nils-herrmann/clean_scirepeval huggingface dataset:
A new look into the spectral and light variations of epsilon Aur

Investigating long series of spectral and photometric observations, we found that the orbital elements of epsilon Aur are subject to much larger uncertainties than usually believed. The H alpha emission is found to move basically with the F primary but its exact location should still be investigated. We also find strong additional absorption and large reddening of the object near the third contact during the eclipse. Episodic atmospheric mass transfer from the F primary towards its companion is tentatively suggested.
Comparison of Capital Costs per Route-Kilometre in Urban Rail

Because of the prominent position of urban rail in reducing urban transport-related problems, such as congestion and air pollution, insights into the costs of possible new urban rail projects is very relevant for those involved with cost estimations, policy makers, cost-benefit analysts, and other target groups. Knowledge of the differences in costs per kilometre, including explanations of differences and their breakdowns is currently lacking in the literature. This paper aims to provide a first stage insight into how cost per kilometre varies across urban rail projects. The methodology applied is a simple cost comparison across projects where the data collected are comparable. We conclude that capital costs per route-kilometre of urban rail vary highly between projects. Looking at European projects and excluding outliers, the total capital costs per route-kilometre (including stations and rolling stock) lie mainly between US$50-100 million (2002 prices). Including US projects, the range is US$50-150 million. The main reasons for the high variation in the route-kilometre costs are differences between projects as regards the ratio of underground to above-ground construction, ground conditions, station spacing, type of rolling stock, environmental and safety constraints and labour costs. We warn, however, that the observations used to reach the conclusions are too few to obtain results with statistical significance. Our results must therefore be seen as a first step towards collecting more data so that a more succinct statistical analysis can be conducted. Another conclusion is therefore that this area has future research potential.
Turbulence-induced collision velocities and rates between different sized dust grains

We study the collision rates and velocities for point-particles of different sizes in turbulent flows. We construct fits for the collision rates at specified velocities (effectively a collisional velocity probability distribution) for particle stopping time ratios up to four; already by that point the collisional partners are very poorly correlated and so the results should be robust for even larger stopping time ratios. Significantly, we find that while particles of very different masses have approximately Maxwellian collisional statistics, as the mass ratio shrinks the distribution changes dramatically. At small stopping time ratios, the collisional partners are highly correlated and we find a population of high number density (clustered), low relative-velocity particle pairs. Unlike in the case of identical stopping time collisional partners, this low relative-velocity clustered population is collisional, but the clustering is barely adequate to trigger bulk effects such as the streaming instability. We conclude our analysis by constructing a master fit to the collisional statistics as a function only of the stopping time ratio. Together with our previous work for identical stopping time particle pairs, this provides a recipe for including collisional velocity probability distributions in dust coagulation models for protoplanetary disks. We also include our recipe for determining particle collisional diagnostics from numerical simulations.
Anatomy of the Chase

A lot of research activity has recently taken place around the chase procedure, due to its usefulness in data integration, data exchange, query optimization, peer data exchange and data correspondence, to mention a few. As the chase has been investigated and further developed by a number of research groups and authors, many variants of the chase have emerged and associated results obtained. Due to the heterogeneous nature of the area it is frequently difficult to verify the scope of each result. In this paper we take closer look at recent developments, and provide additional results. Our analysis allows us create a taxonomy of the chase variations and the properties they satisfy. 
Two of the most central problems regarding the chase is termination, and discovery of restricted classes of sets of dependencies that guarantee termination of the chase. The search for the restricted classes has been motivated by a fairly recent result that shows that it is undecidable to determine whether the chase with a given dependency set will terminate on a given instance. There is a small dissonance here, since the quest has been for classes of sets of dependencies guaranteeing termination of the chase on all instances, even though the latter problem was not known to be undecidable. We resolve the dissonance in this paper by showing that determining whether the chase with a given set of dependencies terminates on all instances is coRE-complete. Our reduction also gives us the aforementioned instance-dependent RE-completeness result as a byproduct. For one of the restricted classes, the stratified sets dependencies, we provide new complexity results for the problem of testing whether a given set of dependencies belongs to it. These results rectify some previous claims that have occurred in the literature.
Exploiting correlation and budget constraints in Bayesian multi-armed bandit optimization

We address the problem of finding the maximizer of a nonlinear smooth function, that can only be evaluated point-wise, subject to constraints on the number of permitted function evaluations. This problem is also known as fixed-budget best arm identification in the multi-armed bandit literature. We introduce a Bayesian approach for this problem and show that it empirically outperforms both the existing frequentist counterpart and other Bayesian optimization methods. The Bayesian approach places emphasis on detailed modelling, including the modelling of correlations among the arms. As a result, it can perform well in situations where the number of arms is much larger than the number of allowed function evaluation, whereas the frequentist counterpart is inapplicable. This feature enables us to develop and deploy practical applications, such as automatic machine learning toolboxes. The paper presents comprehensive comparisons of the proposed approach, Thompson sampling, classical Bayesian optimization techniques, more recent Bayesian bandit approaches, and state-of-the-art best arm identification methods. This is the first comparison of many of these methods in the literature and allows us to examine the relative merits of their different features.
Sequential testing over multiple stages and performance analysis of data fusion

We describe a methodology for modeling the performance of decision-level data fusion between different sensor configurations, implemented as part of the JIEDDO Analytic Decision Engine (JADE). We first discuss a Bayesian network formulation of classical probabilistic data fusion, which allows elementary fusion structures to be stacked and analyzed efficiently. We then present an extension of the Wald sequential test for combining the outputs of the Bayesian network over time. We discuss an algorithm to compute its performance statistics and illustrate the approach on some examples. This variant of the sequential test involves multiple, distinct stages, where the evidence accumulated from each stage is carried over into the next one, and is motivated by a need to keep certain sensors in the network inactive unless triggered by other sensors.
Galaxy Zoo: Motivations of Citizen Scientists

Citizen science, in which volunteers work with professional scientists to conduct research, is expanding due to large online datasets. To plan projects, it is important to understand volunteers' motivations for participating. This paper analyzes results from an online survey of nearly 11,000 volunteers in Galaxy Zoo, an astronomy citizen science project. Results show that volunteers' primary motivation is a desire to contribute to scientific research. We encourage other citizen science projects to study the motivations of their volunteers, to see whether and how these results may be generalized to inform the field of citizen science.
The Phenomenology of Right Handed Neutrinos

Neutrinos are the only particles in the Standard Model (SM) of particle physics that have only been observed with left handed chirality to date. If right handed (RH) neutrinos exist, they could be responsible for several phenomena that have no explanation within the SM, including neutrino oscillations, the baryon asymmetry of the universe, dark matter (DM) and dark radiation (DR). After a pedagogical introduction, we review recent progress in the phenomenology of RH neutrinos. We in particular discuss the mass ranges suggested by hints for neutrino oscillation anomalies and DR (eV), sterile neutrino DM scenarios (keV) and experimentally testable theories of baryogenesis (GeV to TeV). We summarize constraints from theoretical considerations, laboratory experiments, astrophysics and cosmology for each of these.
Entanglement Entropy at Large Central Charge

Two-dimensional conformal field theories with a large central charge and a small number of low-dimension operators are studied using the conformal block expansion. A universal formula is derived for the Renyi entropies of N disjoint intervals in the ground state, valid to all orders in a series expansion. This is possible because the full perturbative answer in this regime comes from the exchange of the stress tensor and other descendants of the vacuum state. Therefore, the Renyi entropy is related to the Virasoro vacuum block at large central charge. The entanglement entropy, computed from the Renyi entropy by an analytic continuation, decouples into a sum of single-interval entanglements. This field theory result agrees with the Ryu-Takayanagi formula for the holographic entanglement entropy of a 2d CFT, applied to any number of intervals, and thus can be interpreted as a microscopic calculation of the area of minimal surfaces in 3d gravity.
ABC Reinforcement Learning

We introduce a simple, general framework for likelihood-free Bayesian reinforcement learning, through Approximate Bayesian Computation (ABC). The advantage is that we only require a prior distribution on a class of simulators. This is useful when a probabilistic model of the underlying process is too complex to formulate, but where detailed simulation models are available. ABC-RL allows the use of any Bayesian reinforcement learning technique in this case. It can be seen as an extension of simulation methods to both planning and inference. We experimentally demonstrate the potential of this approach in a comparison with LSPI. Finally, we introduce a theorem showing that ABC is sound.
A Massively Parallel Associative Memory Based on Sparse Neural Networks

Associative memories store content in such a way that the content can be later retrieved by presenting the memory with a small portion of the content, rather than presenting the memory with an address as in more traditional memories. Associative memories are used as building blocks for algorithms within database engines, anomaly detection systems, compression algorithms, and face recognition systems. A classical example of an associative memory is the Hopfield neural network. Recently, Gripon and Berrou have introduced an alternative construction which builds on ideas from the theory of error correcting codes and which greatly outperforms the Hopfield network in capacity, diversity, and efficiency. In this paper we implement a variation of the Gripon-Berrou associative memory on a general purpose graphical processing unit (GPU). The work of Gripon and Berrou proposes two retrieval rules, sum-of-sum and sum-of-max. The sum-of-sum rule uses only matrix-vector multiplication and is easily implemented on the GPU. The sum-of-max rule is much less straightforward to implement because it involves non-linear operations. However, the sum-of-max rule gives significantly better retrieval error rates. We propose a hybrid rule tailored for implementation on a GPU which achieves a 880-fold speedup without sacrificing any accuracy.
Non-Hermitian $\cal PT$-symmetric quantum mechanics of relativistic particles with the restriction of mass

The modified Dirac equations for the massive particles with the replacement of the physical mass m with the help of the relation m → m1 + γ5m2 are investigated. It is shown that for a fermion theory with a γ5-mass term, the limiting of the mass specter by the value mmax = m1 /2m2 takes place. In this case the different regions of the unbroken PT symmetry may be expressed by means of the restriction of the physical mass m ≤ mmax. It should be noted that in the approach which was developed by C.Bender et al. for the PT -symmetric version of the massive Thirring model with γ5-mass term, the region of the unbroken PT -symmetry was found in the form m1 ≥ m2 . However on the basis of the mass limitation m ≤ mmax we obtain that the domain m1 ≥ m2 consists of two different parametric sectors: i) 0 ≤ m2 ≤ m1/ √ 2 -this values of mass parameters m1,m2 correspond to the traditional particles for which in the limit mmax → ∞ the modified models are converting to the ordinary Dirac theory with the physical mass m; ii)m1/ √ 2 ≤ m2 ≤ m1 this is the case of the unusual particles for which equations of motion does not have a limit, when mmax → ∞. The presence of this possibility lets hope for that in Nature indeed there are some ”exotic fermion fields”. As a matter of fact the formulated criterions may be used as a major test in the process of the division of considered models into ordinary and exotic fermion theories. It is tempting to think that the quanta of the exotic fermion field have a relation to the structure of the ”dark matter”. PACS numbers: 02.30.Jr, 03.65.-w, 03.65.Ge, 12.10.-g, 12.20.-m
Internal cumulants for femtoscopy with fixed charged multiplicity

A detailed understanding of all effects and influences on higher-order correlations is essential. At low charged multiplicity, the effect of a non-Poissonian multiplicity distribution can significantly distort correlations. Evidently, the reference samples with respect to which correlations are measured should yield a null result in the absence of correlations. We show how the careful specification of desired properties necessarily leads to an average-of-multinomials reference sample. The resulting internal cumulants and their averaging over several multiplicities fulfill all requirements of correctly taking into account non-Poissonian multiplicity distributions as well as yielding a null result for uncorrelated fixed- samples. Various correction factors are shown to be approximations at best. Careful rederivation of statistical variances and covariances within the frequentist approach yields errors for cumulants that differ from those used so far. We finally briefly discuss the implementation of the analysis through a multiple event buffer algorithm.
#Bigbirds Never Die: Understanding Social Dynamics of Emergent Hashtags

We examine the growth, survival, and context of 256 novel hashtags during the 2012 U.S. presidential debates. Our analysis reveals the trajectories of hashtag use fall into two distinct classes: "winners" that emerge more quickly and are sustained for longer periods of time than other "also-rans" hashtags. We propose a "conversational vibrancy" framework to capture dynamics of hashtags based on their topicality, interactivity, diversity, and prominence. Statistical analyses of the growth and persistence of hashtags reveal novel relationships between features of this framework and the relative success of hashtags. Specifically, retweets always contribute to faster hashtag adoption, replies extend the life of "winners" while having no effect on "also-rans." This is the first study on the lifecycle of hashtag adoption and use in response to purely exogenous shocks. We draw on theories of uses and gratification, organizational ecology, and language evolution to discuss these findings and their implications for understanding social influence and collective action in social media more generally.
Usage-based vs. Citation-based Methods for Recommending Scholarly Research Articles

There are two principal data sources for collaborative ltering recommenders in scholarly digital libraries: usage data obtained from harvesting a large, distributed collection of Open URL web logs and citation data obtained from the journal articles. This study explores the characteristics of recommendations generated by implementations of these two methods: the ‘bX’ system by ExLibris and an experimental citation-based recommender, Sarkanto. Recommendations from each system were compared according to their semantic similarity to the seed article that was used to generate them. Since the full text of the articles was not available for all the recommendations in both systems, the semantic similarity between the seed article and the recommended articles was deemed to be the semantic distance between the journals in which the articles were published. The semantic distance between journals was computed from the \semantic vectors" distance between all the terms in the full-text of the available articles in that journal and this study shows that citation-based recommendations are more semantically diverse than usage-based ones. These recommenders are complementary since most of the time, when one recommender produces recommendations the other does not.
High-frequency market-making for multi-dimensional Markov processes

In this paper we complete and extend our previous work on stochastic control applied to high frequency market-making with inventory constraints and directional bets. Our new model admits several state variables (e.g. market spread, stochastic volatility and intensities of market orders) provided the full system is Markov. The solution of the corresponding HJB equation is exact in the case of zero inventory risk. The inventory risk enters into play in two ways: a path-dependent penalty based on the volatility and a penalty at expiry based on the market spread. We perform perturbation methods on the inventory risk parameter and obtain explicitly the solution and its controls up to first order. We also include transaction costs; we show that the spread of the market-maker is widened to compensate the transaction costs, but the expected gain per traded spread remains constant. We perform several numerical simulations to assess the effect of the parameters on the PNL, showing in particular how the directional bet and the inventory risk change the shape of the PNL density. Finally, we extend our results to the case of multi-aset market-making strategies; we show that the correct notion of inventory risk is the L2-norm of the (multi-dimensional) inventory with respect to the inventory penalties.
Axial current generation from electric field: chiral electric separation effect.

We study a relativistic plasma containing charged chiral fermions in an external electric field. We show that with the presence of both vector and axial charge densities, the electric field can induce an axial current along its direction and thus cause chirality separation. We call it the chiral electric separation effect (CESE). On a very general basis, we argue that the strength of CESE is proportional to μ(V)μ(A) with μ(V) and μ(A) the chemical potentials for vector charge and axial charge. We then explicitly calculate this CESE conductivity coefficient in thermal QED at leading-log order. The CESE can manifest a new gapless wave mode propagating along the electric field. Potential observable effects of CESE in heavy-ion collisions are also discussed.
Parallelization in Scientific Workflow Management Systems

Over the last two decades, scientific workflow management systems (SWfMS) have emerged as a means to facilitate the design, execution, and monitoring of reusable scientific data processing pipelines. At the same time, the amounts of data generated in various areas of science outpaced enhancements in computational power and storage capabilities. This is especially true for the life sciences, where new technologies increased the sequencing throughput from kilobytes to terabytes per day. This trend requires current SWfMS to adapt: Native support for parallel workflow execution must be provided to increase performance; dynamically scalable "pay-per-use" compute infrastructures have to be integrated to diminish hardware costs; adaptive scheduling of workflows in distributed compute environments is required to optimize resource utilization. In this survey we give an overview of parallelization techniques for SWfMS, both in theory and in their realization in concrete systems. We find that current systems leave considerable room for improvement and we propose key advancements to the landscape of SWfMS.
Detecting Overlapping Temporal Community Structure in Time-Evolving Networks

We present a principled approach for detecting overlapping temporal community structure in dynamic networks. Our method is based on the following framework: find the overlapping temporal community structure that maximizes a quality function associated with each snapshot of the network subject to a temporal smoothness constraint. A novel quality function and a smoothness constraint are proposed to handle overlaps, and a new convex relaxation is used to solve the resulting combinatorial optimization problem. We provide theoretical guarantees as well as experimental results that reveal community structure in real and synthetic networks. Our main insight is that certain structures can be identified only when temporal correlation is considered and when communities are allowed to overlap. In general, discovering such overlapping temporal community structure can enhance our understanding of real-world complex networks by revealing the underlying stability behind their seemingly chaotic evolution.
White Dwarfs constrain Dark Forces

The white dwarf luminosity function, which provides information about their cooling, has been measured with high precision in the past few years. Simulations that include well known Standard Model physics give a good fit to the data. This leaves little room for new physics and makes these astrophysical objects a good laboratory for testing models beyond the Standard Model. It has already been suggested that white dwarfs might provide some evidence for the existence of axions. In this work we study the constraints that the white dwarf luminosity function puts on physics beyond the Standard Model involving new light particles (fermions or bosons) that can be pair-produced in a white dwarf and then escape to contribute to its cooling. We show, in particular, that we can severely constrain the parameter space of models with dark forces and light hidden sectors (lighter than a few tens of keV). The bounds we find are often more competitive than those from current lab searches and those expected from most future searches.
Pareidolic Dark Matter (PaDaM)

Dark matter is a sphinx (Oort 1932; Zwicky 1933; Rubin & Ford 1970; Tyutchev 1869). Despite ingenious hunting strategies, we continue to chase after this notoriously elusive creature within the dark zoo (Feng 2010; Fan et al. 2013). In the sky, there are X-ray “mice” (Gaensler et al. 2004), radio “snakes” (Uchida et al. 1992), even an optical “Crab” (Rosse 1844; Mitchell 1855). The latter may have been a “pineapple”, as a matter of fact (Dewhirst 1983). But such discussion is beyond the scope of our tract.