2,703 research outputs found

    Multivariate Modeling of Quasar Variability with an Attention-based Variational Autoencoder

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    This thesis applied HeTVAE, an attention-based VAE neural network capable of multivariate modeling of time series, to a dataset of several thousand multi-band AGN light curves from ZTF and was one of the first attempts to use a neural network to harness the stochastic light curves in their multivariate form. Whereas standard models of AGN variability make prior assumptions, HeTVAE uses no prior knowledge and is able to learn the data distribution in a regularized latent space, reading semantic information via its up-to-date self-supervised training regimen. We have successfully created a dataset class for preprocessing the irregular multivariate time series and in order to interface with the quasi-off-the-shelf network more conveniently. Also, we have trained several different model iterations using one, two or all three of the filter dimensions from ZTF on Durham’s NCC compute cluster, while configuring useful hyper parameter choices to work robustly for the astronomical dataset. In the network's training, we employed the Adam optimizer with a reduce-on-plateau learning rate schedule and a KL-annealing schedule optimize the VAE’s performance. In experimenting, we show how the VAE has learned the data distribution of the light curves by generating simulated light curves and its interpretability by visualizing attention scores and by visualizing the way the light curves are distributed along the continuous latent space using PCA. We show it orders the light curves across a smooth gradient from those those that have both low amplitude short-term variation and high amplitude long-term variation, to those with little variability, to those with both short-term and long-term high-amplitude variation in the condensed space. We also use PCA to display a potential filtering algorithm that enables parsing through large datasets in an intuitive way and present some of the pitfalls of algorithmic bias in anomaly detection. Finally, we fine-tuned the structurally correct but imprecise multivariate interpolations output by HeTVAE to three objects to show how they could improve constraints on time-delay estimates in the context of reverberation mapping for the relatively poor-cadenced ZTF data. In short, HeTVAE's use cases are ranged and it is a step in the right direction as far as being able to help organize and process the millions of AGN light curves incoming from Vera C. Rubin Observatory’s Legacy Survey of Space and Time in their full 6 optical broadband filter multivariate form

    The Gemini Planet Imager Exoplanet Survey : giant planet and brown dwarf demographics from 10 to 100 au

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    We present a statistical analysis of the first 300 stars observed by the Gemini Planet Imager Exoplanet Survey. This subsample includes six detected planets and three brown dwarfs; from these detections and our contrast curves we infer the underlying distributions of substellar companions with respect to their mass, semimajor axis, and host stellar mass. We uncover a strong correlation between planet occurrence rate and host star mass, with stars M* > 1.5 M⊙ more likely to host planets with masses between 2 and 13MJup and semimajor axes of 3–100 au at 99.92% confidence. We fit a double power-law model in planet mass (m) and semimajor axis (a) for planet populations around high-mass stars (M* > 1.5 M⊙) of the form d2N/(dm da) ∝ mα aÎČ, finding α = −2.4 ± 0.8 and ÎČ = −2.0 ± 0.5, and an integrated occurrence rate of 9+5-4% between 5–13MJup and 10–100 au. A significantly lower occurrence rate is obtained for brown dwarfs around all stars, with 0.8+0.8-0.5% of stars hosting a brown dwarf companion between 13–80MJup and 10–100 au. Brown dwarfs also appear to be distributed differently in mass and semimajor axis compared to giant planets; whereas giant planets follow a bottom-heavy mass distribution and favor smaller semimajor axes, brown dwarfs exhibit just the opposite behaviors. Comparing to studies of short-period giant planets from the radial velocity method, our results are consistent with a peak in occurrence of giant planets between ∌1 and 10 au. We discuss how these trends, including the preference of giant planets for high-mass host stars, point to formation of giant planets by core/pebble accretion, and formation of brown dwarfs by gravitational instability.Peer reviewe

    Ancient DNA of narrow-headed vole reveal common features of the Late Pleistocene population dynamics in cold-adapted small mammals

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    The narrow-headed vole, collared lemming and common vole were the most abundant small mammal species across the Eurasian Late Pleistocene steppe-tundra environment. Previous ancient DNA studies of the collared lemming and common vole have revealed dynamic population histories shaped by climatic fluctuations. To investigate the extent to which species with similar adaptations share common evolutionary histories, we generated a dataset comprised the mitochondrial genomes of 139 ancient and 6 modern narrow-headed voles from several sites across Europe and northwestern Asia covering approximately the last 100 thousand years (kyr). We inferred Bayesian time-aware phylogenies using 11 radiocarbon-dated samples to calibrate the molecular clock. Divergence of the main mtDNA lineages across the three species occurred during marine isotope stages (MIS) 7 and MIS 5, suggesting a common response of species adapted to open habitat during interglacials. We identified several time-structured mtDNA lineages in European narrow-headed vole, suggesting lineage turnover. The timing of some of these turnovers was synchronous across the three species, allowing us to identify the main drivers of the Late Pleistocene dynamics of steppe- and cold-adapted species.NWOVI.C.191.070Human Origin

    The degree of alignment between circumbinary disks and their binary hosts

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    Funding: I.C. was supported by NASA through the NASA Hubble Fellowship grant HST-HF2-51405.001-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., for NASA, under contract NAS5-26555.All four circumbinary (CB) protoplanetary disks orbiting short-period (P < 20 days) double-lined spectroscopic binaries (SB2s)—a group that includes UZ Tau E, for which we present new Atacama Large Millimeter/Submillimeter Array data—exhibit sky-plane inclinations idisk that match, to within a few degrees, the sky-plane inclinations i⋆ of their stellar hosts. Although for these systems the true mutual inclinations ξ between disk and binary cannot be directly measured because relative nodal angles are unknown, the near coincidence of i disk and i⋆ suggests that ξ is small for these most compact of systems. We confirm this hypothesis using a hierarchical Bayesian analysis, showing that 68% of CB disks around short-period SB2s have ξ < 3.°0. Near coplanarity of CB disks implies near coplanarity of CB planets discovered by Kepler, which in turn implies that the occurrence rate of close-in CB planets is similar to that around single stars. By contrast, at longer periods ranging from 30 to 105 days (where the nodal degeneracy can be broken via, e.g., binary astrometry), CB disks exhibit a wide range of mutual inclinations, from coplanar to polar. Many of these long-period binaries are eccentric, as their component stars are too far separated to be tidally circularized. We discuss how theories of binary formation and disk-binary gravitational interactions can accommodate all these observations.Publisher PDFPeer reviewe

    The persistent shadow of the supermassive black hole of M 87

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    In April 2019, the Event Horizon Telescope (EHT) Collaboration reported the first-ever event-horizon-scale images of a black hole, resolving the central compact radio source in the giant elliptical galaxy M 87. These images reveal a ring with a southerly brightness distribution and a diameter of ∌42 ÎŒas, consistent with the predicted size and shape of a shadow produced by the gravitationally lensed emission around a supermassive black hole. These results were obtained as part of the April 2017 EHT observation campaign, using a global very long baseline interferometric radio array operating at a wavelength of 1.3 mm. Here, we present results based on the second EHT observing campaign, taking place in April 2018 with an improved array, wider frequency coverage, and increased bandwidth. In particular, the additional baselines provided by the Greenland telescope improved the coverage of the array. Multiyear EHT observations provide independent snapshots of the horizon-scale emission, allowing us to confirm the persistence, size, and shape of the black hole shadow, and constrain the intrinsic structural variability of the accretion flow. We have confirmed the presence of an asymmetric ring structure, brighter in the southwest, with a median diameter of 43.3−3.1+1.5 Όas. The diameter of the 2018 ring is remarkably consistent with the diameter obtained from the previous 2017 observations. On the other hand, the position angle of the brightness asymmetry in 2018 is shifted by about 30° relative to 2017. The perennial persistence of the ring and its diameter robustly support the interpretation that the ring is formed by lensed emission surrounding a Kerr black hole with a mass ∌6.5 × 109 M⊙. The significant change in the ring brightness asymmetry implies a spin axis that is more consistent with the position angle of the large-scale jet

    Ancient and modern DNA track temporal and spatial population dynamics in the European fallow deer since the Eemian interglacial

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    This is the final version. Available on open access from Nature Research via the DOI in this recordData availability: All DNA sequences are available on Genbank under accession numbers KY564399–KY564432; OR220344-OR220389, OR531442, OR531443, OR232305-OR232317 and in the supplement.Anthropogenic factors have impacted the diversity and evolutionary trajectory of various species. This can be through factors such as pressure on population size or range, habitat fragmentation, or extensive manipulation and translocation. Here we use time-calibrated data to better understand the pattern and processes of evolution in the heavily manipulated European fallow deer (Dama dama). During the Pleistocene, fallow deer had a broad distribution across Europe and were found as far north as Britain during the Eemian interglacial. The last glacial period saw fallow deer retreat to southern refugia and they did not disperse north afterwards. Their recolonisation was mediated by people and, from northern Europe and the British Isles, fallow deer were transported around the world. We use ancient and modern mitochondrial DNA (mtDNA) and mitogenomic data from Eemian Britain to assess the pattern of change in distribution and lineage structure across Europe over time. We find founder effects and mixed lineages in the northern populations, and stability over time for populations in southern Europe. The Eemian sample was most similar to a lineage currently in Italy, suggesting an early establishment of the relevant refuge. We consider the implications for the integration of anthropogenic and natural processes towards a better understanding of the evolution of fallow deer in Europe.Arts and Humanities Research Council (AHRC

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Low- and high-resource opinion summarization

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    Customer reviews play a vital role in the online purchasing decisions we make. The reviews express user opinions that are useful for setting realistic expectations and uncovering important details about products. However, some products receive hundreds or even thousands of reviews, making them time-consuming to read. Moreover, many reviews contain uninformative content, such as irrelevant personal experiences. Automatic summarization offers an alternative – short text summaries capturing the essential information expressed in reviews. Automatically produced summaries can reflect overall or particular opinions and be tailored to user preferences. Besides being presented on major e-commerce platforms, home assistants can also vocalize them. This approach can improve user satisfaction by assisting in making faster and better decisions. Modern summarization approaches are based on neural networks, often requiring thousands of annotated samples for training. However, human-written summaries for products are expensive to produce because annotators need to read many reviews. This has led to annotated data scarcity where only a few datasets are available. Data scarcity is the central theme of our works, and we propose a number of approaches to alleviate the problem. The thesis consists of two parts where we discuss low- and high-resource data settings. In the first part, we propose self-supervised learning methods applied to customer reviews and few-shot methods for learning from small annotated datasets. Customer reviews without summaries are available in large quantities, contain a breadth of in-domain specifics, and provide a powerful training signal. We show that reviews can be used for learning summarizers via a self-supervised objective. Further, we address two main challenges associated with learning from small annotated datasets. First, large models rapidly overfit on small datasets leading to poor generalization. Second, it is not possible to learn a wide range of in-domain specifics (e.g., product aspects and usage) from a handful of gold samples. This leads to subtle semantic mistakes in generated summaries, such as ‘great dead on arrival battery.’ We address the first challenge by explicitly modeling summary properties (e.g., content coverage and sentiment alignment). Furthermore, we leverage small modules – adapters – that are more robust to overfitting. As we show, despite their size, these modules can be used to store in-domain knowledge to reduce semantic mistakes. Lastly, we propose a simple method for learning personalized summarizers based on aspects, such as ‘price,’ ‘battery life,’ and ‘resolution.’ This task is harder to learn, and we present a few-shot method for training a query-based summarizer on small annotated datasets. In the second part, we focus on the high-resource setting and present a large dataset with summaries collected from various online resources. The dataset has more than 33,000 humanwritten summaries, where each is linked up to thousands of reviews. This, however, makes it challenging to apply an ‘expensive’ deep encoder due to memory and computational costs. To address this problem, we propose selecting small subsets of informative reviews. Only these subsets are encoded by the deep encoder and subsequently summarized. We show that the selector and summarizer can be trained end-to-end via amortized inference and policy gradient methods

    Exploring the calibration of cosmological probes used in gravitational-wave and multi-messenger astronomy

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    The field of gravitational wave astronomy has grown remarkably since the first direct detection of gravitational waves on 14th September 2015. The signal, originating from the merger of two black holes, was detected by the two US-based Advanced LIGO interferometers in Hanford (Washington State) and Livingston (Louisiana). The second observing run of the Advanced LIGO and Virgo detectors marked the first detection of a binary neutron star merger, along with its electromagnetic counterparts. The optical follow-up of the merger led to the first confirmed observations of a kilonova, an electromagnetic counterpart to binary neutron star and neutron star-black hole mergers whose existence was first predicted in 1970s. Following the multimessenger observations of the binary neutron star merger GW170817, constraints were put on the rate of expansion of the Universe using both gravitational wave and electromagnetic data. These measurements could help us understand the current tension between early-Universe and late-Universe measurements of the Hubble constant H0. The use of gravitational wave signals for measuring the rate of expansion of the Universe was proposed by Schutz in 1986. Compact binary coalescences can be used as distance markers, a gravitational wave analogue to standard candles: "Standard Sirens". Measurements of the Hubble constant from standard sirens are independent from previous methods of constraining H0. Bright sirens are gravitational wave signals that are detected coincidentally with electromagnetic signatures. These "bright" gravitational wave sirens are powerful cosmological probes, allowing us to extract information on both the distance and the redshift of the source. It is therefore important to maximise these coincident detections, and to carefully calibrate the data extracted from any standard siren. The work presented in this thesis can be divided into three main topics, all under the umbrella of maximising scientific returns from observations of compact binary coalescences. These three topics are: kilonova parameter estimation, cosmology with gravitational waves, and calibration of advanced gravitational wave detectors. We present work on inferring parameters from kilonova light curves. Ejecta parameters and information about the merging time of the progenitor is extracted from simulated kilonova light curves. We explore the consequence of neglecting some aspects of microphysics on the resulting parameter estimation. We also present new results on the inference of the Hubble constant through the application of a robust test of galaxy catalogue completeness to the current gravitational wave cosmology pipeline. We explore the impact of adopting a robust estimate of the apparent magnitude threshold mthr for the galaxy catalogues used in gravitational wave cosmology on the final inference of the Hubble constant H0 from standard sirens, and compare the results to those obtained when adopting a conservative estimate for mthr. Finally, we present the first results from the prototype of a Newtonian Calibrator at the LIGO Hanford detector. Calibrating the LIGO detectors is crucial to the extraction of the gravitational wave source parameters that are used in cosmology with standard sirens

    Simultaneous Multiparametric and Multidimensional Cardiovascular Magnetic Resonance Imaging

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