nils-herrmann/clean_scirepeval huggingface dataset:
Black hole solution in third order Lovelock gravity has no Gauss-Bonnet limit

We revisit the spherically symmetric third order Lovelock black hole solution in 7-dimensions. We show that the general solution for the metric function does not admit the Gauss-Bonnet (GB) limit. This is not expected due to the linear superposition of the second (GB) and third order Lovelock Lagrangians in the general action. It is found that the two branches of the GB solutions are indeed the limit of the other two complex solutions of the eld equations in the third order Lovelock gravity. These two complex solutions could not be accepted as the solutions of the Einstein’s eld equations which are supposed to be real values function on entire real r axis. A new solution which is only valid if the third order Lovelock parameter is small is introduced which can be considered as the natural extension of the general relativity (GR) to the third order Lovelock modied theory of gravity. We also generalize the discussion to the higher dimensional third order Lovelock gravity coupled to the matter sources with cosmological constant.
Einstein's equivalence principle in cosmology

We study physical consequences of the Einstein equivalence principle (EEP) for a Hubble observer in FLRW universe. We introduce the local inertial coordinates with the help of a special conformal transformation. The local inertial metric is Minkowski-flat and materialized by a congruence of time-like geodesics of static observers. The static observers are equipped with the ideal clocks measuring the proper time that is synchronized with the clocks of the Hubble observer. The local inertial metric is used for physical measurements of spacetime intervals with the ideal clocks and rulers. The special conformal transformation preserves null geodesics but does not keep invariant time-like geodesics. Moreover, it makes the rate of the local time coordinate dependent on velocity of the particle which makes impossible to rich the uniform parameterization of the world lines of static observers and light geodesics with a single parameter - they differ by the conformal factor of FLRW metric. It tells us that the metric on the light cone is not Minkowski-flat but depends on the scale factor of FLRW universe and it can be interpreted as a weak violation of EEP for photons. The importance of this violation for gravitational physics is that some of local experiments conducted with freely-propagating electromagnetic waves may be sensitive to the Hubble expansion. We show that the Hubble constant H can be measured within the solar system by means of high-precision spacecraft Doppler tracking as a blue shift of frequency of radio waves circulating in the Earth-spacecraft radio link. We also analyze the behavior of the standing wave in a microwave resonator and show that the standing wave is insensitive to the Hubble expansion.
Robust Sparse Signal Recovery for Compressed Sensing with Sampling and Dictionary Uncertainties

Compressed sensing (CS) shows that a signal having a sparse or compressible representation can be recovered from a small set of linear measurements. In classical CS theory, the sampling matrix and dictionary are assumed be known exactly in advance. However, uncertainties exist due to sampling distortion, finite grids of the parameter space of dictionary, etc. In this paper, we take a generalized sparse signal model, which simultaneously considers the sampling and dictionary uncertainties. Based on the new signal model, a new optimization model for robust sparse signal recovery is proposed. This optimization model can be deduced with stochastic robust approximation analysis. Both convex relaxation and greedy algorithms are used to solve the optimization problem. For the convex relaxation method, a sufficient condition for recovery by convex relaxation method is given; For the greedy algorithm, it is realized by the introduction of a pre-processing of the sensing matrix and the measurements. In numerical experiments, both simulated data and real-life ECG data based results show that the proposed method has a better performance than the current methods.
High Moment Variations and Their Application

We propose a new method of measuring the third and fourth moments of return distribution based on quadratic variation method when the return process is assumed to have zero drift. The realized third and fourth moment variations computed from high‐frequency return series are good approximations to corresponding actual moments of the return distribution. An investor holding an asset with skewed or fat‐tailed distribution is able to hedge the tail risk by contracting the third or fourth moment swap under which the float leg of realized variation and the predetermined fixed leg are exchanged. Thus, constructed portfolio follows more Gaussian‐like distribution and hence the investor effectively hedges the tail risk.
Graph measures and network robustness

Network robustness research aims at finding a measure to quantify network robustness. Once such a measure has been established, we will be able to compare networks, to improve existing networks and to design new networks that are able to continue to perform well when it is subject to failures or attacks. In this paper we survey a large amount of robustness measures on simple, undirected and unweighted graphs, in order to offer a tool for network administrators to evaluate and improve the robustness of their network. The measures discussed in this paper are based on the concepts of connectivity (including reliability polynomials), distance, betweenness and clustering. Some other measures are notions from spectral graph theory, more precisely, they are functions of the Laplacian eigenvalues. In addition to surveying these graph measures, the paper also contains a discussion of their functionality as a measure for topological network robustness.
Influence of shear motion on evolution of molecular clouds in the spiral galaxy M 51

We have investigated the dynamics of the molecular gas and the evolution of GMAs in the spiral galaxy M51 with the NRO 45-m telescope. The velocity components of the molecular gas perpendicular and parallel to the spiral arms are derived at each spiral phase from the distribution of the line-of-sight velocity of the CO gas. In addition, the shear motion in the galactic disk is determined from the velocity vectors at each spiral phase. It is revealed that the distributions of the shear strength and of GMAs are anti-correlated. GMAs exist only in the area of the weak shear strength and further on the upstream side of the high shear strength. GMAs and most of GMCs exist in the regions where the shear critical surface density is smaller than the gravitational critical surface density, indicating that they can stably grow by self-gravity and the collisional agglomeration of small clouds without being destroyed by shear motion. These indicate that the shear motion is an important factor in evolution of GMCs and GMAs.
An exact framework for uncertainty quantification in Monte Carlo simulation

In the context of Monte Carlo (MC) simulation of particle transport Uncertainty Quantification (UQ) addresses the issue of predicting non statistical errors affecting the physical results, i.e. errors deriving mainly from uncertainties in the physics data and/or in the model they embed. In the case of a single uncertainty a simple analytical relation exists among its the Probability Density Function (PDF) and the corresponding PDF for the output of the simulation: this allows a complete statistical analysis of the results of the simulation. We examine the extension of this result to the multi-variate case, when more than one of the physical input parameters are affected by uncertainties: a typical scenario is the prediction of the dependence of the simulation on input cross section tabulations.
ON THE OUTER EDGES OF PROTOPLANETARY DUST DISKS

The expectation that aerodynamic drag will force the solids in a gas-rich protoplanetary disk to spiral in toward the host star on short timescales is one of the fundamental problems in planet formation theory. The nominal efficiency of this radial drift process is in conflict with observations, suggesting that an empirical calibration of solid transport mechanisms in a disk is highly desirable. However, the fact that both radial drift and grain growth produce a similar particle size segregation in a disk (such that larger particles are preferentially concentrated closer to the star) makes it difficult to disentangle a clear signature of drift alone. We highlight a new approach, by showing that radial drift leaves a distinctive “fingerprint” in the dust surface density profile that is directly accessible to current observational facilities. Using an analytical framework for dust evolution, we demonstrate that the combined effects of drift and (viscous) gas drag naturally produce a sharp outer edge in the dust distribution (or, equivalently, a sharp decrease in the dust-to-gas mass ratio). This edge feature forms during the earliest phase in the evolution of disk solids, before grain growth in the outer disk has made much progress, and is preserved over longer timescales when both growth and transport effects are more substantial. The key features of these analytical models are reproduced in detailed numerical simulations, and are qualitatively consistent with recent millimeter-wave observations that find gas/dust size discrepancies and steep declines in dust continuum emission in the outer regions of protoplanetary disks.
HERWIRI2: Exponentiated Electroweak Corrections in a Hadronic Event Generator

Baylor University Waco, TX 76798, USAE-mail:bfl_ward@baylor.eduReaching the desired precision level for W and Z processes at the LHC will require a mixture ofhigher-order QCD and electroweak corrections. HERWIRI2 isa step in implementing QED ⊗QCD exponentiationin a hadroniceventgenerator. This programimplementsleadingelectroweakcorrections and coherent exclusive exponentiation in a HERWIG environment. We discuss thestatus of the program, recent tests, and future developments.36th International Conference on High Energy Physics,July 4-11, 2012Melbourne,
Dealing with the Fuzziness of Human Reasoning

Reasoning, the most important human brain operation, is charactrized by a degree fuzziness. In the present paper we construct a fuzzy model for the reasoning process giving through the calculation of the possibilities of all possible individuals' profiles a quantitative/qualitative view of their behaviour during the above process and we use the centroid defuzzification technique for measuring the reasoning skills. We also present a number of classroom experiments illustrating our results in practice.
AdS Chern-Simons gravity induces conformal gravity

The leitmotif of this paper is the question of whether four- and higher even-dimensional Conformal Gravities do have a Chern-Simons pedigree. We show that Weyl gravity can be obtained as dimensional reduction of a five-dimensional Chern-Simons action for a suitable (gauged-fixed, tractor-like) five-dimensional AdS connection. The gauge-fixing and dimensional reduction program admits a readily generalization to higher dimensions for the case of certain conformal gravities obtained by contractions of the Weyl tensor.
Complexity measurement of natural and artificial languages

We compared entropy for texts written in natural languages English, Spanish and artificial languages computer software based on a simple expression for the entropy as a function of message length and specific word diversity. Code text written in artificial languages showed higher entropy than text of similar length expressed in natural languages. Spanish texts exhibit more symbolic diversity than English ones. Results showed that algorithms based on complexity measures differentiate artificial from natural languages, and that text analysis based on complexity measures allows the unveiling of important aspects of their nature. We propose specific expressions to examine entropy related aspects of tests and estimate the values of entropy, emergence, self-organization, and complexity based on specific diversity and message length.
Unified Growth Theory: A puzzling collection of myths based on hyperbolic illusions

The Unified Growth Theory is a puzzling collection of myths based on illusions created by hyperbolic distributions. Some of these myths are discussed. The examination of data shows that the three stages of growth (Malthusian Regime, Post-Malthusian Regime and Modern Growth Regime) did not exist and that Industrial Revolution had no influence on the economic growth and on the growth of human population. All elaborate explanations revolving around phantom features created by hyperbolic illusions might be fascinating but they are scientifically unacceptable and, consequently, they do not explain the economic growth. The data clearly indicate that the economic growth was not as complicated as described by the Unified Growth Theory but elegantly simple.
Bayesian Discovery of Threat Networks

A novel unified Bayesian framework for network detection is developed, under which a detection algorithm is derived based on random walks on graphs. The algorithm detects threat networks using partial observations of their activity, and is proved to be optimum in the Neyman-Pearson sense. The algorithm is defined by a graph, at least one observation, and a diffusion model for threat. A link to well-known spectral detection methods is provided, and the equivalence of the random walk and harmonic solutions to the Bayesian formulation is proven. A general diffusion model is introduced that utilizes spatio-temporal relationships between vertices, and is used for a specific space-time formulation that leads to significant performance improvements on coordinated covert networks. This performance is demonstrated using a new hybrid mixed-membership blockmodel introduced to simulate random covert networks with realistic properties.
On Constructing Constrained Tree Automata Recognizing Ground Instances of Constrained Terms

An inductive theorem proving method for constrained term rewriting systems, which is based on rewriting induction, needs a decision procedure for reduction-completeness of constrained terms. In addition, the sufficient complete property of constrained term rewriting systems enables us to relax the side conditions of some inference rules in the proving method. These two properties can be reduced to intersection emptiness problems related to sets of ground instances for constrained terms. This paper proposes a method to construct deterministic, complete, and constraint-complete constrained tree automata recognizing ground instances of constrained terms.
Node Query Preservation for Deterministic Linear Top-Down Tree Transducers

This paper discusses the decidability of node query preservation problems for XML document transformations. We assume a transformation given by a deterministic linear top-down data tree transducer (abbreviated as DLT^V) and an n-ary query based on runs of a tree automaton. We say that a DLT^V Tr strongly preserves a query Q if there is a query Q' such that for every document t, the answer set of Q' for Tr(t) is equal to the answer set of Q for t. Also we say that Tr weakly preserves Q if there is a query Q' such that for every t_d in the range of Tr, the answer set of Q' for t_d is equal to the union of the answer set of Q for t such that t_d = Tr(t). We show that the weak preservation problem is coNP-complete and the strong preservation problem is in 2-EXPTIME.
XPath Node Selection over Grammar-Compressed Trees

XML document markup is highly repetitive and therefore well compressible using grammar-based compression. Downward, navigational XPath can be executed over grammar-compressed trees in PTIME: the query is translated into an automaton which is executed in one pass over the grammar. This result is well-known and has been mentioned before. Here we present precise bounds on the time complexity of this problem, in terms of big-O notation. For a given grammar and XPath query, we consider three different tasks: (1) to count the number of nodes selected by the query (2) to materialize the pre-order numbers of the selected nodes, and (3) to serialize the subtrees at the selected nodes.
Model for atomic dielectric response in strong, time-dependent laser fields

A nonlocal quantum-mechanical model is presented for calculating the atomic dielectric response to a strong laser electric field. By replacing the Coulomb potential with a nonlocal potential in the Schr\"odinger equation, a 3 + 1-dimensional calculation of the time-dependent electric dipole moment can be reformulated as a 0 + 1-dimensional integral equation that retains the three-dimensional dynamics, while offering significant computational savings. The model is benchmarked against an established ionization model and ab initio simulation of the time-dependent Schr\"odinger equation. The reduced computational overhead makes the model a promising candidate to incorporate full quantum-mechanical time dynamics in laser pulse propagation simulations.
Scalable Data Cube Analysis over Big Data

Data cubes are widely used as a powerful tool to provide multidimensional views in data warehousing and On-Line Analytical Processing (OLAP). However, with increasing data sizes, it is becoming computationally expensive to perform data cube analysis. The problem is exacerbated by the demand of supporting more complicated aggregate functions (e.g. CORRELATION, Statistical Analysis) as well as supporting frequent view updates in data cubes. This calls for new scalable and efficient data cube analysis systems. In this paper, we introduce HaCube, an extension of MapReduce, designed for efficient parallel data cube analysis on large-scale data by taking advantages from both MapReduce (in terms of scalability) and parallel DBMS (in terms of efficiency). We also provide a general data cube materialization algorithm which is able to facilitate the features in MapReduce-like systems towards an efficient data cube computation. Furthermore, we demonstrate how HaCube supports view maintenance through either incremental computation (e.g. used for SUM or COUNT) or recomputation (e.g. used for MEDIAN or CORRELATION). We implement HaCube by extending Hadoop and evaluate it based on the TPC-D benchmark over billions of tuples on a cluster with over 320 cores. The experimental results demonstrate the efficiency, scalability and practicality of HaCube for cube analysis over a large amount of data in a distributed environment.
Search for neutrinoless double-beta decay of Mo100 with the NEMO-3 detector

We report the results of a search for the neutrinoless double-β decay (0νββ) of Mo100, using the NEMO-3 detector to reconstruct the full topology of the final state events. With an exposure of 34.7  kg·y, no evidence for the 0νββ signal has been found, yielding a limit for the light Majorana neutrino mass mechanism of T1/2(0νββ)>1.1×1024 years (90% C.L.) once both statistical and systematic uncertainties are taken into account. Depending on the nuclear matrix elements this corresponds to an upper limit on the Majorana effective neutrino mass of ⟨mν⟩<0.3–0.9  eV (90% C.L.). Constraints on other lepton number violating mechanisms of 0νββ decays are also given. Searching for high-energy double electron events in all suitable sources of the detector, no event in the energy region [3.2–10] MeV is observed for an exposure of 47  kg·y.
Search for continuous gravitational waves: improving robustness versus instrumental artifacts

The standard multidetector F-statistic for continuous gravitational waves is susceptible to false alarms from instrumental artifacts, for example monochromatic sinusoidal disturbances (“lines”). This vulnerability to line artifacts arises because the F-statistic compares the signal hypothesis to a Gaussian-noise hypothesis, and hence is triggered by anything that resembles the signal hypothesis more than Gaussian noise. Various ad-hoc veto methods to deal with such line artifacts have been proposed and used in the past. Here we develop a Bayesian framework that includes an explicit alternative hypothesis to model disturbed data. We introduce a simple line model that defines lines as signal candidates appearing only in one detector. This allows us to explicitly compute the odds between the signal hypothesis and an extended noise hypothesis, resulting in a new detection statistic that is more robust to instrumental artifacts. We present and discuss results from Monte-Carlo tests on both simulated data and on detector data from the fifth LIGO science run. We find that the line-robust statistic retains the detection power of the standard F-statistic in Gaussian noise. In the presence of line artifacts it is more sensitive, even compared to the popular F-statistic consistency veto, over which it improves by as much as a factor of two in detectable signal strength.
Evolving functional network properties and synchronizability during human epileptic seizures.

We assess electrical brain dynamics before, during, and after 100 human epileptic seizures with different anatomical onset locations by statistical and spectral properties of functionally defined networks. We observe a concave-like temporal evolution of characteristic path length and cluster coefficient indicative of a movement from a more random toward a more regular and then back toward a more random functional topology. Surprisingly, synchronizability was significantly decreased during the seizure state but increased already prior to seizure end. Our findings underline the high relevance of studying complex systems from the viewpoint of complex networks, which may help to gain deeper insights into the complicated dynamics underlying epileptic seizures.
Feasibility of Lithium Storage on Graphene and Its Derivatives.

Nanomaterials are anticipated to be promising storage media, owing to their high surface-to-mass ratio. The high hydrogen capacity achieved by using graphene has reinforced this opinion and motivated investigations of the possibility to use it to store another important energy carrier - lithium (Li). While the first-principles computations show that the Li capacity of pristine graphene, limited by Li clustering and phase separation, is lower than that offered by Li intercalation in graphite, we explore the feasibility of modifying graphene for better Li storage. It is found that certain structural defects in graphene can bind Li stably, yet a more efficacious approach is through substitution doping with boron (B). In particular, the layered C3B compound stands out as a promising Li storage medium. The monolayer C3B has a capacity of 714 mAh/g (as Li1.25C3B), and the capacity of stacked C3B is 857 mAh/g (as Li1.5C3B), which is about twice as large as graphite's 372 mAh/g (as LiC6). Our results help clarify the mechanism of Li storage in low-dimensional materials, and shed light on the rational design of nanoarchitectures for energy storage.