nils-herrmann/clean_scirepeval huggingface dataset:
A SECOND-ORDER GODUNOV METHOD FOR MULTI-DIMENSIONAL RELATIVISTIC MAGNETOHYDRODYNAMICS

We describe a new Godunov algorithm for relativistic magnetohydrodynamics (RMHD) that combines a simple, unsplit second-order accurate integrator with the constrained transport (CT) method for enforcing the solenoidal constraint on the magnetic field. A variety of approximate Riemann solvers are implemented to compute the fluxes of the conserved variables. The methods are tested with a comprehensive suite of multi-dimensional problems. These tests have helped us develop a hierarchy of correction steps that are applied when the integration algorithm predicts unphysical states due to errors in the fluxes, or errors in the inversion between conserved and primitive variables. Although used exceedingly rarely, these corrections dramatically improve the stability of the algorithm. We present preliminary results from the application of these algorithms to two problems in RMHD: the propagation of supersonic magnetized jets and the amplification of magnetic field by turbulence driven by the relativistic Kelvin–Helmholtz instability (KHI). Both of these applications reveal important differences between the results computed with Riemann solvers that adopt different approximations for the fluxes. For example, we show that the use of Riemann solvers that include both contact and rotational discontinuities can increase the strength of the magnetic field within the cocoon by a factor of 10 in simulations of RMHD jets and can increase the spectral resolution of three-dimensional RMHD turbulence driven by the KHI by a factor of two. This increase in accuracy far outweighs the associated increase in computational cost. Our RMHD scheme is publicly available as part of the Athena code.
Geometric Algebra: A natural representation of three-space

Historically, there have been many attempts to produce an appropriate mathematical formalism for modeling the nature of physical space, such as Euclid's geometry, Descartes' system of Cartesian coordinates, the Argand plane, Hamilton's quaternions and Gibbs' vector system using the dot and cross products. We illustrate however, that Clifford's geometric algebra (GA) provides the most elegant description of physical space. Supporting this conclusion, we firstly show how geometric algebra subsumes the key elements of the competing formalisms and secondly how it provides an intuitive representation of the basic concepts of points, lines, areas and volumes. We also provide two examples where GA has been found to provide an improved description of two key physical phenomena, electromagnetism and quantum theory, without using tensors or complex vector spaces. This paper also provides pedagogical tutorial-style coverage of the various basic applications of geometric algebra in physics.
Bio-inspired Methods for Dynamic Network Analysis in Science Mapping

We apply bio-inspired methods for the analysis of different dynamic bibliometric networks (linking papers by citation, authors, and keywords, respectively). Biological species are clusters of individuals defined by widely different criteria and in the biological perspective it is natural to (1) use different categorizations on the same entities (2) to compare the different categorizations and to analyze the dissimilarities, especially as they change over time. We employ the same methodology to comparisons of bibliometric classifications. We constructed them as analogs of three species concepts: cladistic or lineage based, similarity based, and "biological species" (based on co-reproductive ability). We use the Rand and Jaccard indexes to compare classifications in different time intervals. The experiment is aimed to address the classic problem of science mapping, as to what extent the various techniques based on different bibliometric indicators, such as citations, keywords or authors are able to detect convergent structures in the litrerature, that is, to identify coherent specialities or research directions and their dynamics.
Formalising the multidimensional nature of social networks

Individuals interact with conspecifics in a number of behavioural contexts or dimensions. Here, we formalise this by considering a social network between n individuals interacting in b behavioural dimensions as a nxnxb multidimensional object. In addition, we propose that the topology of this object is driven by individual needs to reduce uncertainty about the outcomes of interactions in one or more dimension. The proposal grounds social network dynamics and evolution in individual selection processes and allows us to define the uncertainty of the social network as the joint entropy of its constituent interaction networks. In support of these propositions we use simulations and natural 'knock-outs' in a free-ranging baboon troop to show (i) that such an object can display a small-world state and (ii) that, as predicted, changes in interactions after social perturbations lead to a more certain social network, in which the outcomes of interactions are easier for members to predict. This new formalisation of social networks provides a framework within which to predict network dynamics and evolution under the assumption that it is driven by individuals seeking to reduce the uncertainty of their social environment.
Numerical simulation of fundamental trapped sausage modes

We integrate the 2D MHD ideal equations of a straight slab to simulate observational results associated with fundamental sausage trapped modes.  Starting from a non-equilibrium state with a dense chromospheric layer, we analyse the evolution of the internal plasma dynamics of magnetic loops, subject to line-tying boundary conditions, and with the coronal parameters described in Asai et al. (2001) and Melnikov et al. (2002) to investigate the onset and damping of sausage modes.  To integrate the equations we used a high resolution shock-capturing (HRSC) method specially designed to deal appropriately with flow discontinuities.  Due to non-linearities and inhomogeneities, pure modes are difficult to sustain and always occur coupled among them so as to satisfy, e.g., the line-tying constraint. We found that, in one case, the resonant coupling of the sausage fundamental mode with a slow one results in a non-dissipative damping of the former.  In scenarios of thick and dense loops, where the analytical theory predicts the existence of fundamental trapped sausage modes, the coupling of fast and slow quasi-periodic modes -with a node at the center of the longitudinal speed- occur contributing to the damping of the fast mode. If a discontinuity in the total pressure between the loop and the corona is assumed, a fundamental fast sausage transitory leaky regime is spontaneously produced and an external compressional Alfv\'en wave takes away the magnetic energy.
Algorithm for a microfluidic assembly line.

Microfluidic technology has revolutionized the control of flows at small scales giving rise to new possibilities for assembling complex structures on the microscale. We analyze different possible algorithms for assembling arbitrary structures, and demonstrate that a sequential assembly algorithm can manufacture arbitrary 3D structures from identical constituents. We illustrate the algorithm by showing that a modified Hele-Shaw cell with 7 controlled flow rates can be designed to construct the entire English alphabet from particles that irreversibly stick to each other.
Spin-state crossover and hyperfine interactions of ferric iron in MgSiO(3) perovskite.

Using density functional theory plus Hubbard U calculations, we show that the ground state of (Mg,Fe)(Si,Fe)O(3) perovskite, the major mineral phase in Earth's lower mantle, has high-spin ferric iron (S=5/2) at both dodecahedral (A) and octahedral (B) sites. With increasing pressure, the B-site iron undergoes a spin-state crossover to the low-spin state (S=1/2) between 40 and 70 GPa, while the A-site iron remains in the high-spin state. This B-site spin-state crossover is accompanied by a noticeable volume reduction and an increase in quadrupole splitting, consistent with recent x-ray diffraction and Mössbauer spectroscopy measurements. The anomalous volume reduction leads to a significant softening in bulk modulus during the crossover, suggesting a possible source of seismic-velocity anomalies in the lower mantle.
Who Is the Best Player Ever? A Complex Network Analysis of the History of Professional Tennis

We considered all matches played by professional tennis players between 1968 and2010, and, on the basis of this data set, constructed a directed and weighted network of contacts. The resulting graph showed complex features, typical of many real networked systems studied in literature. We developed a diffusion algorithm and applied it to the tennis contact network in order to rank professional players. Jimmy Connors was identified as the best player in the history of tennis according to our ranking procedure. We performed a complete analysis by determining the best players on specific playing surfaces as well as the best ones in each of the years covered by the data set. The results of our technique were compared to those of two other well established methods. In general, we observed that our ranking method performed better: it had a higher predictive power and did not require the arbitrary introduction of external criteria for the correct assessment of the quality of players. The present work provides novel evidence of the utility of tools and methods of network theory in real applications.
Toward a resolution of the proton size puzzle

We show that off-mass-shell effects arising from the internal structure of the proton provide a new proton polarization mechanism in the Lamb shift, proportional to the lepton mass to the fourth power. This effect is capable of resolving the current puzzle regarding the difference in the proton radius extracted from muonic compared with electronic hydrogen experiments. These off-mass-shell effects could be probed in several other experiments. A significant ambiguity appearing in dispersion relation evaluations of the proton polarizability contribution to the Lamb shift is noted.
Statistical mechanics of semi-supervised clustering in sparse graphs

We theoretically study semi-supervised clustering in sparse graphs in the presence of pair-wise constraints on the cluster assignments of nodes. We focus on bi-cluster graphs and study the impact of semi-supervision for varying constraint density and overlap between the clusters. Recent results for unsupervised clustering in sparse graphs indicate that there is a critical ratio of within-cluster and between-cluster connectivities below which clusters cannot be recovered with better than random accuracy. The goal of this paper is to examine the impact of pair-wise constraints on the clustering accuracy. Our results suggest that the addition of constraints does not provide automatic improvement over the unsupervised case. When the density of the constraints is sufficiently small, their only impact is to shift the detection threshold while preserving the criticality. Conversely, if the density of (hard) constraints is above the percolation threshold, the criticality is suppressed and the detection threshold disappears.
Designing evanescent optical interactions to control the expression of Casimir forces in optomechanical structures

We propose an optomechanical structure consisting of a photonic-crystal (holey) membrane suspended above a layered silicon-on-insulator substrate in which resonant bonding/antibonding optical forces created by externally incident light from above enable all-optical control and actuation of stiction effects induced by the Casimir force. In this way, one can control how the Casimir force is expressed in the mechanical dynamics of the membrane, not by changing the Casimir force directly but by optically modifying the geometry and counteracting the mechanical spring constant to bring the system in or out of regimes where Casimir physics dominate. The same optical response (reflection spectrum) of the membrane to the incident light can be exploited to accurately measure the effects of the Casimir force on the equilibrium separation of the membrane.
Information transmission in genetic regulatory networks: a review

Genetic regulatory networks enable cells to respond to changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits has deepened our understanding of what kinds of computations genetic regulatory networks can perform, and with what reliability. These advances have motivated researchers to look for connections between the architecture and function of genetic regulatory networks. Transmitting information between a network’s inputs and outputs has been proposed as one such possible measure of function, relevant in certain biological contexts. Here we summarize recent developments in the application of information theory to gene regulatory networks. We first review basic concepts in information theory necessary for understanding recent work. We then discuss the functional complexity of gene regulation, which arises from the molecular nature of the regulatory interactions. We end by reviewing some experiments that support the view that genetic networks responsible for early development of multicellular organisms might be maximizing transmitted ‘positional information’.
Chemical pathways in ultracold reactions of SrF molecules

ultralow temperatures by characterizing the resonant states of the complex. Observing these transition-state resonances and interpreting their influence in chemical reactions is a long-standing goal of physical chemistry and one in which the high-energy resolution of ultracold molecules may be of great help. Set against this backdrop, it would also be useful to explore other molecules reacting at ultralow temperatures to gain additional insight into what can be learned. To this end, the SrF molecule is an appealing candidate and the one with which we deal with in this article. SrF is a prime example of a class of molecules that have been identified as amenable to direct laser cooling from a beam [20], and in fact laser cooling has been recently demonstrated [21]. It is quite polar (dipolemoment ≈1.4D),sothatelectricfieldmanipulationisa possibility. Moreover, it has an open-shell 2 � ground state that gives it a magnetic moment as well. This circumstance opens opportunities such as trapping the molecules magnetically, while manipulating their interactions electrically [22]. In this article, we explore the possibility and mechanisms for chemical reactions of SrF molecules at ultralow temperatures. We make several observations. First, the exchange reaction
Macrostate Parameter and Investment Risk Diagrams for 2008 and 2009

In this paper are made some considerations of the application of phenomenological thermodynamics in risk analysis for the transaction on financial markets, using the concept of economic entropy and the macrostate parameter introduced by us in a previous works [15,16]. The investment risk diagrams for a number of Romanian listed companies in 2008 and 2009 years were calculed. Also, the evolution of the macrostate parameter during financial and economic crisis in Romania are studied.
Econophysical Approaches for the Direct Foreign Investments

In this paper will be applied some principles and methods from econophysics in the case of the direct foreign investitions (D.F.I.), particularised for the Greenfield type, and mixed firms of trade and industrial production (Joint Ventures). To this aim will be used some similarities and parallelisms between the mentioned economic domains and some phenomena and processes from physics, especially from thermodynamics, solid state physics (the grow of crystals and thin policrystalline layers etc.), electromagnetism etc.
MERGERS OF SUPERMASSIVE BLACK HOLES IN ASTROPHYSICAL ENVIRONMENTS

Modeling the late inspiral and mergers of supermassive black holes (BHs) is central to understanding accretion processes and the conditions under which electromagnetic (EM) emission accompanies gravitational waves (GWs). We use fully general relativistic hydrodynamics simulations to investigate how EM signatures correlate with BH spins, mass ratios, and the gaseous environment in this final phase of binary evolution. In all scenarios, we find some form of characteristic EM variability whose detailed pattern depends on the spins and binary mass ratios. Binaries in hot accretion flows exhibit a flare followed by a sudden drop in luminosity associated with the plunge and merger, as well as quasi-periodic oscillations correlated with the GWs during the inspiral. Conversely, circumbinary disk systems are characterized by a low luminosity of variable emission, suggesting challenging prospects for their detection.
Efficiently enclosing the compact binary parameter space by singular-value decomposition

Gravitational-wave searches for the merger of compact binaries use matched filtering as the method of detecting signals and estimating parameters. Such searches construct a fine mesh of filters covering a signal parameter space at high density. Previously it has been shown that singular-value decomposition can reduce the effective number of filters required to search the data. Here we study how the basis provided by the singular-value decomposition changes dimension as a function of template-bank density. We will demonstrate that it is sufficient to use the basis provided by the singular-value decomposition of a low-density bank to accurately reconstruct arbitrary points within the boundaries of the template bank. Since this technique is purely numerical, it may have applications to interpolating the space of numerical relativity waveforms.
Aircraft Proximity Maps Based on Data-Driven Flow Modeling

With the forecast increase in air traffic demand over the next decades, it is imperative to develop tools to provide traffic flow managers with the information required to support decision making. In particular, decision-support tools for traffic flow management should aid in limiting controller workload and complexity, while supporting increases in air traffic throughput. While many decision-support tools exist for short-term traffic planning, few have addressed the strategic needs for medium- and long-term planning for time horizons greater than 30 minutes. This paper seeks to address this gap through the introduction of 3D aircraft proximity maps that evaluate the future probability of presence of at least one or two aircraft at any given point of the airspace. Three types of proximity maps are presented: presence maps that indicate the local density of traffic; conflict maps that determine locations and probabilities of potential conflicts; and outliers maps that evaluate the probability of conflict due to aircraft not belonging to dominant traffic patterns. These maps provide traffic flow managers with information relating to the complexity and difficulty of managing an airspace. The intended purpose of the maps is to anticipate how aircraft flows will interact, and how outliers impact the dominant traffic flow for a given time period. This formulation is able to predict which "critical" regions may be subject to conflicts between aircraft, thereby requiring careful monitoring. These probabilities are computed using a generative aircraft flow model. Time-varying flow characteristics, such as geometrical configuration, speed, and probability density function of aircraft spatial distribution within the flow, are determined from archived Enhanced Traffic Management System data, using a tailored clustering algorithm. Aircraft not belonging to flows are identified as outliers.
Reinforced communication and social navigation: remember your friends and remember yourself

In social systems, people communicate with each other and form groups based on their interests. The pattern of interactions, the network, and the ideas that flow on the network naturally evolve together. Researchers use simple models to capture the feedback between changing network patterns and ideas on the network, but little is understood about the role of past events in the feedback process. Here, we introduce a simple agent-based model to study the coupling between peoples' ideas and social networks, and better understand the role of history in dynamic social networks. We measure how information about ideas can be recovered from information about network structure and, the other way around, how information about network structure can be recovered from information about ideas. We find that it is, in general, easier to recover ideas from the network structure than vice versa.
Foundations of a theory of quantum gravity

After a long technical and consequently philosophical disgression about the necessity of the construction presented in this book, a logically consistent and precise theory of quantum gravity is presented. The construction of this theory goes in several steps; at first we take a fairly conservative point of view and stumble upon some technical difficulties. Consequently, we investigate a new mathematical implication of an old idea to solve these problems; the latter suggest however a completely new way of doing quantum theory. This novel theory automatically incoorporates an extended form of gravity as well as a quantum gauge theory. We compute that the well known free quantum field theories and Newtonian gravity emerge in a suitable limit. The philosophy constructed here is to a high degree Whiteheadian.
Introduction to dark matter experiments

This is a set of four lectures presented at the Theoretical Advanced Study Institute (TASI-09) in June 2009. I provide an introduction to experiments designed to detect WIMP dark matter directly, focusing on building intuitive understanding of the characteristics of potential WIMP signals and the experimental techniques. After deriving the characteristics of potential signals in direct-detection experiments for standard WIMP models, I summarize the general experimental methods shared by most direct-detection experiments and review the advantages, challenges, and status of such searches (as of late 2009). Experiments are already probing SUSY models, with best limits on the spin-independent coupling below 10^-7 pb.
Open quantum system approach to the Gibbons-Hawking effect of de Sitter space-time.

We analyze, in the paradigm of open quantum systems, the reduced dynamics of a freely falling two-level detector in de Sitter space-time in weak interaction with a reservoir of fluctuating quantized conformal scalar fields in the de Sitter-invariant vacuum. We find that the detector is asymptotically driven to a thermal state at the Gibbons-Hawking temperature, regardless of its initial state. Our discussion, therefore, shows that the Gibbons-Hawking effect of de Sitter space-time can be understood as a manifestation of thermalization phenomena that involves decoherence and dissipation in open quantum systems.
How Many Nodes are Effectively Accessed in Complex Networks?

The measurement called accessibility has been proposed as a means to quantify the efficiency of the communication between nodes in complex networks. This article reports important results regarding the properties of the accessibility, including its relationship with the average minimal time to visit all nodes reachable after h steps along a random walk starting from a source, as well as the number of nodes that are visited after a finite period of time. We characterize the relationship between accessibility and the average number of walks required in order to visit all reachable nodes (the exploration time), conjecture that the maximum accessibility implies the minimal exploration time, and confirm the relationship between the accessibility values and the number of nodes visited after a basic time unit. The latter relationship is investigated with respect to three types of dynamics, namely: traditional random walks, self-avoiding random walks, and preferential random walks.