LIGO mismatch of $6.9\times10^{-4}$ together with an $\sim 8.4\times$ speedup in waveform evaluation, surpassing both symbolic regression and conventional machine learning baselines. Beyond producing an accurate model, the workflow identifies compact physical structure from the learned representation. As an astrophysical application, we use \texttt{GWAgent} to analyze the eccentricity of GW200129 and infer $e_{20\mathrm{Hz}}=0.099^{+0.063}_{-0.044}$. These results show that validation-constrained agentic workflows can produce accurate, fast, and interpretable surrogates for scientific simulations and inference.

gr-qc

GW190711_030756 and GW200114_020818: astrophysical interpretation of two asymmetric binary black hole mergers in the IAS catalog

We provide a comprehensive analysis of GW190711_030756 and GW200114_020818, two of the most significant binary black hole merger candidates in the IAS catalog, with probabilities of astrophysical origin $p_{\rm astro}=0.99$ and $0.71$, respectively, and signal-to-noise ratios of approximately $10.0$ and $13.4$. We employ numerical relativity surrogate models to infer both the source properties and the remnant properties of these two candidates. We find that both GW190711_030756 and GW200114_020818 are asymmetric-mass binaries, with inferred mass ratios of $0.35^{+0.32}_{-0.15}$ and $\leq 0.20$. In addition, GW200114_020818 is inferred to have a source-frame total mass of approximately $220M_{\odot}$ and highly spinning black holes, with primary (secondary) dimensionless spin magnitudes of $0.96^{+0.03}_{-0.07}$ ($0.84^{+0.13}_{-0.34}$), closely resembling GW231123_135430. We further find that GW200114\_020818 has a confidently negative effective inspiral spin of $\chi_{\rm eff}=-0.60^{+0.22}_{-0.13}$ and exhibits strong spin precession, characterized by an effective precession parameter of $\chi_{\rm p}=0.60^{+0.21}_{-0.19}$. GW200114_020818 (when considered alongside GW231123_135430) points towards an emerging population of massive, rapidly spinning BBH mergers. While GW231123_135430 is consistent with mergers in globular clusters, producing systems like GW200114_020818 in such environments remains difficult even under hierarchical merger scenarios. The probability that the remnant black hole of GW190711_030756 (GW200114_020818) is retained in its host environment is $0.079$ ($0.0002$), $0.62$ ($0.965$), and $0.997$ ($1$) if the merger occurred in a globular cluster, a nuclear star cluster, or an elliptical galaxy, respectively.

astro-ph.HE

Searching for precessing binary systems with mode-by-mode filtering and marginalization

Nearly all previous binary black hole searches in LIGO--Virgo--KAGRA (LVK) gravitational wave data have assumed that the component spins are aligned with the orbital angular momentum, thereby neglecting spin-precession effects in the waveform, which can lead to potentially missing interesting signals. Precessing searches are challenging, because the extra degrees of freedom due to misaligned spins lead to: $(i)$ a much larger number of templates compared to the aligned-spin configurations, $(ii)$ an increased rate of background triggers. To address this, we develop novel precessing signal template banks using mode-by-mode filtering and marginalization methods. We use the precession harmonic decomposition from Fairhurst et al. (2019) and filter each precessing harmonic separately with the data. We then marginalize over the SNRs from different harmonics in our detection statistic. We also use machine learning methods to improve our search efficiency: $(i)$ we use singular value decomposition together with random forest regressor to reduce redundancy in the dominant precessing-harmonic templates; $(ii)$ we use normalizing flows to generate optimal prior samples for harmonic SNRs for the marginalized statistic. We show that marginalizing (instead of maximizing) over the harmonic mode SNRs increases the search sensitive volume by $\sim 10\%$. Results from searching in LVK data using this framework will be reported in a companion paper.

gr-qc

A Linearized Approach to Radial-Velocity Extraction. II: Shot-Noise-Limited Precision via Spectral Factorization

We generalize the short-time Fourier transform (STFT) formalism for radial velocity extraction to cases where the underlying spectral components are unknown. The method factorizes a spectroscopic time series into principal spectra and time-dependent kernels, enabling simultaneous recovery of both. In Fourier space, each inverse-wavelength slice is decomposed by singular value decomposition, and radial velocity shifts are inferred from phase differences between epochs. In the high-SNR regime, this provides a linearized and statistically tractable estimate of differential velocities. The method is validated on synthetic and SOAP simulations and applied to EXPRES observations of HD 34411 and $\tau$ Ceti, recovering coherent signals and reaching the instrumental precision limit of ~30 cm/s. Apart from p-mode modulation, the residuals show no significant long-term correlations and allow the detection of signals with semi-amplitudes down to ~50 cm/s with $\lesssim10$ cm/s uncertainty. The framework thus enables extreme-precision radial velocity measurements in the presence of spectral variability, representing a step toward detecting and characterizing Earth-like planets around solar-type stars.

astro-ph.EP

Data-driven extraction and phenomenology of eccentric harmonics in eccentric spinning binary black hole mergers

Newtonian and post-Newtonian (PN) calculations indicate that the phenomenology of eccentric binary black hole (BBH) merger waveforms is significantly more complex than that of their quasi-circular counterparts. Each spherical harmonic mode of the radiation can be further decomposed into several eccentricity-induced components, referred to as eccentric harmonics. Unlike the (cumulative) spherical harmonic modes, these constituent eccentric harmonics exhibit monotonically time-varying amplitudes and frequencies. However, these eccentric harmonics are not directly accessible in numerical relativity (NR) simulations or current eccentric waveform models. Using the recently developed data-driven framework gwMiner, which combines singular value decomposition, input from post-Newtonian theory, and signal processing techniques, we extract eccentric harmonics from eccentric, aligned-spin waveforms for six different spherical harmonic modes: (2,1), (2,2), (3,2), (3,3), (4,3), (4,4). We demonstrate that the phase (frequency) of each eccentric harmonic takes the form $j\,\phi_{\ell,m,\lambda} + \phi_{\ell,m,\rm ecc}$ ($j\,f_{\ell,m,\lambda} + f_{\ell,m,\rm ecc}$), where $\phi_{\ell,m,\lambda}$ ($f_{\ell,m,\lambda}$) corresponds to the secular orbital phase (frequency), and $\phi_{\ell,m,\rm ecc}$ ($f_{\ell,m,\rm ecc}$) is an additional contribution that depends solely on the eccentricity. We further find that $\phi_{\ell,m,\lambda}$ is the same across different spherical harmonic modes $(\ell, m)$, whereas the eccentric correction term $\phi_{\ell,m,\rm ecc}$ scales with $\ell$. Using effective-one-body dynamics, we further show that $\phi_{\ell,m,\lambda}$ is nothing but the relativistic anomaly and $\phi_{\ell,m,\rm ecc}$ is related to the precession advances.

gr-qc

Binary black hole population inference combining confident and marginal events from the $\tt{IAS\text{-}HM}$ search pipeline

We present the population properties of binary black hole mergers identified by the $\tt{IAS\text{-}HM}$ pipeline (which incorporates higher-order modes in the search templates) during the third observing run (O3) of the LIGO, Virgo, and KAGRA (LVK) detectors. In our population inference analysis, instead of only using events above a sharp cut based on a particular detection threshold (e.g., false alarm rate), we use a Bayesian framework to consistently include both marginal and confident events. We find that our inference based solely on highly significant events ($p_{\mathrm{astro}} \sim 1$) is broadly consistent with the GWTC-3 population analysis performed by the LVK collaboration. However, incorporating marginal events into the analysis leads to a preference for stronger redshift evolution in the merger rate and an increased density of asymmetric mass-ratio mergers relative to the GWTC-3 analysis, while remaining within its allowed parameter ranges. Using simple parametric models to describe the binary black hole population, we estimate a merger rate density of $32.4^{+18.5}_{-12.2}\ \mathrm{Gpc}^{-3}\,\mathrm{yr}^{-1}$ at redshift $z = 0.2$, and a redshift evolution parameter of $\kappa = 4.4^{+1.9}_{-2.0}$. Assuming a power-law form for the mass ratio distribution ($\propto q^{\beta}$), we infer $\beta = 0.1^{+1.9}_{-1.4}$, indicating a relatively flat distribution. These results highlight the potential impact of marginal events on population inferences and motivate future analyses with data from upcoming observing runs.

gr-qc

Sampler-free gravitational wave inference using matrix multiplication

Parameter estimation (PE) for compact binary coalescence (CBC) events observed by gravitational wave (GW) laser interferometers is a core task in GW astrophysics. We present a method to compute the posterior distribution efficiently without relying on stochastic samplers. First, we show how to select sets of intrinsic and extrinsic parameters that efficiently cover the relevant phase space. We then show how to compute the likelihood for all combinations of these parameters using dot products. We describe how to assess and tune the integration accuracy, making the outcome predictable and adaptable to different applications. The low computational cost allows full PE in minutes on a single CPU, with the potential for further acceleration using multiple CPUs or GPUs. We implement this method in the $\texttt{dot-PE}$ package, enabling sensitive searches using the full evidence integral for precessing CBCs and supporting large waveform banks ($\sim10^5$--$10^6$ waveforms), regardless of waveform generation cost.

gr-qc

Improving gravitational wave search sensitivity with TIER: Trigger Inference using Extended strain Representation

We introduce a machine learning (ML) framework called $\texttt{TIER}$ for improving the sensitivity of gravitational wave search pipelines. Typically, search pipelines only use a small region of strain data in the vicinity of a candidate signal to construct the detection statistic. However, extended strain data ($\sim 10$ s) in the candidate's vicinity can also carry valuable complementary information. We show that this information can be efficiently captured by ML classifier models trained on sparse summary representation/features of the extended data. Our framework is easy to train and can be used with already existing candidates from any search pipeline, and without requiring expensive injection campaigns. Furthermore, the output of our model can be easily integrated into the detection statistic of a search pipeline. Using $\texttt{TIER}$ on triggers from the $\texttt{IAS-HM}$ pipeline, we find up to $\sim 20\%$ improvement in sensitive volume time in LIGO-Virgo-Kagra O3 data, with improvements concentrated in regions of high masses and unequal mass ratios. Applying our framework increases the significance of several near-threshold gravitational-wave candidates, especially in the pair-instability mass gap and intermediate-mass black hole (IMBH) ranges.

gr-qc

A New Search Pipeline for Short Gamma Ray Bursts in Fermi/GBM Data -- A 50% Increase in the Number of Detections

In this paper, we present the development and the results of a new search pipeline for short gamma-ray bursts (sGRBs) in the publicly available data from the Gamma-Ray Burst Monitor (GBM) on board the Fermi satellite. This pipeline uses rigorous statistical methods that are designed to maximize the information extracted from the Fermi/GBM detectors. Our approach differs substantially from existing search efforts in several aspects: The pipeline includes the construction of template banks, Poisson matched filtering, background estimation, background misestimation correction, automatic routines to filter contaminants, statistical estimation of the signal location and a quantitative estimator of the signal probability to be of a cosmological, terrestrial, or solar origin. Our analysis also includes operating the pipeline on "time-slided" copies of the data, which allows exact significance assessment and $p_{\text{astro}}$ computation, akin to the state-of-the-art gravitational waves (GW) data analysis pipelines. Depending on the spectral properties of the bursts, our pipeline achieves a signal-to-noise ratio (SNR) improvement by a factor of 2 to 15 over the onboard GBM triggering algorithm. This enhancement increases the detectable volume for sGRBs and results in an approximate 50% increase in sGRB detections in the 2014 GBM dataset. As a further consequence of the sensitivity increase, we detect hundreds of soft gamma-ray flares of galactic origin. This improved sensitivity enhances the chances of detecting fainter, off-axis GRBs that would likely fall below the standard triggering thresholds. Applying this pipeline to the full GBM archive is expected to expand further the joint sGRB-GW detection volume.

astro-ph.HE

Searching for intermediate mass ratio binary black hole mergers in the third observing run of LIGO-Virgo-KAGRA

Intermediate mass ratio inspirals (IMRIs) of binary black holes with mass ratios $10^{-4}\lesssim q \lesssim 0.1$ are astrophysically interesting sources of gravitational waves. Mergers of intermediate-mass black holes (IMBHs) with stellar-mass black holes would be IMRIs, so their detection can help us probe the formation mechanisms of IMBHs. They can also help us perform precise tests of general relativity due to the presence of strong higher-order mode emission. We perform a search for aligned-spin IMRIs within the data of the two LIGO detectors in the third observing run (O3) of the LIGO-Virgo-KAGRA (LVK) collaboration, including higher modes in the template banks for the first time. We use the IAS-HM pipeline for our search and construct template banks in the range $1/100 < q<1/18$ using the SEOBNRv5HM waveform model. Our banks retain a similar level of effectualness for IMRPhenomXHM and BHPTNRSur2dq1e3 waveforms, making our search results relatively robust against waveform systematics. We show that the sensitivity volume of the search increases by up to $\sim 500\%$ upon inclusion of higher modes. We do not find any significant candidates with inverse false alarm rate (IFAR) $> 1$ year in the O3 data. This gives us upper limits on the IMRI merger rate in the local Universe, ranging from $\sim 30$ to $10^3$ Gpc$^{-3}$ yr$^{-1}$ depending on the masses of the black holes in the binary. These constraints are consistent with rate predictions in the literature. Our projections indicate that we would be able to detect IMRIs or constrain some of their proposed formation channels in the fourth (O4) and fifth (O5) observing runs.

gr-qc

No Evidence for Second-Scale Periodicity in FRB 20201124A from FAST Observations

Fast Radio Bursts (FRBs) are bright and short radio flashes of cosmological origin. Although a great number of FRBs were detected in the last two decades, their progenitors and the physical processes that create them are unknown. In recent years, magnetars have been proposed as one of the leading progenitor candidates. A striking feature that can hint at such a magnetar origin is second-scale periodicity. In this paper, we define a robust procedure to search for such periodicity and estimate the significance of its results. We search for such periodicity in the bursts of FRB 20201124A, observed by the Five-hundred-meter Aperture Spherical Telescope (FAST) between April and June 2021. Our analysis does not find any significant periodicity. We discuss the differences between our non-detection and the ~1.7s periodicity claim by C. Du et al. (2025).

astro-ph.HE

gwharmone: first data-driven surrogate for eccentric harmonics in binary black hole merger waveforms

We present gwharmone, the first data-driven surrogate model for eccentric harmonics (as well as the full radiation content) of the dominant quadrupolar mode in eccentric, non-spinning binary black hole mergers. Our model is trained on 173 waveforms, each $100,000M$ long (where $M$ is the total mass), generated for mass ratios $q \in [1,3.5]$ and eccentricities $e_{\rm ref} \in [0,0.2]$ (at the start of the waveform). The eccentric harmonics are extracted from the effective-one-body waveforms using the \texttt{gwMiner} package. We apply a singular value decomposition (SVD) to obtain a set of reduced basis vectors, necessary to construct a lower-dimensional representation of data, and use Gaussian Process Regression (GPR) to interpolate SVD coefficients across parameter space, allowing for prediction at new parameter points. The model includes the effect of mean anomaly, its evaluation cost is only $\sim 0.1$ second and it achieves an average time-domain (validation) error of ~0.001 and frequency-domain (validation) mismatches below 0.01 for advanced LIGO sensitivity. Our model can therefore be useful in efficient searches and parameter estimation of eccentric mergers. gwharmone will be publicly available through the gwModels package.

astro-ph.HE

Data-driven extraction, phenomenology and modeling of eccentric harmonics in binary black hole merger waveforms

Newtonian and post-Newtonian (PN) calculations suggest that each spherical harmonic mode of the gravitational waveforms (radiation) emitted by eccentric binaries can be further decomposed into several eccentricity-induced modes (indexed by $j=1$ to $j=\infty$), referred to as eccentric harmonics. These harmonics exhibit monotonically time-varying amplitudes and instantaneous frequencies, unlike the full eccentric spherical harmonic modes. However, computing or extracting these harmonics are not straightforward in current numerical relativity (NR) simulations and eccentric waveform models. To address this, Patterson \textit{et al} have developed a framework to extract the eccentric harmonics directly from effective-one-body formalism waveforms. In this paper, we build on the ideas presented in Patterson \textit{et al} and propose a data-driven framework, utilizing singular-value decomposition (SVD), that incorporates additional features based on PN intuition to ensure monotonicity in the extracted harmonics. We further demonstrate that the phase (frequency) of these harmonics is simply $j\phi_{\lambda}+\phi_{\rm ecc}$ ($jf_{\lambda}+f_{\rm ecc}$) where $\phi_{\lambda}$ ($f_{\lambda}$) is related to the secular orbital phase (frequency) and $\phi_{\rm ecc}$ ($f_{\rm ecc}$) is an additional phase (frequency) that only depends on the eccentricity. We also provide simple analytical fits to obtain the harmonics as a function of the mean anomaly. These relations may prove useful in constructing faithful models that can be employed in cheap and efficient searches and parameter estimation of eccentric mergers. Our framework is modular and can be extended for any other eccentric waveform models or simulation frameworks. The framework is available through the \texttt{gwMiner} package.

gr-qc

Significant increase in sensitive volume of a gravitational wave search upon including higher harmonics

Most gravitational wave searches to date have included only the quadrupole mode in their search templates. Here, we demonstrate that incorporating higher harmonics improves the search sensitive volume for detecting binary black hole mergers, challenging the conclusion of previous studies. Using the $\tt{IAS-HM}$ detection pipeline, and the simulated (injection) signals from the LIGO-Virgo-Kagra (LVK) collaboration, we quantify the improvement in sensitivity due to the inclusion of higher harmonics. This improvement is significant for systems with higher mass ratios and larger total masses, with gains in sensitivity even exceeding $100\%$ at certain high masses. We also show that, due to using a marginalized detection statistic, the $\tt{IAS-HM}$ pipeline performs roughly as well as its quadrupole-mode-only counterpart even for equal mass-ratio mergers, and its sensitive volume is either better than or comparable to that of the individual LVK pipelines.

gr-qc