nils-herrmann/clean_scirepeval huggingface dataset:
The SAMI Galaxy Survey: Early Data Release

We present the Early Data Release of the Sydney–AAO Multi-object Integral field spectrograph (SAMI) Galaxy Survey. The SAMI Galaxy Survey is an ongoing integral field spectroscopic survey of _3400 low-redshift (z < 0:12) galaxies, covering galaxies in the field and in groups within the Galaxy And Mass Assembly (GAMA) survey regions, and a sample of galaxies in clusters. In the Early Data Release, we publicly release the fully calibrated datacubes for a representative selection of 107 galaxies drawn from the GAMA regions, along with information about these galaxies from the GAMA catalogues. All datacubes for the Early Data Release galaxies can be downloaded individually or as a set from the SAMI Galaxy Survey website. In this paper we also assess the quality of the pipeline used to reduce the SAMI data, giving metrics that quantify its performance at all stages in processing the raw data into calibrated datacubes. The pipeline gives excellent results throughout, with typical sky subtraction residuals in the continuum of 0.9–1.2 per cent, a relative flux calibration uncertainty of 4.1 per cent (systematic) plus 4.3 per cent (statistical), and atmospheric dispersion removed with an accuracy of 0:0009, less than a fifth of a spaxel.
Learning Rank Functionals: An Empirical Study

Ranking is a key aspect of many applications, such as information retrieval, question answering, ad placement and recommender systems. Learning to rank has the goal of estimating a ranking model automatically from training data. In practical settings, the task often reduces to estimating a rank functional of an object with respect to a query. In this paper, we investigate key issues in designing an effective learning to rank algorithm. These include data representation, the choice of rank functionals, the design of the loss function so that it is correlated with the rank metrics used in evaluation. For the loss function, we study three techniques: approximating the rank metric by a smooth function, decomposition of the loss into a weighted sum of element-wise losses and into a weighted sum of pairwise losses. We then present derivations of piecewise losses using the theory of high-order Markov chains and Markov random fields. In experiments, we evaluate these design aspects on two tasks: answer ranking in a Social Question Answering site, and Web Information Retrieval.
Permutation Models for Collaborative Ranking

We study the problem of collaborative filtering where ranking information is available. Focusing on the core of the collaborative ranking process, the user and their community, we propose new models for representation of the underlying permutations and prediction of ranks. The first approach is based on the assumption that the user makes successive choice of items in a stage-wise manner. In particular, we extend the Plackett-Luce model in two ways - introducing parameter factoring to account for user-specific contribution, and modelling the latent community in a generative setting. The second approach relies on log-linear parameterisation, which relaxes the discrete-choice assumption, but makes learning and inference much more involved. We propose MCMC-based learning and inference methods and derive linear-time prediction algorithms.
Null Models for Community Detection in Spatially-Embedded, Temporal Networks

In the study of networks, it is often insightful to use algorithms to determine mesoscale features such as “community structure”, in which densely connected sets of nodes constitute “communities” that have sparse connections to other communities. The most popular way of detecting communities algorithmically is to optimize the quality function known as modularity. When optimizing modularity, one compares the actual connections in a (static or time-dependent) network to the connections obtained from a random-graph ensemble that acts as a null model. The communities are then the sets of nodes that are connected to each other densely relative to what is expected from the null model. Clearly, the process of community detection depends fundamentally on the choice of null model, so it is important to develop and analyze novel null models that take into account appropriate features of the system under study. In this paper, we investigate the effects of using null models that take incorporate spatial information, and we propose a novel null model based on the radiation model of population spread. We also develop novel synthetic spatial benchmark networks in which the connections between entities are based on distance or flux between nodes, and we compare the performance of both static and time-dependent radiation null models to the standard (“Newman-Girvan”) null model for modularity optimization and a recently-proposed gravity null model. In our comparisons, we use both the above synthetic benchmarks and time-dependent correlation networks that we construct using countrywide dengue fever incidence data for Peru. We also evaluate a recently-proposed correlation null model, which was developed specifically for correlation networks that are constructed from time series, on the epidemic-correlation data. Our findings underscore the need to use appropriate generative models for the development of spatial null models for community detection. PACS numbers 87.19.Xx,89.20.-a,89.75.Fb,05.45.Tp
Student Difficulties with the Dirac Delta Function

The Dirac delta function is a standard mathematical tool used in multiple topical areas in the undergraduate physics curriculum. While Dirac delta functions are usually introduced in order to simplify a problem mathematically, students often struggle to manipulate and interpret them. To better understand student difficulties with the delta function at the upper-division level, we examined responses to traditional exam questions and conducted think-aloud interviews. Our analysis was guided by an analytical framework that focuses on how students activate, construct, execute, and reflect on the Dirac delta function in physics. Here, we focus on student difficulties using the delta function to express charge distributions in the context of junior-level electrostatics. Challenges included: invoking the delta function spontaneously, constructing two- and three-dimensional delta functions, integrating novel delta function expressions, and recognizing that the delta function can have units.
Field Theory of Macroeconomics

In this article we will show that the Macro-Economy and its growth can be
modelled and explained exactly in principle by commonly known Field Theory from
theoretical physics. We will show the main concepts and calculations needed and
show that calculation and prediction of economic growth then gets indeed
possible in Dollars and Cents. As every field theory it is based on an equation
of continuity, which in economic terms means the full balance of all sources
and sinks of Capital (Assets) and real Goods (GDP) in the bulk. Uniqueness of
field theory of macroeconomics then can be derived from adapting Noether's
Theorems, which is based on the notion of invariants to derive unique field
equations. We will show that the only assumption which is needed for a
self-consistent non-linear macro-economic theory is that the well known
Quantity Equation, used in corrected formulation, holds at least locally in
time.
Unified molecular field theory for collinear and noncollinear Heisenberg antiferromagnets

In this study, a unified molecular field theory (MFT) is presented that applies to both collinear and planar noncollinear Heisenberg antiferromagnets (AFs) on the same footing. The spins in the system are assumed to be identical and crystallographically equivalent. This formulation allows calculations of the anisotropic magnetic susceptibility χ versus temperature T below the AF ordering temperature TN to be carried out for arbitrary Heisenberg exchange interactions Jij between arbitrary neighbors j of a given spin i without recourse to magnetic sublattices. The Weiss temperature θp in the Curie-Weiss law is written in terms of the Jij values and TN in terms of the Jij values and an assumed AF structure. Other magnetic and thermal properties are then expressed in terms of quantities easily accessible from experiment as laws of corresponding states for a given spin S. For collinear ordering these properties are the reduced temperature t=T/TN, the ratio f = θp/TN, and S. For planar noncollinear helical or cycloidal ordering, an additional parameter is the wave vector of the helix or cycloid. The MFT is also applicable to AFs with other AF structures. The MFT predicts that χ(T ≤ TN) of noncollinear 120° spin structures on triangular lattices ismore » isotropic and independent of S and T and thus clarifies the origin of this universally observed behavior. The high-field magnetization and heat capacity for fields applied perpendicular to the ordering axis (collinear AFs) and ordering plane (planar noncollinear AFs) are also calculated and expressed for both types of AF structures as laws of corresponding states for a given S, and the reduced perpendicular field versus reduced temperature phase diagram is constructed.« less
Effusive atomic oven nozzle design using an aligned microcapillary array.

We present a simple and inexpensive design for a multichannel effusive oven nozzle which provides improved atomic beam collimation and thus extended oven lifetimes. Using this design, we demonstrate an atomic lithium source suitable for trapped-atom experiments. At a nozzle temperature of 525 °C, the collimated atomic beam flux directly after the nozzle is 1.2 × 10(14) atoms/s with a peak beam intensity greater than 5.0 × 10(16) atoms/s/sr. This suggests an oven lifetime of several decades of continuous operation.
Securing Cloud from Cloud Drain

Today, in the world of communication, connected systems is growing at a rapid pace. To accommodate this growth the need for computational power and storage is also increasing at a similar rate. Companies are investing a large amount of resources in buying, maintaining and ensuring availability of the system to their customers. To mitigate these issues, cloud computing is playing a major role.The underlying concept of cloud computing dates back to the 50's but the term entering into widespread usage can be traced to 2006 when Amazon.com announced the Elastic Compute Cloud.In this paper, we will discuss about cloud security approaches. We have used the term Cloud-Drain to define data leakage in case of security compromise.
Electromagnetism as an emergent phenomenon: a step-by-step guide

We give a detailed description of electrodynamics as an emergent theory from condensed-matter-like structures, not only per se but also as a warm-up for the study of the much more complex case of gravity. We concentrate on two scenarios that, although qualitatively different, share some important features with the idea of extracting the basic generic ingredients that give rise to emergent electrodynamics and, more generally, to gauge theories. We start with Maxwellʼs mechanical model for electrodynamics, where Maxwellʼs equations appear as dynamical consistency conditions. We next take a superfluid 3He-like system as representative of a broad class of fermionic quantum systems whose low-energy physics reproduces classical electrodynamics (Dirac and Maxwell equations as dynamical low-energy laws). An important lesson that can be derived from both analyses is that the vector potential has a microscopic physical reality and only in the low-energy regime is this physical reality blurred in favor of gauge invariance, which in addition turns out to be secondary to effective Lorentz invariance.
A Review of High School Level Astronomy Student Research Projects Over the Last Two Decades

Since the early 1990s with the arrival of a variety of new technologies, the capacity for authentic astronomical research at the high school level has skyrocketed. This potential, however, has not realised the bright-eyed hopes and dreams of the early pioneers who expected to revolutionise science education through the use of telescopes and other astronomical instrumentation in the classroom. In this paper, a general history and analysis of these attempts is presented. We define what we classify as an Astronomy Research in the Classroom (ARiC) project and note the major dimensions on which these projects differ before describing the 22 major student research projects active since the early 1990s. This is followed by a discussion of the major issues identified that affected the success of these projects and provide suggestions for similar attempts in the future.
The Basic Reproduction Number as a Predictor for Epidemic Outbreaks in Temporal Networks

The basic reproduction number R 0—the number of individuals directly infected by an infectious person in an otherwise susceptible population—is arguably the most widely used estimator of how severe an epidemic outbreak can be. This severity can be more directly measured as the fraction of people infected once the outbreak is over, Ω. In traditional mathematical epidemiology and common formulations of static network epidemiology, there is a deterministic relationship between R 0 and Ω. However, if one considers disease spreading on a temporal contact network—where one knows when contacts happen, not only between whom—then larger R 0 does not necessarily imply larger Ω. In this paper, we numerically investigate the relationship between R 0 and Ω for a set of empirical temporal networks of human contacts. Among 31 explanatory descriptors of temporal network structure, we identify those that make R 0 an imperfect predictor of Ω. We find that descriptors related to both temporal and topological aspects affect the relationship between R 0 and Ω, but in different ways.
Geometrical Origins of Contractility in Disordered Actomyosin Networks

Movement within eukaryotic cells largely originates from localized forces exerted by myosin motors on scaffolds of actin filaments. Although individual motors locally exert both contractile and extensile forces, large actomyosin structures at the cellular scale are overwhelmingly contractile, suggesting that the scaffold serves to favor contraction over extension. While this mechanism is well understood in highly organized striated muscle, its origin in disordered networks such as the cell cortex is unknown. Here, we develop a mathematical model of the actin scaffold’s local two- or three-dimensional mechanics and identify four competing contraction mechanisms. We predict that one mechanism dominates, whereby local deformations of the actin break the balance between contraction and extension. In this mechanism, contractile forces result mostly from motors plucking the filaments transversely rather than buckling them longitudinally. These findings shed light on recent in vitro experiments and provide a new geometrical understanding of contractility in the myriad of disordered actomyosin systems found in vivo.
Fourier analysis of the IR response of van der Waals materials

In this letter, we report on an analytical technique for optical investigations of semitransparent samples. By Fourier transforming optical spectra with Fabry-Perot resonances we extract information about sample thickness and its discrete variations. Moreover, this information is used to recover optical spectra devoid of Fabry-Perot fringes, which simplifies optical modelling, and can reveal previously concealed spectral features. To illustrate its use, we apply our technique to a Si wafer as well as six different cleavable layered materials, including topological insulators, thermoelectrics, and magnetic insulators. In the layered materials, we find strong evidence of large step edges and thickness inhomogeneity, and cannot conclusively exclude the presence of voids in the bulk of cleaved samples. This could strongly affect the interpretation of transport and optical data of crystals with topologically protected surfaces states.
Colloquium: Graphene spectroscopy

Spectroscopic studies of electronic phenomena in graphene are reviewed. A variety of methods and techniques are surveyed, from quasiparticle spectroscopies (tunneling, photoemission) to methods probing density and current response (infrared optics, Raman) to scanning probe nanoscopy and ultrafast pump-probe experiments. Vast complimentary information derived from these investigations is shown to highlight unusual properties of Dirac quasiparticles and many-body interaction effects in the physics of graphene.
Initial value formulation of dynamical Chern-Simons gravity

We derive an initial value formulation for dynamical Chern-Simons gravity, a modification of general relativity involving parity-violating higher derivative terms. We investigate the structure of the resulting system of partial differential equations thinking about linearization around arbitrary backgrounds. This type of consideration is necessary if we are to establish well-posedness of the Cauchy problem. Treating the field equations as an effective field theory we find that weak necessary conditions for hyperbolicity are satisfied. For the full field equations we find that there are states from which subsequent evolution is not determined. Generically the evolution system closes, but the full field equations are in no sense hyperbolic. In a cursory mode analysis we find that the equations of motion contain terms that may cause ill-posedness of the initial value problem.
Short-range interactions versus long-range correlations in bird flocks.

Bird flocks are a paradigmatic example of collective motion. One of the prominent traits of flocking is the presence of long range velocity correlations between individuals, which allow them to influence each other over the large scales, keeping a high level of group coordination. A crucial question is to understand what is the mutual interaction between birds generating such nontrivial correlations. Here we use the maximum entropy (ME) approach to infer from experimental data of natural flocks the effective interactions between individuals. Compared to previous studies, we make a significant step forward as we retrieve the full functional dependence of the interaction on distance, and find that it decays exponentially over a range of a few individuals. The fact that ME gives a short-range interaction even though its experimental input is the long-range correlation function, shows that the method is able to discriminate the relevant information encoded in such correlations and single out a minimal number of effective parameters. Finally, we show how the method can be used to capture the degree of anisotropy of mutual interactions.
A Quantum Network of Silicon Qubits using Mid-Infrared Graphene Plasmons

Joint Quantum Institute, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA(Dated: July 31, 2014)We consider a quantum network of mid-infrared, graphene plasmons coupled to the hydrogen-likeexcited states of group-V donors in silicon. First, we show how to use plasmon-enhanced light-matter interactions to achieve single-shot spin readout of the donor qubits via optical excitationand electrical detection of the emitted plasmons. We then show how plasmons in high mobilitygraphene nanoribbons can be used to achieve high- delity, two-qubit gates and entanglement ofdistant Si donor qubits. The proposed device is readily compatible with existing technology andfabrication methods.
The EAGLE project: Simulating the evolution and assembly of galaxies and their environments

We introduce the Virgo Consortium's EAGLE project, a suite of hydrodynamical simulations that follow the formation of galaxies and black holes in representative volumes. We discuss the limitations of such simulations in light of their finite resolution and poorly constrained subgrid physics, and how these affect their predictive power. One major improvement is our treatment of feedback from massive stars and AGN in which thermal energy is injected into the gas without the need to turn off cooling or hydrodynamical forces, allowing winds to develop without predetermined speed or mass loading factors. Because the feedback efficiencies cannot be predicted from first principles, we calibrate them to the z~0 galaxy stellar mass function and the amplitude of the galaxy-central black hole mass relation, also taking galaxy sizes into account. The observed galaxy mass function is reproduced to ≲0.2 dex over the full mass range, 108<M∗/M⊙≲1011, a level of agreement close to that attained by semi-analytic models, and unprecedented for hydrodynamical simulations. We compare our results to a representative set of low-redshift observables not considered in the calibration, and find good agreement with the observed galaxy specific star formation rates, passive fractions, Tully-Fisher relation, total stellar luminosities of galaxy clusters, and column density distributions of intergalactic CIV and OVI. While the mass-metallicity relations for gas and stars are consistent with observations for M∗≳109M⊙, they are insufficiently steep at lower masses. The gas fractions and temperatures are too high for clusters of galaxies, but for groups these discrepancies can be resolved by adopting a higher heating temperature in the subgrid prescription for AGN feedback. EAGLE constitutes a valuable new resource for studies of galaxy formation.
Processing Social Media Messages in Mass Emergency

Social media platforms provide active communication channels during mass convergence and emergency events such as disasters caused by natural hazards. As a result, first responders, decision makers, and the public can use this information to gain insight into the situation as it unfolds. In particular, many social media messages communicated during emergencies convey timely, actionable information. Processing social media messages to obtain such information, however, involves solving multiple challenges including: parsing brief and informal messages, handling information overload, and prioritizing different types of information found in messages. These challenges can be mapped to classical information processing operations such as filtering, classifying, ranking, aggregating, extracting, and summarizing. We survey the state of the art regarding computational methods to process social media messages and highlight both their contributions and shortcomings. In addition, we examine their particularities, and methodically examine a series of key subproblems ranging from the detection of events to the creation of actionable and useful summaries. Research thus far has, to a large extent, produced methods to extract situational awareness information from social media. In this survey, we cover these various approaches, and highlight their benefits and shortcomings. We conclude with research challenges that go beyond situational awareness, and begin to look at supporting decision making and coordinating emergency-response actions.
Graphene as a tunable THz reservoir for shaping the Mollow triplet of an artificial atom via plasmonic effects

(Received 29 April 2014; revised manuscript received 30 June 2014; published 12 August 2014)Using a realistic quantum master equation, we show that the resonance ﬂuorescence spectra of a two-levelartiﬁcialatom(quantumdot)canbetunedbyadjustingitsphotoniclocaldensityofstatesviabiasingoneormoregraphene monolayers. The structured photon reservoir is included using a photon Green function theory whichfully accounts for the loss and dispersion. The ﬁeld-driven Mollow triplet spectrum can be actively controlled bythe graphene bias in the THz frequency regime. We also consider the effect of a dielectric support environmentand multiple graphene layers on the emitted ﬂuorescence. Finally, thermal bath effects are considered and areshown to be important for low THz frequencies.