nils-herrmann/clean_scirepeval huggingface dataset:
Evolving Black Hole Horizons in General Relativity and Alternative Gravity

From the microscopic point of view, realistic black holes are time-dependent and the teleological concept of the event horizon fails. At present, the apparent or trapping horizon seem to be its best replacements in various areas of black hole physics. We discuss the known phenomenology of apparent and trapping horizons for analytical solutions of General Relativity and alternative theories of gravity. These specific examples (we focus on spherically symmetric inhomogeneities in a background cosmological spacetime) are useful as toy models for research on various aspects of black hole physics.
Remarks on mechanical approach to observable Universe

We consider the Universe deep inside the cell of uniformity. At these scales, the Universe is filled with inhomogeneously distributed discrete structures (galaxies, groups and clusters of galaxies), which perturb the background Friedmann model. Here, the mechanical approach (Eingorn & Zhuk, 2012) is the most appropriate to describe the dynamics of the inhomogeneities which is defined, on the one hand, by gravitational potentials of inhomogeneities and, on the other hand, by the cosmological expansion of the Universe. In this paper, we present additional arguments in favor of this approach. First, we estimate the size of the cell of uniformity. With the help of the standard methods of statistical physics and for the galaxies of the type of the Milky Way and Andromeda, we get that it is of the order of 190 Mpc which is rather close to observations. Then, we show that the nonrelativistic approximation (with respect to the peculiar velocities) is valid for z≲10, i.e. approximately for 13 billion years from the present moment. We consider scalar perturbations and, within the ΛCDM model, justify the main equations. Moreover, we demonstrate that radiation can be naturally incorporated into our scheme. This emphasizes the viability of our approach. This approach gives a possibility to analyze different cosmological models and compare them with the observable Universe. For example, we indicate some problematic aspects of the spatially flat models. Such models require a rather specific distribution of the inhomogeneities to get a finite potential at any points outside gravitating masses. We also criticize the application of the Schwarzschild-de Sitter solution to the description of the motion of test bodies on the cosmological background.
Characterizing and modeling an electoral campaign in the context of Twitter: 2011 Spanish Presidential Election as a case study

Transmitting messages in the most efficient way as possible has always been one of politicians' main concerns during electoral processes. Due to the rapidly growing number of users, online social networks have become ideal platforms for politicians to interact with their potential voters. Exploiting the available potential of these tools to maximize their influence over voters is one of politicians' actual challenges. To step in this direction, we have analyzed the user activity in the online social network Twitter, during the 2011 Spanish Presidential electoral process, and found that such activity is correlated with the election results. We introduce a new measure to study political sentiment in Twitter, which we call the relative support. We have also characterized user behavior by analyzing the structural and dynamical patterns of the complex networks emergent from the mention and retweet networks. Our results suggest that the collective attention is driven by a very small fraction of users. Furthermore, we have analyzed the interactions taking place among politicians, observing a lack of debate. Finally, we develop a network growth model to reproduce the interactions taking place among politicians.
Non-linear dependences in finance

The thesis is composed of three parts. Part I introduces the mathematical and statistical tools that are relevant for the study of dependences, as well as statistical tests of Goodness-of-fit for empirical probability distributions. I propose two extensions of usual tests when dependence is present in the sample data and when observations have a fat-tailed distribution. The financial content of the thesis starts in Part II. I present there my studies regarding the "cross-sectional" dependences among the time series of daily stock returns, i.e. the instantaneous forces that link several stocks together and make them behave somewhat collectively rather than purely independently. A calibration of a new factor model is presented here, together with a comparison to measurements on real data. Finally, Part III investigates the temporal dependences of single time series, using the same tools and measures of correlation. I propose two contributions to the study of the origin and description of "volatility clustering": one is a generalization of the ARCH-like feedback construction where the returns are self-exciting, and the other one is a more original description of self-dependences in terms of copulas. The latter can be formulated model-free and is not specific to financial time series. In fact, I also show here how concepts like recurrences, records, aftershocks and waiting times, that characterize the dynamics in a time series can be written in the unifying framework of the copula.
Simple holographic model of nonlinear conductivity

gary@physics.ucsb.edu, niqbal@kitp.ucsb.edu, jss55@physics.ucsb.eduAbstractWe present a simple analytic gravitational solution which describes the holographic dual ofa 2 + 1-dimensional conductor which goes beyond the usual linear response. In particularit includes Joule heating. We nd that the nonlinear frequency-dependent conductivity isa constant. Surprisingly, the pressure remains isotropic. We also apply an electric eld toa holographic insulator and show that there is a maximum electric eld below which it canremain an insulator. Above this critical value, we argue that it becomes a conductor due topair creation of charged particles. Finally, we study 1+1 and 3+1 dimensional conductors atthe nonlinear level; here exact solutions are not available and a perturbative analysis showsthat the current becomes time dependent, but in a way that is captured by a time-dependent
Multi-Layer Graph Analysis for Dynamic Social Networks

Modern social networks frequently encompass multiple distinct types of connectivity information; for instance, explicitly acknowledged friend relationships might complement behavioral measures that link users according to their actions or interests. One way to represent these networks is as multi-layer graphs, where each layer contains a unique set of edges over the same underlying vertices (users). Edges in different layers typically have related but distinct semantics; depending on the application multiple layers might be used to reduce noise through averaging, to perform multifaceted analyses, or a combination of the two. However, it is not obvious how to extend standard graph analysis techniques to the multi-layer setting in a flexible way. In this paper we develop latent variable models and methods for mining multi-layer networks for connectivity patterns based on noisy data.
mTim: Rapid and accurate transcript reconstruction from RNA-Seq data

Recent advances in high-throughput cDNA sequencing (RNA-Seq) technology have revolutionized transcriptome studies. A major motivation for RNA-Seq is to map the structure of expressed transcripts at nucleotide resolution. With accurate computational tools for transcript reconstruction, this technology may also become useful for genome (re-)annotation, which has mostly relied on de novo gene finding where gene structures are primarily inferred from the genome sequence. We developed a machine-learning method, called mTim (margin-based transcript inference method) for transcript reconstruction from RNA-Seq read alignments that is based on discriminatively trained hidden Markov support vector machines. In addition to features derived from read alignments, it utilizes characteristic genomic sequences, e.g. around splice sites, to improve transcript predictions. mTim inferred transcripts that were highly accurate and relatively robust to alignment errors in comparison to those from Cufflinks, a widely used transcript assembly method.
Why do Earth satellites stay up

Satellites in low Earth orbits must accurately conserve their orbital eccentricity, since a decrease in perigee of only 5–10% would cause them to crash. However, these satellites are subject to gravitational perturbations from Earth's multipole moments, the Moon, and the Sun that are not spherically symmetric and hence do not conserve angular momentum, especially over the tens of thousands of orbits made by a typical satellite. Why then do satellites not crash? We describe a vector-based analysis of the long-term behavior of satellite orbits and apply this to several toy systems containing a single non-Keplerian perturbing potential. If only the quadrupole (or J2) potential from the Earth's equatorial bulge is present, all near-circular orbits are stable. If only the octupole (or J3) potential is present, all such orbits crash. If only the lunar or solar potential is present, all near-circular orbits with inclinations to the ecliptic exceeding 39° are unstable. We describe the behavior of satellites in th...
Credit risk and the instability of the financial system: An ensemble approach

The instability of the financial system as experienced in recent years and in previous periods is often linked to credit defaults, i.e., to the failure of obligors to make promised payments. Given the large number of credit contracts, this problem is amenable to be treated with approaches developed in statistical physics. We introduce the idea of ensemble averaging and thereby uncover generic features of credit risk. We then show that the often advertised concept of diversification, i.e., reducing the risk by distributing it, is deeply flawed when it comes to credit risk. The risk of extreme losses remains due to the ever present correlations, implying a substantial and persistent intrinsic danger to the financial system.
Using cosmology to establish the quantization of gravity

While many aspects of general relativity have been tested, and general principles of quantum dynamics demand its quantization, there is no direct evidence for that. It has been argued that development of detectors sensitive to individual gravitons is unlikely, and perhaps impossible. We argue here, however, that measurement of polarization of the Cosmic Microwave Background due to a long wavelength stochastic background of gravitational waves from Inflation in the Early Universe would firmly establish the quantization of gravity.
FOSSIL IMPRINT OF A POWERFUL FLARE AT THE GALACTIC CENTER ALONG THE MAGELLANIC STREAM

The Fermi satellite discovery of the gamma-ray emitting bubbles extending 50° (10 kpc) from the Galactic center has revitalized earlier claims that our Galaxy has undergone an explosive episode in the recent past. We now explore a new constraint on such activity. The Magellanic Stream is a clumpy gaseous structure free of stars trailing behind the Magellanic Clouds, passing over the south Galactic pole (SGP) at a distance of at least 50–100 kpc from the Galactic center. Several groups have detected faint Hα emission along the Magellanic Stream (1.1 ± 0.3 × 10−18 erg cm−2 s−1 arcsec−2) which is a factor of five too bright to have been produced by the Galactic stellar population. The brightest emission is confined to a cone with half angle θ1/2 ≈ 25° roughly centered on the SGP. Time-dependent models of Stream clouds exposed to a flare in ionizing photon flux show that the ionized gas must recombine and cool for a time interval To = 0.6 − 2.9 Myr for the emitted Hα surface brightness to drop to the observed level. A nuclear starburst is ruled out by the low star formation rates across the inner Galaxy, and the non-existence of starburst ionization cones in external galaxies extending more than a few kiloparsecs. Sgr A⋆ is a more likely candidate because it is two orders of magnitude more efficient at converting gas to UV radiation. The central black hole (M• ≈ 4 × 106M☉) can supply the required ionizing luminosity with a fraction of the Eddington accretion rate (fE ∼ 0.03–0.3, depending on uncertain factors, e.g., Stream distance) typical of Seyfert galaxies. In support of nuclear activity, the Hα emission along the Stream has a polar angle dependence peaking close to the SGP. Moreover, it is now generally accepted that the Stream over the SGP must be farther than the Magellanic Clouds. At the lower halo gas densities, shocks become too ineffective and are unlikely to give rise to a polar angle dependence in the Hα emission. Thus it is plausible that the Stream Hα emission arose from a “Seyfert flare” that was active 1–3 Myr ago, consistent with the cosmic ray lifetime in the Fermi bubbles. Sgr A⋆ activity today is greatly suppressed (70–80 dB) relative to the Seyfert outburst. The rapid change over a huge dynamic range in ionizing luminosity argues for a compact UV source with an extremely efficient (presumably magneto-hydrodynamic) “drip line” onto the accretion disk.
New measure of multifractality and its application in finances

We provide an alternative method for analysis of multifractal properties of time series. The new approach takes into account the behaviour of the whole multifractal profile of the generalized Hurst exponent $h(q)$ for all moment orders $q$, not limited only to the edge values of $h(q)$ describing in MFDFA scaling properties of smallest and largest fluctuations in signal. The meaning of this new measure is clarified and its properties are investigated for synthetic multifractal data and real signals taken from stock market. We show that the proposed new measure is free of problems one can meet in real nonstationary signals, while searching their multifractal signatures.
Dynamical R-parity violation.

We present a new paradigm for supersymmetric theories with R-parity violation (RPV). At high scale, R parity is conserved in the visible sector but spontaneously broken in the supersymmetry-breaking sector. The breaking is then dynamically mediated to the visible sector and is manifested via nonrenormalizable operators at low energy. Consequently, RPV operators originate from the Kähler potential rather than the superpotential, and are naturally suppressed by the supersymmetry-breaking scale, explaining their small magnitudes. A new set of nonholomorphic RPV operators is identified and found to often dominate over the standard RPV ones. We study the relevant low-energy constraints arising from baryon-number violating processes, proton decay, and flavor changing neutral currents, which may all be satisfied if a solution to the standard model flavor puzzle is incorporated. The chiral structure of the RPV operators implies new and distinct collider signatures, indicating the need to alter current techniques in searching for RPV at the LHC.
Matrix Fourier transform in dynamic theory of elasticity of piecewise homogeneous medium

The analytical solving dynamic problems of elasticity theory for piecewise homogeneous half-space is found. The explicit construction of direct and inverse Fourier's vector transform with discontinuous coefficients is presented. The technique of applying Fourier's vector transform with discontinuous coefficients for solving problems of mathematical physics in the heterogeneous environments is developed on an example of the dynamic problems of the elasticity theory.
T3B — an experiment to measure the time structure of hadronic showers

The goal of the T3B experiment is the measurement of the time structure of hadronic showers with nanosecond precision and high spatial resolution together with the CALICE hadron calorimeter prototypes, with a focus on the use of tungsten as absorber medium. The detector consists of a strip of 15 scintillator cells individually read out by silicon photomultipliers (SiPMs) and fast oscilloscopes with a PC-controlled data acquisition system. The data reconstruction uses an iterative subtraction technique which provides a determination of the arrival time of each photon on the light sensor with sub-nanosecond precision. The calibration is based on single photon-equivalent dark pulses constantly recorded during data taking, automatically eliminating the temperature dependence of the SiPM gain. In addition, a statistical correction for SiPM afterpulsing is demonstrated. To provide the tools for a comparison of T3B data with GEANT4 simulations, a digitization routine, which accounts for the detector response to energy deposits in the detector, has been implemented.
Pricing and Hedging Derivative Securities with Unknown Local Volatilities

A common assumption in financial engineering is that the market price for any derivative coincides with an objectively defined risk-neutral price - a plausible assumption only if traders collectively possess objective knowledge about the price dynamics of the underlying security over short time scales. Here we assume that traders have an objective knowledge about the underlying security's price trajectories only for large time scales. We show that avoidance of arbitrage that is still feasible uniquely determines the prices of options with large expiration times, and we derive limit theorems useful for estimation of model parameters and present-value analysis of derivative portfolios.
CHAOS AND UNPREDICTABILITY IN EVOLUTION

The possibility of complicated dynamic behavior driven by nonlinear feedbacks in dynamical systems has revolutionized science in the latter part of the last century. Yet despite examples of complicated frequency dynamics, the possibility of long‐term evolutionary chaos is rarely considered. The concept of “survival of the fittest” is central to much evolutionary thinking and embodies a perspective of evolution as a directional optimization process exhibiting simple, predictable dynamics. This perspective is adequate for simple scenarios, when frequency‐independent selection acts on scalar phenotypes. However, in most organisms many phenotypic properties combine in complicated ways to determine ecological interactions, and hence frequency‐dependent selection. Therefore, it is natural to consider models for evolutionary dynamics generated by frequency‐dependent selection acting simultaneously on many different phenotypes. Here we show that complicated, chaotic dynamics of long‐term evolutionary trajectories in phenotype space is very common in a large class of such models when the dimension of phenotype space is large, and when there are selective interactions between the phenotypic components. Our results suggest that the perspective of evolution as a process with simple, predictable dynamics covers only a small fragment of long‐term evolution.
SUBSTRUCTURE IN BULK VELOCITIES OF MILKY WAY DISK STARS

We find that Galactic disk stars near the anticenter exhibit velocity asymmetries in both the Galactocentric radial and vertical components across the midplane as well as azimuthally. These findings are based on Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) spectroscopic velocities for a sample of ∼400, 000 F-type stars, combined with proper motions from the PPMXL catalog for which we have derived corrections to the zero points based in part on spectroscopically discovered galaxies and QSOs from LAMOST. In the region within 2 kpc outside the Sun's radius and ±2 kpc from the Galactic midplane, we show that stars above the plane exhibit net outward radial motions with downward vertical velocities, while stars below the plane have roughly the opposite behavior. We discuss this in the context of other recent findings, and conclude that we are likely seeing the signature of vertical disturbances to the disk due to an external perturbation.
High energy rho meson leptoproduction

We investigate the longitudinal and transverse polarized cross-sections of the leptoproduction of the rho meson in the high energy limit. Our model is based on the computation of the impact factor gamma*(lambda_gamma) -> rho(lambda_rho) using the twist expansion in the forward limit and expressed in the impact parameter space. This treatment involves in the final stage the twist 2 and twist 3 distribution amplitudes (DAs) of the rho meson and the dipole scattering amplitude. Taking models that exist for the DAs and for the dipole cross-section, we get a phenomenological model for the helicity amplitudes, we compare our predictions with HERA data and get a fairly good description for large enough virtualities of the photon.
Predicting Adoption Probabilities in Social Networks

In a social network, adoption probability refers to the probability that a social entity will adopt a product, service, or opinion in the foreseeable future. Such probabilities are central to fundamental issues in social network analysis, including the influence maximization problem. In practice, adoption probabilities have significant implications for applications ranging from social network-based target marketing to political campaigns, yet predicting adoption probabilities has not received sufficient research attention. Building on relevant social network theories, we identify and operationalize key factors that affect adoption decisions: social influence, structural equivalence, entity similarity, and confounding factors. We then develop the locally weighted expectation-maximization method for Naive Bayesian learning to predict adoption probabilities on the basis of these factors. The principal challenge addressed in this study is how to predict adoption probabilities in the presence of confounding factors that are generally unobserved. Using data from two large-scale social networks, we demonstrate the effectiveness of the proposed method. The empirical results also suggest that cascade methods primarily using social influence to predict adoption probabilities offer limited predictive power and that confounding factors are critical to adoption probability predictions.
THE NEUTRON STAR MASS DISTRIBUTION

In recent years, the number of pulsars with secure mass measurements has increased to a level that allows us to probe the underlying neutron star (NS) mass distribution in detail. We critically review the radio pulsar mass measurements. For the first time, we are able to analyze a sizable population of NSs with a flexible modeling approach that can effectively accommodate a skewed underlying distribution and asymmetric measurement errors. We find that NSs that have evolved through different evolutionary paths reflect distinctive signatures through dissimilar distribution peak and mass cutoff values. NSs in double NS and NS–white dwarf (WD) systems show consistent respective peaks at 1.33 M☉ and 1.55 M☉, suggesting significant mass accretion (Δm ≈ 0.22 M☉) has occurred during the spin-up phase. The width of the mass distribution implied by double NS systems is indicative of a tight initial mass function while the inferred mass range is significantly wider for NSs that have gone through recycling. We find a mass cutoff at ∼2.1 M☉ for NSs with WD companions, which establishes a firm lower bound for the maximum NS mass. This rules out the majority of strange quark and soft equation of state models as viable configurations for NS matter. The lack of truncation close to the maximum mass cutoff along with the skewed nature of the inferred mass distribution both enforce the suggestion that the 2.1 M☉ limit is set by evolutionary constraints rather than nuclear physics or general relativity, and the existence of rare supermassive NSs is possible.