nils-herrmann/clean_scirepeval huggingface dataset:
Thermodynamics of Quantum Isolated Horizons with model Hamiltonians

Following a recent proposal, we consider the most general structure possible for the Hamiltonian operator associated with the Quantum Isolated Horizon(QIH) with explanations of the underlying physical motivations. An extensive thermodynamic analysis with this model Hamiltonian is presented. Considering {\it fixed} number of punctures, the canonical partition function can now be written in the usual energy ensemble. Arguing that the known classical results must follow in the correspondence limit (viz. the equilibrium temperature as observed by a local observer) the model is fixed, yielding the energy spectrum of the QIH.
On preferred axes in WMAP cosmic microwave background data after subtraction of the integrated Sachs-Wolfe effect

There is currently a debate over the existence of claimed statistical anomalies in the cosmic microwave background (CMB), recently confirmed in Planck data. Recent work has focussed on methods for measuring statistical significance, on masks and on secondary anisotropies as potential causes of the anomalies. We investigate simultaneously the method for accounting for masked regions and the foreground integrated Sachs-Wolfe (ISW) signal. We search for trends in different years of WMAP CMB data with different mask treatments. We reconstruct the ISW field due to the 2 Micron All-Sky Survey (2MASS) and the NRAO VLA Sky Survey (NVSS) up to l = 5, and we focus on the Axis of Evil (AoE) statistic and even/odd mirror parity, both of which search for preferred axes in the Universe. We find that removing the ISW reduces the significance of these anomalies in WMAP data, though this does not exclude the possibility of exotic physics. In the spirit of reproducible research, all reconstructed maps and codes will be made available for download at http://www.cosmostat.org/anomaliesCMB.html.
VERY LOW ENERGY SUPERNOVAE FROM NEUTRINO MASS LOSS

It now seems likely that some percentage of more massive supernova progenitors do not explode by any of the currently discussed explosion mechanisms. This has led to speculation concerning the observable transients that might be produced if such a supernova fails. Even if a prompt outgoing shock fails to form in a collapsing presupernova star, one must still consider the hydrodynamic response of the star to the abrupt loss of mass via neutrinos as the core forms a protoneutron star. Following a suggestion by Nadezhin, we calculate the hydrodynamical responses of typical supernova progenitor stars to the rapid loss of approximately 0.2–0.5 M☉ of gravitational mass from their centers. In a red supergiant star, a very weak supernova with total kinetic energy ∼1047 erg results. The binding energy of a large fraction of the hydrogen envelope before the explosion is of the same order and, depending upon assumptions regarding the maximum mass of a neutron star, most of it is ejected. Ejection speeds are ∼100 km s−1 and luminosities ∼1039 erg s−1 are maintained for about a year. A significant part of the energy comes from the recombination of hydrogen. The color of the explosion is extremely red and the events bear some similarity to “luminous red novae,” but have much lower speeds.
Planck 2013 results. I. Overview of products and scientific results

The European Space Agency’s Planck satellite, dedicated to studying the early Universe and its subsequent evolution, was launched 14 May 2009 and has been scanning the microwave and submillimetre sky continuously since 12 August 2009. In March 2013, ESA and the Planck Collaboration released the initial cosmology products based on the first 15.5 months of Planck data, along with a set of scientific and technical papers and a web-based explanatory supplement. This paper gives an overview of the mission and its performance, the processing, analysis, and characteristics of the data, the scientific results, and the science data products and papers in the release. The science products include maps of the cosmic microwave background (CMB) and diffuse extragalactic foregrounds, a catalogue of compact Galactic and extragalactic sources, and a list of sources detected through the Sunyaev-Zeldovich effect. The likelihood code used to assess cosmological models against the Planck data and a lensing likelihood are described. Scientific results include robust support for the standard six-parameter ΛCDM model of cosmology and improved measurements of its parameters, including a highly significant deviation from scale invariance of the primordial power spectrum. The Planck values for these parameters and others derived from them are significantly different from those previously determined. Several large-scale anomalies in the temperature distribution of the CMB, first detected by WMAP, are confirmed with higher confidence. Planck sets new limits on the number and mass of neutrinos, and has measured gravitational lensing of CMB anisotropies at greater than 25σ. Planck finds no evidence for non-Gaussianity in the CMB. Planck’s results agree well with results from the measurements of baryon acoustic oscillations. Planck finds a lower Hubble constant than found in some more local measures. Some tension is also present between the amplitude of matter fluctuations (σ8) derived from CMB data and that derived from Sunyaev-Zeldovich data. The Planck and WMAP power spectra are offset from each other by an average level of about 2% around the first acoustic peak. Analysis of Planck polarization data is not yet mature, therefore polarization results are not released, although the robust detection of E-mode polarization around CMB hot and cold spots is shown graphically.
Constraints on dark matter annihilation from CMB observations before Planck

We compute the bounds on the dark matter (DM) annihilation cross section using the most recent Cosmic Microwave Background measurements from WMAP9, SPT'11 and ACT'10. We consider DM with mass in the MeV–TeV range annihilating 100% into either an e+e− or a μ+μ− pair. We consider a realistic energy deposition model, which includes the dependence on the redshift, DM mass and annihilation channel. We exclude the canonical thermal relic abundance cross section (σv = 3 × 10−26cm3s−1) for DM masses below 30 GeV and 15 GeV for the e+e− and μ+μ− channels, respectively. A priori, DM annihilating in halos could also modify the reionization history of the Universe at late times. We implement a realistic halo model taken from results of state-of-the-art N-body simulations and consider a mixed reionization mechanism, consisting on reionization from DM as well as from first stars. We find that the constraints on DM annihilation remain unchanged, even when large uncertainties on the halo model parameters are considered.
On the optimality of a L1/L1 solver for sparse signal recovery from sparsely corrupted compressive measurements

This short note proves the $\ell_2-\ell_1$ instance optimality of a $\ell_1/\ell_1$ solver, i.e a variant of \emph{basis pursuit denoising} with a $\ell_1$ fidelity constraint, when applied to the estimation of sparse (or compressible) signals observed by sparsely corrupted compressive measurements. The approach simply combines two known results due to Y. Plan, R. Vershynin and E. Cand\`es.
Node-based learning of multiple Gaussian graphical models

We consider the problem of estimating high-dimensional Gaussian graphical models corresponding to a single set of variables under several distinct conditions. This problem is motivated by the task of recovering transcriptional regulatory networks on the basis of gene expression data containing heterogeneous samples, such as different disease states, multiple species, or different developmental stages. We assume that most aspects of the conditional dependence networks are shared, but that there are some structured differences between them. Rather than assuming that similarities and differences between networks are driven by individual edges, we take a node-based approach, which in many cases provides a more intuitive interpretation of the network differences. We consider estimation under two distinct assumptions: (1) differences between the K networks are due to individual nodes that are perturbed across conditions, or (2) similarities among the K networks are due to the presence of common hub nodes that are shared across all K networks. Using a row-column overlap norm penalty function, we formulate two convex optimization problems that correspond to these two assumptions. We solve these problems using an alternating direction method of multipliers algorithm, and we derive a set of necessary and sufficient conditions that allows us to decompose the problem into independent subproblems so that our algorithm can be scaled to high-dimensional settings. Our proposal is illustrated on synthetic data, a webpage data set, and a brain cancer gene expression data set.
Realistic polarizing Sagnac topology with DC readout for the Einstein Telescope

The Einstein Telescope (ET) is a proposed future gravitational wave detector. Its design is original, using a triangular orientation of three detectors and a xylophone configuration, splitting each detector into one high-frequency and one low-frequency system. In other aspects the current design retains the dual-recycled Michelson interferometer typical of current detectors, such as Advanced LIGO. In this paper, we investigate the feasibility of replacing the low-frequency part of the ET detectors with a Sagnac interferometer. We show that a Sagnac interferometer, using realistic optical parameters based on the ET design, could provide a similar level of radiation pressure noise suppression without the need for a signal recycling mirror and the extensive filter cavities. We consider the practical issues of a realistic, power-recycled Sagnac, using linear arm cavities and polarizing optics. In particular, we investigate the effects of nonperfect polarizing optics and propose a new method for the generation of a local oscillator field similar to the DC readout scheme of current detectors.
Smart Rewiring for Network Robustness

While new forms of attacks are developed every day to compromise essential infrastructures, service providers are also expected to develop strategies to mitigate the risk of extreme failures. In this context, tools of network science have been used to evaluate network robustness and propose resilient topologies against attacks. We present here a new rewiring method to modify the network topology improving its robustness, based on the evolution of the network largest component during a sequence of targeted attacks. In comparison to previous strategies, our method lowers by several orders of magnitude the computational effort necessary to improve robustness. Our rewiring also drives the formation of layers of nodes with similar degree while keeping a highly modular structure. This modular onion-like structure is a particular class of the onion-like structure previously described in the literature. We apply our rewiring strategy to an unweighted representation of the World Air-transportation network and show that an improvement of thirty percent in its overall robustness can be achieved through smart swaps of around nine percent of its links.
New Physics in Neutron Beta Decay

Limits on parameters describing physics beyond the Standard Model are presented. The most general Lorentz invariant effective Hamiltonian at the quark-lepton level involving vector, scalar and tensor operators has been used. The fits have been done using the most precise and up to date experimental data for correlation coefficients measured in free neutron beta decay as well as the Fierz term measured in superallowed Fermi decays.
Generalised measures for the evaluation of community detection methods

Community detection can be considered as a variant of cluster analysis applied to complex networks. For this reason, all existing studies have been using tools derived from this field when evaluating community detection algorithms. However, those are not completely relevant in the context of network analysis, because they ignore an essential part of the available information: the network structure. Therefore, they can lead to incorrect interpretations. In this article, we review these measures, and illustrate this limitation. We propose a modification to solve this problem, and apply it to the three most widespread measures: purity, Rand index and normalised mutual information (NMI). We then perform an experimental evaluation on artificially generated networks with realistic community structure. We assess the relevance of the modified measures by comparison with their traditional counterparts, and also relatively to the topological properties of the community structures. On these data, the modified NMI turns out to provide the most relevant results.
Quantifying the Impact of Leveraging and Diversification on Systemic Risk

Excessive leverage, i.e. the abuse of debt financing, is considered one of the primary factors in the default of financial institutions. Systemic risk results from correlations between individual default probabilities that cannot be considered independent. Based on the structural framework by Merton (1974), we discuss a model in which these correlations arise from overlaps in banks’ portfolios. Portfolio diversification is used as a strategy to mitigate losses from investments in risky projects. We calculate an optimal level of diversification that has to be reached for a given level of excessive leverage to still mitigate an increase in systemic risk. In our model, this optimal diversification further depends on the market size and the market conditions (e.g. volatility). It allows to distinguish between a safe regime, in which excessive leverage does not result in an increase of systemic risk, and a risky regime, in which excessive leverage cannot be mitigated leading to an increased systemic risk. Our results are of relevance for financial regulators.
Thawing models in the presence of a generalized Chaplygin gas

In this paper we consider a cosmological model whose main components are a scalar field and a generalized Chaplygin gas. We obtain an exact solution for a flat arbitrary potential. This solution have the right dust limit when the Chaplygin parameter $A\rightarrow 0$. We use the dynamical systems approach in order to describe the cosmological evolution of the mixture for an exponential self-interacting scalar field potential. We study the scalar field with an arbitrary self-interacting potential using the "Method of $f$-devisers." Our results are illustrated for the special case of a coshlike potential. We find that usual scalar-field-dominated and scaling solutions cannot be late-time attractors in the presence of the Chaplygin gas (with $\alpha>0$). We recover the standard results at the dust limit ($A\rightarrow 0$). In particular, for the exponential potential, the late-time attractor is a pure generalized Chaplygin solution mimicking an effective cosmological constant. In the case of arbitrary potentials, the late-time attractors are de Sitter solutions in the form of a cosmological constant, a pure generalized Chaplygin solution or a continuum of solutions, when the scalar field and the Chaplygin gas densities are of the same orders of magnitude. The different situations depend on the parameter choices.
Not conformally Einstein metrics in conformal gravity

The equations of motion of four-dimensional conformal gravity, whose Lagrangian is the square of the Weyl tensor, require that the Bach tensor Eμν=(∇ρ∇σ+12Rρσ)Cμρνσ?> vanishes. Since Eμν is zero for any Einstein metric, and any conformal scaling of such a metric, it follows that large classes of solutions in four-dimensional conformal gravity are simply given by metrics that are conformal to Einstein metrics (including Ricci flat). In fact it becomes more intriguing to find solutions that are not conformally Einstein. We obtain five new such vacua, which are homogeneous and have asymptotic generalized Lifshitz anisotropic scaling symmetry. Four of these solutions can be further generalized to metrics that are conformal to classes of pp-waves, with a covariantly-constant null vector. We also obtain large classes of generalized Lifshitz vacua in Einstein–Weyl gravity.
Ranking journals: could Google Scholar Metrics be an alternative to Journal Citation Reports and Scimago Journal Rank?

The launch of Google Scholar Metrics as a tool for assessing scientific journals may be serious competition for Thomson Reuters' Journal Citation Reports, and for the Scopus‐powered Scimago Journal Rank. A review of these bibliometric journal evaluation products is performed. We compare their main characteristics from different approaches: coverage, indexing policies, search and visualization, bibliometric indicators, results analysis options, economic cost, and differences in their ranking of journals. Despite its shortcomings, Google Scholar Metrics is a helpful tool for authors and editors in identifying core journals. As an increasingly useful tool for ranking scientific journals, it may also challenge established journals products.
On the Jeffreys-Lindley's paradox

This paper discusses the dual interpretation of the Jeffreys--Lindley's paradox associated with Bayesian posterior probabilities and Bayes factors, both as a differentiation between frequentist and Bayesian statistics and as a pointer to the difficulty of using improper priors while testing. We stress the considerable impact of this paradox on the foundations of both classical and Bayesian statistics. While assessing existing resolutions of the paradox, we focus on a critical viewpoint of the paradox discussed by Spanos (2013) in Philosophy of Science.
A quantum speedup in machine learning: finding an N-bit Boolean function for a classification

We compare quantum and classical machines designed for learning an N-bit Boolean function in order to address how a quantum system improves the machine learning behavior. The machines of the two types consist of the same number of operations and control parameters, but only the quantum machines utilize the quantum coherence naturally induced by unitary operators. We show that quantum superposition enables quantum learning that is faster than classical learning by expanding the approximate solution regions, i.e., the acceptable regions. This is also demonstrated by means of numerical simulations with a standard feedback model, namely random search, and a practical model, namely differential evolution.
Preferential attachment in online networks: measurement and explanations

We perform an empirical study of the preferential attachment phenomenon in temporal networks and show that on the Web, networks follow a nonlinear preferential attachment model in which the exponent depends on the type of network considered. The classical preferential attachment model for networks by Barabási and Albert (1999) assumes a linear relationship between the number of neighbors of a node in a network and the probability of attachment. Although this assumption is widely made in Web Science and related fields, the underlying linearity is rarely measured. To fill this gap, this paper performs an empirical longitudinal (time-based) study on forty-seven diverse Web network datasets from seven network categories and including directed, undirected and bipartite networks. We show that contrary to the usual assumption, preferential attachment is nonlinear in the networks under consideration. Furthermore, we observe that the deviation from linearity is dependent on the type of network, giving sublinear attachment in certain types of networks, and superlinear attachment in others. Thus, we introduce the preferential attachment exponent β as a novel numerical network measure that can be used to discriminate different types of networks. We propose explanations for the behavior of that network measure, based on the mechanisms that underly the growth of the network in question.
ANDROMEDA (M31) OPTICAL AND INFRARED DISK SURVEY. I. INSIGHTS IN WIDE-FIELD NEAR-IR SURFACE PHOTOMETRY

We present wide-field near-infrared J and Ks images of the Andromeda Galaxy (M31) taken with WIRCam at the Canada–France–Hawaii Telescope as part of the Andromeda Optical and Infrared Disk Survey. This data set allows simultaneous observations of resolved stars and near-infrared (NIR) surface brightness across M31's entire bulge and disk (within R = 22 kpc), permitting a direct test of the stellar composition of near-infrared light in a nearby galaxy. Here we develop NIR observation and reduction methods to recover a uniform surface brightness map across the 3° × 1° disk of M31 with 27 WIRCam fields. Two sky-target nodding strategies are tested, and we find that strictly minimizing sky sampling latency cannot improve background subtraction accuracy to better than 2% of the background level due to spatio-temporal variations in the NIR skyglow. We fully describe our WIRCam reduction pipeline and advocate using flats built from night-sky images over a single night, rather than dome flats that do not capture the WIRCam illumination field. Contamination from scattered light and thermal background in sky flats has a negligible effect on the surface brightness shape compared to the stochastic differences in background shape between sky and galaxy disk fields, which are ∼0.3% of the background level. The most dramatic calibration step is the introduction of scalar sky offsets to each image that optimizes surface brightness continuity. Sky offsets reduce the mean surface brightness difference between observation blocks from 1% to <0.1% of the background level, though the absolute background level remains statistically uncertain to 0.15% of the background level. We present our WIRCam reduction pipeline and performance analysis to give specific recommendations for the improvement of NIR wide-field imaging methods.
Extracting the Information Backbone in Online System

Information overload is a serious problem in modern society and many solutions such as recommender system have been proposed to filter out irrelevant information. In the literature, researchers have been mainly dedicated to improving the recommendation performance (accuracy and diversity) of the algorithms while they have overlooked the influence of topology of the online user-object bipartite networks. In this paper, we find that some information provided by the bipartite networks is not only redundant but also misleading. With such “less can be more” feature, we design some algorithms to improve the recommendation performance by eliminating some links from the original networks. Moreover, we propose a hybrid method combining the time-aware and topology-aware link removal algorithms to extract the backbone which contains the essential information for the recommender systems. From the practical point of view, our method can improve the performance and reduce the computational time of the recommendation system, thus improving both of their effectiveness and efficiency.
Low lying spectroscopy of odd-odd $^{146}$Eu

Electron Capture (EC) decay of $^{146}$Gd($\it{t_{1/2}}$ = 48d) to the low lying states of $^{146}$Eu has been studied using high-resolution $\gamma$ ray spectroscopy. The $^{146}$Gd activity was produced by ($\alpha$, 2n) reaction at E$_{\alpha}$ = 32 MeV using 93.8% enriched $^{144}$Sm target. The level structure has been considerably modified from the measurement of $\gamma$ ray singles, $\gamma\gamma$ coincidences and decay half lives. Lifetime measurement has been performed for the 3$^-$ (114.06 keV) and 2$^-$ (229.4 keV) levels of $^{146}$Eu using Mirror Symmetric Centroid Difference (MSCD) method with LaBr$_3$ (Ce) detectors. The lifetimes for these two states have been found to be 5.38 $\pm$ 2.36 ps and 8.38 $\pm$ 2.19 ps respectively. Shell model calculation has been performed using OXBASH code in order to interpret the results.