nils-herrmann/clean_scirepeval huggingface dataset:
Stacking of SKA data: comparing uv-plane and image-plane stacking

Stacking as a tool for studying objects that are not individually detected is becoming popular even for radio interferometric data, and will be widely used in the SKA era. Stacking is typically done using imaged data rather than directly using the visibilities (the uv-data). We have investigated and developed a novel algorithm to do stacking using the uv-data. We have performed exten- sive simulations comparing to image-stacking, and summarize the results of these simulations. Furthermore, we disuss the implications in light of the vast data volume produced by the SKA. Having access to the uv-stacked data provides a great advantage, as it allows the possibility to properly analyse the result with respect to calibration artifacts as well as source properties such as size. For SKA the main challenge lies in archiving the uv-data. For purposes of robust stacking analysis, it would be strongly desirable to either keep the calibrated uv-data at least in an aver- age form, or implement a stacking queue where stacking positions could be provided prior to the observations and the uv-stacking is done almost in real time.
SPIRAL INSTABILITY CAN DRIVE THERMONUCLEAR EXPLOSIONS IN BINARY WHITE DWARF MERGERS

Thermonuclear, or Type Ia supernovae (SNe Ia), originate from the explosion of carbon–oxygen white dwarfs, and serve as standardizable cosmological candles. However, despite their importance, the nature of the progenitor systems that give rise to SNe Ia has not been hitherto elucidated. Observational evidence favors the double-degenerate channel in which merging white dwarf binaries lead to SNe Ia. Furthermore, significant discrepancies exist between observations and theory, and to date, there has been no self-consistent merger model that yields a SNe Ia. Here we show that a spiral mode instability in the accretion disk formed during a binary white dwarf merger leads to a detonation on a dynamical timescale. This mechanism sheds light on how white dwarf mergers may frequently yield SNe Ia.
Gamma-ray lines from SN2014J

On 21 January 2014, SN2014J was discovered in M82 and found to be the closest type Ia supernova (SN Ia) in the last four decades. INTEGRAL observed SN2014J from the end of January until late June for a total exposure time of about 7 Ms. SNe Ia light curves are understood to be powered by the radioactive decay of iron peak elements of which 56Ni is dominantly synthesized during the thermonuclear disruption of a CO white dwarf (WD). The measurement of γ-ray lines from the decay chain 56Ni→56Co→56Fe provides unique information about the explosion in supernovae. Canonical models assume 56Ni buried deeply in the supernova cloud, absorbing most of the early γ-rays, and only the consecutive decay of 56Co should become directly observable through the overlaying material several weeks after the explosion when the supernova envelope dilutes as it expands. Surprisingly, with the spectrometer on INTEGRAL, SPI, we detected 56Ni γ-ray lines at 158 and 812 keV at early times with flux levels corresponding to roughly 10% of the total expected amount of 56Ni, and at relatively small velocities. This implies some mechanism to create a major amout of 56Ni at the outskirts, and at the same time to break the spherical symmetry of the supernova. One plausible explanation would be a belt accreted from a He companion star, exploding, and triggering the explosion of the white dwarf. The full set of observations of SN2014J show 56Co γ-ray lines at 847 and 1238 keV, and we determine for the first time a SN Ia γ-ray light curve. The irregular appearance of these γ-ray lines allows deeper insights about the explosion morphology from its temporal evolution and provides additional evidence for an asymmetric explosion, from our high-resolution spectroscopy and comparisons with recent models.
Adaptive Scheduling in MCMC and Probabilistic Programming

We introduce an adaptive output-sensitive inference algorithm for MCMC and probabilistic programming, Adaptive Random Database. The algorithm is based on a single-site updating Metropolis-Hasting sampler, the Random Database (RDB) algorithm. Adaptive RDB (ARDB) differs from the original RDB in that the schedule of selecting variables proposed for modification is adapted based on the output of of the probabilistic program, rather than being fixed and uniform. We show that ARDB still converges to the correct distribution. We compare ARDB to RDB on several test problems highlighting different aspects of the adaptation scheme.
Biobjective Nonnegative Matrix Factorization: Linear Versus Kernel-Based Models

Nonnegative matrix factorization (NMF) is a powerful class of feature extraction techniques that has been successfully applied in many fields, particularly in signal and image processing. Current NMF techniques have been limited to a single-objective optimization problem, in either its linear or nonlinear kernel-based formulation. In this paper, we propose to revisit the NMF as a multiobjective problem, particularly a biobjective one, where the objective functions defined in both input and feature spaces are taken into account. By taking the advantage of the sum-weighted method from the literature of multiobjective optimization, the proposed biobjective NMF determines a set of nondominated, Pareto optimal, solutions. Moreover, the corresponding Pareto front is approximated and studied. Experimental results on unmixing synthetic and real hyperspectral images confirm the efficiency of the proposed biobjective NMF compared with the state-of-the-art methods.
Limit Cycles Sparked by Mutation in the Repeated Prisoner's Dilemma

We explore a replicator-mutator model of the repeated Prisoner's Dilemma involving three strategies: always cooperate (ALLC), always defect (ALLD), and tit-for-tat (TFT). The dynamics resulting from single unidirectional mutations are considered, with detailed results presented for the mutations TFT $\rightarrow$ ALLC and ALLD $\rightarrow$ ALLC. For certain combinations of parameters, given by the mutation rate $\mu$ and the complexity cost $c$ of playing tit-for-tat, we find that the population settles into limit cycle oscillations, with the relative abundance of ALLC, ALLD, and TFT cycling periodically. Surprisingly, these oscillations can occur for unidirectional mutations between any two strategies. In each case, the limit cycles are created and destroyed by supercritical Hopf and homoclinic bifurcations, organized by a Bogdanov-Takens bifurcation. Our results suggest that stable oscillations are a robust aspect of a world of ALLC, ALLD, and costly TFT; the existence of cycles does not depend on the details of assumptions of how mutation is implemented.
The ELENA Project at CERN

CERN has a longstanding tradition of pursuing fundamental physics on extreme low and high energy scales. The present physics knowledge is successfully described by the Standard Model and the General Relativity. In the anti-matter regime many predictions of this established theory still remain experimentally unverified and one of the most fundamental open problems in physics concerns the question of asymmetry between particles: why is the observable and visible universe apparently composed almost entirely of matter and not of anti-matter? There is a huge interest in the very compelling scientiic case for anti-hydrogen and low energy anti-proton physics, here to name especially the Workshop on New Opportunities in the Physics Landscape at CERN which was convened in May 2009 by the CERN Directorate and culminated in the decision for the final approval of the construction of the Extra Low ENergy Antiproton (ELENA) ring by the Research Board in June 2011. ELENA is a CERN project aiming to construct a small 30 m circumference synchrotron to further decelerate anti-protons from the Antiproton Decelerator (AD) from 5.3 MeV down to 100 keV.
Optical technologies for observation of low Earth orbit objects

In order to avoid collisions with space debris, the near Earth orbit must be continuously scanned by 
either ground- or spaced-based facilities. For the low Earth orbit, radar telescopes are the workhorse 
for this task, especially due to their continuous availability. However, optical observation methods can 
deliver complementary information, especially towards high accuracy measurements. 
Passive-optical observations are inexpensive and can yield very precise information about the apparent 
position of the object in the sky via comparison with background stars. However, the object's distance 
from the observer is not readily accessible, which constitutes a major drawback of this approach for the 
precise calculation of the orbital elements. 
Two experimental methods have been devised to overcome this problem: Using two observatories a few 
kilometres apart, strictly simultaneous observations of the same object yield an accurate, instantaneous 
3D position determination through measurement of the parallax. If only one observatory is available, 
a pulsed laser can be used in addition to the passive-optical channel to measure the distance to the 
object, in a similar fashion as used by the satellite laser ranging community. However, compared to 
conventional laser ranging, a stronger laser and more elaborate tracking algorithms are necessary. The 
two approaches can also be combined by illuminating the object with a pulsed laser from one observatory 
and measuring the return times at both observatories. 
These techniques are explored by German Aerospace Center in Stuttgart using its orbital debris 
research observatory, in cooperation with the Satellite Laser Ranging station in Graz and the Geode- 
tic Observatory in Wettzell. This contribution will present some of the results and plans for further 
measurement campaigns.
Bayesian Learning for Low-Rank matrix reconstruction

We develop latent variable models for Bayesian learning based low-rank matrix completion and reconstruction from linear measurements. For under-determined systems, the developed methods are shown to reconstruct low-rank matrices when neither the rank nor the noise power is known a-priori. We derive relations between the latent variable models and several low-rank promoting penalty functions. The relations justify the use of Kronecker structured covariance matrices in a Gaussian based prior. In the methods, we use evidence approximation and expectation-maximization to learn the model parameters. The performance of the methods is evaluated through extensive numerical simulations.
Quantum gravitational anomaly as a dark matter

The general properties of a perfect relativistic fluid resulting from the quantum gravitational anomaly are investigated. It is found that, in the limit of a weak gravitational field, this fluid possesses a polytropic equation of state characterized by two universal constants: the polytropic constant and the natural polytropic index. Based on the astrophysical data, the estimates for the polytropic constant are given. It is shown that this fluid can describe a considerable part of the cold dark matter. The quantum theory of such a fluid is constructed in the framework of the background field method. The Ward identities associated with the entropy and vorticity conservation laws are derived. The leading gradient corrections to the pressure of the perfect fluid are found and the restrictions on their form are obtained. These restrictions guarantee, in particular, the absence of ghosts in the model. The second order nonlinear corrections to the equations of motion of a perfect relativistic fluid are analyzed and the explicit expressions for the transverse and longitudinal perturbations induced by a sufficiently strong sound wave are obtained. A dynamical solution to the problem of time in quantum gravity is proposed.
Gravitating non-Abelian cosmic strings

In this paper we study regular cosmic string solutions of the non-Abelian Higgs model coupled with the Einstein gravity. In order to do that, we constructed a set of coupled differential ordinary equation. Because there is no closed solution for this set of equations, we solve it numerically. The solutions that we are interested in asymptote to a flat space-time with a planar angle deficit. This model under consideration present two bosonic sectors, besides the non-Abelian gauge one, coupled minimally with the gravitational fields. The two bosonic sectors may present a direct coupling, which plays an important role on the behavior of the matter and gauge fields and also on the behavior on the geometry of the spacetime. We explicitly analyze the behaviors of the energy density and planar angle deficit as function of the energy scale where the gauge symmetry is spontaneously broken and the coupling interaction between the bosonic sectors.
A benchmark model to assess community structure in evolving networks

Detecting the time evolution of the community structure of networks is crucial to identify major changes in the internal organization of many complex systems, which may undergo important endogenous or exogenous events. This analysis can be done in two ways: considering each snapshot as an independent community detection problem or taking into account the whole evolution of the network. In the first case, one can apply static methods on the temporal snapshots, which correspond to configurations of the system in short time windows, and match afterward the communities across layers. Alternatively, one can develop dedicated dynamic procedures so that multiple snapshots are simultaneously taken into account while detecting communities, which allows us to keep memory of the flow. To check how well a method of any kind could capture the evolution of communities, suitable benchmarks are needed. Here we propose a model for generating simple dynamic benchmark graphs, based on stochastic block models. In them, the time evolution consists of a periodic oscillation of the system's structure between configurations with built-in community structure. We also propose the extension of quality comparison indices to the dynamic scenario.
Arbitrage-Free Pricing of XVA - Part I: Framework and Explicit Examples

We develop a novel framework for computing the total valuation adjustment (XVA) of a European claim accounting for funding costs, counterparty credit risk, and collateralization. Based on no-arbitrage arguments, we derive the nonlinear backward stochastic differential equations (BSDEs) associated with the replicating portfolios of long and short positions in the claim. This leads to the definition of buyer's and seller's XVA which in turn identify a no-arbitrage interval. When borrowing and lending rates coincide we provide a fully explicit expression for the uniquely determined price of XVA, expressed as a percentage of the price of the traded claim, and for the corresponding replication strategies. This extends the result of Piterbarg by incorporating the effect of premature contract termination due to default risk of the trader and of his counterparty.
A New Efficient Method for Calculating Similarity Between Web Services

Web services allow communication between heterogeneous systems in a distributed environment. Their enormous success and their increased use led to the fact that thousands of Web services are present on the Internet. This significant number of Web services which not cease to increase has led to problems of the difficulty in locating and classifying web services, these problems are encountered mainly during the operations of web services discovery and substitution. Traditional ways of search based on keywords are not successful in this context, their results do not support the structure of Web services and they consider in their search only the identifiers of the web service description language (WSDL) interface elements. The methods based on semantics (WSDLS, OWLS, SAWSDL…) which increase the WSDL description of a Web service with a semantic description allow raising partially this problem, but their complexity and difficulty delays their adoption in real cases. Measuring the similarity between the web services interfaces is the most suitable solution for this kind of problems, it will classify available web services so as to know those that best match the searched profile and those that do not match. Thus, the main goal of this work is to study the degree of similarity between any two web services by offering a new method that is more effective than existing works.
Which galaxy mass estimator can we trust

We address the problem that dynamical masses of high-redshift massive galaxies, derived using virial scaling, often come out lower than stellar masses inferred from population fitting to multi-band photometry. We compare dynamical and stellar masses for various samples spanning ranges of mass, compactness and redshift, including the SDSS. The discrepancy between dynamical and stellar masses occurs both at low and high redshifts, and systematically increases with galaxy compactness. Because it is unlikely that stellar masses show systematic errors with galaxy compactness, the correlation of mass discrepancy with compactness points to errors in the dynamical mass estimates which assume homology with massive, nearby ellipticals. We quantify the deviations from homology and propose specific non-virial scaling of dynamical mass with effective radius and velocity dispersion.
THE ENERGY DEPENDENCE OF GRB MINIMUM VARIABILITY TIMESCALES

We constrain the minimum variability timescales for 938 gamma-ray bursts (GRBs) observed by the Fermi/Gamma-ray Burst Monitor instrument prior to 2012 July 11. The tightest constraints on progenitor radii derived from these timescales are obtained from light curves in the hardest energy channel. In the softer bands—or from measurements of the same GRBs in the hard X-rays from Swift—we show that variability timescales tend to be a factor of two to three longer. Applying a survival analysis to account for detections and upper limits, we find median minimum timescale in the rest frame for long-duration and short-duration GRBs of 45 and 10 ms, respectively. Less than 10% of GRBs show evidence for variability on timescales below 2 ms. These shortest timescales require Lorentz factors ≳ 400 ?> and imply typical emission radii R ≈ 1 × 10 14 ?> cm for long-duration GRBs and R ≈ 3 × 10 13 ?> cm for short-duration GRBs. We discuss implications for the GRB fireball model and investigate whether or not GRB minimum timescales evolve with cosmic time.
Determinants of Meme Popularity

Online social media have greatly affected the way in which we communicate with each other. However, little is known about what are the fundamental mechanisms driving dynamical information flow in online social systems. Here, we introduce a generative model for online sharing behavior and analytically show, using techniques from mathematical population genetics, that competition between memes for the limited resource of user attention leads to a type of self-organized criticality, with heavy-tailed distributions of meme popularity: a few memes "go viral" but the majority become only moderately popular. The time-dependent solutions of the model are shown to fit empirical micro-blogging data on hashtag usage, and to predict novel scaling features of the data. The presented framework, in contrast to purely empirical studies or simulation-based models, clearly distinguishes the roles of two distinct factors affecting meme popularity: the memory time of users and the connectivity structure of the social network.
Advances in Human Action Recognition: A Survey

Human action recognition has been an important topic in computer vision due to its many applications such as video surveillance, human machine interaction and video retrieval. One core problem behind these applications is automatically recognizing low-level actions and high-level activities of interest. The former is usually the basis for the latter. This survey gives an overview of the most recent advances in human action recognition during the past several years, following a well-formed taxonomy proposed by a previous survey . From this state-of-the-art survey, researchers can view a panorama of progress in this area for future research.
Inferring and Learning from Neuronal Correspondences

We introduce and study methods for inferring and learning from correspondences among neurons. The approach enables alignment of data from distinct multiunit studies of nervous systems. We show that the methods for inferring correspondences combine data eectively from cross-animal studies to make joint inferences about behavioral decision making that are not possible with the data from a single animal. We focus on data collection, machine learning, and prediction in the representative and long-studied invertebrate nervous system of the European medicinal leech. Acknowledging the computational intractability of the general problem of identifying correspondences among neurons, we introduce ecient computational procedures for matching neurons across animals. The methods include techniques that adjust for missing cells or additional cells in the dierent data sets that may reect biological or experimental variation. The methods highlight the value harnessing inference and learning in new kinds of computational microscopes for multiunit neurobiological studies.
Probing the topological charge of a vortex beam with dynamic angular double slits.

When a vortex beam with a spiral phase structure passes through dynamic angular double slits (ADS), the interference pattern changes alternatively between destructive and constructive at the angular bisector of the ADS. This change is due to their phase difference. Based on this property, we experimentally demonstrate a simple method to precisely and efficiently determine the topological charge of vortex beams. Furthermore, this scheme allows for the simultaneous determination of the modulus and the sign of the topological charge of the vortex beams.
Minimal Length Effects on Tunnelling from Spherically Symmetric Black Holes

We investigate effects of the minimal length on quantum tunnelling from spherically symmetric black holes using the Hamilton-Jacobi method incorporating the minimal length. We first derive the deformed Hamilton-Jacobi equations for scalars and fermions, both of which have the same expressions. The minimal length correction to the Hawking temperature is found to depend on the black hole’s mass and the mass and angular momentum of emitted particles. Finally, we calculate a Schwarzschild black hole's luminosity and find the black hole evaporates to zero mass in infinite time.
Theory of linear optical absorption in diamond-shaped graphene quantum dots

In this paper, optical and electronic properties of diamond shaped graphene quantum dots (DQDs) have been studied by employing large-scale electron-correlated calculations. The computations have been performed using the \pi-electron Pariser-Parr-Pople model Hamiltonian, which incorporates long-range Coulomb interactions. The influence of electron-correlation effects on the ground and excited states has been included by means of the configuration-interaction approach, used at various levels. Our calculations have revealed that the absorption spectra are red-shifted with the increasing sizes of quantum dots. It has been observed that the first peak of the linear optical absorption, which represents the optical gap, is not the most intense peak. This result is in excellent agreement with the experimental data, but in stark contrast to the predictions of the tight-binding model, according to which the first peak is the most intense peak, pointing to the importance of electron-correlation effects.