nils-herrmann/clean_scirepeval huggingface dataset:
Stellar feedback by radiation pressure and photoionization

The relative impact of radiation pressure and photoionization feedback from young stars on surrounding gas is studied with hydrodynamic radiative transfer (RT) simulations. The calculations focus on the single-scattering (direct radiation pressure) and optically thick regime, and adopt a moment-based RT-method implemented in the moving-mesh code AREPO. The source luminosity, gas density profile and initial temperature are varied. At typical temperatures and densities of molecular clouds, radiation pressure drives velocities of order ~20 km/s over 1-5 Myr; enough to unbind the smaller clouds. However, these estimates ignore the effects of photoionization that naturally occur concurrently. When radiation pressure and photoionization act together, the latter is substantially more efficient, inducing velocities comparable to the sound speed of the hot ionized medium (10-15 km/s) on timescales far shorter than required for accumulating similar momentum with radiation pressure. This mismatch allows photoionization to dominate the feedback as the heating and expansion of gas lowers the central densities, further diminishing the impact of radiation pressure. Our results indicate that a proper treatment of the impact of young stars on the interstellar medium needs to primarily account for their ionization power whereas direct radiation pressure appears to be a secondary effect. This conclusion may change if extreme boosts of the radiation pressure by photon trapping are assumed.
Cosmological super-bounce

We study a model for a non-singular cosmic bounce in N=1 supergravity, based on supergravity versions of the ghost condensate and cubic Galileon scalar field theories. The bounce is preceded by an ekpyrotic contracting phase which prevents the growth of anisotropies in the approach to the bounce, and allows for the generation of scale-invariant density perturbations that carry over into the expanding phase of the universe. We present the conditions required for the bounce to be free of ghost excitations, as well as the tunings that are necessary in order for the model to be in agreement with cosmological observations. All of these conditions can be met. Our model thus provides a proof-of-principle that non-singular bounces are viable in supergravity, despite the fact that during the bounce the null energy condition is violated.
Individual Biases, Cultural Evolution, and the Statistical Nature of Language Universals: The Case of Colour Naming Systems

Language universals have long been attributed to an innate Universal Grammar. An alternative explanation states that linguistic universals emerged independently in every language in response to shared cognitive or perceptual biases. A computational model has recently shown how this could be the case, focusing on the paradigmatic example of the universal properties of colour naming patterns, and producing results in quantitative agreement with the experimental data. Here we investigate the role of an individual perceptual bias in the framework of the model. We study how, and to what extent, the structure of the bias influences the corresponding linguistic universal patterns. We show that the cultural history of a group of speakers introduces population-specific constraints that act against the pressure for uniformity arising from the individual bias, and we clarify the interplay between these two forces.
Sticky Continuous Processes have Consistent Price Systems

Under proportional transaction costs, a price process is said to have a consistent price system, if there is a semimartingale with an equivalent martingale measure that evolves within the bid-ask spread. We show that a continuous, multi-asset price process has a consistent price system, under arbitrarily small proportional transaction costs, if it satisfies a natural multi-dimensional generalization of the stickiness condition introduced by Guasoni , 569-582 (2006)].
The Unreasonable Fundamental Incertitudes Behind Bitcoin Mining

Bitcoin is a "crypto currency", a decentralized electronic payment scheme based on cryptography which has recently gained excessive popularity. Scientific research on bitcoin is less abundant. A paper at Financial Cryptography 2012 conference explains that it is a system which "uses no fancy cryptography", and is "by no means perfect". It depends on a well-known cryptographic standard SHA-256. In this paper we revisit the cryptographic process which allows one to make money by producing bitcoins. We reformulate this problem as a Constrained Input Small Output (CISO) hashing problem and reduce the problem to a pure block cipher problem. We estimate the speed of this process and we show that the cost of this process is less than it seems and it depends on a certain cryptographic constant which we estimated to be at most 1.86. These optimizations enable bitcoin miners to save tens of millions of dollars per year in electricity bills. Miners who set up mining operations face many economic incertitudes such as high volatility. In this paper we point out that there are fundamental incertitudes which depend very strongly on the bitcoin specification. The energy efficiency of bitcoin miners have already been improved by a factor of about 10,000, and we claim that further improvements are inevitable. Better technology is bound to be invented, would it be quantum miners. More importantly, the specification is likely to change. A major change have been proposed in May 2013 at Bitcoin conference in San Diego by Dan Kaminsky. However, any sort of change could be flatly rejected by the community which have heavily invested in mining with the current technology. Another question is the reward halving scheme in bitcoin. The current bitcoin specification mandates a strong 4-year cyclic property. We find this property totally unreasonable and harmful and explain why and how it needs to be changed.
Template banks for binary black hole searches with numerical relativity waveforms

Gravitational waves from coalescing stellar-mass black hole binaries (BBHs) are expected to be detected by the Advanced Laser Interferometer gravitational-wave observatory and Advanced Virgo. Detection searches operate by matched filtering the detector data using a bank of waveform templates. Traditionally, template banks for BBHs are constructed from intermediary analytical waveform models which are calibrated against numerical relativity simulations and which can be evaluated for any choice of BBH parameters. This paper explores an alternative to the traditional approach, namely, the construction of template banks directly from numerical BBH simulations. Using nonspinning BBH systems as an example, we demonstrate which regions of the mass-parameter plane can be covered with existing numerical BBH waveforms. We estimate the required number and required length of BBH simulations to cover the entire nonspinning BBH parameter plane up to mass ratio 10, thus illustrating that our approach can be used to guide parameter placement of future numerical simulations. We derive error bounds which are independent of analytical waveform models; therefore, our formalism can be used to independently test the accuracy of such waveform models. The resulting template banks are suitable for advanced LIGO searches.
The Blue Box White Paper

This white paper is an explanation of Ben and Dave's TARDIS time machine, written for laypeople who are interested in time travel, but have no technical knowledge of Einstein's Theory of General Relativity. 
The first part of this paper is an introduction to the pertinent ideas from Einstein's theory of curved spacetime, followed by a review of other popular time machine spacetimes. We begin with an introduction to curvature and lightcones. We then explain the Alcubierre Warp Drive, the Morris-Thorne wormhole, and the Tipler cylinder. 
We then describe the Traversable Achronal Retrograde Domain in Spacetime (TARDIS), and explain some of its general properties. Our TARDIS is a bubble of spacetime curvature which travels along a closed loop in space and time. A person travelling within the bubble will feel a constant acceleration. A person outside of the TARDIS will see two bubbles: one which is evolving forwards in time, and one which is evolving backwards in time. We then discuss the physical limitations which may prevent us from ever constructing a TARDIS. 
Finally, we discuss the method through which a TARDIS can be used to travel between arbitrary points in space and time, and the possible dangers involved with exiting a TARDIS from the wrong side. 
Before we begin, would you like a Jelly Baby?
Traversable Achronal Retrograde Domains In Spacetime

There are many spacetime geometries in general relativity which contain closed timelike curves. A layperson might say that retrograde time travel is possible in such spacetimes. To date no one has discovered a spacetime geometry which emulates what a layperson would describe as a time machine. 
The purpose of this paper is to propose such a space-time geometry. In our geometry, a bubble of curvature travels along a closed trajectory. The inside of the bubble is Rindler spacetime, and the exterior is Minkowski spacetime. Accelerating observers inside of the bubble travel along closed timelike curves. The walls of the bubble are generated with matter which violates the classical energy conditions. We refer to such a bubble as a Traversable Achronal Retrograde Domain In Spacetime.
Necessary and Sufficient Conditions for Novel Word Detection in Separable Topic Models

The simplicial condition and other stronger conditions that imply it have recently played a central role in developing polynomial time algorithms with provable asymptotic consistency and sample complexity guarantees for topic estimation in separable topic models. Of these algorithms, those that rely solely on the simplicial condition are impractical while the practical ones need stronger conditions. In this paper, we demonstrate, for the first time, that the simplicial condition is a fundamental, algorithm-independent, information-theoretic necessary condition for consistent separable topic estimation. Furthermore, under solely the simplicial condition, we present a practical quadratic-complexity algorithm based on random projections which consistently detects all novel words of all topics using only up to second-order empirical word moments. This algorithm is amenable to distributed implementation making it attractive for 'big-data' scenarios involving a network of large distributed databases.
Transitive Reduction of Citation Networks

Citation networks form directed acyclic graphs. The transitive reduction of such a DAG removes all edges in the graph that are implied by transitivity, but retains the causal structure of the original network. We investigate how the degree distribution, clustering coecients and relationship between time of publication and degree (representing citation count) are changed under transitive reduction. We show that models which accurately reproduce the degree distribution of a citation network before transitive reduction may not do so afterwards and hence suggest that these models fail to accurately capture the causal structure of the network. We also investigate how the citation count of individual papers is changed and suggest that information about the types of citations a paper receives can be inferred from the number of citations which are retained after transitive reduction. These methods are tested on citation networks from the hep-th and hep-ph sections of the arXiv repository, and all data has been made publicly available . As the number of papers published in scientic
Dimensions, Structures and Security of Networks

One of the main issues in modern network science is the phenomenon of cascading failures of a small number of attacks. Here we define the dimension of a network to be the maximal number of functions or features of nodes of the network. It was shown that there exist linear networks which are provably secure, where a network is linear, if it has dimension one, that the high dimensions of networks are the mechanisms of overlapping communities, that overlapping communities are obstacles for network security, and that there exists an algorithm to reduce high dimensional networks to low dimensional ones which simultaneously preserves all the network properties and significantly amplifies security of networks. Our results explore that dimension is a fundamental measure of networks, that there exist linear networks which are provably secure, that high dimensional networks are insecure, and that security of networks can be amplified by reducing dimensions.
Community Structures Are Definable in Networks, and Universal in Real World

Community detecting is one of the main approaches to understanding networks \cite{For2010}. 
However it has been a longstanding challenge to give a definition for community structures of networks. Here we found that community structures are definable in networks, and are universal in real world. We proposed the notions of entropy- and conductance-community structure ratios. It was shown that the definitions of the modularity proposed in \cite{NG2004}, and our entropy- and conductance-community structures are equivalent in defining community structures of networks, that randomness in the ER model \cite{ER1960} and preferential attachment in the PA \cite{Bar1999} model are not mechanisms of community structures of networks, and that the existence of community structures is a universal phenomenon in real networks. Our results demonstrate that community structure is a universal phenomenon in the real world that is definable, solving the challenge of definition of community structures in networks. This progress provides a foundation for a structural theory of networks.
Homophyly Networks - A Structural Theory of Networks

A grand challenge in network science is apparently the missing of a structural theory of networks. The authors have showed that the existence of community structures is a universal phenomenon in real networks, and that neither randomness nor preferential attachment is a mechanism of community structures of network \footnote{A. Li, J. Li, and Y. Pan, Community structures are definable in networks, and universal in the real world, To appear.}. This poses a fundamental question: What are the mechanisms of community structures of real networks? Here we found that homophyly is the mechanism of community structures and a structural theory of networks. We proposed a homophyly model. It was shown that networks of our model satisfy a series of new topological, probabilistic and combinatorial principles, including a fundamental principle, a community structure principle, a degree priority principle, a widths principle, an inclusion and infection principle, a king node principle, and a predicting principle etc, leading to a structural theory of networks. Our model demonstrates that homophyly is the underlying mechanism of community structures of networks, that nodes of the same community share common features, that power law and small world property are never obstacles of the existence of community structures in networks, and that community structures are definable in networks.
Poincar\'e gauge theory in 3D: canonical stability of the scalar sector

We outline the results of the canonical analysis of the three-dimensional Poincar\'e gauge theory, defined by the general parity-invariant Lagrangian with eight free parameters [11]. In the scalar sector, containing scalar or pseudoscalar (A)dS modes, the stability of the canonical structure under linearization is used to identify dynamically acceptable values of the parameters.
Introduction to Black Hole Evaporation

These lecture notes are an elementary and pedagogical introduction to the black hole evaporation, based on a lecture given by the author at the Ninth Modave Summer School in Mathematical Physics and are intended for PhD students. First, quantum field theory in curved spacetime is studied and tools needed for the remaining of the course are introduced. Then, quantum field theory in Rindler spacetime in 1+1 dimensions and in the spacetime of a spherically collapsing star are considered, leading to Unruh and Hawking effects, respectively. Finally, some consequences such as thermodynamics of black holes and information loss paradox are discussed.
Many-flavor Schwinger model at finite chemical potential

We study thermodynamic properties of the Schwinger model on a torus with f flavors of massless fermions and flavor-dependent chemical potentials. Generalizing the two-flavor case, we present a representation of the partition function in the form of a multidimensional theta function and show that the model exhibits a rich phase structure at zero temperature. The different phases, characterized by certain values of the particle numbers, are separated by first-order phase transitions. We work out the phase structure in detail for three and four fermion flavors and conjecture, based on an exploratory investigation of the five, six, and eight flavor case, that the maximal number of coexisting phases at zero temperature grows exponentially with increasing f.
Love can be Tough to Measure

The waveform phase for a neutron star binary can be split into point-particle terms and finite-size terms (characterized by the Love number) that account for equation of state effects. The latter first enter at 5 post-Newtonian (PN) order (i.e. proportional to the tenth power of the orbital velocity), but the former are only known completely to 3.5 PN order, with higher order terms only known to leading-order in the mass-ratio. We here find that not including point-particle terms at 4PN order to leadingand first-order in the mass ratio in the template model can severely deteriorate our ability to measure the equation of state. This problem can be solved if one uses numerical waveforms once their own systematic errors are under control.
Bioinformatics Knowledge Transmission (training, learning, and teaching): overview and flexible comparison of computer based training approaches

The merger of computer science, mathematics, and life sciences has brought about the discipline known as bioinformatics. However, the transmission (e.g. training, learning, and teaching) of this knowledge becomes an important issue. Many tools have been developed to help the bioinformatics community with that transmission challenge. When selecting the best of these tools, called here BKTMS (Bioinformatics Knowledge Transmission Management Systems), there may be confusion. What makes a good BKTMS? How can we make this choice efficiently? These questions remain unanswered for many users (e.g. learner, teacher and student, trainer and trainee, administrator). This paper provides a critical review of 32 existing BKTMS and a flexible comparison. This review and evaluation will be used to gain insight into the tools, systems, and capabilities that will be added to or excluded from a new proposed model for the next generation of BKTMS, involving multidisciplinary, web semantic tools (e.g. web services, workflow) and standards like LOM, or SCORM.
Density-Based and Transport-Based Core-Periphery Structures in Networks

Networks often possess mesoscale structures, and studying them can yield insights into both structure and function. It is most common to study community structure, but numerous other types of mesoscale structures also exist. In this paper, we examine core-periphery structures based on both density and transport. In such structures, core network components are well-connected both among themselves and to peripheral components, which are not well-connected to anything. We examine core-periphery structures in a wide range of examples of transportation, social, and financial networks-including road networks in large urban areas, a rabbit warren, a dolphin social network, a European interbank network, and a migration network between counties in the United States. We illustrate that a recently developed transport-based notion of node coreness is very useful for characterizing transportation networks. We also generalize this notion to examine core versus peripheral edges, and we show that the resulting diagnostic is also useful for transportation networks. To examine the properties of transportation networks further, we develop a family of generative models of roadlike networks. We illustrate the effect of the dimensionality of the embedding space on transportation networks, and we demonstrate that the correlations between different measures of coreness can be very different for different types of networks.
Provable Security of Networks

We propose a definition of {\it security} and a definition of {\it robustness} of networks against the cascading failure models of deliberate attacks and random errors respectively, and investigate the principles of the security and robustness of networks. We propose a {\it security model} such that networks constructed by the model are provably secure against any attacks of small sizes under the cascading failure models, and simultaneously follow a power law, and have the small world property with a navigating algorithm of time complex $O(\log n)$. It is shown that for any network $G$ constructed from the security model, $G$ satisfies some remarkable topological properties, including: (i) the {\it small community phenomenon}, that is, $G$ is rich in communities of the form $X$ of size poly logarithmic in $\log n$ with conductance bounded by $O(\frac{1}{|X|^{\beta}})$ for some constant $\beta$, (ii) small diameter property, with diameter $O(\log n)$ allowing a navigation by a $O(\log n)$ time algorithm to find a path for arbitrarily given two nodes, and (iii) power law distribution, and satisfies some probabilistic and combinatorial principles, including the {\it degree priority theorem}, and {\it infection-inclusion theorem}. By using these principles, we show that a network $G$ constructed from the security model is secure for any attacks of small scales under both the uniform threshold and random threshold cascading failure models. Our security theorems show that networks constructed from the security model are provably secure against any attacks of small sizes, for which natural selections of {\it homophyly, randomness} and {\it preferential attachment} are the underlying mechanisms.
Higgs boson decays to γ and invisible particles in the standard model

Using the Higgs boson mass $m_h=125$ GeV, the radiative Higgs decays $h\rightarrow\gamma \nu_l\bar\nu_l$ with $\nu_l = \nu_e,\,\nu_\mu$ and $\nu_\tau$ are analyzed in the standard model. Our calculation shows that the inclusive width of these processes, i.e., the sum of $\Gamma(h\to\gamma\nu_l\bar\nu_l)$ for ${\nu_l=\nu_e,\nu_\mu,\nu_\tau}$, is $1.41$ keV, which is about $15\%$ of $\Gamma(h\to\gamma\gamma)$. Therefore, the observation of these channels in the future precise experiments may provide us some useful information on the Higgs physics both in the standard model and in its possible extensions.