nils-herrmann/clean_scirepeval huggingface dataset:
Microscopic Dirac Spectrum in a 2d Gauge Theory with Zero Chiral Condensate

Fermionic theories with a vanishing chiral condensate (in the chiral limit) have recently attracted considerable interest; in particular variants of multi-flavour QCD are candidates for this behaviour. Here we consider the 2-flavour Schwinger model as a simple theory with this property. Based on simulations with light dynamical overlap fermions, we test the hypothesis that in such models the low lying Dirac eigenvalues could be decorrelated. That has been observed in 4d Yang-Mills theories at high temperature, but it cannot be confirmed for the 2-flavour Schwinger model. We also discuss subtleties in the evaluation of the mass anomalous dimension and its IR extrapolation.
Transforming High School Physics With Modeling And Computation

The Engage to Excel (PCAST) report, the National Research Council's Framework for K-12 Science Education, and the Next Generation Science Standards all call for transforming the physics classroom into an environment that teaches students real scientific practices. This work describes the early stages of one such attempt to transform a high school physics classroom. Specifically, a series of model-building and computational modeling exercises were piloted in a ninth grade Physics First classroom. Student use of computation was assessed using a proctored programming assignment, where the students produced and discussed a computational model of a baseball in motion via a high-level programming environment (VPython). Student views on computation and its link to mechanics was assessed with a written essay and a series of think-aloud interviews. This pilot study shows computation's ability for connecting scientific practice to the high school science classroom.
Law of Urination: all mammals empty their bladders over the same duration

Many urological studies rely upon animal models such as rats and pigs whose urination physics and correlation to humans are poorly understood. Here we elucidate the hydrodynamics of urination across five orders of magnitude in animal mass. Using high-speed videography and flow rate measurement at Zoo Atlanta, we discover the "Law of Urination," which states animals empty their bladders over nearly constant duration of average 21 seconds (standard deviation 13 seconds). This feat is made possible by larger animals having longer urethras, thus higher gravitational force and flow speed. Smaller mammals are challenged during urination due to high viscous and surface tension forces that limit their urine to single drops. Our findings reveal the urethra constitutes as a flow enhancing device, enabling the urinary system to be scaled up without compromising its function. This study may help in the diagnosis of urinary problems in animals and in inspiring the design of scalable hydrodynamic systems based on those in nature.
An agent-based model of the cognitive mechanisms underlying the origins of creative cultural evolution

Human culture is uniquely cumulative and open-ended. Using a computational model of cultural evolution in which neural network based agents evolve ideas for actions through invention and imitation, we tested the hypothesis that this is due to the capacity for recursive recall. We compared runs in which agents were limited to single-step actions to runs in which they used recursive recall to chain simple actions into complex ones. Chaining resulted in higher cultural diversity, open-ended generation of novelty, and no ceiling on the mean fitness of actions. Both chaining and no-chaining runs exhibited convergence on optimal actions, but without chaining this set was static while with chaining it was ever-changing. Chaining increased the ability to capitalize on the capacity for learning. These findings show that the recursive recall hypothesis provides a computationally plausible explanation of why humans alone have evolved the cultural means to transform this planet.
Holographic lattices give the graviton an effective mass.

We discuss the dc conductivity of holographic theories with translational invariance broken by a background lattice. We show that the presence of the lattice induces an effective mass for the graviton via a gravitational version of the Higgs mechanism. This allows us to obtain, at leading order in the lattice strength, an analytic expression for the dc conductivity in terms of the size of the lattice at the horizon. In locally critical theories this leads to a power law resistivity that is in agreement with an earlier field theory analysis of Hartnoll and Hofman.
CMB distortion anisotropies due to the decay of primordial magnetic fields

We investigate the power spectrum of the distortion of Cosmic Microwave Background (CMB) due to the decay of the primordial magnetic fields. It is known that there are two-types of the CMB distortions, so-called µ- and y-types and we find that the signal of the y-type distortion becomes larger than that of the µ-type one. We also discuss cross power spectra between the CMB distortions and the CMB temperature anisotropy, which are naturally generated due to the existence of the primordial magnetic fields. We find that such cross power spectra have small amplitudes compared with the auto-power spectra of the CMB distortions because of the Silk damping effect of the temperature anisotropy. We also investigate the possibility of detecting such signal in the future CMB experiments, including not only absolutely calibrated experiments such as PIXIE but also relatively calibrated experiments such as LiteBIRD and CMBpol.
Nuclear charge-exchange excitations in localized covariant density functional theory

The recent progress in the studies of nuclear charge-exchange excitations with localized covariant density functional theory is briefly presented, by taking the fine struc- ture of spin-dipole excitations in 16 O as an example. It is shown that the constraints in- troduced by the Fock terms of the relativistic Hartree-Fock scheme into the particle-hole residual interactions are straightforward and robust.
Extinction Times of Epidemic Outbreaks in Networks

In the Susceptible–Infectious–Recovered (SIR) model of disease spreading, the time to extinction of the epidemics happens at an intermediate value of the per-contact transmission probability. Too contagious infections burn out fast in the population. Infections that are not contagious enough die out before they spread to a large fraction of people. We characterize how the maximal extinction time in SIR simulations on networks depend on the network structure. For example we find that the average distances in isolated components, weighted by the component size, is a good predictor of the maximal time to extinction. Furthermore, the transmission probability giving the longest outbreaks is larger than, but otherwise seemingly independent of, the epidemic threshold.
The magnetic characteristics of Galactic OB stars from the MiMeS survey of magnetism in massive stars

The Magnetism in Massive Stars (MiMeS) project represents the largest systematic survey of stellar magnetism ever undertaken. Based on a sample of over 550 Galactic B and O-type stars, the MiMeS project has derived the basic characteristics of magnetism in hot, massive stars. Herein we report preliminary results.
Understanding the chain fountain

If a chain is initially at rest in a beaker at a height h1 above the ground, and the end of the chain is pulled over the rim of the beaker and down towards the ground and then released, the chain will spontaneously ‘flow’ out of the beaker under gravity. Furthermore, the beads do not simply drag over the edge of the beaker but form a fountain reaching a height h2 above it. We show that the formation of a fountain requires that the beads come into motion not only by being pulled upwards by the part of the chain immediately above the pile, but also by being pushed upwards by an anomalous reaction force from the pile of stationary chain. We propose possible origins for this force, argue that its magnitude will be proportional to the square of the chain velocity and predict and verify experimentally that h2∝h1.
On the Magnetohydrodynamics/Gravity Correspondence

The fluid/gravity correspondence relates solutions of the incompressible Navier-Stokes equation to metrics which solve the Einstein equations. In this paper we extend this duality to a new magnetohydrodynamics/gravity correspondence, which translates solutions of the equations of magnetohydrodynamics (describing charged fluids) into geometries that satisfy the Einstein-Maxwell equations. We present an explicit example of this new correspondence in the context of flat Minkowski space. We show that a perturbative deformation of the Rindler wedge satisfies the Einstein-Maxwell equations provided that the parameters appearing in the expansion, which we interpret as fluid fields, satisfy the magnetohydrodynamics equations. As a byproduct of our analysis we show that in four dimensions, the dual geometry is algebraically special Petrov type II.
A hole-ographic spacetime

We embed spherical Rindler space – a geometry with a spherical hole in its center – in asymptotically AdS spacetime and show that it carries a gravitational entropy proportional to the area of the hole. Spherical AdS-Rindler space is holographically dual to an ultraviolet sector of the boundary field theory given by restriction to a strip of finite duration in time. Because measurements have finite durations, local observers in the field theory can only access information about bounded spatial regions. We propose a notion of differential entropy that captures uncertainty about the state of a system left by the collection of local, finite-time observables. For two-dimensional conformal field theories we use holography and the strong subadditivity of entanglement to propose a formula for differential entropy and show that it precisely reproduces the areas of circular holes in AdS3. Extending the notion to field theories on strips with variable durations in time, we show more generally that differential entropy computes the areas of all closed, inhomogenous curves on a spatial slice of AdS3. We discuss the extension to higher dimensional field theories, the relation of differential entropy to entanglement between scales, and some implications for the emergence of space from the RG flow of entangled field theories. vijay@physics.upenn.edu,czech@stanford.edu,bdchowdh@asu.edu,m.p.heller,J.deBoer@uva.nl ar X iv :1 31 0. 42 04 v3 [ he pth ] 1 1 Ju n 20 14
Demystifying Information-Theoretic Clustering

We propose a novel method for clustering data which is grounded in information-theoretic principles and requires no parametric assumptions. Previous attempts to use information theory to define clusters in an assumption-free way are based on maximizing mutual information between data and cluster labels. We demonstrate that this intuition suffers from a fundamental conceptual flaw that causes clustering performance to deteriorate as the amount of data increases. Instead, we return to the axiomatic foundations of information theory to define a meaningful clustering measure based on the notion of consistency under coarse-graining for finite data.
An FCA-based Boolean Matrix Factorisation for Collaborative Filtering

We propose a new approach for Collaborative filtering which is based on Boolean Matrix Factorisation (BMF) and Formal Concept Analysis. In a series of experiments on real data (Movielens dataset) we compare the approach with the SVDand NMF-based algorithms in terms of Mean Average Error (MAE). One of the experimental consequences is that it is enough to have a binary-scaled rating data to obtain almost the same quality in terms of MAE by BMF than for the SVD-based algorithm in case of non-scaled data.
Hierarchical block structures and high-resolution model selection in large networks

Discovering and characterizing the large-scale topological features in empirical networks are crucial steps in understanding how complex systems function. However, most existing methods used to obtain the modular structure of networks suffer from serious problems, such as being oblivious to the statistical evidence supporting the discovered patterns, which results in the inability to separate actual structure from noise. In addition to this, one also observes a resolution limit on the size of communities, where smaller but well-defined clusters are not detectable when the network becomes large. This phenomenon occurs not only for the very popular approach of modularity optimization, which lacks built-in statistical validation, but also for more principled methods based on statistical inference and model selection, which do incorporate statistical validation in a formally correct way. Here we construct a nested generative model that, through a complete description of the entire network hierarchy at multiple scales, is capable of avoiding this limitation, and enables the detection of modular structure at levels far beyond those possible with current approaches. Even with this increased resolution, the method is based on the principle of parsimony, and is capable of separating signal from noise, and thus will not lead to the identification of spurious modules even on sparse networks. Furthermore, it fully generalizes other approaches in that it is not restricted to purely assortative mixing patterns, directed or undirected graphs, and ad hoc hierarchical structures such as binary trees. Despite its general character, the approach is tractable, and can be combined with advanced techniques of community detection to yield an efficient algorithm that scales well for very large networks.
Analyzing user behavior across social sharing environments

In this work we present an in-depth analysis of the user behaviors on different Social Sharing systems. We consider three popular platforms, Flickr, Delicious and StumbleUpon, and, by combining techniques from social network analysis with techniques from semantic analysis, we characterize the tagging behavior as well as the tendency to create friendship relationships of the users of these platforms. The aim of our investigation is to see if (and how) the features and goals of a given Social Sharing system reflect on the behavior of its users and, moreover, if there exists a correlation between the social and tagging behavior of the users. We report our findings in terms of the characteristics of user profiles according to three different dimensions: (i) intensity of user activities, (ii) tag-based characteristics of user profiles, and (iii) semantic characteristics of user profiles.
Complexity, economic science and possible economic benefits of climate change mitigation policy

Conventional economic analysis of stringent climate change mitigation policy generally concludes various levels of economic slowdown as a result of substantial spending on low carbon technology. Equilibrium economics however could not explain or predict the current economic crisis, which is of financial nature. Meanwhile the economic impacts of climate policy find their source through investments for the diffusion of environmental innovations, in parts a financial problem. Here, we expose how results of economic analysis of climate change mitigation policy depend entirely on assumptions and theory concerning the finance of the diffusion of innovations, and that in many cases, results are simply re-iterations of model assumptions. We show that, while equilibrium economics always predict economic slowdown, methods using non-equilibrium approaches suggest the opposite could occur. We show that the solution to understanding the economic impacts of reducing greenhouse gas emissions lies with research on the dynamics of the financial sector interacting with innovation and technology developments, economic history providing powerful insights through important analogies with previous historical waves of innovation.
Particle acceleration around a five-dimensional Kerr black hole

In the paper  authors have studied the center-ofmass (CM) energy of colliding two particles near the rotating black hole. They observed the divergence of the CM energy in the extreme rotating black hole case with the fine-tuning of the momentum of one of the particles (so called BSW process after the names of the authors - Banados, Silk, and West). The analysis of the CM energy of two colliding particles at the equatorial plane tends to extremely high energies for the extremal central black hole when it rotates with maximal speed and the maximal rotating black hole can be considered as high energy scale collider of normal and dark matter particles which can be detected by the observer at infinity. Since BSW process has been introduced the mechanism of particle acceleration near the black hole has been intensively studied by many of authors for the different space-time metric describing black hole.   have studied two particles acceleration, the multiple scattering and their CM energy in case of non extreme rotating black hole. The acceleration mechanism of the particles when they are in the stable circular orbits has been considered in . Recent studies have shown that the naked singularities that are formed due to the gravitational collapse of massive stars provide a suitable environment where particles could get accelerated and collide at arbitrarily high center-of-mass energies [4–7].   studied the collision of two particles with the different rest masses moving in the equatorial plane in a Kerr-Taub-NUT spacetime and found that the CM energy depends not only on the rotation parameter,
Natural CMT2 Variation Is Associated With Genome-Wide Methylation Changes and Temperature Seasonality

As Arabidopsis thaliana has colonized a wide range of habitats across the world it is an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we used public data from two collections of A. thaliana accessions to associate genetic variability at individual loci with differences in climates at the sampling sites. We use a novel method to screen the genome for plastic alleles that tolerate a broader climate range than the major allele. This approach reduces confounding with population structure and increases power compared to standard genome-wide association methods. Sixteen novel loci were found, including an association between Chromomethylase 2 (CMT2) and temperature seasonality where the genome-wide CHH methylation was different for the group of accessions carrying the plastic allele. Cmt2 mutants were shown to be more tolerant to heat-stress, suggesting genetic regulation of epigenetic modifications as a likely mechanism underlying natural adaptation to variable temperatures, potentially through differential allelic plasticity to temperature-stress.  A central problem when studying adaptation to a new environment is the interplay between genetic variation and phenotypic plasticity. Arabidopsis thaliana has colonized a wide range of habitats across the world and it is therefore an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we study two collections of A. thaliana accessions from across Eurasia to identify loci associated with differences in climates at the sampling sites. A new genome-wide association analysis method was developed to detect adaptive loci where the alleles tolerate different climate ranges. Sixteen novel such loci were found including a strong association between Chromomethylase 2 (CMT2) and temperature seasonality. The reference allele dominated in areas with less seasonal variability in temperature, and the alternative allele existed in both stable and variable regions. Our results thus link natural variation in CMT2 and epigenetic changes to temperature adaptation. We showed experimentally that plants with a defective CMT2 gene tolerate heat-stress better than plants with a functional gene. Together this strongly suggests a role for genetic regulation of epigenetic modifications in natural adaptation to temperature and illustrates the importance of re-analyses of existing data using new analytical methods to obtain deeper insights into the underlying biology from available data.
Non-Gaussianities in Dissipative EFT of Inflation Coupled to a Fluid

We studied models of inflation with a preferred clock specifying the end of inflation and giving the curvature perturbations, coupled with another non-equivalent clock that at late times defines the same frame and do not contribute to the density perturbations. This can happen in the framework of dissipative EFT of inflation where the additional degrees of freedom include a fluid developing sound waves propagating with sound speed $c_{sr}$. The fluid defines a preferred frame comoving with it. The paradigmatic example of this is the warm inflation scenario. We studied the dynamics of this systems during inflation and the three-point function. We saw that in the strong dissipation regime the nonlinear parameter induced by the new terms is $|f_{\rm NL}| \sim 1/c_{sr}^2$, not enhanced by the dissipation parameter which enters the two-point function. We checked that the squeezed limit of the three-point function still satisfies the consistency condition with corrections of order $\mathcal{O}(k_L^2/k_S^2)$. We computed the Planck constraints for the case of warm inflation obtaining a bound of $\gamma\lesssim 10^5 H$ for the clock coupled to radiation. For decreasing sound speed the bound decreases. We also checked that the shape of the three-point function corresponding to the model studied here is a mixture between equilateral and orthogonal with a small local component, which is more consistent with Planck's results.
Automated Lattice Perturbation Theory

I review recent developments in automated lattice perturbation theory. Starting with an overview of lattice perturbation theory, I focus on the three automation packages currently “on the market”: HiPPy/HPsrc, Pastor and PhySyHCAl. I highlight some recent applications of these methods, particularly in B physics. In the final section I briefly discuss the related, but distinct, approach of numerical stochastic perturbation theory.
The Origin of Fat Tails

We propose a random walk model of asset returns where the parameters depend on market stress. Stress is measured by, e.g., the value of an implied volatility index. We show that model parameters including standard deviations and correlations can be estimated robustly and that all distributions are approximately normal. Fat tails in observed distributions occur because time series sample different stress levels and therefore different normal distributions. This provides a quantitative description of the observed distribution including the fat tails. We discuss simple applications in risk management and portfolio construction.