A number of candidate repeating partial tidal disruption events (rpTDEs) have been reported in recent years. If these events are confirmed, the high fraction of observed rpTDEs among all tidal disruption events (TDEs) is in tension with prediction of the loss cone channel. We further point out an inequality $M_\bullet \lesssim 4\times 10^6 M_\odot (T_{\rm obt}/10\ {\rm yr})^{4/9}$ that must be satisfied for rpTDEs of solar type stars in the loss cone channel, where $M_\bullet$ is the central supermassive black hole (SMBH) mass and $T_{\rm obt}$ is the orbital period of the star. However the majority of reported rpTDE candidates potentially violate this inequality, indicating an alternative formation channel. In the commonly invoked Hills mechanism, the captured stars produced by tidal disruption of near-contact binaries can evade this inequality and may be the dominant source of rpTDEs. If the same process operates in the Galactic Center, there should exist a population of hypervelocity stars (HVSs) ejected with velocities as high as $3.6\times 10^3 (M_\bullet/10^6 M_\odot)^{1/6}\ {\rm km\ s}^{-1}$, which however have not been detected. A complete search for HVSs in the Milky Way will be critical for testing this prediction.
This chapter places evolutionary demography in the history of population thought, and more particularly in relations between demography and evolutionary population biology. Darwin conceived evolution as a dynamics of variation arising from the behaviour of populations at intra- and inter-species levels. While Malthus’s principle of population was an important early stimulus, Darwin resolved the core problem in evolution -- how mechanisms of variation combine to produce divergence of character -- by analogy to Smith’s account of the division of labour. With the benefit of hindsight, we can describe Darwinian population thinking as the first general methodology in which it became possible to combine bottom-up observation including enumeration of local population dynamics with top-down statistical methods. The two components entail different concepts of population, which may be characterised broadly as ‘open’ and ‘closed’. Their combination shows that evolutionary theory is rooted in the same sources of population thinking that gave rise to demography: the former lie in Classical population thinking and early modern population arithmetics, and the latter in 19th-century statistics and probability. Hereditary influences remained a ‘black box’ in Darwin’s theory, which only began to be unpacked with the rediscovery of Mendel’s research. The second half of the chapter traces the central role which demographic methods played in topical and analytical developments of the first half of the 20th century, including both the formulation and critique of eugenics, the emergence of population ecology, and the rise of the mathematical theory of population genetics. There is an irony here: even as demographic methods came to play an integral role, mainstream demographers became less and less involved. The ‘separatism’ of demography and evolutionary biology often remarked in the post-war era thus has deeper roots. These lie partly in topical issues, like reactions against eugenics, but more importantly in a conceptual shift in how we understand relationships between ultimate and proximate mechanisms of population change, and its implications for analysis and modelling. Evolutionary theory entails a balance of methods and insights drawing on both population concepts, which demography has not yet achieved. The concluding section provides examples of how current evolutionary demography is now integrating these developments into demographic explanation.
The planetary population synthesis method aims at comprehensively testing planet formation theories against observational evidence and providing theoretical sets of planets to help interpret observations and inform instrument development. Recent developments on the theoretical and observational sides are reviewed: First, observational constraints are summarized, then, the work flow of population synthesis and its two main components are presented, which are, global end-to-end models of planetary formation and evolution and probability distributions for the disk initial conditions. Next, the output of four recent population synthesis models is compared in detail and differences and similarities are discussed. The goal is to help the reader understand the assumptions that were made and how they impact the results. Furthermore, future directions of research are identified and the impact of current and future observational programs is discussed. With JWST, evidence on disk and planet compositions emerges. Planet formation models need to prepare for these near-future developments by including self-consistent magnetic wind-driven gas and dust disk evolution, planetary migration, as well as employ hybrid pebble and planetesimal accretion, which are identified as dominant modes of accretion in different mass regimes.
This paper introduces smoothed pseudo-population bootstrap methods for the purposes of variance estimation and the construction of confidence intervals for finite population quantiles. In an i.i.d. context, it has been shown that resampling from a smoothed estimate of the distribution function instead of the usual empirical distribution function can improve the convergence rate of the bootstrap variance estimator of a sample quantile. We extend the smoothed bootstrap to the survey sampling framework by implementing it in pseudo-population bootstrap methods for high entropy, single-stage survey designs, such as simple random sampling without replacement and Poisson sampling. Given a kernel function and a bandwidth, it consists of smoothing the pseudo-population from which bootstrap samples are drawn using the original sampling design. Given that the implementation of the proposed algorithms requires the specification of the bandwidth, we develop a plug-in selection method along with a grid search selection method based on a bootstrap estimate of the mean squared error. Simulation results suggest a gain in efficiency associated with the smoothed approach as compared to the standard pseudo-population bootstrap for estimating the variance of a quantile estimator together with mixed results regarding confidence interval coverage.
We present the first short-duration candidate microlensing events from the Kepler K2 mission. From late April to early July 2016, Campaign 9 of K2 obtained high temporal cadence observations over a 3.7 square degree region of the Galactic bulge. Its primary objectives were to look for evidence of a free-floating planet (FFP) population using microlensing, and demonstrate the feasibility of space-based planetary microlensing surveys. Though Kepler K2 is far from optimal for microlensing, the recently developed MCPM photometric pipeline enables us to identify and model microlensing events. We describe our blind event-selection pipeline in detail and use it to recover 22 short-duration events with effective timescales of less than 10 days previously announced by the OGLE and KMTNet ground-based surveys. We also announce five new candidate events. One of these is a caustic-crossing binary event, consistent with a bound planet and modelled as such in a companion study. The other four have very short durations (effective timescales less than 0.1 days) typical of an Earth-mass FFP population. Whilst Kepler was not designed for crowded-field photometry, the K2C9 dataset clearly demonstrates the feasibility of conducting blind space-based microlensing surveys towards the Galactic bulge.
Fully understanding narratives often requires identifying events in the context of whole documents and modeling the event relations. However, document-level event extraction is a challenging task as it requires the extraction of event and entity coreference, and capturing arguments that span across different sentences. Existing works on event extraction usually confine on extracting events from single sentences, which fail to capture the relationships between the event mentions at the scale of a document, as well as the event arguments that appear in a different sentence than the event trigger. In this paper, we propose an end-to-end model leveraging Deep Value Networks (DVN), a structured prediction algorithm, to efficiently capture cross-event dependencies for document-level event extraction. Experimental results show that our approach achieves comparable performance to CRF-based models on ACE05, while enjoys significantly higher computational efficiency.
Alex R. Pettitt, Fumi Egusa, Clare L. Dobbs
et al.
With the advent of modern observational efforts providing extensive giant molecular cloud catalogues, understanding the evolution of such clouds in a galactic context is of prime importance. While numerous previous numerical and theoretical works have focused on the cloud properties in isolated discs, few have looked into the cloud population in an interacting disc system. We present results of the first study investigating the evolution of the cloud population in galaxy experiencing an M51-like tidal fly-by using numerical simulations including star formation, interstellar medium cooling and stellar feedback. We see the cloud population shift to large unbound clouds in the wake of the companion passage, with the largest clouds appearing as fleeting short-lived agglomerations of smaller clouds within the tidal spiral arms, brought together by large scale streaming motions. These are then sheared apart as they leave the protection of the spiral arms. Clouds appear to lead diverse lives, even within similar environments, with some being born from gas shocked by filaments streaming into the spiral arms, and others from effectively isolated smaller colliding pairs. Overall this cloud population produces a shallower mass function than the disc in isolation, especially in the arms compared to the inter-arm regions. Direct comparisons to M51 observations show similarities between cloud populations, though models tailored to the mass and orbital models of M51 appear necessary to precisely reproduce the cloud population.
Shafi Goldwasser, Rafail Ostrovsky, Alessandra Scafuro
et al.
We introduce a new coordination problem in distributed computing that we call the population stability problem. A system of agents each with limited memory and communication, as well as the ability to replicate and self-destruct, is subjected to attacks by a worst-case adversary that can at a bounded rate (1) delete agents chosen arbitrarily and (2) insert additional agents with arbitrary initial state into the system. The goal is perpetually to maintain a population whose size is within a constant factor of the target size $N$. The problem is inspired by the ability of complex biological systems composed of a multitude of memory-limited individual cells to maintain a stable population size in an adverse environment. Such biological mechanisms allow organisms to heal after trauma or to recover from excessive cell proliferation caused by inflammation, disease, or normal development. We present a population stability protocol in a communication model that is a synchronous variant of the population model of Angluin et al. In each round, pairs of agents selected at random meet and exchange messages, where at least a constant fraction of agents is matched in each round. Our protocol uses three-bit messages and $ω(\log^2 N)$ states per agent. We emphasize that our protocol can handle an adversary that can both insert and delete agents, a setting in which existing approximate counting techniques do not seem to apply. The protocol relies on a novel coloring strategy in which the population size is encoded in the variance of the distribution of colors. Individual agents can locally obtain a weak estimate of the population size by sampling from the distribution, and make individual decisions that robustly maintain a stable global population size.
In statistics education, the concept of population is widely felt hard to grasp, as a result of vague explanations in textbooks. Some textbook authors therefore chose not to mention it. This paper offers a new explanation by proposing a new theoretical framework of population and sampling, which aims to achieve high mathematical sensibleness. In the explanation, the term population is given clear definition, and the relationship between simple random sampling and iid random variables are examined mathematically.
Suppose one has data from one or more completed vaccine efficacy trials and wishes to estimate the efficacy in a new setting. Often logistical or ethical considerations make running another efficacy trial impossible. Fortunately, if there is a biomarker that is the primary modifier of efficacy, then the biomarker-conditional efficacy may be identical in the completed trials and the new setting, or at least informative enough to meaningfully bound this quantity. Given a sample of this biomarker from the new population, we might hope we can bridge the results of the completed trials to estimate the vaccine efficacy in this new population. Unfortunately, even knowing the true conditional efficacy in the new population fails to identify the marginal efficacy due to the unknown conditional unvaccinated risk. We define a curve that partially identifies (lower bounds) the marginal efficacy in the new population as a function of the population's marginal unvaccinated risk, under the assumption that one can identify bounds on the conditional unvaccinated risk in the new population. Interpreting the curve only requires identifying plausible regions of the marginal unvaccinated risk in the new population. We present a nonparametric estimator of this curve and develop valid lower confidence bounds that concentrate at a parametric rate. We use vaccine terminology throughout, but the results apply to general binary interventions and bounded outcomes.
Observation of phenotypic diversity in a population of genetically identical cells is often linked to the stochastic nature of chemical reactions involved in gene regulatory networks. We investigate the distribution of population averaged gene expression levels as a function of population, or sample, size for several stochastic gene expression models to find out to what extent population averaged quantities reflect the underlying mechanism of gene expression. We consider three basic gene regulation networks corresponding to transcription with and without gene state switching and translation. Using analytical expressions for the probability generating function of observables and Large Deviation Theory, we calculate the distribution and first two moments of the population averaged mRNA and protein levels as a function of model parameters, population size and number of measurements contained in a data set. We validate our results using stochastic simulations also report exact results on the asymptotic properties of population averages which show qualitative differences among different models.
G. Ingrosso, S. Calchi Novati, F. De Paolis
et al.
We re-consider the polarization of the star light that may arise during microlensing events due to the high gradient of magnification across the atmosphere of the source star, by exploring the full range of microlensing and stellar physical parameters. Since it is already known that only cool evolved giant stars give rise to the highest polarization signals, we follow the model by Simmons et al. (2002) to compute the polarization as due to the photon scattering on dust grains in the stellar wind. Motivated by the possibility to perform a polarization measurement during an ongoing microlensing event, we consider the recently reported event catalog by the OGLE collaboration covering the 2001-2009 campaigns (OGLE-III events), that makes available the largest and more comprehensive set of single lens microlensing events towards the Galactic bulge. The study of these events, integrated by a Monte Carlo analysis, allows us to estimate the expected polarization profiles and to predict for which source stars and at which time is most convenient to perform a polarization measurement in an ongoing event. We find that about two dozens of OGLE-III events (about 1 percent of the total) have maximum polarization degree in the range 0.1 < P_{\rm max} <1 percent, corresponding to source stars with apparent magnitude I < 14.5, being very cool red giants.This signal is measurable by using the FORS2 polarimeter at VLT telescope with about 1 hour integration time.
A strong demographic Allee effect in which the expected population growth rate is negative below a certain critical population size can cause high extinction probabilities in small introduced populations. However, many species are repeatedly introduced to the same location and eventually one population may overcome the Allee effect by chance. With the help of stochastic models, we investigate how much genetic diversity such successful populations harbour on average and how this depends on offspring-number variation, an important source of stochastic variability in population size. We find that with increasing variability, the Allee effect increasingly promotes genetic diversity in successful populations. Successful Allee-effect populations with highly variable population dynamics escape rapidly from the region of small population sizes and do not linger around the critical population size. Therefore, they are exposed to relatively little genetic drift. We show that here---unlike in classical population genetics models---the role of offspring-number variation cannot be accounted for by an effective-population-size correction. Thus, our results highlight the importance of detailed biological knowledge, in this case on the probability distribution of family sizes, when predicting the evolutionary potential of newly founded populations or when using genetic data to reconstruct their demographic history.
The strong fluctuations in the initial energy density of heavy-ion collisions allow an efficient selection of events corresponding to a specific initial geometry. For such "shape engineered events", the elliptic flow coefficient, $v_2$, of unidentified charged particles, pions and (anti-)protons in Pb-Pb collisions at $\snn = 2.76$ TeV is measured by the ALICE collaboration. $v_2$ obtained with the event plane method at mid-rapidity, $|η|<0.8$, is reported for different collision centralities as a function of transverse momentum, $\pt$, out to $\pt=20$ GeV/$c$. The measured $v_2$ for the shape engineered events is significantly larger or smaller than the average which demonstrates the ability to experimentally select events with the desired shape of the initial spatial asymmetry.
In classical physics the joint probability of a number of individually rare independent events is given by the Poisson distribution. It describes, for example, unidirectional transfer of population between the densely and sparsely populated states of a classical two-state system. We derive a quantum version of the law for a large number of non-interacting systems (particles) obeying Bose-Einstein statistics. The classical low is significantly modified by quantum interference, which allows, among other effects, for the counter flow of particles back into the densely populated state. Suggested observation of this classically forbidden counter flow effect can be achieved with modern laser-based techniques used for manipulating and trapping of cold atoms.
The current star formation models imply that the binary fraction of population III stars is non zero. The evolution of such binaries must have led to formation of compact object binaries. In this paper we estimate the gravitational wave background originating in such binaries and discuss its observability. The properties of the population III binaries are investigated using a binary population synthesis code. We numerically model the background and we take into account the evolution of eccentric binaries. The gravitational wave background from population III binaries dominates the spectrum below 100 Hz. If the binary fraction is larger than 0.01 the background will be detectable by LISA and DECIGO. Gravitational wave background from population III binaries will dominate the spectrum below 100 Hz. LISA, ET and DECIGO should either see it easily or, in case of non detection, provide very strong constraints on the properties of the population III stars.