nils-herrmann/clean_scirepeval huggingface dataset:
Results from MINOS and NOvA

The MINOS experiment, operating in the NuMI beam since 2005, has provided the most precise measurement of the atmospheric mass splitting |Δm232|, and the recent combination of the vμ, ve, and atmospheric neutrino samples has provided some evidence of non-maximal mixing, and hints about the neutrino mass hierarchy and the θ23 octant. Construction of the NOvA experiment, situated off-axis in the upgraded NuMI beam, is almost complete. Over the coming years it will have significant power to probe the questions of the mass hierarchy, θ23 octant, and the possibility of CP violation in the lepton sector. This paper gives an overview of the results from MINOS, and of the sensitivity of the NOνA experiment.
Nonperturbative lepton-sea fermions in the nucleon and the proton radius puzzle

A potential explanation [U.~D.~Jentschura, Phys.\ Rev.\ A {\bf 88}, 062514 (2013)] of the proton radius puzzle originating from the non-perturbative lepton-pair content of the proton is studied. Well-defined quantities that depend on this lepton-pair content are evaluated. Each is found to be of the order of $10({\alpha\over \pi})^2$, so that we find such a lepton-pair content exists in the proton. However, we argue that this relatively large result and general features of loop diagrams rule out the possibility of lepton-pair content as an explanation of the proton radius puzzle. In addition, the contributions of a class of explanations of the proton radius puzzle (for which the dependence on the $\mu p$ relative distance is as a contact interaction) is determined.
A maximum entropy framework for nonexponential distributions

Many statistical distributions, particularly among social and biological systems, have “heavy tails,” which are situations where rare events are not as improbable as would have been guessed from more traditional statistics. Heavy-tailed distributions are the basis for the phrase “the rich get richer.” Here, we propose a basic principle underlying systems with heavy-tailed distributions. We show that it is the same principle (maximum entropy) used in statistical physics and statistics to estimate probabilistic models from relatively few constraints. The heavy-tail principle can be expressed in terms of shared costs and economies of scale. The probability distribution we derive is a mathematical digamma function, and we show that it accurately fits 13 real-world data sets. Probability distributions having power-law tails are observed in a broad range of social, economic, and biological systems. We describe here a potentially useful common framework. We derive distribution functions for situations in which a “joiner particle” k pays some form of price to enter a community of size , where costs are subject to economies of scale. Maximizing the Boltzmann–Gibbs–Shannon entropy subject to this energy-like constraint predicts a distribution having a power-law tail; it reduces to the Boltzmann distribution in the absence of economies of scale. We show that the predicted function gives excellent fits to 13 different distribution functions, ranging from friendship links in social networks, to protein–protein interactions, to the severity of terrorist attacks. This approach may give useful insights into when to expect power-law distributions in the natural and social sciences.
Multiple bubbles and fingers in a Hele-Shaw channel: complete set of steady solutions

Analytical solutions for both a finite assembly and a periodic array of bubbles steadily moving in a Hele-Shaw channel are presented. The particular case of multiple fingers penetrating into the channel and moving jointly with an assembly of bubbles is also analysed. The solutions are given by a conformal mapping from a multiply connected circular domain in an auxiliary complex plane to the fluid region exterior to the bubbles. In all cases the desired mapping is written explicitly in terms of certain special transcendental functions, known as the secondary Schottky–Klein prime functions. Taken together, the solutions reported here represent the complete set of solutions for steady bubbles and fingers in a horizontal Hele-Shaw channel when surface tension is neglected. All previous solutions under these assumptions are particular cases of the general solutions reported here. Other possible applications of the formalism described here are also discussed.
Multiple bubble dynamics and velocity selection in Laplacian growth without surface tension

We predict a novel selection phenomenon in nonlinear interface dynamics out of equilibrium. Using a recently developed formalism based on the Schottky-Klein prime functions, we extended the existing integrable theory from a single interface to multiple moving interfaces. After applying this extended theory to the two-dimensional Laplacian growth, we derive a new rich class of exact non-singular solutions for the unsteady dynamics of an arbitrary assembly of air bubbles within a layer of a viscous ﬂuid in a Hele-Shaw cell. These solutions demonstrate that all bubbles reach an asymptotic velocity, U , which is precisely twice greater than the velocity, V , of the uniform background ﬂow, i.e., U = 2 V . The result does not depend on the number of bubbles. Contrary to common belief, the predicted velocity selection does not require surface tension or any other external regularization.
SURVEY SIMULATIONS OF A NEW NEAR-EARTH ASTEROID DETECTION SYSTEM

We have carried out simulations to predict the performance of a new space-based telescopic survey operating at thermal infrared wavelengths that seeks to discover and characterize a large fraction of the potentially hazardous near-Earth asteroid (NEA) population. Two potential architectures for the survey were considered: one located at the Earth–Sun L1 Lagrange point, and one in a Venus-trailing orbit. A sample cadence was formulated and tested, allowing for the self-follow-up necessary for objects discovered in the daytime sky on Earth. Synthetic populations of NEAs with sizes as small as 140 m in effective spherical diameter were simulated using recent determinations of their physical and orbital properties. Estimates of the instrumental sensitivity, integration times, and slew speeds were included for both architectures assuming the properties of newly developed large-format 10 μm HgCdTe detector arrays capable of operating at ∼35 K. Our simulation included the creation of a preliminary version of a moving object processing pipeline suitable for operating on the trial cadence. We tested this pipeline on a simulated sky populated with astrophysical sources such as stars and galaxies extrapolated from Spitzer Space Telescope and Wide-field Infrared Explorer data, the catalog of known minor planets (including Main Belt asteroids, comets, Jovian Trojans, planets, etc.), and the synthetic NEA model. Trial orbits were computed for simulated position-time pairs extracted from the synthetic surveys to verify that the tested cadence would result in orbits suitable for recovering objects at a later time. Our results indicate that the Earth–Sun L1 and Venus-trailing surveys achieve similar levels of integral completeness for potentially hazardous asteroids larger than 140 m; placing the telescope in an interior orbit does not yield an improvement in discovery rates. This work serves as a necessary first step for the detailed planning of a next-generation NEA survey.
Chemical Enrichment RGS cluster Sample (CHEERS): Constraints on turbulence

Feedback from active galactic nuclei, galactic mergers, and sloshing are thought to give rise to turbulence, which may prevent cooling in clusters.  We aim to measure the turbulence in clusters of galaxies and compare the measurements to some of their structural and evolutionary properties.  It is possible to measure the turbulence of the hot gas in clus ters by estimating the velocity widths of their X-ray emissi on lines. The Reflection Grating Spectrometers aboard XMM- Newton are currently the only instruments provided with suffi cient effective area and spectral resolution in this energy domain. We benefi ted from excellent 1.6 Ms new data provided by the Chemical Enrichment RGS cluster sample (CHEERS) project.  The new observations improve the quality of the archival data and allow us to place constraints for some clusters, which were not accessible in previous work. One-half of the sample shows upper limits on turbulence less than 500 km s −1 . For several sources, our data are consistent with relatively strong turbulence w ith upper limits on the velocity widths that are larger than 1 000 km s −1 . The NGC 507 group of galaxies shows transonic velocities, which are most likely associated with the merging phenomena and bulk motions occurring in this object. Where both low- and high-ionization emission lines have good enough statistics, we fin d larger upper limits for the hot gas, which is partly due to the different spatial extents of the hot and cool gas phases. Our upper limits are larger than the Mach numbers required to balance cooling, suggesting that dissipation of turbulence may prevent cooling, although other heating processes could be dominant. The systematics associated with the spatial profile of the source continuum make th is technique very challenging, though still powerful, for current instr uments. In a forthcoming paper we will use the resonant-scattering technique to place lower-limits on the velocity broadening and provide further insights on turbulence. The ASTRO-H and Athena missions will revolutionize the velocity estimates and discriminate bet ween different spatial regions and temperature phases.
Elastic Processing of Analytical Query Workloads on IaaS Clouds

Many modern applications require the evaluation of analytical queries on large amounts of data. Such queries entail joins and heavy aggregations that often include user-defined functions (UDFs). The most efficient way to process these specific type of queries is using tree execution plans. In this work, we develop an engine for analytical query processing and a suite of specialized techniques that collectively take advantage of the tree form of such plans. The engine executes these tree plans in an elastic IaaS cloud infrastructure and dynamically adapts by allocating and releasing pertinent resources based on the query workload monitored over a sliding time window. The engine offers its services for a fee according to service-level agreements (SLAs) associated with the incoming queries; its management of cloud resources aims at maximizing the profit after removing the costs of using these resources. We have fully implemented our algorithms in the Exareme dataflow processing system. We present an extensive evaluation that demonstrates that our approach is very efficient (exhibiting fast response times), elastic (successfully adjusting the cloud resources it uses as the engine continually adapts to query workload changes), and profitable (approximating very well the maximum difference between SLA-based income and cloud-based expenses).
Summary of the Topical Workshop on Top Quark Differential Distributions 2014

We summarise the Topical Workshop on Top Quark Differential Distributions 2014, which took place in Cannes immediately before the annual Top2014 conference. The workshop was motivated by the availability of top quark differential distributions at NNLO and the forthcoming LHC 13 TeV data. The main goal of the workshop was to explore the impact of improved calculations of top quark production on precision LHC measurements, PDF determinations and searches for physics beyond the Standard Model, as well as finding ways in which the high precision data from ATLAS, CMS and LHCb can be used to further refine theoretical predictions for top production.
Entropy-Based Financial Asset Pricing

We investigate entropy as a financial risk measure. Entropy explains the equity premium of securities and portfolios in a simpler way and, at the same time, with higher explanatory power than the beta parameter of the capital asset pricing model. For asset pricing we define the continuous entropy as an alternative measure of risk. Our results show that entropy decreases in the function of the number of securities involved in a portfolio in a similar way to the standard deviation, and that efficient portfolios are situated on a hyperbola in the expected return – entropy system. For empirical investigation we use daily returns of 150 randomly selected securities for a period of 27 years. Our regression results show that entropy has a higher explanatory power for the expected return than the capital asset pricing model beta. Furthermore we show the time varying behavior of the beta along with entropy.
Nuclear structure studies of $^{24}$F

The structure of the $^{24}$F nucleus has been studied at GANIL using the $\beta$ decay of $^{24}$O and the in-beam $\gamma$-ray spectroscopy from the fragmentation of projectile nuclei. Combining these complementary experimental techniques, the level scheme of $^{24}$F has been constructed up to 3.6 Mev by means of particle-$\gamma$ and particle-$\gamma\gamma$ coincidence relations. Experimental results are compared to shell-model calculations using the standard USDA and USDB interactions as well as ab-initio valence-space Hamiltonians calculated from the in-medium similarity renormalization group based on chiral two- and three-nucleon forces. Both methods reproduce the measured level spacings well, and this close agreement allows unidentified spins and parities to be consistently assigned.
Reinforcement Learning and Nonparametric Detection of Game-Theoretic Equilibrium Play in Social Networks

This paper studies two important signal processing aspects of equilibrium behavior in non-cooperative games arising in social networks, namely, reinforcement learning and detection of equilibrium play. The first part of the paper presents a reinforcement learning (adaptive filtering) algorithm that facilitates learning an equilibrium by resorting to diffusion cooperation strategies in a social network. Agents form homophilic social groups, within which they exchange past experiences over an undirected graph. It is shown that, if all agents follow the proposed algorithm, their global behavior is attracted to the correlated equilibria set of the game. The second part of the paper provides a test to detect if the actions of agents are consistent with play from the equilibrium of a concave potential game. The theory of revealed preference from microeconomics is used to construct a non-parametric decision test and statistical test which only require the probe and associated actions of agents. A stochastic gradient algorithm is given to optimize the probe in real time to minimize the Type-II error probabilities of the detection test subject to specified Type-I error probability. We provide a real-world example using the energy market, and a numerical example to detect malicious agents in an online social network.
Causal inference for ordinal outcomes

Many outcomes of interest in the social and health sciences, as well as in modern applications in computational social science and experimentation on social media platforms, are ordinal and do not have a meaningful scale. Causal analyses that leverage this type of data, termed ordinal non-numeric, require careful treatment, as much of the classical potential outcomes literature is concerned with estimation and hypothesis testing for outcomes whose relative magnitudes are well defined. Here, we propose a class of finite population causal estimands that depend on conditional distributions of the potential outcomes, and provide an interpretable summary of causal effects when no scale is available. We formulate a relaxation of the Fisherian sharp null hypothesis of constant effect that accommodates the scale-free nature of ordinal non-numeric data. We develop a Bayesian procedure to estimate the proposed causal estimands that leverages the rank likelihood. We illustrate these methods with an application to educational outcomes in the General Social Survey.
On the Relationship between Sum-Product Networks and Bayesian Networks

In this paper, we establish some theoretical connections between Sum-Product Networks (SPNs) and Bayesian Networks (BNs). We prove that every SPN can be converted into a BN in linear time and space in terms of the network size. The key insight is to use Algebraic Decision Diagrams (ADDs) to compactly represent the local conditional probability distributions at each node in the resulting BN by exploiting context-specific independence (CSI). The generated BN has a simple directed bipartite graphical structure. We show that by applying the Variable Elimination algorithm (VE) to the generated BN with ADD representations, we can recover the original SPN where the SPN can be viewed as a history record or caching of the VE inference process. To help state the proof clearly, we introduce the notion of {\em normal} SPN and present a theoretical analysis of the consistency and decomposability properties. We conclude the paper with some discussion of the implications of the proof and establish a connection between the depth of an SPN and a lower bound of the tree-width of its corresponding BN.
Optimisation using Natural Language Processing: Personalized tour recommendation for museums

This paper proposes a new method to provide personalized tour recommendation for museum visits. It combines an optimization of preference criteria of visitors with an automatic extraction of artwork importance from museum information based on Natural Language Processing using textual energy. This project includes researchers from computer and social sciences. Some results are obtained with numerical experiments. They show that our model clearly improves the satisfaction of the visitor who follows the proposed tour. This work foreshadows some interesting outcomes and applications about on-demand personalized visit of museums in a very near future.
Driven diffusive systems with mutually interactive Langmuir kinetics.

We investigate the simple one-dimensional driven model, the totally asymmetric exclusion process, coupled to mutually interactive Langmuir kinetics. This model is motivated by recent studies on clustering of motor proteins on microtubules. In the proposed model, the attachment and detachment rates of a particle are modified depending upon the occupancy of neighboring sites. We first obtain continuum mean-field equations and in certain limiting cases obtain analytic solutions. We show how mutual interactions increase (decrease) the effects of boundaries on the phase behavior of the model. We perform Monte Carlo simulations and demonstrate that our analytical approximations are in good agreement with the numerics over a wide range of model parameters. We present phase diagrams over a selective range of parameters.
On the role of spatial dynamics and topology on network flows

Particle flows in spatial networks are susceptible to congestion. In this paper, we analyze the phase transitions of these networks to a state of congested transport and the influence of both topology and spatial dynamics on its emergence. We systematically show that the value of the critical loading rate at which congestion emerges is affected by the addition of spatial dynamics, changing the nature of this transition from a continuous to a discontinuous one. Our numerical results are confirmed by introducing an analytical solvable framework. As a case of study, we explore the implications of our findings in the San Francisco road network where we can locate the roads that originate the congested phase. These roads are spatially constrained, and not necessarily those with high betweenness as predicted by models without spatial dynamics.
Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology

We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein’s neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans.  (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution.
Stellar activity as noise in exoplanet detection – II. Application to M dwarfs

The ubiquity of M dwarf stars combined with their low masses and luminosities make them prime targets in the search for nearby, habitable exoplanets. We investigate the effects of starspot-induced radial velocity (RV) jitter on detection and characterization of planets orbiting M dwarfs. We create surface spot configurations with both random spot coverage and active regions. Synthetic stellar spectra are calculated from a given spot map, and RV measurements are obtained using cross-correlation technique. We add the RV signal of an orbiting planet to these jitter measurements, and reduce the data to "measure" the planetary parameters. We investigate the detectability of planets around M dwarfs of different activity levels, and the recovery of input planetary parameters. When studying the recovery of the planetary period we note that while our original orbital radius places the planet inside the HZ of its star, even at a filling factor of 2% a few of our measurements fall outside the "conservative Habitable Zone". Higher spot filling factors result in more and higher deviations. Our investigations suggest that caution should be used when characterizing planets discovered with the RV method around stars that are (or are potentially) active.