arXiv subjects

Simona J. Miller

Publications and source records attributed to Simona J. Miller.

8 recordsLinked to original sources

arXiv2026

Evidence of the pair instability gap from black hole masses

Stellar theory predicts a forbidden range of black-hole masses between ${\sim}50$--$130\,M_\odot$ due to pair-instability supernovae, but evidence for such a gap in the mass distribution from gravitational-wave astronomy has proved elusive. Early hints of a cutoff in black-hole masses at ${\sim} 45\,M_\odot$ disappeared with the subsequent discovery of more massive binary black holes. Here, we report evidence of the pair-instability gap in LIGO--Virgo--KAGRA's fourth gravitational wave transient catalog (GWTC-4), with a lower boundary of $44_{-4}^{+5} M_\odot$ (90\% credibility). While the gap is not present in the distribution of \textit{primary} masses $m_1$ (the bigger of the two black holes in a binary system), it appears unambiguously in the distribution of \textit{secondary} masses $m_2$, where $m_2 \leq m_1$. The location of the gap lines up well with a previously identified transition in the binary black-hole spin distribution; binaries with primary components in the gap tend to spin more rapidly than those below the gap. We interpret these findings as evidence for a subpopulation of hierarchical mergers: binaries where the primary component is the product of a previous black-hole merger and thus populates the gap. Our measurement of the location of the pair-instability gap constrains the $S$-factor for $^{12}\rm{C}(α,γ)^{16}\rm{O}$ at 300keV to $260_{-108}^{+190}$ keV barns.

astro-ph.HE↗

arXiv2026

Coalescing Compact Binary Parameter Estimation with Gravitational Waves in the Presence of non-Gaussian Transient Noise

Data from gravitational-wave (GW) detectors often contains a high rate of non-Gaussian transient noise, known as glitches. The parameters estimated from GW signals coinciding with detector glitches are occasionally biased away from their true values. During the first part of the fourth LIGO-Virgo-KAGRA (LVK) observing run, 29% of GW candidates had overlapping or nearby glitches in one or more detectors. In the latter part of the fourth observation run, sensitivity improvements have increased the rates of GW detection. Consequently, scenarios in which GW signals and detector glitches overlap in time are more likely. In this study, we quantify shifts in inferred posterior distributions for short-duration compact binary coalescence GW signals interacting with common LIGO glitches as a function of time between the signal merger time and the glitch. We find statistically significant biases in parameter estimation for mass, spin, and sky position for "blip", "thunder", and "fast-scattering" glitches. Using these results, we provide estimates of what parameters are most affected by overlapping noise sources, as well as what constitutes a "safe" time separation between a gravitational wave signal and a glitch, without requiring glitch subtraction for unbiased source property estimation. We find that in a majority of cases, all parameters are susceptible to significant bias due to glitch interference. Additionally, we find that glitches that occur within the time prior of the GW signal cause more extreme biases than glitches outside of the time prior.

gr-qc↗

arXiv2026

Posterior Predictive Checks for Gravitational-wave Populations: Limitations and Improvements

When selecting a model to characterize an astrophysical population, it is crucial to assess whether that model fits the data and, if not, how it can be improved. To this end, posterior predictive checks (PPCs) are a widely-used statistical test of model fit when inferring gravitational-wave source populations. However, PPCs exhibit limitations when assessing single-event parameters with large measurement uncertainty, like the spin tilt angles of the binary black holes (BBHs) observable with the LIGO-Virgo-KAGRA (LVK) detectors. When single-event inference is prior-dominated, traditional PPCs fail to flag even very poor model fits. In this work, we assess the efficacy of various alternative PPCs on poorly-constrained parameters. We compare PPCs conducted on event- vs. data-level parameters (e.g. posterior samples vs. maximum likelihood points), and explore two additional event-level PPCs: partial predictive checks and split predictive checks. Independent of measurement uncertainty, we find that PPCs on maximum likelihood parameters are always more discerning of model misspecification than any event-level PPC. However, when investigating simulated GWTC-3.0-like catalogs, none of the alternative PPCs show significant improvement over those traditionally used, indicating that at that sensitivity, any limited information in the data about spin tilts is insufficient to diagnose model misspecification. Finally, we apply our suite of PPCs to the spin magnitude and tilt distributions inferred in the most recent LVK catalog, GWTC-4.0. We conclude that the Gaussian Component Spins model used therein under-predicts BBHs with large spin magnitudes and over-predicts those with perfectly anti-aligned tilts.

gr-qc↗

arXiv2025

Measuring spin precession from massive black hole binaries with gravitational waves: insights from time-domain signal morphology

Robustly measuring binary black hole spins via gravitational waves is key to understanding these systems' astrophysical origins, but remains challenging -- especially for high-mass systems, whose signals are short and dominated by the merger. Nonetheless, events like GW190521 show that strong spin precession can indeed be gleaned. In this work, we track how spin precession imprints on simulated high-mass binary black hole signals cycle-by-cycle using time-domain inference. We investigate a suite of signals, all with the same spins and (near-unity) mass ratio -- yielding identical spin evolution -- but different signal-to-noise ratios (SNRs), total masses, and extrinsic angles, all of which affect the observed waveform morphology. We truncate each signal at various times and infer source parameters using only the data before or after each cutoff. The resultant posterior allows us to identify which time segments of each signal inform its spin precession constraints. We find that at a sufficiently high post-peak SNR ($\sim 20$), spin precession can be constrained by the NRSur7dq4 waveform model when just the post-peak data (i.e., ringdown) are visible. Similarly, at a large enough pre-cutoff SNR ($\sim 10$), spin precession can be constrained using only pre-peak data (i.e., inspiral); this occurs for signals with detector-frame total mass $\lesssim 100 M_{\odot}$ at GW190521's full-signal SNR. Finally, we vary the inclination, polarization, and phase angles, finding that their configuration need not be fine-tuned to measure spin precession, even for very high-mass and short signals with two to three observable cycles. We do not find that the same morphological features consistently drive precession constraints: in some signals, precession inference hinges on the relationship between a loud merger and quiet pre-merger cycle, as was the case for GW190521, but this is not generically true.

gr-qc↗

arXiv2025

Mapping Parameter Correlations in Spinning Binary Black Hole Mergers

The spins of binary black holes measured with gravitational waves provide insights about the formation, evolution, and dynamics of these systems. However, interpreting these measurements-especially for heavy black holes-remains an open problem. While the imprint of spin during the inspiral phase, where the black holes are well-separated, is understood through analytic descriptions of the dynamics, no such expressions exist for the merger. Though numerical relativity simulations provide an exact solution (to within numerical error), the imprint of the full six spin degrees of freedom on the signal is not transparent. In the absence of analytic expressions for the merger and to advance our ability to interpret massive binary black hole spin measurements, here we propose a waveform-based approach. Leveraging a neural network to efficiently calculate mismatches between waveforms, we identify regions in the parameter space of spins and mass ratio that result in low mismatches and thus similar waveforms. We map these regions with a Gaussian fit, thus identifying correlations and quantifying their strength. For low-mass, inspiral-dominated systems, we recover the known physical imprint: larger aligned spins are correlated with more equal masses as they have opposite effects on the inspiral length. For high-mass, merger-dominated signals, a qualitatively similar correlation is present, though its shape is altered and strength decreases with larger total mass. Correlations between in-plane spins and mass ratio follow a similar trend, with their shape and strength altered as the mass increases. Our new methodology of waveform-based correlation mapping provides a first step toward systematically modeling spin effects in merger-dominated signals across the full intrinsic parameter-space and motivates future effective spin parameters beyond the reach of analytic methods.

gr-qc↗

arXiv2024

Gravitational waves carry information beyond effective spin parameters but it is hard to extract

Gravitational wave observations of binary black hole mergers probe their astrophysical origins via the binary spin, namely the spin magnitudes and directions of each component black hole, together described by six degrees of freedom. However, the emitted signals primarily depend on two effective spin parameters that condense the spin degrees of freedom to those parallel and those perpendicular to the orbital plane. Given this reduction in dimensionality between the physically relevant problem and what is typically measurable, we revisit the question of whether information about the component spin magnitudes and directions can successfully be recovered via gravitational-wave observations, or if we simply extrapolate information about the distributions of effective spin parameters. To this end, we simulate three astrophysical populations with the same underlying effective-spin distribution but different spin magnitude and tilt distributions, on which we conduct full individual-event and population-level parameter estimation. We find that parameterized population models can indeed qualitatively distinguish between populations with different spin magnitude and tilt distributions at current sensitivity. However, it remains challenging to either accurately recover the true distribution or to diagnose biases due to model misspecification. We attribute the former to practical challenges of dealing with high-dimensional posterior distributions, and the latter to the fact that each individual event carries very little information about the full six spin degrees of freedom.

gr-qc↗

arXiv2024

GW190521: tracing imprints of spin-precession on the most massive black hole binary

GW190521 is a remarkable gravitational-wave signal on multiple fronts: its source is the most massive black hole binary identified to date and could have spins misaligned with its orbit, leading to spin-induced precession -- an astrophysically consequential property linked to the binary's origin. However, due to its large mass, GW190521 was only observed during its final 3-4 cycles, making precession constraints puzzling and giving rise to alternative interpretations, such as eccentricity. Motivated by these complications, we trace the observational imprints of precession on GW190521 by dissecting the data with a novel time domain technique, allowing us to explore the morphology and interplay of the few observed cycles. We find that precession inference hinges on a quiet portion of the pre-merger data that is suppressed relative to the merger-ringdown. Neither pre-merger nor post-merger data alone are the sole driver of inference, but rather their combination: in the quasi-circular scenario, precession emerges as a mechanism to accommodate the lack of a stronger pre-merger signal in light of the observed post-merger. In terms of source dynamics, the pre-merger suppression arises from a tilting of the binary with respect to the observer. Establishing such a consistent picture between the source dynamics and the observed data is crucial for characterizing the growing number of massive binary observations and bolstering the robustness of ensuing astrophysical claims.

astro-ph.HE↗

arXiv2022

No evidence that the majority of black holes in binaries have zero spin

The spin properties of merging black holes observed with gravitational waves can offer novel information about the origin of these systems. The magnitude and orientations of black hole spins offer a record of binaries' evolutionary history, encoding information about massive stellar evolution and the astrophysical environments in which binary black holes are assembled. Recent analyses of the binary black hole population have yielded conflicting portraits of the black hole spin distribution. Some work suggests that black hole spins are small but non-zero and exhibit a wide range of misalignment angles relative to binaries' orbital angular momenta. Other work concludes that the majority of black holes are non-spinning while the remainder are rapidly rotating and primarily aligned with their orbits. We revisit these conflicting conclusions, employing a variety of complementary methods to measure the distribution of spin magnitudes and orientations among binary black hole mergers. We find that the existence of a sub-population of black hole with vanishing spins is not required by current data. Should such a sub-population exist, we conclude that it must contain $\lesssim 60\%$ of binaries. Additionally, we find evidence for significant spin-orbit misalignment among the binary black hole population, with some systems exhibiting misalignment angles greater than $90^{\circ}$, and see no evidence for an approximately spin-aligned sub-population.

astro-ph.HE↗