nils-herrmann/clean_scirepeval huggingface dataset:
Inertial particle trapping in an open vortical flow

Recent numerical results on advection dynamics have shown that particles denser than the fluid can remain trapped indefinitely in a bounded region of an open fluid flow. Here, we investigate this counterintuitive phenomenon both numerically and analytically to establish the conditions under which the underlying particle-trapping attractors can form. We focus on a two-dimensional open flow composed of a pair of vortices and its specular image, which is a system we represent as a vortex pair plus a wall along the symmetry line. Considering particles that are much denser than the fluid, referred to as heavy particles, we show that two attractors form in the neighbourhood of the vortex pair provided that the particle Stokes number is smaller than a critical value of order unity. In the absence of the wall, the attractors are fixed points in the frame rotating with the vortex pair, and the boundaries of their basins of attraction are smooth. When the wall is present, the point attractors describe counter-rotating ellipses in this frame, with a period equal to half the period of one isolated vortex pair. The basin boundaries remain smooth if the distance from the vortex pair to the wall is large. However, these boundaries are shown to become fractal if the distance to the wall is smaller than a critical distance that scales with the inverse square root of the Stokes number. This transformation is related to the breakdown of a separatrix that gives rise to a heteroclinic tangle close to the vortices, which we describe using a Melnikov function. For an even smaller distance to the wall, we demonstrate that a second separatrix breaks down and a new heteroclinic tangle forms farther away from the vortices, at the boundary between the open and closed streamlines. Particles released in the open part of the flow can approach the attractors and be trapped permanently provided that they cross the two separatrices, which can occur under the effect of flow unsteadiness. Furthermore, the trapping of heavy particles from the open flow is shown to be robust to the presence of viscosity, noise and gravity. Navier–Stokes simulations for large flow Reynolds numbers show that viscosity does not destroy the attracting points until vortex merging takes place, while simulation of thermal noise shows that particle trapping persists for extended periods provided that the Péclet number is large. The presence of a gravitational field does not alter the permanent trapping by the attracting points if the settling velocities are not too large. For larger settling velocities, however, gravity can also give rise to a limit-cycle attractor next to the external separatrix and to a new form of trapping from the open flow that is not mediated by a heteroclinic tangle.
Information Filtering on Coupled Social Networks

In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybrid pattern can not only provide more accurate recommendations, but also enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding of the structure and function of coupled social networks.
Anatomy of a Bail-In

To mitigate potential contagion from future banking crises, the European Commission recently proposed a framework which would provide for the bail-in of bank creditors in the event of failure. In this study, we examine this framework retrospectively in the context of failed European banks during the global nancial crisis. Empirical ndings suggest that equity and subordinated bond holders would have been the main losers from the e535 billion impairment losses realized by failed European banks. Losses attributed to senior debt holders would, on aggregate, have been proportionally small, while no losses would have been imposed on depositors. Cross-country analysis, incorporating stress-tests, reveals a divergence of outcomes with subordinated debt holders wiped out in a number of countries, while senior debt holders of Greek, Austrian and Irish banks would have required bail-in.
Efficient method for evaluating energy-dependent sum rules

Energy-dependent sum rules are useful tools in many fields of physics. In nuclear physics, they typically involve an integration of the response function over the nuclear spectrum with a weight function composed of integer powers of the energy. More complicated weight functions are also encountered, e.g., in nuclear polarization corrections of atomic spectra. Using the Lorentz integral transform method and the Lanczos algorithm, we derive a computationally efficient technique for evaluating such sum rules that avoids the explicit calculation of both the continuum states and the response function itself. Our numerical results for electric dipole sum rules of the Helium-4 nucleus with various energy-dependent weights show rapid convergence with respect to the number of Lanczos steps. This demonstrates the usefulness of the method in a variety of electroweak reactions.
The Call of the Crowd: Event Participation in Location-Based Social Services

Understanding the social and behavioral forces behind event participation is not only interesting from the viewpoint of social science, but also has important applications in the design of personalized event recommender systems. This paper takes advantage of data from a widely used location-based social network, Foursquare, to analyze event patterns in three metropolitan cities. We put forward several hypotheses on the motivating factors of user participation and confirm that social aspects play a major role in determining the likelihood of a user to participate in an event. While an explicit social filtering signal accounting for whether friends are attending dominates the factors, the popularity of an event proves to also be a strong attractor. Further, we capture an implicit social signal by performing random walks in a high dimensional graph that encodes the place type preferences of friends and that proves especially suited to identify relevant niche events for users. Our findings on the extent to which the various temporal, spatial and social aspects underlie users’ event preferences lead us to further hypothesize that a combination of factors better models users’ event interests. We verify this through a supervised learning framework. We show that for one in three users in London and one in five users in New York and Chicago it identifies the exact event the user would attend among the pool of suggestions.
Omega Risk Model with Tax

In this paper we study the Omega risk model with surplus-dependent tax payments in a time-homogeneous diffusion setting. The new model incorporates practical features from both the Omega risk model(Albrecher and Gerber and Shiu (2011)) and the risk model with tax(Albrecher and Hipp (2007)). We explicitly characterize the Laplace transform of the occupation time of an Azema-Yor process(e.g. a process refracted by functionals of its running maximum) below a constant level until the first hitting time of another Azema-Yor process or until an independent exponential time. This result unifies and extends recent literature(Li and Zhou (2013) and Zhang (2014)) incorporating some of their results as special cases. We explicitly characterize the Laplace transform of the time of bankruptcy in the Omega risk model with tax and discuss an extension to integral functionals. Finally we present examples using a Brownian motion with drift.
Chemlambda, universality and self-multiplication

We present chemlambda (or the chemical concrete machine), an artificial chemistry with the following properties: (a) is Turing complete, (b) has a model of decentralized, distributed computing associated to it, (c) works at the level of individual (artificial) molecules, subject of reversible, but otherwise deterministic interactions with a small number of enzymes, (d) encodes information in the geometrical structure of the molecules and not in their numbers, (e) all interactions are purely local in space and time. This is part of a larger project to create computing, artificial chemistry and artificial life in a distributed context, using topological and graphical languages.
A Necro-Biological Explanation for the Fermi Paradox

As we learn more about the frequency and size distribution of exoplanets, we are discovering that terrestrial planets are exceedingly common. The distribution of orbital periods in turn results in many of these planets being the occupants of the Habitable Zone of their host stars. Here we show that a conclusion of prevalent life in the universe presents a serious danger due to the risk of spreading Spontaneous Necro-Animation Psychosis (SNAP), or Zombie-ism. We quantify the extent of the danger posed to Earth through the use of the Zombie Drake Equation and show how this serves as a possible explanation for the Fermi Paradox. We demonstrate how to identify the resulting necro-signatures present in the atmospheres where a zombie apocalypse may have occurred so that the risk may be quantified. We further argue that it is a matter of planetary defense and security that we carefully monitor and catalog potential SNAP-contaminated planets in order to exclude contact with these worlds in a future space-faring era.
WATER CLOUDS IN Y DWARFS AND EXOPLANETS

The formation of clouds affects brown dwarf and planetary atmospheres of nearly all effective temperatures. Iron and silicate condense in L dwarf atmospheres and dissipate at the L/T transition. Minor species such as sulfides and salts condense in mid- to late T dwarfs. For brown dwarfs below Teff ∼ 450 K, water condenses in the upper atmosphere to form ice clouds. Currently, over a dozen objects in this temperature range have been discovered, and few previous theoretical studies have addressed the effect of water clouds on brown dwarf or exoplanetary spectra. Here we present a new grid of models that include the effect of water cloud opacity. We find that they become optically thick in objects below Teff ∼ 350–375 K. Unlike refractory cloud materials, water-ice particles are significantly nongray absorbers; they predominantly scatter at optical wavelengths through the J band and absorb in the infrared with prominent features, the strongest of which is at 2.8 μm. H2O, NH3, CH4, and H2 CIA are dominant opacity sources; less abundant species may also be detectable, including the alkalis, H2S, and PH3. PH3, which has been detected in Jupiter, is expected to have a strong signature in the mid-infrared at 4.3 μm in Y dwarfs around Teff = 450 K; if disequilibrium chemistry increases the abundance of PH3, it may be detectable over a wider effective temperature range than models predict. We show results incorporating disequilibrium nitrogen and carbon chemistry and predict signatures of low gravity in planetary mass objects. Finally, we make predictions for the observability of Y dwarfs and planets with existing and future instruments, including the James Webb Space Telescope and Gemini Planet Imager.
Radiative inflation and dark energy RIDEs again after BICEP2

Following the ground-breaking measurement of the tensor-to-scalar ratio r=0.20+0.07-0.05 by the BICEP2 collaboration, we perform a statistical analysis of a model that combines Radiative Inflation with Dark Energy (RIDE) based on the M2|Φ|2 ln (|Φ|2/Λ2) potential and compare its predictions to those based on the traditional chaotic inflation M2|Φ|2 potential. We find a best-fit value in the RIDE model of r=0.18 as compared to r=0.17 in the chaotic model, with the spectral index being nS=0.96 in both models.
The fifth dimension in the worldline formalism, holography, and the Wilson flow

We develop a model for hadrons in the framework of the worldline formalism. While being based wholly in four-dimensional quantum field theory, it shares many features with holographic approaches: Already by the use of the worldline formalism the approach appears intrinsically quantum mechanical. As auxiliary fifth dimension Schwinger’s proper time is grouped with the physical four spacetime dimensions into an AdS 5 geometry, which is warped due to conformal-symmetry breaking effects. Hidden local symmetry is emergent. The four-dimensional sources are extended to five-dimensional fields by a Wilson flow (gradient flow). A variational principle for the flow reproduces exactly the corresponding holographic computation. The worldline approach also yields the higher-dimensional description in the nonrelativistic case.
Tensile strained $In_{x}Ga_{1-x}P$ membranes for cavity optomechanics

We investigate the optomechanical properties of tensile-strained ternary InGaP nanomembranes grown on GaAs. This material system combines the benefits of highly strained membranes based on stoichiometric silicon nitride, with the unique properties of thin-film semiconductor single crystals, as previously demonstrated with suspended GaAs. Here we employ lattice mismatch in epitaxial growth to impart an intrinsic tensile strain to a monocrystalline thin film (approximately 30 nm thick). These structures exhibit mechanical quality factors of 2*10^6 or beyond at room temperature and 17 K for eigenfrequencies up to 1 MHz, yielding Q*f products of 2*10^12 Hz for a tensile stress of ~170 MPa. Incorporating such membranes in a high finesse Fabry-Perot cavity, we extract an upper limit to the total optical loss (including both absorption and scatter) of 40 ppm at 1064 nm and room temperature. Further reductions of the In content of this alloy will enable tensile stress levels of 1 GPa, with the potential for a significant increase in the Q*f product, assuming no deterioration in the mechanical loss at this composition and strain level. This materials system is a promising candidate for the integration of strained semiconductor membrane structures with low-loss semiconductor mirrors and for realizing stacks of membranes for enhanced optomechanical coupling.
The CALICE digital hadron calorimeter: calibration and response to pions and positrons

In order to measure the jet products of the hadronic decays of electroweak bosons in a future lepton collider with 3-4% resolution, a novel approach named Particle Flow Algorithms is proposed. The Particle Flow Algorithms attempt to measure each particle in a hadronic jet individually, using the detector providing the best energy/momentum resolution. The role of the hadronic calorimeters is to measure the neutral component of the hadronic jets. In this context, the CALICE Collaboration developed the Digital Hadron Calorimeter, which uses Resistive Plate Chambers as active media. The 1-bit resolution (digital) readout of 1 × 1 cm2 pads achieves a world record in the number of readout channels already at the prototyping stage. Here we report on the results from the analysis of pion events of momenta between 2 to 60 GeV/c collected in the Fermilab test beam with an emphasis on the intricate calibration procedures.
Approximation schemes for many-objective query optimization

The goal of multi-objective query optimization (MOQO) is to find query plans that realize a good compromise between conflicting objectives such as minimizing execution time and minimizing monetary fees in a Cloud scenario. A previously proposed exhaustive MOQO algorithm needs hours to optimize even simple TPC-H queries. This is why we propose several approximation schemes for MOQO that generate guaranteed near-optimal plans in seconds where exhaustive optimization takes hours. We integrated all MOQO algorithms into the Postgres optimizer and present experimental results for TPC-H queries; we extended the Postgres cost model and optimize for up to nine conflicting objectives in our experiments. The proposed algorithms are based on a formal analysis of typical cost functions that occur in the context of MOQO. We identify properties that hold for a broad range of objectives and can be exploited for the design of future MOQO algorithms.
Prospects for heavy flavour measurements with the ALICE inner tracker upgrade

ALICE is the general purpose heavy-ion detector at the CERN LHC. Its goal is to investigate the properties of the strongly interacting matter under the extreme conditions of density and temperature reached in Pb-Pb collisions, with the aim to characterize the Quark-Gluon Plasma (QGP). In this scenario, the upgrade of the ALICE inner tracker targets physics topics in which ALICE can bring a unique contribution to the QGP characterization via the heavy flavour probes. We present an overview of the inner tracker upgrade and the expected physics performance for heavy flavour measurements.
Topologically robust transport of photons in a synthetic gauge field.

Electronic transport is localized in low-dimensional disordered media. The addition of gauge fields to disordered media leads to fundamental changes in the transport properties. We implement a synthetic gauge field for photons using silicon-on-insulator technology. By determining the distribution of transport properties, we confirm that waves are localized in the bulk and localization is suppressed in edge states. Our system provides a new platform for investigating the transport properties of photons in the presence of synthetic gauge fields.
Parametrized post-Einsteinian framework for gravitational wave bursts

The population of stellar-mass, compact object binaries that merge with non-negligible eccentricity may be large enough to motivate searches with ground-based gravitational wave detectors. Such events could be exceptional laboratories to test General Relativity in the dynamical, strong-field regime, as a larger fraction of the energy is emitted at high velocities, compared to quasicircular inspirals. A serious obstacle here, however, is the challenge of computing theoretical waveforms for eccentric systems with the requisite accuracy for use in a matched-filter search. The corresponding waveforms are more a sequence of concentrated bursts of energy emitted near periapse than a continuous waveform. Based on this, an alternative approach, stacking excess power over the set of time-frequency tiles coincident with the bursts, was recently suggested as a more practical (though suboptimal) detection strategy. The leading-order “observable” that would be inferred from such a detection would be a sequence of discrete numbers characterizing the position and size of each time-frequency tile. In General Relativity, this (possibly large) sequence of numbers is uniquely determined by the small set of parameters describing the binary at formation. In this paper, following the spirit of the parametrized post-Einsteinian framework developed for quasicircular inspiral, we propose a simple, parametrized deformation of the baseline general relativistic burst algorithm for eccentric inspiral events that would allow for model-independent tests of Einstein’s theory in this high-velocity, strong-field regime.
Venture: a higher-order probabilistic programming platform with programmable inference

We describe Venture, an interactive virtual machine for probabilistic programming that aims to be sufficiently expressive, extensible, and efficient for general-purpose use. Like Church, probabilistic models and inference problems in Venture are specified via a Turing-complete, higher-order probabilistic language descended from Lisp. Unlike Church, Venture also provides a compositional language for custom inference strategies built out of scalable exact and approximate techniques. We also describe four key aspects of Venture's implementation that build on ideas from probabilistic graphical models. First, we describe the stochastic procedure interface (SPI) that specifies and encapsulates primitive random variables. The SPI supports custom control flow, higher-order probabilistic procedures, partially exchangeable sequences and ``likelihood-free'' stochastic simulators. It also supports external models that do inference over latent variables hidden from Venture. Second, we describe probabilistic execution traces (PETs), which represent execution histories of Venture programs. PETs capture conditional dependencies, existential dependencies and exchangeable coupling. Third, we describe partitions of execution histories called scaffolds that factor global inference problems into coherent sub-problems. Finally, we describe a family of stochastic regeneration algorithms for efficiently modifying PET fragments contained within scaffolds. Stochastic regeneration linear runtime scaling in cases where many previous approaches scaled quadratically. We show how to use stochastic regeneration and the SPI to implement general-purpose inference strategies such as Metropolis-Hastings, Gibbs sampling, and blocked proposals based on particle Markov chain Monte Carlo and mean-field variational inference techniques.
Gender Asymmetries in Reality and Fiction: The Bechdel Test of Social Media

The subjective nature of gender inequality motivates the analysis and comparison of data from real and fictional human interaction. We present a computational extension of the Bechdel test: A popular tool to assess if a movie contains a male gender bias, by looking for two female characters who discuss about something besides a man. We provide the tools to quantify Bechdel scores for both genders, and we measure them in movie scripts and large datasets of dialogues between users of MySpace and Twitter. Comparing movies and users of social media, we find that movies and Twitter conversations have a consistent male bias, which does not appear when analyzing MySpace. Furthermore, the narrative of Twitter is closer to the movies that do not pass the Bechdel test than to those that pass it. 
We link the properties of movies and the users that share trailers of those movies. Our analysis reveals some particularities of movies that pass the Bechdel test: Their trailers are less popular, female users are more likely to share them than male users, and users that share them tend to interact less with male users. Based on our datasets, we define gender independence measurements to analyze the gender biases of a society, as manifested through digital traces of online behavior. Using the profile information of Twitter users, we find larger gender independence for urban users in comparison to rural ones. Additionally, the asymmetry between genders is larger for parents and lower for students. Gender asymmetry varies across US states, increasing with higher average income and latitude. This points to the relation between gender inequality and social, economical, and cultural factors of a society, and how gender roles exist in both fictional narratives and public online dialogues.