nils-herrmann/clean_scirepeval huggingface dataset:
Cyclic and coherent states in flocks with topological distance

A simple model of the two dimensional collective motion of a group of mobile agents have been studied. Like birds, these agents travel in open free space where each of them interacts with the first $n$ neighbors determined by the topological distance with a free boundary condition. Using the same prescription for interactions used in the Vicsek model with scalar noise it has been observed that the flock, in absence of the noise, arrives at a number of interesting stationary states. In the `single sink state' the entire flock maintains perfect cohesion and coherence. In the `cyclic state' every agent executes a uniform circular motion, and the entire flock executes a pulsating dynamics i.e., expands and contracts periodically between a minimum and a maximum size of the flock. When refreshing rate of the interaction zone is the fastest, the entire flock gets fragmented into smaller clusters of different sizes. On introduction of scalar noise a crossover is observed when the agents cross over from a ballistic motion to a diffusive motion. Expectedly the crossover time is dependent on the strength of the noise $\eta$ and diverges as $\eta \to 0$. In simpler version the translational degrees of freedom of the agents are suppressed but their angular motion are retained. Here agents are the spins, placed at the sites of a square lattice with periodic boundary condition. Every spin interacts with its $n$ = 2, 3 or 4 nearest neighbors. In the stationary state the entire spin pattern moves as a whole when interactions are anisotropic with $n$ = 2 and 3; but it is completely frozen when the interaction is isotropic with $n=4$. These spin configurations have vortex-antivortex pairs whose density increases as the noise $\eta$ increases and follows an excellent finite-size scaling analysis.
Perturbative stability of the approximate Killing field eigenvalue problem

An approximate Killing field may be defined on a compact, Riemannian geometry by solving an eigenvalue problem for a certain elliptic operator. This paper studies the effect of small perturbations in the Riemannian metric on the resulting vector field. It shows that small metric perturbations, as measured using a Sobolev-type supremum norm on the space of Riemannian geometries on a fixed manifold, yield small perturbations in the approximate Killing field, as measured using a Hilbert-type square integral norm. It also discusses applications to the problem of computing the spin of a generic black hole in general relativity.
Adiabatic theorems with and without spectral gap condition for non-semisimple spectral values

We establish adiabatic theorems with and without spectral gap condition for general operators $A(t): D(A(t)) \subset X \to X$ with possibly time-dependent domains in a Banach space $X$. We first prove adiabatic theorems with uniform and non-uniform spectral gap condition (including a slightly extended adiabatic theorem of higher order). In these adiabatic theorems the considered spectral subsets $\sigma(t)$ have only to be compact -- in particular, they need not consist of eigenvalues. We then prove an adiabatic theorem without spectral gap condition for not necessarily (weakly) semisimple eigenvalues: in essence, it is only required there that the considered spectral subsets $\sigma(t) = \{ \lambda(t) \}$ consist of eigenvalues $\lambda(t) \in \partial \sigma(A(t))$ and that there exist projections $P(t)$ reducing $A(t)$ such that $A(t)|_{P(t)D(A(t))}-\lambda(t)$ is nilpotent and $A(t)|_{(1-P(t))D(A(t))}-\lambda(t)$ is injective with dense range in $(1-P(t))X$ for almost every~$t$. In all these theorems, the regularity conditions imposed on $t \mapsto A(t)$, $\sigma(t)$, $P(t)$ are fairly mild. We explore the strength of the presented adiabatic theorems in numerous examples. And finally, we apply the adiabatic theorems for time-dependent domains to obtain -- in a very simple way -- adiabatic theorems for operators $A(t)$ defined by symmetric sesquilinear forms.
Higher-order symmetry energy of nuclear matter and the inner edge of neutron star crusts

The parabolic approximation to the equation of state of the isospin asymmetric nuclear matter (ANM) is widely used in the literature to make predictions for the nuclear structure and the neutron star properties. Based on the realistic M3Y-Paris and M3Y-Reid nucleon-nucleon interactions, we investigate the effects of the higher-order symmetry energy on the proton fraction in neutron stars and the location of the inner edge of their crusts and their core-crust transition density and pressure, thermodynamically. Analytical expressions for different-order symmetry energy coefficients of ANM are derived using the realistic interactions mentioned above. It is found that the higher-order terms of the symmetry energy coefficients up to its eighth-order (E$_{sym8}$) contributes substantially to the proton fraction in $\beta$ stable neutron star matter at different nuclear matter densities, the core-crust transition density and pressure. Even by considering the symmetry energy coefficients up to E$_{sym8}$, we obtain a significant change of about 40$\%$ in the transition pressure value from the one based on the exact equation of state. Using equations of state based on both Paris and Reid effective interactions which provide saturation incompressibility of symmetric nuclear matter in the range of 220 MeV$\leq$K$_0$$\leq$270 MeV, we estimate the ranges 0.090 fm$^{-3}$$\leq$$\rho_t$$\leq$0.095 fm$^{-3}$ and 0.49 MeV fm$^{-3}$$\leq$P$_t$$\leq$ 0.59 MeV fm$^{-3}$ for the liquid core-solid crust transition density and pressure, respectively. The corresponding range of the proton fraction at this transition density range is found to be 0.029$\leq$x$_{p(t)}$$\leq$0.032.
A DDoS-Aware IDS Model Based on Danger Theory and Mobile Agents

Most of the security problems in large and distributed information systems are vastly complex. Few research on detection of burgeoning Distributed Denial of Service (DDoS) attacks, leads us to expand our perspectives to a comprehensive architectural approach in which particular issues like arrangement and communication of system components appear. In this paper, many useful ideas from the behaviour of biological immune systems are elicited based on the results of the latest immunological researches, especially Danger Theory. They are applied to create a model for immunization of distributed intrusion detection systems (IDSs) that are resistant to DDoS. Although a general model for various IDSs is proposed and implemented in this research, a particular simulation scenario for detecting DDoS in a wireless sensor network (WSN) is planned as an example to assess the general ability of the proposed model in detecting undesirable events.
PSO-MISMO Modeling Strategy for MultiStep-Ahead Time Series Prediction

Multistep-ahead time series prediction is one of the most challenging research topics in the field of time series modeling and prediction, and is continually under research. Recently, the multiple-input several multiple-outputs (MISMO) modeling strategy has been proposed as a promising alternative for multistep-ahead time series prediction, exhibiting advantages compared with the two currently dominating strategies, the iterated and the direct strategies. Built on the established MISMO strategy, this paper proposes a particle swarm optimization (PSO)-based MISMO modeling strategy, which is capable of determining the number of sub-models in a self-adaptive mode, with varying prediction horizons. Rather than deriving crisp divides with equal-size s prediction horizons from the established MISMO, the proposed PSO-MISMO strategy, implemented with neural networks, employs a heuristic to create flexible divides with varying sizes of prediction horizons and to generate corresponding sub-models, providing considerable flexibility in model construction, which has been validated with simulated and real datasets.
Twin paradox with macroscopic clocks in superconducting circuits

We propose an implementation of a twin-paradox scenario in superconducting circuits, with velocities as large as a few percent of the speed of light. Ultrafast modulation of the boundary conditions for the electromagnetic field in a microwave cavity simulates a clock moving at relativistic speeds. Since our cavity has a finite length, the setup allows us to investigate the role of clock size as well as interesting quantum effects on time dilation. In particular, our theoretical results show that the time dilation increases for larger cavity lengths and is shifted due to quantum particle creation.
Urban mobility scaling: Lessons from ‘little data’

Recent mobility scaling research, using new data sources, often relies on aggregated data alone. Hence, these studies face difficulties characterizing the influence of factors such as transportation mode on mobility patterns. This paper attempts to complement this research by looking at a category-rich mobility data set. In order to shed light on the impact of categories, as a case study, we use conventionally collected German mobility data. In contrast to `check-in'-based data, our results are not biased by Euclidean distance approximations. In our analysis, we show that aggregation can hide crucial differences between trip length distributions, when subdivided by categories. For example, we see that on an urban scale (0 to ~ 15 km), walking, versus driving, exhibits a highly different scaling exponent, thus universality class. Moreover, mode share and trip length are responsive to day-of-week and time-of-day. For example, in Germany, although driving is relatively less frequent on Sundays than on Wednesdays, trips seem to be longer. In addition, our work may shed new light on the debate between distance-based and intervening-opportunity mechanisms affecting mobility patterns, since mode may be chosen both according to trip length and urban form.
Random Sparse Graphs with a Given Degree Sequence

Let $\mathbb{G}^{D}$ be the set of graphs $G(V,\, E)$ with $\left|V\right|=n$, and the degree sequence equal to $D=(d_{1},\, d_{2},\,\dots,\, d_{n})$. In addition, for $\frac{1}{2}<a<1$, we define the set of graphs with an almost given degree sequence $D$ as follows, \[ \mathbb{G}_{a}^{D}:=\cup\,\mathbb{G}^{\bar{D}}, \] where the union is over all degree sequences $\bar{D}$ such that, for $1\leq i\leq n$, we have $\left|d_{i}-\bar{d}_{i}\right|<d_{i}^{a}$. 
Now, if we chose random graphs $\mathcal{G}_{\mathbf{g}}\left(D\right)$ and $\mathcal{G}_{\mathbf{a}}\left(D\right)$ uniformly out of the sets $\mathbb{G}^{D}$ and $\mathbb{G}_{a}^{D}$, respectively, what do they look like? This has been studied when $\mathcal{G}_{\mathbf{g}}\left(D\right)$ is a dense graph, i.e. $\left|E\right|=\Theta(n^{2})$, in the sense of graphons, or when $\mathcal{G}_{\mathbf{g}}\left(D\right)$ is very sparse, i.e. $d_{n}^{2}=o(\left|E\right|)$. In the case of sparse graphs with an almost given degree sequence, we investigate this question, and give the finite tree subgraph structure of $\mathcal{G}_{\mathbf{a}}\left(D\right)$ under some mild conditions. For the random graph $\mathcal{G}_{\mathbf{g}}\left(D\right)$ with a given degree sequence, we re-derive the finite tree structure in dense and very sparse cases to give a continuous picture. 
Moreover, for a pair of vectors $\left(D_{1},D_{2}\right)\in\mathbb{Z}^{n_{1}}\times\mathbb{Z}^{n_{2}}$, we let $\mathcal{G}_{\mathbf{b}}\left(D_{1},D_{2}\right)$ be the random bipartite graph that is chosen uniformly out of the set $\mathbb{G}^{D_{1},D_{2}}$, where $\mathbb{G}^{D_{1},D_{2}}$ is the set of all bipartite graphs with the degree sequence $\left(D_{1},D_{2}\right)$. We are able to show the result for $\mathcal{G}_{\mathbf{b}}\left(D_{1},D_{2}\right)$ without any further conditions.
Learning without Concentration

We obtain sharp bounds on the estimation error of the Empirical Risk Minimization procedure, performed in a convex class and with respect to the squared loss, without assuming that class members and the target are bounded functions or have rapidly decaying tails. Rather than resorting to a concentration-based argument, the method used here relies on a “small-ball” assumption and thus holds for classes consisting of heavy-tailed functions and for heavy-tailed targets. The resulting estimates scale correctly with the “noise level” of the problem, and when applied to the classical, bounded scenario, always improve the known bounds.
Effect of Memory on the Dynamics of Random Walks on Networks

Pathways of diffusion observed in real-world systems often require stochastic processes going beyond first-order Markov models, as implicitly assumed in network theory. In this work, we focus on second-order Markov models, and derive an analytical expression for the effect of memory on the spectral gap and thus, equivalently, on the characteristic time needed for the stochastic process to asymptotically reach equilibrium. Perturbation analysis shows that standard first-order Markov models can either overestimate or underestimate the diffusion rate of flows across the modular structure of a system captured by a second-order Markov network. We test the theoretical predictions on a toy example and on numerical data, and discuss their implications for network theory, in particular in the case of temporal or multiplex networks.
Chaff from the wheat: characterization and modeling of deleted questions on stack overflow

Stack Overflow is the most popular Community based Question Answering (CQA) website for programmers on the web with 2.05M users, 5.1M questions and 9.4M answers. Stack Overflow has explicit, detailed guidelines on how to post questions and an ebullient moderation community. Despite these precise communications and safeguards, questions posted on Stack Overflow can be extremely off topic or very poor in quality. Such questions can be deleted from Stack Overflow at the discretion of experienced community members and moderators. We present the first study of deleted questions on Stack Overflow. We divide our study into two parts - (i) Characterization of deleted questions over ~5 years (2008-2013) of data, (ii) Prediction of deletion at the time of question creation. Our characterization study reveals multiple insights on question deletion phenomena. We find that it takes substantial time to vote a question to be deleted but once voted, the community takes swift action. We also see that question authors delete their questions to salvage reputation points. We notice some instances of accidental deletion of good quality questions but such questions are voted back to be undeleted quickly. We discover a pyramidal structure of question quality on Stack Overflow and find that deleted questions lie at the bottom (lowest quality) of the pyramid. We also build a predictive model to detect the deletion of question at the creation time. We experiment with 47 features -- based on User Profile, Community Generated, Question Content and Syntactic style -- and report an accuracy of 66%. Our findings reveal important suggestions for content quality maintenance on community based question answering websites. To the best of our knowledge, this is the first large scale study on poor quality (deleted) questions on Stack Overflow.
Similarity of ionized gas nebulae around unobscured and obscured quasars

Quasar feedback is suspected to play a key role in the evolution of massive galaxies, by removing or reheating gas in quasar host galaxies and thus limiting the amount of star formation. In this paper we continue our investigation of quasar-driven winds on galaxy-wide scales. We conduct Gemini Integral Field Unit spectroscopy of a sample of luminous unobscured (type 1) quasars, to determine the morphology and kinematics of ionized gas around these objects, predominantly via observations of the [O III]5007 emission line. We find that ionized gas nebulae extend out to ~13 kpc from the quasar, that they are smooth and round, and that their kinematics are inconsistent with gas in dynamical equilibrium with the host galaxy. The observed morphological and kinematic properties are strikingly similar to those of ionized gas around obscured (type 2) quasars with matched [O III] luminosity, with marginal evidence that nebulae around unobscured quasars are slightly more compact. Therefore in samples of obscured and unobscured quasars carefully matched in [O III] luminosity we find support for the standard geometry-based unification model of active galactic nuclei, in that the intrinsic properties of quasars, of their hosts and of their ionized gas appear to be very similar. Given the apparent ubiquity of extended ionized regions, we are forced to conclude that either the quasar is at least partially illuminating pre-existing gas or that both samples of quasars are seen during advanced stages of quasar feedback. In the latter case, we may be biased by our [O III]-based selection against quasars in the early "blow-out" phase, for example due to dust obscuration.
Relativistic spinor equation of photon

In this paper, we have proposed the spiron equation of free and non-free photon, and give the spin operator and spin wave function of photon. We calculate the helicity of photon and prove there are left-handed and right-handed photon. By the spiron equation of non-free photon, we can study the quantum property of photon in medium, which can be used in quantum optics, photonic crystals and so on.
The statistical dynamics of a spatial logistic model and the related kinetic equation

There is studied an infinite system of point entities in $\mathbb{R}^d$ which reproduce themselves and die, also due to competition. The system's states are probability measures on the space of configurations of entities. Their evolution is described by means of a BBGKY-type equation for the corresponding correlation (moment) functions. It is proved that: (a) these functions evolve on a bounded time interval and remain sub-Poissonian due to the competition; (b) in the Vlasov scaling limit they converge to the correlation functions of the time-dependent Poisson point field the density of which solves the kinetic equation obtained in the scaling limit from the equation for the correlation functions. A number of properties of the solutions of the kinetic equation are also established.
More Algorithms for Provable Dictionary Learning

In dictionary learning, also known as sparse coding, the algorithm is given samples of the form $y = Ax$ where $x\in \mathbb{R}^m$ is an unknown random sparse vector and $A$ is an unknown dictionary matrix in $\mathbb{R}^{n\times m}$ (usually $m > n$, which is the overcomplete case). The goal is to learn $A$ and $x$. This problem has been studied in neuroscience, machine learning, visions, and image processing. In practice it is solved by heuristic algorithms and provable algorithms seemed hard to find. Recently, provable algorithms were found that work if the unknown feature vector $x$ is $\sqrt{n}$-sparse or even sparser. Spielman et al. \cite{DBLP:journals/jmlr/SpielmanWW12} did this for dictionaries where $m=n$; Arora et al. \cite{AGM} gave an algorithm for overcomplete ($m >n$) and incoherent matrices $A$; and Agarwal et al. \cite{DBLP:journals/corr/AgarwalAN13} handled a similar case but with weaker guarantees. 
This raised the problem of designing provable algorithms that allow sparsity $\gg \sqrt{n}$ in the hidden vector $x$. The current paper designs algorithms that allow sparsity up to $n/poly(\log n)$. It works for a class of matrices where features are individually recoverable, a new notion identified in this paper that may motivate further work. 
The algorithm runs in quasipolynomial time because they use limited enumeration.
Of course we share! Testing Assumptions about Social Tagging Systems

Social tagging systems have established themselves as an important part in today's web and have attracted the interest from our research community in a variety of investigations. The overall vision of our community is that simply through interactions with the system, i.e., through tagging and sharing of resources, users would contribute to building useful semantic structures as well as resource indexes using uncontrolled vocabulary not only due to the easy-to-use mechanics. Henceforth, a variety of assumptions about social tagging systems have emerged, yet testing them has been difficult due to the absence of suitable data. In this work we thoroughly investigate three available assumptions - e.g., is a tagging system really social? - by examining live log data gathered from the real-world public social tagging system BibSonomy. Our empirical results indicate that while some of these assumptions hold to a certain extent, other assumptions need to be reflected and viewed in a very critical light. Our observations have implications for the design of future search and other algorithms to better reflect the actual user behavior.
Critical Nodes In Directed Networks

Critical nodes or "middlemen" have an essential place in both social and economic networks when considering the flow of information and trade. This paper extends the concept of critical nodes to directed networks. We identify strong and weak middlemen. Node contestability is introduced as a form of competition in networks; a duality between uncontested intermediaries and middlemen is established. The brokerage power of middlemen is formally expressed and a general algorithm is constructed to measure the brokerage power of each node from the networks adjacency matrix. Augmentations of the brokerage power measure are discussed to encapsulate relevant centrality measures. We use these concepts to identify and measure middlemen in two empirical socio-economic networks, the elite marriage network of Renaissance Florence and Krackhardt's advice network.
Disorder-tuned selection of order in bilayer graphene

The nature of the interaction-driven spontaneously broken-symmetry state in charge-neutral bilayer graphene (BLG) has attracted a lot of interest. Theoretical studies predict various ordered states as the candidates for the ground state of BLG in the absence of external fields. Several experiments have been performed by different groups to identify the nature of the collective ground state in BLG. However, so far, there is no consensus: some experiments show evidence that suggests the establishment of a nematic gapless state, while others present results that are more consistent with the establishment of a fully gapped state. Moreover, even among the experiments that appear to see a bulk gap, some of the samples are found to be conducting (suggesting the existence of gapless edge states), while others are insulating. Here we explore the hypothesis that disorder might explain the discrepancy between experiments. We find that the pair-breaking effect due to nonmagnetic short-range disorder varies among the candidate ground states, giving rise to different amounts of suppression of their mean-field transition temperatures. Our results indicate that BLG can undergo a transition between different ordered states as a function of the disorder strength, providing a possible scenario to resolve the discrepancy between experimental observations.