nils-herrmann/clean_scirepeval huggingface dataset:
Tachyon stars

We consider a self-gravitating body composed of ideal Fermi gas of tachyons at zero temperature. The Oppenheimer-Volkoff equation is solved for various central densities and various tachyon mass parameter m. Although a pure tachyon star has finite mass, it cannot occur in nature because the equilibrium condition P = 0 and the causality condition cannot be satisfied simultaneously. A stable configuration with tachyon content must be covered with a non-tachyon envelope. The boundary between the tachyon core and the envelope is determined by the critical pressure PT , which depends on the tachyon mass m. The tachyon core is dominant and its mass can exceed many times the solar mass M when m is much smaller than the nucleon mass mp, while at large m compared with mp, the main contribution to the total stellar mass is due to the envelope whose material determines the parameters of the whole star. However, the parameters of the tachyon core do not depend on the envelope material. When the tachyon core appears, its mass MT and radius rT grow up with increasing central density until maximum values are reached, after which the mass and radius slowly decrease. The redshift at the surface of the tachyon core does not depend on m and never exceeds zmax ' 0.3. The maximum mass of tachyon core and its maximum radius are achieved at certain central density and obey universal formulas MT max/M = 0.52m 2 p/m 2 and rT max[km] = 4.07m 2 p/m 2 that allow to estimate arbitrary supermassive tachyonic bodies at the cosmological scale. 1 ar X iv :1 11 0. 25 23 v2 [ as tr oph .C O ] 2 4 N ov 2 01 1
Measuring Time of Flight Using Satellite-Based Clocks

Considering the OPERA neutrino-velocity measurement from the point of view of a GPS satellite we find that the detector at Gran Sasso has a velocity component in the order of $10^{-5}c$ towards the neutrino emission location at CERN. On GPS-receivers this translates into first-order Doppler terms, therefore a correction is required for, among other things, this ephemeris-and-location-dependent relativistic effect. To ensure correct time-of-flight measurements using satellite-based clocks we propose to extend their calibration procedures with an explicit check on these relativistic corrections.
Bubble Oscillations and Motion under Vibration.

Bubbles under vibration can behave in unusual ways, e.g., moving downward against the force of buoyancy. While the bubble downward motion due to the Bjerknes force is well known at acoustic frequencies close to the bubble resonant frequency, these experiments demonstrate that these effects can be observed at relatively low frequencies as well. Experiments were performed in a thin, quasi-two-dimensional rectangular acrylic box partially filled with 20-cSt PDMS silicone oil with overlying ambient air. The apparatus was subjected to sinusoidal axial vibration that produced breakup of the gas-liquid free surface, producing liquid jets into the air, droplets pinching off from these jets, gas cavities in the liquid from impacts of these droplets, and bubble transport below the interface. Vibration conditions for the attached videos are 280 Hz frequency, 15 g acceleration, and 94 micron peak-to-peak displacement. Behaviors shown in the videos include the following. 1. Free surface breakup into jets and droplets, and formation of bubbles under the free surface. 2. Bubbles thus generated moving downward in the cell. 3. Bubbles attracted to the first bubble deep in the cell and eventually merging to form a large bubble at the base of the cell. 4. Bubble cluster at the base of the cell merging to form a larger bubble, which stabilizes at a levitated location below the free surface and acts to damp out the surface breakup. 5. The levitated bubble interface and its breakup are similar to the free surface breakup into jets and droplets, but the jets in the bubble are facing downward. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
Updated Report on Acceleration of Polarized Protons to 120-150 GeV/c at Fermilab

The SPIN@FERMI collaboration has updated its 1991-95 Reports on the acceleration of polarized protons in Fermilab's Main Injector, which was commissioned by Fermilab. This Updated Report summarizes some updated Physics Goals for a 120-150 GeV/c polarized proton beam. It also contains an updated discussion of the Modifications and Hardware needed for a polarized beam in the Main Injector, along with an updated Schedule and Budget.
No-go theorem for critical phenomena in large-N(c) QCD.

We derive some rigorous results on the chiral phase transition in QCD and QCD-like theories with a large number of colors, N(c), based on the QCD inequalities and the large-N(c) orbifold equivalence. We show that critical phenomena and associated soft modes are forbidden in flavor-symmetric QCD at finite temperature T and finite but not so large quark chemical potential μ for any nonzero quark mass. In particular, the critical point in QCD at a finite baryon chemical potential μ(B)=N(c)μ is ruled out, if the coordinate (T, μ) is outside the pion condensed phase in the corresponding phase diagram of QCD at a finite isospin chemical potential μ(I)=2μ.
Can mosquitoes fly in the rain

Collisions with raindrops are one of many obstacles insects face during flight. In this fluid dynamics video, we present a series of high-speed films of impacts between mosquitoes and raindrops. We also present drop impacts upon insect mimics, which are unsupported styrofoam balls of the same mass as mosquitoes. High-speed videography and particle tracking during collision are employed to determine the insect position versus time. We determine the magnitude of acceleration by considering the momentum transfer and impact duration. Experiments with live mosquitoes indicate a surprising ability to quickly recover flight post-collision, despite accelerations of 30-300 gravities over durations of 1 ms.
The Virtual Reality Conjecture

We take our world to be an objective reality, but is it? The assumption that the physical world exists in and of itself has struggled to assimilate the findings of modern physics for some time now. For example, an objective space and time would just "be", but in relativity, space contracts and time dilates. Likewise objective "things" should just inherently exist, but the entities of quantum theory are probability of existence smears, that spread, tunnel, superpose and entangle in physically impossible ways. Cosmology even tells us that our entire physical universe just "popped up", from nowhere, about 14 billion years ago. This is not how an objectively real world should behave! Yet traditional alternatives don't work much better. That the world is just an illusion of the mind doesn't explain its consistent realism and Descartes dualism, that another reality beyond the physical exists, just doubles the existential problem. It is time to consider an option we might normally dismiss out of hand. This essay explores the virtual reality conjecture, that the physical world is the digital output of non-physical quantum processing. It finds it neither illogical, nor unscientific, nor incompatible with current physics. In this model, quantum entities are programs, movement is the transfer of processing, interactions are processing overloads and the fields of physics are network properties. It has no empty space, no singularities and all the conservations of physics just conserve processing. Its prediction, that the collision of high frequency light in a vacuum can create permanent matter, will test it. If the physical world has the properties of a processing output, physics must rewrite the story behind its equations.
Evolution of spatially embedded branching trees with interacting nodes

We study the evolution of branching trees embedded in Euclidean spaces with suppressed branching of spatially close nodes. This cooperative branching process accounts for the effect of overcrowding of nodes in the embedding space and mimics the evolution of life processes (the so-called "tree of life") in which a new level of complexity emerges as a short transition followed by a long period of gradual evolution or even complete extinction. We consider the models of branching trees in which each new node can produce up to two twigs within a unit distance from the node in the Euclidean space, but this branching is suppressed if the newborn node is closer than at distance $a$ from one of the previous generation nodes. This results in an explosive (exponential) growth in the initial period, and, after some crossover time $t_x \sim \ln(1/a)$ for small $a$, in a slow (power-law) growth. This special point is also a transition from "small" to "large words" in terms of network science. We show that if the space is restricted, then this evolution may end by extinction.
Viral Evolution and Adaptation as a Multivariate Branching Process

In the present work we analyze the problem of adaptation and evolution of RNA virus populations, by defining the basic stochastic model as a multivariate branching process in close relation with the branching process advanced by Demetrius, Schuster and Sigmund ("Polynucleotide evolution and branching processes",  (1985) 239-262), in their study of polynucleotide evolution. We show that in the absence of beneficial forces the model is exactly solvable. As a result it is possible to prove several key results directly related to known typical properties of these systems like (i) proof, in the context of the theory of branching processes, of the lethal mutagenesis criterion proposed by Bull, Sanju\'an and Wilke ("Theory of lethal mutagenesis for viruses",  (2007) 2930-2939); (ii) a new proposal for the notion of relaxation time with a quantitative prescription for its evaluation and (iii) the quantitative description of the evolution of the expected values in four distinct regimes: transient, "stationary" equilibrium, extinction threshold and lethal mutagenesis. Moreover, new insights on the dynamics of evolving virus populations can be foreseen.
Network Clustering Approximation Algorithm Using One Pass Black Box Sampling

Finding a good clustering of vertices in a network, where vertices in the same cluster are more tightly connected than those in different clusters, is a useful, important, and well-studied task. Many clustering algorithms scale well, however they are not designed to operate upon internet-scale networks with billions of nodes or more. We study one of the fastest and most memory efficient algorithms possible - clustering based on the connected components in a random edge-induced subgraph. When defining the cost of a clustering to be its distance from such a random clustering, we show that this surprisingly simple algorithm gives a solution that is within an expected factor of two or three of optimal with either of two natural distance functions. In fact, this approximation guarantee works for any problem where there is a probability distribution on clusterings. We then examine the behavior of this algorithm in the context of social network trust inference.
Does OPERA probe that the Earth is moving

The OPERA experiment reported recently a puzzling result. The time of flight of a neutrino beam between the CERN and the Gran Sasso Laboratory has been measured to be slightly shorter than expected. More precisely, an early arrival time of the neutrino with respect to the one computed assuming the speed of light in vacuum of 60.7 ns was measured, with a quite high confidence level. Alternatively, one can conclude that the neutrinos travelled 18.2 m more than light would do in vacuum. In this short paper, we suggest a possible systematic effect that does not appear in the analysis and which can easily been probed to be confirmed.
Normal Mode Expansion of Damped Coupled Oscillators in 3 dimensions

In this paper, I aim to study free oscillations of a system of oscillators in more than one dimensions in the absence of damping. The basic approach lies in decoupling the motion in the individual perpendicular directions. Once the equations are decoupled, the existent techniques of Normal mode expansion for 1-dimensional oscillators are used to solve for the equations of motion. I also study the motion of a driven system of oscillators in higher dimensions in the presence of a velocity dependent damping force.
The chiral representation of the $\pi N$ scattering amplitude and the pion-nucleon sigma term

We present a novel analysis of the $\ensuremath{\pi}N$ scattering amplitude in Lorentz covariant baryon chiral perturbation theory renormalized in the extended-on-mass-shell scheme. This amplitude, valid up to $\mathcal{O}({p}^{3})$ in the chiral expansion, systematically includes the effects of the $\ensuremath{\Delta}(1232)$ in the $\ensuremath{\delta}$-counting, has the right analytic properties, and is renormalization-scale independent. This approach overcomes the limitations that previous chiral analyses of the $\ensuremath{\pi}N$ scattering amplitude had, providing an accurate description of the partial wave phase shifts of the Karlsruhe-Helsinki and George-Washington groups up to energies just below the resonance region. We also study the solution of the Matsinos group which focuses on the parameterization of the data at low energies. Once the values of the low-energy constants are determined by adjusting the center-of-mass energy dependence of the amplitude to the scattering data, we obtain predictions on different observables. In particular, we extract an accurate value for the pion-nucleon sigma term, ${\ensuremath{\sigma}}_{\ensuremath{\pi}N}$. This allows us to avoid the usual method of extrapolation to the unphysical region of the amplitude. Our study indicates that the inclusion of modern meson-factory and pionic-atom data favors relatively large values of the sigma term. We report the value ${\ensuremath{\sigma}}_{\ensuremath{\pi}N}=59(7)\text{ }\text{ }\mathrm{MeV}$ and comment on implications that this result may have.
Consistency of community detection in networks under degree-corrected stochastic block models

Community detection is a fundamental problem in network analysis, with applications in many diverse areas. The stochastic block model is a common tool for model-based community detection, and asymptotic tools for checking consistency of community detection under the block model have been recently developed. However, the block model is limited by its assumption that all nodes within a community are stochastically equivalent, and provides a poor fit to networks with hubs or highly varying node degrees within communities, which are common in practice. The degree-corrected stochastic block model was proposed to address this shortcoming and allows variation in node degrees within a community while preserving the overall block community structure. In this paper we establish general theory for checking consistency of community detection under the degree-corrected stochastic block model and compare several community detection criteria under both the standard and the degree-corrected models. We show which criteria are consistent under which models and constraints, as well as compare their relative performance in practice. We find that methods based on the degree-corrected block model, which includes the standard block model as a special case, are consistent under a wider class of models and that modularity-type methods require parameter constraints for consistency, whereas likelihood-based methods do not. On the other hand, in practice, the degree correction involves estimating many more parameters, and empirically we find it is only worth doing if the node degrees within communities are indeed highly variable. We illustrate the methods on simulated networks and on a network of political blogs.
The large-scale structure of journal citation networks

We analyse the large-scale structure of the journal citation network built from information contained in the Thomson-Reuters Journal Citation Reports. To this end, we take advantage of the network science paraphernalia and explore network properties like density, percolation robustness, average and largest node distances, reciprocity, incoming and outgoing degree distributions, as well as assortative mixing by node degrees. We discover that the journal citation network is a dense, robust, small, and reciprocal world. Furthermore, in and out node degree distributions display long-tails, with few vital journals and many trivial ones, and they are strongly positively correlated.
A NEW TYPE OF COMPACT STELLAR POPULATION: DARK STAR CLUSTERS

Among the most explored directions in the study of dense stellar systems is the investigation of the effects of the retention of supernova remnants, especially that of the massive stellar remnant black holes (BHs), in star clusters. By virtue of their eventual high central concentration, these stellar mass BHs potentially invoke a wide variety of physical phenomena, the most important ones being emission of gravitational waves (GWs), formation of X-ray binaries, and modification of the dynamical evolution of the cluster. Here we propose, for the first time, that rapid removal of stars from the outer parts of a cluster by the strong tidal field in the inner region of our Galaxy can unveil its BH sub-cluster, which appears as a star cluster that is gravitationally bound by an invisible mass. We study the formation and properties of such systems through direct N-body computations and estimate that they can be present in significant numbers in the inner region of the Milky Way. We call such objects “dark star clusters” (DSCs) as they appear dimmer than normal star clusters of similar mass and they comprise a predicted, new class of entities. The finding of DSCs will robustly cross-check BH retention; they will not only constrain the uncertain natal kicks of BHs, thereby the widely debated theoretical models of BH formation, but will also pinpoint star clusters as potential sites for GW emission for forthcoming ground-based detectors such as the Advanced LIGO. Finally, we also discuss the relevance of DSCs for the nature of IRS 13E.
Integration and Contagion in US Housing Markets

This paper explores integration and contagion among US metropolitan housing markets. The analysis applies Federal Housing Finance Agency (FHFA) house price repeat sales indexes from 384 metropolitan areas to estimate a multi-factor model of U.S. housing market integration. It then identifies statistical jumps in metropolitan house price returns as well as MSA contemporaneous and lagged jump correlations. Finally, the paper evaluates contagion in housing markets via parametric assessment of MSA house price spatial dynamics. A R-squared measure reveals an upward trend in MSA housing market integration over the 2000s to approximately .83 in 2010. Among California MSAs, the trend was especially pronounced, as average integration increased from about .55 in 1997 to close to .95 in 2008! The 2000s bubble period similarly was characterized by elevated incidence of statistical jumps in housing returns. Again, jump incidence and MSA jump correlations were especially high in California. Analysis of contagion among California markets indicates that house price returns in San Francisco often led those of surrounding communities; in contrast, southern California MSA house price returns appeared to move largely in lock step. The high levels of housing market integration evidenced in the analysis suggest limited investor opportunity to diversify away MSA-specific housing risk. Further, results suggest that macro and policy shocks propagate through a large number of MSA housing markets. Research findings are relevant to all market participants, including institutional investors in MBS as well as those who regulate housing, the housing GSEs, mortgage lenders, and related financial institutions.
The falling slinky

The slinky, released from rest hanging under its own weight, falls in a peculiar manner. The bottom stays at rest until a wave hits it from above. Two cases - one unphysical one where the slinky is able to pass through itself, and the other where the coils of the slinky collide creating a shock wave travelling down the slinky are analysed. In the former case, the bottom begins to move much later than in the latter.
Multiband quasiparticle interference in the topological insulator Cu_(x)Bi_(2)Te_(3)

We present angle resolved photoemission experiments and scanning tunneling spectroscopy results on the doped topological insulator Cu0.2Bi2Te3. Quasi-particle interference (QPI) measurements, based on high resolution conductance maps of the local density of states show that there are three distinct energy windows for quasi-particle scattering. Using a model Hamiltonian for this system two new scattering channels are identified: the first between the surface states and the conduction band and the second between conduction band states. We also observe that the real space density modulation has a predominant three-fold symmetry, which rules out a simple, isotropic impurity potential. We obtain agreement between experiment and theory by considering a modified scattering potential that is consistent with having mostly Bi-Te anti-site defects as scatterers.
Quantum fluctuations around black hole horizons in Bose-Einstein condensates

We study several realistic configurations allowing to realize an acoustic horizon in the flow of a one dimensional Bose-Einstein condensate. In each case we give an analytical description of the flow pattern, of the spectrum of Hawking radiation and of the associated quantum fluctuations. Our calculations confirm that the non local correlations of the density fluctuations previously studied in a simplified model provide a clear signature of Hawking radiation also in realistic configurations. In addition we explain by direct computation how this non local signal relates to short range modifications of the density correlations.
Hierarchical Information Clustering by Means of Topologically Embedded Graphs

We introduce a graph-theoretic approach to extract clusters and hierarchies in complex data-sets in an unsupervised and deterministic manner, without the use of any prior information. This is achieved by building topologically embedded networks containing the subset of most significant links and analyzing the network structure. For a planar embedding, this method provides both the intra-cluster hierarchy, which describes the way clusters are composed, and the inter-cluster hierarchy which describes how clusters gather together. We discuss performance, robustness and reliability of this method by first investigating several artificial data-sets, finding that it can outperform significantly other established approaches. Then we show that our method can successfully differentiate meaningful clusters and hierarchies in a variety of real data-sets. In particular, we find that the application to gene expression patterns of lymphoma samples uncovers biologically significant groups of genes which play key-roles in diagnosis, prognosis and treatment of some of the most relevant human lymphoid malignancies.