nils-herrmann/clean_scirepeval huggingface dataset:
Towards an Automated Classification of Transient Events in Synoptic Sky Surveys

We describe the development of a system for an automated, iterative, real-time classification of transient events discovered in synoptic sky surveys. The system under development incorporates a number of Machine Learning techniques, mostly using Bayesian approaches, due to the sparse nature, heterogeneity, and variable incompleteness of the available data. The classifications are improved iteratively as the new measurements are obtained. One novel feature is the development of an automated follow-up recommendation engine, that suggest those measurements that would be the most advantageous in terms of resolving classification ambiguities and/or characterization of the astrophysically most interesting objects, given a set of available follow-up assets and their cost functions. This illustrates the symbiotic relationship of astronomy and applied computer science through the emerging discipline of AstroInformatics.
Bridge Copula Model for Option Pricing

In this paper we present a new multi-asset pricing model, which is built upon newly developed families of solvable multi-parameter single-asset diffusions with a nonlinear smile-shaped volatility and an affine drift. Our multi-asset pricing model arises by employing copula methods. In particular, all discounted single-asset price processes are modeled as martingale diffusions under a risk-neutral measure. The price processes are so-called UOU diffusions and they are each generated by combining a variable (Ito) transformation with a measure change performed on an underlying Ornstein-Uhlenbeck (Gaussian) process. Consequently, we exploit the use of a normal bridge copula for coupling the single-asset dynamics while reducing the distribution of the multi-asset price process to a multivariate normal distribution. Such an approach allows us to simulate multidimensional price paths in a precise and fast manner and hence to price path-dependent financial derivatives such as Asian-style and Bermudan options using the Monte Carlo method. We also demonstrate how to successfully calibrate our multi-asset pricing model by fitting respective equity option and asset market prices to the single-asset models and their return correlations (i.e. the copula function) using the least-square and maximum-likelihood estimation methods.
Web Search Queries Can Predict Stock Market Volumes

We live in a computerized and networked society where many of our actions leave a digital trace and affect other people’s actions. This has lead to the emergence of a new data-driven research field: mathematical methods of computer science, statistical physics and sociometry provide insights on a wide range of disciplines ranging from social science to human mobility. A recent important discovery is that search engine traffic (i.e., the number of requests submitted by users to search engines on the www) can be used to track and, in some cases, to anticipate the dynamics of social phenomena. Successful examples include unemployment levels, car and home sales, and epidemics spreading. Few recent works applied this approach to stock prices and market sentiment. However, it remains unclear if trends in financial markets can be anticipated by the collective wisdom of on-line users on the web. Here we show that daily trading volumes of stocks traded in NASDAQ-100 are correlated with daily volumes of queries related to the same stocks. In particular, query volumes anticipate in many cases peaks of trading by one day or more. Our analysis is carried out on a unique dataset of queries, submitted to an important web search engine, which enable us to investigate also the user behavior. We show that the query volume dynamics emerges from the collective but seemingly uncoordinated activity of many users. These findings contribute to the debate on the identification of early warnings of financial systemic risk, based on the activity of users of the www.
Expanding universe as a classical solution in the Lorentzian matrix model for nonperturbative superstring theory

Recently we have shown by Monte Carlo simulation that expanding (3+1)-dimensional universe appears dynamically from a Lorentzian matrix model for type IIB superstring theory in (9+1)-dimensions. The mechanism for the spontaneous breaking of rotational symmetry relies crucially on the noncommutative nature of the space. Here we study the classical equations of motion as a complementary approach. In particular, we find a unique class of SO(3) symmetric solutions, which exhibits the time-dependence compatible with the expanding universe. The space-space noncommutativity is exactly zero, whereas the space-time noncommutativity becomes significant only towards the end of the expansion. We interpret the Monte Carlo results and the classical solution as describing the behavior of the model at earlier time and at later time, respectively.
A limit order book model for latency arbitrage

We consider a single security market based on a limit order book and two investors, with different speeds of trade execution. If the fast investor can preempt the slower investor, we show that this allows the fast trader to obtain risk free profits, but that these profits cannot be scaled. We derive the fast trader’s optimal behaviour when she has only distributional knowledge of the slow trader’s actions, with few restrictions on the possible prior distributions. We also consider the slower trader’s response to the presence of a fast trader in a market, and the effects of the introduction of a ‘Tobin tax’ on financial transactions. We show that such a tax can lead to the elimination of profits from preemptive strategies. Consequently, a Tobin tax can both increase market efficiency and attract traders to a market.
Leveraging User Diversity to Harvest Knowledge on the Social Web

Social web users are a very diverse group with varying interests, levels of expertise, enthusiasm, and expressiveness. As a result, the quality of content and annotations they create to organize content is highly variable. While several approaches have been proposed to mine social annotations, for example, to learn folksonomies that reflect how people relate narrower concepts to broader ones, these methods treat all users and the annotations they create uniformly. We propose a framework to automatically identify experts, i.e., knowledgeable users who create high quality annotations, and use their knowledge to guide folksonomy learning. We evaluate the approach on a large body of social annotations extracted from the photo sharing site Flickr. We show that using expert knowledge leads to more detailed and accurate folksonomies. Moreover, we show that including annotations from non-expert, or novice, users leads to more comprehensive folksonomies than using experts' knowledge alone.
Evolution of Supernova Remnants Expanding out of the Dense Circumstellar Matter into the Rarefied Interstellar Medium

We carry out 3D-hydrodynamical calculations for the interaction of expanding supernova ejecta with the dense circumstellar matter (CSM) and the rarefied interstellar medium (ISM) outside. The CSM is composed of the stellar wind matter from the progenitor in its pre-supernova phase, and assumed to be axially symmetric: more matter around the equator than in the polar direction driven by rotation of the progenitor. Because of high density of the CSM, the ionization state of the shock-heated ejecta quickly becomes equilibrium with the electron temperature. When the blast wave breaks out of the CSM into the rarefied ISM, the shocked ejecta cools rapidly due to adiabatic expansion, and hence an over-ionized/recombining plasma would be left. The ejecta is reheated by the second reverse shock due to the interaction with the ISM. We calculate the emission measure of the supernova remnant (SNR) along the line of sight, and find that the over-ionized plasma appears to be bar-like with wings in the edge-on (equatorial view), while shell-like in the face-on (polar view) geometry with respect to the rotation axis. The hot gas heated by the blast wave exists in the outermost region of the SNR with a nearly complete shell, but the X-rays therefrom are too faint to be observable. Thus, depending on the viewing angle, the SNR of the over-ionized plasma would exhibit center-filled morphology in X-rays, like W49B, a mixed-morphology SNR. The bar-like structure is swept out by the second reverse shock and disappears eventually, and then the SNR becomes shell-like in both the equatorial and polar views in the later phase of the evolution.
Notes from Sidney Coleman's Physics 253a

These notes were taken by Brian Hill during Sidney Coleman's lectures on Quantum Field Theory (Physics 253), given at Harvard University in Fall semester of the 1986-1987 academic year. They were recently typeset and edited by Yuan-Sen Ting and Bryan Gin-ge Chen. Although most of topics in the second part of the course (Physics 253b) were assembled and published in Coleman's book "Aspects of Symmetry", these notes remain the principal source for the Physics 253a materials.
Recovering a Clipped Signal in Sparseland

In many data acquisition systems it is common to observe signals whose amplitudes have been clipped. We present two new algorithms for recovering a clipped signal by leveraging the model assumption that the underlying signal is sparse in the frequency domain. Both algorithms employ ideas commonly used in the field of Compressive Sensing; the first is a modified version of Reweighted $\ell_1$ minimization, and the second is a modification of a simple greedy algorithm known as Trivial Pursuit. An empirical investigation shows that both approaches can recover signals with significant levels of clipping
About Statistical Questions Involved in the Data Analysis of the OPERA Experiment

The authors of the OPERA experiment [] claim that "the measurement indicates an early arrival time of CNGS muon neutrinos with respect to the one computed assuming the speed of light in vacuum". In this note we analyze the statistical aspects of the experimental results presented in , assuming that no hidden experimental bias exists. Due to statistical constraints, we show (through two different methods) that the experimental data presented in  do not permit to conclude unambiguously with the existence of a superluminal behavior of neutrinos. The problem lies essentially in the interpretation of the data and not in their veracity.
Fundamental Measurements in Economics and in the Theory of Consciousness

A new constructivist approach to modeling in economics and theory of consciousness is proposed. The state of elementary object is defined as a set of its measurable consumer properties. A proprietor's refusal or consent for the offered transaction is considered as a result of elementary economic measurement. Elementary (indivisible) technology, in which the object's consumer values are variable, in this case can be formalized as a generalized economic measurement. The algebra of such measurements has been constructed. It has been shown that in the general case the quantum-mechanical formalism of the theory of selective measurements is required for description of such conditions. The economic analogs of the elementary slit experiments in physics have been created. The proposed approach can be also used for consciousness modeling.
How to Use Experimental Data to Compute the Probability of Your Theory

This article is geared towards theorists interested in estimating parameters of their theoretical models, and computing their own limits using available experimental data and elementary Mathematica code. The examples given can be useful also to experimentalists who wish to learn how to use Bayesian methods. A thorough introduction precedes the practical part, to make clear the advantages and shortcomings of the method, and to prevent its abuse. The goal of this article is to help bridge the gap between theory and experiment.
What's Wrong With Black Hole Thermodynamics?

Not only is the Bekenstein expression for the entropy of a black hole a convex function of the energy, rather than being a concave function as it must be, it predicts a final equilibrium temperature given by the harmonic mean. This violates the third law, and the principle of maximum work. The property that means are monotonically increasing functions of their argument underscores the error of transferring from temperature means to means in the internal energy when the energy is not a monotonically increasing function of temperature. Whereas the former leads to an increase in entropy, the latter lead to a decrease in entropy thereby violating the second law. The internal energy cannot increase at a slower rate than the temperature itself.
Slowly-rotating stars and black holes in dynamical Chern-Simons gravity

Chern-Simons (CS) modified gravity is an extension to general relativity (GR) in which the metric is coupled to a scalar field, resulting in modified Einstein field equations. In the dynamical theory, the scalar field is itself sourced by the Pontryagin density of the space-time. In this paper, the coupled system of equations for the metric and the scalar field is solved numerically for slowly rotating neutron stars described with realistic equations of state and for slowly rotating black holes. An analytic solution for a constant-density nonrelativistic object is also presented. It is shown that the black hole solution cannot be used to describe the exterior space-time of a star as was previously assumed. In addition, whereas previous analysis were limited to the small-coupling regime, this paper considers arbitrarily large coupling strengths. It is found that the CS modification leads to two effects on the gravitomagnetic sector of the metric: (i) Near the surface of a star or the horizon of a black hole, the magnitude of the gravitomagnetic potential is decreased and frame-dragging effects are reduced in comparison to GR. (ii) In the case of a star, the angular momentum J, as measured by distant observers, is enhanced in CS gravity as compared to standard GR. For a large coupling strength, the near-zone frame-dragging effects become significantly screened, whereas the far-zone enhancements saturate at a maximum value ΔJ_(max)∼(M/R)J_(GR). Using measurements of frame-dragging effects around the Earth by Gravity Probe B and the LAGEOS satellites, a weak but robust constraint is set to the characteristic CS length scale, ξ^(1/4)≲10^8  km.
The Final Stage of Gravitationally Collapsed Thick Matter Layers

In the presence of a minimal length, physical objects cannot collapse to an infinite density, singular, matter point. In this paper, we consider the possible final stage of the gravitational collapse of “thick” matter layers. The energy momentum tensor we choose to model these shell-like objects is a proper modification of the source for “noncommutative geometry inspired,” regular black holes. By using higher momenta of Gaussian distribution to localize matter at finite distance from the origin, we obtain new solutions of the Einstein equation which smoothly interpolates between Minkowski’s geometry near the center of the shell and Schwarzschild’s spacetime far away from the matter layer. The metric is curvature singularity free. Black hole type solutions exist only for “heavy” shells; that is, , where is the mass of the extremal configuration. We determine the Hawking temperature and a modified area law taking into account the extended nature of the source.
A quantum-like approach to the stock market

Modern approaches to stock pricing in quantitative finance are typically founded on the 'Black-Scholes model' and the underlying 'random walk hypothesis'. Empirical data indicate that this hypothesis works well in stable situations but, in abrupt transitions such as during an economical crisis, the random walk model fails and alternative descriptions are needed. For this reason, several proposals have been recently forwarded which are based on the formalism of quantum mechanics. In this paper we apply the 'SCoP formalism', elaborated to provide an operational foundation of quantum mechanics, to the stock market. We argue that a stock market is an intrinsically contextual system where agents' decisions globally influence the market system and stocks prices, determining a nonclassical behavior. More specifically, we maintain that a given stock does not generally have a definite value, e.g., a price, but its value is actualized as a consequence of the contextual interactions in the trading process. This contextual influence is responsible of the non-Kolmogorovian quantum-like behavior of the market at a statistical level. Then, we propose a 'sphere model' within our 'hidden measurement formalism' that describes a buying/selling process of a stock and shows that it is intuitively reasonable to assume that the stock has not a definite price until it is traded. This result is relevant in our opinion since it provides a theoretical support to the use of quantum models in finance.
MyZone: A Next-Generation Online Social Network

This technical report considers the design of a social network that would address the shortcomings of the current ones, and identifies user privacy, security, and service availability as strong motivations that push the architecture of the proposed design to be distributed. We describe our design in detail and identify the property of resiliency as a key objective for the overall design philosophy. 
We define the system goals, threat model, and trust model as part of the system model, and discuss the challenges in adapting such distributed frameworks to become highly available and highly resilient in potentially hostile environments. We propose a distributed solution to address these challenges based on a trust-based friendship model for replicating user profiles and disseminating messages, and examine how this approach builds upon prior work in distributed Peer-to-Peer (P2P) networks.
Optimizing expected utility of dividend payments for a Cram\'er-Lundberg risk proces

We consider the problem of maximizing the discounted utility of dividend payments of an insurance company whose reserves are modeled as a classical Cram\'er-Lundberg risk process. We investigate this optimization problem under the constraint that dividend rate is bounded. We prove that the value function fulfills the Hamilton-Jacobi-Bellman equation and we identify the optimal dividend strategy.
Conceptual Problems in Cosmology

In this essay a critical review of present conceptual problems in current cosmology is provided from a more philosophical point of view. In essence, a digression on how could philosophy help cosmologists in what is strictly their fundamental endeavor is presented. We start by recalling some examples of enduring confrontations among philosophers and physicists on what could be contributed by the formers to the day-time striving of the second ones. Then, a short review of the standard model Friedmann-Lema^ tre-Robertson-Walter (FLRW) of cosmology is given, since Einsteins days throughout the Hubble discover of the expansion of the universe, the Gamow, Alpher and Herman primordial nucleo-synthesis calculations and prediction of the cosmic microwave background (CMB) radiation; as detected by Penzias and Wilson, to Guth-Linde inationary scenarios and the controversial multiverse and landscape ideas as prospective way outs to most cosmic conceptual conundrums. It seems apparent that cosmology is living a golden age with the advent of observations of high precision. Nonetheless, a critical revisiting of the direction in which it should go on appears also needed, for misconcepts like \quantum backgrounds for cosmological classical settings" and \quantum gravity unication" have not been properly constructed up-to-date. Thus, knowledge-building in cosmology, more than in any other eld, should begin with visions of the reality, then taking technical form whenever concepts and relations inbetween are translated into a mathematical structure. It is mandatory, therefore, that the meaning of such concepts be the same for all cosmologists, and that any relationship among all them be tested both logically as well as mathematically. In other words, the notorius feature of improbability of our universe, as is well-known, assures to cosmologists a priviledged degree of freedom for formulating interpretations and theories. However, at the same time, it demands for their formulations and conclusions to be considered in the light of data taken from astrophysical observations.
Geometric Approaches for Generating Prolongations for Nonlinear Partial Differential Equations

The prolongation structure of a two-by-two problem is formulated very generally in terms of exterior differential forms on a standard representation of Pauli matrices. The differential system is general without making reference to any specific equation. An integrability condition is provided which gives by construction the equation to be investigated and whose components involve the structure constants of an SU(2) Lie algebra. Along side this, a related, different kind of prolongation, a type of Wahlquist-Estabrook prolongation, over a closed differential ideal is discussed and some applications are given.
Heterogeneity shapes groups growth in social online communities

Many complex systems are characterized by broad distributions capturing, for example, the size of firms, the population of cities or the degree distribution of complex networks. Typically this feature is explained by means of a preferential growth mechanism. Although heterogeneity is expected to play a role in the evolution, it is usually not considered in the modeling probably due to a lack of empirical evidence on how it is distributed. We characterize the intrinsic heterogeneity of groups in an online community and then show that together with a simple linear growth and an inhomogeneous birth rate it explains the broad distribution of group members.
Mapping (USPTO) Patent Data using Overlays to Google Maps

A technique is developed using patent information available online (at the U.S. Patent and Trademark Office) for the generation of Google Maps. The overlays indicate both the quantity and the quality of patents at the city level. This information is relevant for research questions in technology analysis, innovation studies, and evolutionary economics, as well as economic geography. The resulting maps can also be relevant for technological innovation policies and research and development management, because the U.S. market can be considered the leading market for patenting and patent competition. In addition to the maps, the routines provide quantitative data about the patents for statistical analysis. The cities on the map are colored according to the results of significance tests. The overlays are explored for the Netherlands as a “national system of innovations” and further elaborated in two cases of emerging technologies: ribonucleic acid interference (RNAi) and nanotechnology.