nils-herrmann/clean_scirepeval huggingface dataset:
A Conceptual Network-Based Approach to Inferring the Cultural Evolutionary History of the Baltic Psaltery

The application of conventional phylogenetic techniques for inferring cultural history is problematic due to differences in the nature of information transmission in biological and cultural realms. In culture, units of transmission are not just measurable attributes, but communicable concepts. Therefore, relatedness amongst cultural elements often resides at the conceptual level not captured by traditional phylogenetic methods. This paper takes a cognitively inspired approach to analyzing material cultural history. We show that combining data for physical attributes of cultural artifacts with conceptual information can uncover cultural influences among different ethnolinguistic groups, and reveal new patterns of cultural ancestry. Using the Baltic psaltery, a musical instrument with a well-documented ethnographic and archaeological record, we recovered a previously unacknowledged pattern of historical relationship that is more congruent with geographical distribution and temporal data than is obtained with other approaches.
Agent-Based Stock Market Model with Endogenous Agents' Impact

The three-state agent-based 2D model of financial markets as proposed by Giulia Iori has been extended by introducing increasing trust in the correctly predicting agents, a more realistic consultation procedure as well as a formal validation mechanism. This paper shows that such a model correctly reproduces the three fundamental stylised facts: fat-tail log returns, power-law volatility autocorrelation decay in time and volatility clustering.
Exploiting Neutron-rich Radioactive Ion Beams To Constrain The Symmetry Energy

The Modular Neutron Array (MoNA) and 4 Tm Sweeper magnet were used to measure the free neutrons and heavy charged particles from the radioactive ion beam induced 32Mg + 9Be reaction. The fragmentation reaction was simulated with the Constrained Molecular Dynamics model(CoMD), which demonstrated that the of the heavy fragments and free neutron multiplicities were observables sensitive to the density dependence of the symmetry energy at sub-saturation densities. Through comparison of these simulations with the experimental data constraints on the density dependence of the symmetry energy were extracted. The advantage of radioactive ion beams as a probe of the symmetry energy is demonstrated through examination of CoMD calculations for stable and radioactive beam induced reactions.
Comparison of Fast Amplifiers for Diamond Detectors

The development of Chemical Vapour Deposition (CVD) diamond detectors requests for novel signal amplifiers, capable to match the superb signal-to-noise ratio and timing response of these detectors. Existing amplifiers are still far away from this goal and are the dominant contributors to the overall system noise and the main source of degradation of the energy and timing resolution. We tested a number of commercial amplifiers designed for diamond detector readout to identify the best solution for a particular application. This application required a deposited energy threshold below 100 keV and timing resolution of the order of 200 ps at 200 keV. None of tested amplifiers satisfies these requirements. The best solution to such application found to be the Cividec C6 amplifier, which allows 100 keV minimal threshold, but its coincidence timing resolution at 200 keV is as large as 1.2 ns.
Shapes of Implied Volatility with Positive Mass at Zero

We study the shapes of the implied volatility when the underlying distribution has an atom at zero and analyse the impact of a mass at zero on at-the-money implied volatility and the overall level of the smile. We further show that the behaviour at small strikes is uniquely determined by the mass of the atom up to high asymptotic order, under mild assumptions on the remaining distribution on the positive real line. We investigate the structural difference with the no-mass-at-zero case, showing how one can--theoretically--distinguish between mass at the origin and a heavy-left-tailed distribution. We numerically test our model-free results in stochastic models with absorption at the boundary, such as the CEV process, and in jump-to-default models. Note that while Lee's moment formula tells that implied variance is at most asymptotically linear in log-strike, other celebrated results for exact smile asymptotics such as Benaim and Friz (09) or Gulisashvili (10) do not apply in this setting--essentially due to the breakdown of Put-Call duality.
A fast route to modified gravitational growth

The growth rate of the large-scale structure of the Universe has been advocated as the observable par excellence for testing gravity on cosmological scales. By considering linear-order deviations from general relativity, we show that corrections to the growth rate, $f$, can be expressed as an integral over a ``source'' term, weighted by a theory-independent ``response kernel.'' This leads to an efficient and accurate ``plug-and-play'' expression for generating growth rates in alternative gravity theories, bypassing lengthy theory-specific computations. We use this approach to explicitly show that $f$ is sensitive to a degenerate combination of modified expansion and modified clustering effects. Hence the growth rate, when used in isolation, is not a straightforward diagnostic of modified gravity.
Arbitrage-Free Pricing Before and Beyond Probabilities

"Fundamental theorem of asset pricing" roughly states that absence of arbitrage opportunity in a market is equivalent to the existence of a risk-neutral probability. We give a simple counterexample to this oversimplified statement. Prices are given by linear forms which do not always correspond to probabilities. We give examples of such cases. We also show that arbitrage freedom is equivalent to the continuity of the pricing linear form in the relevant topology. Finally we analyze the possible loss of martingality of asset prices with lognormal stochastic volatility. For positive correlation martingality is lost when the financial process is modelled through standard probability theory. We show how to recover martingality using the appropriate mathematical tools.
Coulomb effects in cold fission from reactions 233U(nth,f) and 235U(nth,f)

The Coulomb effect hypothesis in cold fission, formerly used to interpret fluctuations in the curve of maximal total kinetic energy as a function of fragments mass, in reactions 233U(nth,f), 235U(nth,f) and 239Pu(nth,f), is confirmed by the preference for more asymmetrical charge splits observed in cold fragmentations. Several experimental results on reactions 233U(nth,f) and 235U(nth,f) show that, for two isobaric fragmentations with similar Q-values, the greater is the value of the kinetic energy of the fragments, the greater will be the probability of more asymmetric charge split.
Multi-boson spectrum of the SU(2)-Higgs model

Lattice simulations are used to compute the spectrum of energy levels for all angular momentum and parity quantum numbers in the SU(2)-Higgs model, with parameters chosen to match experimental data from the Higgs-W boson sector of the standard model. Creation operators are constructed for all lattice irreducible representations, and a correlation matrix is formed from which the spectrum is extracted using a variational analysi s. Many multi-boson states are observed and careful analysis reveals that all are consistent with weakly-interacting Higgs and W bosons.
Compression of animated 3D models using HO-SVD

This work presents an analysis of Higher Order Singular Value Decomposition (HO-SVD) applied to lossy compression of 3D mesh animations. We describe strategies for choosing a number of preserved spatial and temporal components after tensor decomposition. Compression error is measured using three metrics (MSE, Hausdorff, MSDM). Results are compared with a method based on Principal Component Analysis (PCA) and presented on a set of animations with typical mesh deformations.
Reading Stockholm Riots 2013 in social media by text-mining

The riots in Stockholm in May 2013 were an event that reverberated in the world media for its dimension of violence that had spread through the Swedish capital. In this study we have investigated the role of social media in creating media phenomena via text mining and natural language processing. We have focused on two channels of communication for our analysis: Twitter and Poloniainfo.se (Forum of Polish community in Sweden). Our preliminary results show some hot topics driving discussion related mostly to Swedish Police and Swedish Politics by counting word usage. Typical features for media intervention are presented. We have built networks of most popular phrases, clustered by categories (geography, media institution, etc.). Sentiment analysis shows negative connotation with Police. The aim of this preliminary exploratory quantitative study was to generate questions and hypotheses, which we could carefully follow by deeper more qualitative methods.
The planets around nn serpentis: still there

We present 25 new eclipse times of the white dwarf binary NN Ser taken with the high-speed camera ULTRACAM on the William Herschel Telescope and New Technology Telescope, the RISE camera on the Liverpool Telescope and HAWK-I on the Very Large Telescope to test the two-planet model proposed to explain variations in its eclipse times measured over the last 25 yr. The planetary model survives the test with flying colours, correctly predicting a progressive lag in eclipse times of 36 s that has set in since 2010 compared to the previous 8 yr of precise times. Allowing both orbits to be eccentric, we find orbital periods of 7.9 ± 0.5 and 15.3 ± 0.3 yr, and masses of 2.3 ± 0.5 and 7.3 ± 0.3 MJ. We also find dynamically long-lived orbits consistent with the data, associated with 2:1 and 5:2 period ratios. The data scatter by 0.07 s relative to the best-fitting model, by some margin the most precise of any of the proposed eclipsing compact object planet hosts. Despite the high precision, degeneracy in the orbit fits prevents a significant measurement of a period change of the binary and of N-body effects. Finally, we point out a major flaw with a previous dynamical stability analysis of NN Ser, and by extension, with a number of analyses of similar systems.
Sequential Monte Carlo Bandits

In this paper we propose a flexible and efficient framework for handling multi-armed bandits, combining sequential Monte Carlo algorithms with hierarchical Bayesian modeling techniques. The framework naturally encompasses restless bandits, contextual bandits, and other bandit variants under a single inferential model. Despite the model's generality, we propose efficient Monte Carlo algorithms to make inference scalable, based on recent developments in sequential Monte Carlo methods. Through two simulation studies, the framework is shown to outperform other empirical methods, while also naturally scaling to more complex problems for which existing approaches can not cope. Additionally, we successfully apply our framework to online video-based advertising recommendation, and show its increased efficacy as compared to current state of the art bandit algorithms.
Measurement of thin films using very long acoustic wavelengths

A procedure for measuring material thickness by means of necessarily long acoustic wavelengths is examined. The approach utilizes a temporal phase lag caused by the impulse time of wave momentum transferred through a thin layer that is much denser than its surrounding medium. In air, it is predicted that solid or liquid layers below approximately 1/2000 of the acoustic wavelength will exhibit a phase shift with an arctangent functional dependence on thickness and layer density. The effect is verified for thin films on the scale of 10 μm using audible frequency sound (7 kHz). Soap films as thin as 100 nm are then measured using 40 kHz air ultrasound. The method's potential for imaging applications is demonstrated by combining the approach with near-field holography, resulting in reconstructions with sub-wavelength resolution in both the depth and lateral directions. Potential implications at very high and very low acoustic frequencies are discussed.
Narrowing the Gap: Random Forests In Theory and In Practice

Despite widespread interest and practical use, the theoretical properties of random forests are still not well understood. In this paper we contribute to this understanding in two ways. We present a new theoretically tractable variant of random regression forests and prove that our algorithm is consistent. We also provide an empirical evaluation, comparing our algorithm and other theoretically tractable random forest models to the random forest algorithm used in practice. Our experiments provide insight into the relative importance of different simplifications that theoreticians have made to obtain tractable models for analysis.
Contraction Principle based Robust Iterative Algorithms for Machine Learning

Iterative algorithms are ubiquitous in the field of data mining. Widely known examples of such algorithms are the least mean square algorithm, backpropagation algorithm of neural networks. Our contribution in this paper is an improvement upon this iterative algorithms in terms of their respective performance metrics and robustness. This improvement is achieved by a new scaling factor which is multiplied to the error term. Our analysis shows that in essence, we are minimizing the corresponding LASSO cost function, which is the reason of its increased robustness. We also give closed form expressions for the number of iterations for convergence and the MSE floor of the original cost function for a minimum targeted value of the L1 norm. As a concluding theme based on the stochastic subgradient algorithm, we give a comparison between the well known Dantzig selector and our algorithm based on contraction principle. By these simulations we attempt to show the optimality of our approach for any widely used parent iterative optimization problem.
Gravitational Radiation from Post-Newtonian Sources and Inspiralling Compact Binaries

To be observed and analyzed by the network of gravitational wave detectors on ground (LIGO, VIRGO, etc.) and by the future detectors in space (eLISA, etc.), inspiralling compact binaries — binary star systems composed of neutron stars and/or black holes in their late stage of evolution — require high-accuracy templates predicted by general relativity theory. The gravitational waves emitted by these very relativistic systems can be accurately modelled using a high-order post-Newtonian gravitational wave generation formalism. In this article, we present the current state of the art on post-Newtonian methods as applied to the dynamics and gravitational radiation of general matter sources (including the radiation reaction back onto the source) and inspiralling compact binaries. We describe the post-Newtonian equations of motion of compact binaries and the associated Lagrangian and Hamiltonian formalisms, paying attention to the self-field regularizations at work in the calculations. Several notions of innermost circular orbits are discussed. We estimate the accuracy of the post-Newtonian approximation and make a comparison with numerical computations of the gravitational self-force for compact binaries in the small mass ratio limit. The gravitational waveform and energy flux are obtained to high post-Newtonian order and the binary’s orbital phase evolution is deduced from an energy balance argument. Some landmark results are given in the case of eccentric compact binaries — moving on quasi-elliptical orbits with non-negligible eccentricity. The spins of the two black holes play an important role in the definition of the gravitational wave templates. We investigate their imprint on the equations of motion and gravitational wave phasing up to high post-Newtonian order (restricting to spin-orbit effects which are linear in spins), and analyze the post-Newtonian spin precession equations as well as the induced precession of the orbital plane.
CAM: Causal Additive Models, high-dimensional order search and penalized regression

We develop estimation for potentially high-dimensional additive structural equation models. A key component of our approach is to decouple order search among the variables from feature or edge selection in a directed acyclic graph encoding the causal structure. We show that the former can be done with nonregularized (restricted) maximum likelihood estimation while the latter can be efficiently addressed using sparse regression techniques. Thus, we substantially simplify the problem of structure search and estimation for an important class of causal models. We establish consistency of the (restricted) maximum likelihood estimator for low- and high-dimensional scenarios, and we also allow for misspecification of the error distribution. Furthermore, we develop an efficient computational algorithm which can deal with many variables, and the new method’s accuracy and performance is illustrated on simulated and real data.
Random Matrix Application to Correlations Among Volatility of Assets

In this paper, we apply tools from the random matrix theory (RMT) to estimates of correlations across volatility of various assets in the S&P 500. The volatility inputs are estimated by modeling price fluctuations as GARCH(1,1) process. The corresponding correlation matrix is constructed. It is found that the distribution of a significant number of eigenvalues of the volatility correlation matrix matches with the analytical result from the RMT. Furthermore, the empirical estimates of short and long-range correlations among eigenvalues, which are within the RMT bounds, match with the analytical results for Gaussian Orthogonal ensemble (GOE) of the RMT. To understand the information content of the largest eigenvectors, we estimate the contribution of GICS industry groups in each eigenvector. In comparison with eigenvectors of correlation matrix for price fluctuations, only few of the largest eigenvectors of volatility correlation matrix are dominated by a single industry group. We also study correlations among `volatility return' and get similar results.
Theoretical Bounds on Mate-Pair Information for Accurate Genome Assembly

Over the past two decades, a series of works have aimed at studying the problem of genome assembly: the process of reconstructing a genome from sequence reads. An early formulation of the genome assembly problem showed that genome reconstruction is NP-hard when framed as finding the shortest sequence that contains all observed reads. Although this original formulation is very simplistic and does not allow for mate-pair information, subsequent formulations have also proven to be NP-hard, and/or may not be guaranteed to return a correct assembly. 
In this paper, we provide an alternate perspective on the genome assembly problem by showing genome assembly is easy when provided with sufficient mate-pair information. Moreover, we quantify the number of mate-pair libraries necessary and sufficient for accurate genome assembly, in terms of the length of the longest repetitive region within a genome. In our analysis, we consider an idealized sequencing model where each mate-pair library generates pairs of error free reads with a fixed and known insert size at each position in the genome. 
Even in this idealized model, we show that accurate genome reconstruction cannot be guaranteed in the worst case unless at least roughly R/2L mate-pair libraries are produced, where R is the length of the longest repetitive region in the genome and L is the length of each read. On the other hand, if (R/L)+1 mate-pair libraries are provided, then a simple algorithm can be used to find a correct genome assembly easily in polynomial time. Although (R/L)+1 mate-pair libraries can be too much to produce in practice, the previous bounds only hold in the worst case. In our last result, we show that if additional conditions hold on a genome, a correct assembly can be guaranteed with only O(log (R/L)) mate-pair libraries.
High Frequency Trading and Asymptotics for Small Risk Aversion in a Markov Renewal Model

We study a an optimal high frequency trading problem within a market microstructure model designed to be a good compromise between accuracy and tractability. The stock price is driven by a Markov Renewal Process (MRP), while market orders arrive in the limit order book via a point process correlated with the stock price itself. In this framework, we can reproduce the adverse selection risk, appearing in two different forms: the usual one due to big market orders impacting the stock price and penalizing the agent, and the weak one due to small market orders and reducing the probability of a profitable execution. We solve the market making problem by stochastic control techniques in this semi-Markov model. In the no risk-aversion case, we provide explicit formula for the optimal controls and characterize the value function as a simple linear PDE. In the general case, we derive the optimal controls and the value function in terms of the previous result, and illustrate how the risk aversion influences the trader strategy and her expected gain. Finally, by using a perturbation method, approximate optimal controls for small risk aversions are explicitly computed in terms of two simple PDE's, reducing drastically the computational cost and enlightening the financial interpretation of the results.
Let My People Go (Home) to Spain: A Genealogical Model of Jewish Identities since 1492

The Spanish government recently announced an official fast-track path to citizenship for any individual who is Jewish and whose ancestors were expelled from Spain during the inquisition-related dislocation of Spanish Jews in 1492. It would seem that this policy targets a small subset of the global Jewish population, that is, restricted to individuals who retain cultural practices associated with ancestral origins in Spain. However, the central contribution of this manuscript is to demonstrate how and why the policy is far more likely to apply to a very large fraction (i.e., the vast majority) of Jews. This claim is supported using a series of genealogical models that include transmissible “identities” and preferential intra-group mating. Model analysis reveals that even when intra-group mating is strong and even if only a small subset of a present-day population retains cultural practices typically associated with that of an ancestral group, it is highly likely that nearly all members of that population have direct genealogical links to that ancestral group, given sufficient number of generations have elapsed. The basis for this conclusion is that not having a link to an ancestral group must be a property of all of an individual’s ancestors, the probability of which declines (nearly) superexponentially with each successive generation. These findings highlight unexpected incongruities induced by genealogical dynamics between present-day and ancestral identities.
DISCOVERY OF GeV EMISSION FROM THE CIRCINUS GALAXY WITH THE FERMI LARGE AREA TELESCOPE

We report the discovery of γ-ray emission from the Circinus galaxy using the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope. Circinus is a nearby (∼4 Mpc) starburst with a heavily obscured Seyfert-type active nucleus, bipolar radio lobes perpendicular to the spiral disk, and kpc-scale jet-like structures. Our analysis of 0.1–100 GeV events collected during 4 yr of LAT observations reveals a significant (≃ 7.3σ) excess above the background. We find no indications of variability or spatial extension beyond the LAT point-spread function. A power-law model used to describe the 0.1–100 GeV γ-ray spectrum yields a flux of (18.8 ± 5.8) × 10−9 photon cm−2 s−1 and photon index 2.19 ± 0.12, corresponding to an isotropic γ-ray luminosity of 3 × 1040 erg s−1. This observed γ-ray luminosity exceeds the luminosity expected from cosmic-ray interactions in the interstellar medium and inverse Compton radiation from the radio lobes. Thus, the origin of the GeV excess requires further investigation.