Search for: All records

Abstract While supermassive black hole (SMBH) binaries are not the only viable source for the low-frequency gravitational wave background (GWB) signal evidenced by the most recent pulsar timing array (PTA) data sets, they are expected to be the most likely. Thus, connecting the measured PTA GWB spectrum and the underlying physics governing the demographics and dynamics of SMBH binaries is extremely important. Previously, Gaussian processes (GPs) and dense neural networks have been used to make such a connection by being built as conditional emulators; their input is some selected evolution or environmental SMBH binary parameters and their output is the emulated mean and standard deviation of the GWB strain ensemble distribution over many Universes. In this paper, we use a normalizing flow (NF) emulator that is trained on the entirety of the GWB strain ensemble distribution, rather than only mean and standard deviation. As a result, we can predict strain distributions that mirror underlying simulations very closely while also capturing frequency covariances in the strain distributions as well as statistical complexities such as tails, non-Gaussianities, and multimodalities that are otherwise not learnable by existing techniques. In particular, we feature various comparisons between the NF-based emulator and the GP approach used extensively in past efforts. Our analyses conclude that the NF-based emulator not only outperforms GPs in the ease and computational cost of training but also outperforms in the fidelity of the emulated GWB strain ensemble distributions. 

Landscapes are formed by long-term interactions between the underlying geology and climatic, edaphic and biotic factors, including human activity. The Kasitu Valley in the Mzimba District of northern Malawi includes the Kasitu River and its adjacent floodplains and uplands, and it has been a location of sustained human occupation since at least 16 thousand years ago (ka) based on archaeological excavations from rockshelters. We trace the changing ecology and geomorphology of the region through soil stable isotopes (δ¹³C, δ¹⁵N), microcharcoal and fossil pollen analysed from alluvial terraces dated by Optically Stimulated Luminescence, and wetland auger cores and archaeological sites dated by radiocarbon. Our results suggest that the region was primarily covered in mosaic forest at ca. 22.5 ka. Middle and Late Holocene samples (6.0–0.5 ka) show an increasingly open, herbaceous landscape over time with an inflection toward more abundant C4 vegetation after 2 ka. Significant upland erosion and terrace formation is also evidenced since 2 ka alongside high concentrations of microcharcoal, suggesting more intensive use of fire. Faecal biomarkers simultaneously indicate higher numbers of humans living adjacent to the archaeological site of Hora 1, which may be indicative of an overall population increase associated with the arrival of Iron Age agropastoralists. More recently, the introduction of exogenous commercial taxa such asPinussp. are correlated with regional afforestation in our proxy record. These results show increasing stepwise human impacts on the local environment, with deforestation and maintenance of open landscapes correlated with the regional introduction and intensification of agriculture during the Late Holocene. 

ABSTRACT Deuterostomes are the major division of animal life which includes sea stars, acorn worms, and humans, among a wide variety of ecologically and morphologically disparate taxa. However, their early evolution is poorly understood, due in part to their disparity, which makes identifying commonalities difficult, as well as their relatively poor early fossil record. Here, we review the available morphological, palaeontological, developmental, and molecular data to establish a framework for exploring the origins of this important and enigmatic group. Recent fossil discoveries strongly support a vermiform ancestor to the group Hemichordata, and a fusiform active swimmer as ancestor to Chordata. The diverse and anatomically bewildering variety of forms among the early echinoderms show evidence of both bilateral and radial symmetry. We consider four characteristics most critical for understanding the form and function of the last common ancestor to Deuterostomia: Hox gene expression patterns, larval morphology, the capacity for biomineralization, and the morphology of the pharyngeal region. We posit a deuterostome last common ancestor with a similar antero‐posterior gene regulatory system to that found in modern acorn worms and cephalochordates, a simple planktonic larval form, which was later elaborated in the ambulacrarian lineage, the ability to secrete calcium minerals in a limited fashion, and a pharyngeal respiratory region composed of simple pores. This animal was likely to be motile in adult form, as opposed to the sessile origins that have been historically suggested. Recent debates regarding deuterostome monophyly as well as the wide array of deuterostome‐affiliated problematica further suggest the possibility that those features were not only present in the last common ancestor of Deuterostomia, but potentially in the ur‐bilaterian. The morphology and development of the early deuterostomes, therefore, underpin some of the most significant questions in the study of metazoan evolution. 

No abstract available. 

Abstract Pulsar timing array observations have found evidence for an isotropic gravitational-wave background with the Hellings–Downs angular correlations between pulsar pairs. This interpretation hinges on the measured shape of the angular correlations, which is predominantly quadrupolar under general relativity. Here we explore a more flexible parameterization: we expand the angular correlations into a sum of Legendre polynomials and use a Bayesian analysis to constrain their coefficients with the 15 yr pulsar timing data set collected by the North American Nanohertz Observatory for Gravitational Waves (NANOGrav). When including Legendre polynomials with multipolesℓ≥ 2, we only find a significant signal in the quadrupole with an amplitude consistent with general relativity and nonzero at the ∼95% confidence level and a Bayes factor of 200. When we include multipolesℓ≤ 1, the Bayes factor evidence for quadrupole correlations decreases by more than an order of magnitude due to evidence for a monopolar signal at approximately 4 nHz, which has also been noted in previous analyses of the NANOGrav 15 yr data. Further work needs to be done in order to better characterize the properties of this monopolar signal and its effect on the evidence for quadrupolar angular correlations. 

Abstract Evidence has emerged for a stochastic signal correlated among 67 pulsars within the 15 yr pulsar-timing data set compiled by the NANOGrav collaboration. Similar signals have been found in data from the European, Indian, Parkes, and Chinese pulsar timing arrays. This signal has been interpreted as indicative of the presence of a nanohertz stochastic gravitational-wave background (GWB). To explore the internal consistency of this result, we investigate how the recovered signal strength changes as we remove the pulsars one by one from the data set. We calculate the signal strength using the (noise-marginalized) optimal statistic, a frequentist metric designed to measure the correlated excess power in the residuals of the arrival times of the radio pulses. We identify several features emerging from this analysis that were initially unexpected. The significance of these features, however, can only be assessed by comparing the real data to synthetic data sets. After conducting identical analyses on simulated data sets, we do not find anything inconsistent with the presence of a stochastic GWB in the NANOGrav 15 yr data. The methodologies developed here can offer additional tools for application to future, more sensitive data sets. While this analysis provides an internal consistency check of the NANOGrav results, it does not eliminate the necessity for additional investigations that could identify potential systematics or uncover unmodeled physical phenomena in the data.