nils-herrmann/clean_scirepeval huggingface dataset:
Cross-Checking Different Sources of Mobility Information

The pervasive use of new mobile devices has allowed a better characterization in space and time of human concentrations and mobility in general. Besides its theoretical interest, describing mobility is of great importance for a number of practical applications ranging from the forecast of disease spreading to the design of new spaces in urban environments. While classical data sources, such as surveys or census, have a limited level of geographical resolution (e.g., districts, municipalities, counties are typically used) or are restricted to generic workdays or weekends, the data coming from mobile devices can be precisely located both in time and space. Most previous works have used a single data source to study human mobility patterns. Here we perform instead a cross-check analysis by comparing results obtained with data collected from three different sources: Twitter, census, and cell phones. The analysis is focused on the urban areas of Barcelona and Madrid, for which data of the three types is available. We assess the correlation between the datasets on different aspects: the spatial distribution of people concentration, the temporal evolution of people density, and the mobility patterns of individuals. Our results show that the three data sources are providing comparable information. Even though the representativeness of Twitter geolocated data is lower than that of mobile phone and census data, the correlations between the population density profiles and mobility patterns detected by the three datasets are close to one in a grid with cells of 2×2 and 1×1 square kilometers. This level of correlation supports the feasibility of interchanging the three data sources at the spatio-temporal scales considered.
On the range of admissible term-structures

In this paper, we analyze the diversity of term structure functions (e.g., yield curves, swap curves, credit curves) constructed in a process which complies with some admissible properties: arbitrage-freeness, ability to fit market quotes and a certain degree of smoothness. When present values of building instruments are expressed as linear combinations of some primary quantities such as zero-coupon bonds, discount factor, or survival probabilities, arbitrage-free bounds can be derived for those quantities at the most liquid maturities. As a matter of example, we present an iterative procedure that allows to compute model-free bounds for OIS-implied discount rates and CDS-implied default probabilities. We then show how mean-reverting term structure models can be used as generators of admissible curves. This framework is based on a particular specification of the mean-reverting level which allows to perfectly reproduce market quotes of standard vanilla interest-rate and default-risky securities while preserving a certain degree of smoothness. The numerical results suggest that, for both OIS discounting curves and CDS credit curves, the operational task of term-structure construction may be associated with a significant degree of uncertainty.
Scaling laws for molecular communication

In this paper, we investigate information-theoretic scaling laws, independent from communication strategies, for point-to-point molecular communication, where it sends/receives information-encoded molecules between nanomachines. Since the Shannon capacity for this is still an open problem, we first derive an asymptotic order in a single coordinate, i.e., i) scaling time with constant number of molecules m and ii) scaling molecules with constant time t. For a single coordinate case, we show that the asymptotic scaling is logarithmic in either coordinate, i.e., Θ(log t) and Θ(log m), respectively. We also study asymptotic behavior of scaling in both time and molecules and show that, if molecules and time are proportional to each other, then the asymptotic scaling is linear, i.e., Θ(t) = Θ(m).
Principal wind turbines for a conditional portfolio approach to wind farms

We introduce a measure for estimating the best risk-return relation of power production in wind farms within a given time-lag, conditioned to the velocity field. The velocity field is represented by a scalar that weighs the influence of the velocity at each wind turbine at present and previous time-steps for the present "state" of the wind field. The scalar measure introduced is a linear combination of the few turbines, that most influence the overall power production. This quantity is then used as the condition for computing a conditional expected return and corresponding risk associated to the future total power output.
Photometric and spectroscopic properties of Type II-P supernovae

We study a sample of 23 Type II Plateau supernovae (SNe II-P), all observed with the same set of instruments. Analysis of their photometric evolution confirms that their typical plateau duration is 100 days with little scatter, showing a tendency to get shorter for more energetic SNe. The rise time from explosion to plateau does not seem to correlate with luminosity. We analyze their spectra, measuring typical ejecta velocities, and confirm that they follow a well behaved power-law decline. We find indications of high-velocity material in the spectra of six of our SNe. We test different dust extinction correction methods by asking the following -- does the uniformity of the sample increase after the application of a given method? A reasonably behaved underlying distribution should become tighter after correction. No method we tested made a significant improvement.
An extension of the Faddeev–Jackiw technique to fields in curved spacetimes

The Legendre transformation on singular Lagrangians, e.g. Lagrangians representing gauge theories, fails due to the presence of constraints. The Faddeev–Jackiw technique, which offers an alternative to that of Dirac, is a symplectic approach to calculating a Hamiltonian paired with a well-defined initial value problem when working with a singular Lagrangian. This phase space coordinate reduction was generalized by Barcelos-Neto and Wotzasek to simplify its application. We present an extension of the Faddeev–Jackiw technique for constraint reduction in gauge field theories and non-gauge field theories that are coupled to a curved spacetime that is described by general relativity. A major difference from previous formulations is that we do not explicitly construct the symplectic matrix, as that is not necessary. We find that the technique is a useful tool that avoids some of the subtle complications of the Dirac approach to constraints. We apply this formulation to the Ginzburg–Landau action and provide a calculation of its Hamiltonian and Poisson brackets in a curved spacetime.
A deep representation for invariance and music classification

Representations in the auditory cortex might be based on mechanisms similar to the visual ventral stream; modules for building invariance to transformations and multiple layers for compositionality and selectivity. In this paper we propose the use of such computational modules for extracting invariant and discriminative audio representations. Building on a theory of invariance in hierarchical architectures, we propose a novel, mid-level representation for acoustical signals, using the empirical distributions of projections on a set of templates and their transformations. Under the assumption that, by construction, this dictionary of templates is composed from similar classes, and samples the orbit of variance-inducing signal transformations (such as shift and scale), the resulting signature is theoretically guaranteed to be unique, invariant to transformations and stable to deformations. Modules of projection and pooling can then constitute layers of deep networks, for learning composite representations. We present the main theoretical and computational aspects of a framework for unsupervised learning of invariant audio representations, empirically evaluated on music genre classification.
A conservative adaptive wavelet method for the shallow‐water equations on the sphere

We introduce an innovative wavelet‐based approach to adjust local grid resolution dynamically to maintain a uniform specified error tolerance. Extending the work of Dubos and Kevlahan, a wavelet multiscale approximation is used to make the Thuburn‐Ringler‐Skamarock‐Klemp (TRiSK) model dynamically adaptive for the rotating shallow‐water equations on the sphere. This article focuses on the challenges encountered when extending the adaptive wavelet method to the sphere and ensuring an efficient parallel implementation using message passing interface (MPI). The wavelet method is implemented in Fortran 95 with an emphasis on computational efficiency and scales well up to O(102) processors for load‐unbalanced scenarios and up to at least O(103) processors for load‐balanced scenarios. The method is verified using standard smooth test cases and a nonlinear test case proposed by Galewsky et al. The dynamical grid adaption provides compression ratios of up to 50 times in a challenging homogenous turbulence test case. The adaptive code is about three times slower per active grid point than the equivalent non‐adaptive TRiSK code and about four times slower per active grid point than an equivalent spectral code. This computationally efficient adaptive dynamical core could serve as the foundation on which to build a complete climate or weather model.
Learning Latent Block Structure in Weighted Networks

Community detection is an important task in network analysis, in which we aim to learn a network partition that groups together vertices with similar community-level connectivity patterns. By finding such groups of vertices with similar structural roles, we extract a compact representation of the network's large-scale structure, which can facilitate its scientific interpretation and the prediction of unknown or future interactions. Popular approaches, including the stochastic block model, assume edges are unweighted, which limits their utility by throwing away potentially useful information. We introduce the `weighted stochastic block model' (WSBM), which generalizes the stochastic block model to networks with edge weights drawn from any exponential family distribution. This model learns from both the presence and weight of edges, allowing it to discover structure that would otherwise be hidden when weights are discarded or thresholded. We describe a Bayesian variational algorithm for efficiently approximating this model's posterior distribution over latent block structures. We then evaluate the WSBM's performance on both edge-existence and edge-weight prediction tasks for a set of real-world weighted networks. In all cases, the WSBM performs as well or better than the best alternatives on these tasks.
The average free volume model for liquids

In this work, the molar volume thermal expansion coefficient of 59 room temperature ionic liquids is compared with their van der Waals volume Vw. Regular correlation can be discerned between the two quantities. An average free volume model, that considers the particles as hard core with attractive force, is proposed to explain the correlation in this study. A combination between free volume and Lennard-Jones potential is applied to explain the physical phenomena of liquids. Some typical simple liquids (inorganic, organic, metallic and salt) are introduced to verify this hypothesis. Good agreement from the theory prediction and experimental data can be obtained.
Theory and Application of Shapelets to the Analysis of Surface Self-assembly Imaging

A method for quantitative analysis of local pattern strength and defects in surface self-assembly imaging is presented and applied to images of stripe and hexagonal ordered domains. The presented method uses "shapelet" functions which were originally developed for quantitative analysis of images of galaxies (∝10(20)m). In this work, they are used instead to quantify the presence of translational order in surface self-assembled films (∝10(-9)m) through reformulation into "steerable" filters. The resulting method is computationally efficient (with respect to the number of filter evaluations), robust to variation in pattern feature shape, and, unlike previous approaches, is applicable to a wide variety of pattern types. An application of the method is presented which uses a nearest-neighbor analysis to distinguish between uniform (defect-free) and nonuniform (strained, defect-containing) regions within imaged self-assembled domains, both with striped and hexagonal patterns.
Higgs dark energy

We study the classical dynamics of a non-Abelian Higgs theory coupled to gravity in an isotropic and homogeneous Universe. For non-minimal coupling, this theory leads to a model of cosmic inflation that is very attractive due to its simplicity and consistency with the latest experimental data. We show that this theory can also explain the current accelerated expansion of the Universe, provided that all the gravitational and bosonic degrees of freedom, together with their symmetries, are correctly taken in account.
Conceptive Artificial Intelligence: Insights from design theory

The current paper offers a perspective on what we term conceptive intelligence - the capacity of an agent to continuously think of new object definitions (tasks, problems, physical systems, etc.) and to look for methods to realize them. The framework, called a Brouwer machine, is inspired by previous research in design theory and modeling, with its roots in the constructivist mathematics of intuitionism. The dual constructivist perspective we describe offers the possibility to create novelty both in terms of the types of objects and the methods for constructing objects. More generally, the theoretical work on which Brouwer machines are based is called imaginative constructivism. Based on the framework and the theory, we discuss many paradigms and techniques omnipresent in AI research and their merits and shortcomings for modeling aspects of design, as described by imaginative constructivism. To demonstrate and explain the type of creative process expressed by the notion of a Brouwer machine, we compare this concept with a system using genetic algorithms for scientific law discovery.
Annual modulation of cosmic relic neutrinos

The cosmic neutrino background (CνB), produced about one second after the big bang, permeates the Universe today. New technological advancements make neutrino capture on beta-decaying nuclei (NCB) a clear path forward towards the detection of the CνB. We show that gravitational focusing by the Sun causes the expected neutrino capture rate to modulate annually. The amplitude and phase of the modulation depend on the phase-space distribution of the local neutrino background, which is perturbed by structure formation. These results also apply to searches for sterile neutrinos at NCB experiments. Gravitational focusing is the only source of modulation for neutrino capture experiments, in contrast to dark-matter direct-detection searches where the Earth’s time-dependent velocity relative to the Sun also plays a role. The cosmic neutrino background (CνB) is a central prediction of standard thermal cosmology . It is similar to the cosmic microwave background (CMB) as both are relic distributions created shortly after the big bang. However, while the CMB formed when the Universe was roughly 400,000 years old, the CνB decoupled from the thermal Universe only ∼1 second after the big bang. Indirect evidence for the CνB arises from the contribution of relic neutrinos to the energy density of the Universe.
Black hole kinematics: the "in"-vacuum energy density and flux for different observers

We have investigated the local invariant scalar observables - energy density and flux - which explicitly depend on the kinematics of the concerned observers in the Vaidya gravitational collapse geometry. The use of globally defined null coordinates allows for the definition of a unique in-vacuum for the scalar field propagating in this background. Computing the stress-energy tensor for this scalar field, we work out the energy density and flux for the static observers outside the horizon and then consider the radially in-falling observers who fall in from some specified initial radius all the way through the horizon and inside to the eventual singularity. Our results confirm the thermal Tolman-shifted energy density and fluxes for the static observers which diverge at the horizon. For the in-falling observer starting from far off, both the quantities -- energy density and flux at the horizon crossing are \emph{regular and finite}. For example, the flux at the horizon for the in-falling observer from infinity is approximately 24 times the flux for the observer at infinity. Compared with the static observers in the near-horizon region, this is quite small. Both the quantities grow as the in-fall progresses inside the horizon and diverge at the singularity.
Absorption of a massive scalar field by a charged black hole

We calculate the absorption cross section of a massive neutral scalar field impinging upon a Reissner-Nordstr\"om black hole. First, we derive key approximations in the high- and low-frequency regimes. Next, we develop a numerical method to compute the cross section at intermediate frequencies, and present a selection of results. Finally, we draw together our complementary approaches to give a quantitative full-spectrum description of absorption.
Optical evidence of surface state suppression in Bi-based topological insulators

A key challenge in condensed matter research is the optimization of topological insulator (TI) compounds for the study and future application of their unique surface states. Truly insulating bulk states would allow the exploitation of predicted surface state properties, such as protection from backscattering, dissipationless spin-polarized currents, and the emergence of novel particles. Towards this end, major progress was recently made with the introduction of highly resistive Bi2Te2Se, in which surface state conductance and quantum oscillations are observed at low temperatures. Nevertheless, an unresolved and pivotal question remains: while room temperature ARPES studies reveal clear evidence of TI surface states, their observation in transport experiments is limited to low temperatures. A better understanding of this surface state suppression at elevated temperatures is of fundamental interest, and crucial for pushing the boundary of device applications towards room-temperature operation. In this work, we simultaneously measure TI bulk and surface states via temperature dependent optical spectroscopy, in conjunction with transport and ARPES measurements. We find evidence of coherent surface state transport at low temperatures, and propose that phonon mediated coupling between bulk and surface states suppresses surface conductance as temperature rises.
Interaction of misaligned magnetospheres in the coalescence of binary neutron stars

We study the dependence of the electromagnetic luminosity --produced by interactions of force-free magnetospheres-- on dipole inclinations in binary neutron star systems. We show that this interaction extracts kinetic energy from the system and powers a Poynting flux with a strong dependence on the dipole orientations. This dependence can be linked to the reconnection and redistribution of magnetic field as the stars interact. Although the details of the Poynting luminosity are very much dependent on the orientation, all the cases considered here nevertheless radiate a large Poynting flux. This robust emission suggests that the pre-merger stage of binary neutron star systems can yield interesting electromagnetic counterparts to gravitational wave events.
Joins via Geometric Resolutions: Worst-case and Beyond

We present a simple geometric framework for the relational join. Using this framework, we design an algorithm that achieves the fractional hypertree-width bound, which generalizes classical and recent worst-case algorithmic results on computing joins. In addition, we use our framework and the same algorithm to show a series of what are colloquially known as beyond worst-case results. The framework allows us to prove results for data stored in Btrees, multidimensional data structures, and even multiple indices per table. A key idea in our framework is formalizing the inference one does with an index as a type of geometric resolution; transforming the algorithmic problem of computing joins to a geometric problem. Our notion of geometric resolution can be viewed as a geometric analog of logical resolution. In addition to the geometry and logic connections, our algorithm can also be thought of as backtracking search with memoization.
Timelike Compton scattering with a linearly polarized photon beam

National Centre for Nuclear Research (NCBJ), Warsaw, Poland(Dated: January 12, 2015)We study the timelike virtual Compton scattering process with a linearly polarized photon beam,in the generalized Bjorken scaling region and in the medium energy range which will be studiedintensely at JLab12 experiments. We deﬁne new observables and show how they should help toaccess the polarized quark and gluon generalized parton distributions.
Bounding quantum correlations with indefinite causal order

Causal inequalities are bounds on correlations obtained when operations take place in a causal sequence, i.e. in which the background time or definite causal structure pre-exists such that every operation is either in the future, in the past or space-like separated from any other operation. Recently, a framework was developed where quantum theory is assumed to be valid in local laboratories, but where no reference is made to any global causal relations between the operations in the laboratories. The framework was shown to allow for correlations that violate a bipartite causal inequality. Here we prove that the maximal violation of the causal inequality is upper bounded (analogously to the Tsirelson bound) under a restricted set of local operations involving binary observables. The bound is lower than what is algebraically possible.
Resonant Brillouin scattering of excitonic polaritons in multiple-quantum-well structures

We present theoretical and experimental study of resonant Brillouin scattering of excitonic polaritons in one-dimensional multiple-quantum-well structure. We obtain general analytical results for the scattering light spectra, valid for arbitrary quantum well arrangement. Application of our theory to the specific case of short-period superlattice shows a perfect quantitative agreement with experimental results for the height, width and position of the Brillouin scattering peaks and allows us to determine the energy, radiative and nonradiative decay rates of quantum well excitons. We reveal the signatures of excitonic polariton formation in the scattering spectra and show, that the spectral width and height are strongly sensitive to the number of wells in the sample.
Is It Possible to OD on Alpha?

It is wellknown that combining multiple hedge fund alpha streams yields diversification benefits to the resultant portfolio. Additionally, crossing trades between different alpha streams reduces transaction costs: As the number of alpha streams increases, the relative turnover of the portfolio decreases with the crossing of more trades. However, Kakushadze and Liewargue that under reasonable assumptions, as the number of alphas increases, turnover does not decrease indefinitely; instead, the turnover approaches a nonvanishing limit related to the correlation structure of the portfolio’s alphas. The authors also point out that, more generally, computational simplifications can be employed when the number of alphas is large.