nils-herrmann/clean_scirepeval huggingface dataset:
Community detection in temporal multilayer networks, and its application to correlation networks

Networks are a convenient way to represent complex systems of interacting entities. Many networks contain “communities” of nodes that are more densely connected to each other than to nodes in the rest of the network. In this paper, we investigate the detection of communities in temporal networks represented as multilayer networks. As a focal example, we study time-dependent financialasset correlation networks. We first argue that the use of the “modularity” quality function—which is defined by comparing edge weights in an observed network to expected edge weights in a “null network”—is application-dependent. We differentiate between “null networks” and “null models” in our discussion of modularity maximization, and we highlight that the same null network can correspond to different null models. We then investigate a multilayer modularity-maximization problem to identify communities in temporal networks. Our multilayer analysis only depends on the form of the maximization problem and not on the specific quality function that one chooses. We introduce a diagnostic to measure persistence of community structure in a multilayer network partition. We prove several results that describe how the multilayer maximization problem measures a trade-off between static community structure within layers and higher values of persistence across layers. We also discuss some implementation issues that the popular “Louvain” heuristic faces with temporal multilayer networks and suggest ways to mitigate them.
Testing Gravity with Pulsars in the SKA Era

The Square Kilometre Array (SKA) will use pulsars to enable precise measurements of strong gravity effects in pulsar systems, which yield tests of gravitational theories that cannot be carried out anywhere else. The Galactic census of pulsars will discover dozens of relativistic pulsar systems, possibly including pulsar -- black hole binaries which can be used to test the "cosmic censorship conjecture" and the "no-hair theorem". Also, the SKA's remarkable sensitivity will vastly improve the timing precision of millisecond pulsars, allowing probes of potential deviations from general relativity (GR). Aspects of gravitation to be explored include tests of strong equivalence principles, gravitational dipole radiation, extra field components of gravitation, gravitomagnetism, and spacetime symmetries.
CLS 2+1 flavor simulations

We report on the status of large volume simulations with 2+1 dynamical fermions which are being performed by the CLS initiative. The algorithmic details include: open boundary conditions, twisted mass reweighting and RHMC, whereas the main feature of the simulation strategy is the approach to the physical point along a trajectory of constant trace of the mass matrix. We comment on the practical side of the above issues using as examples some of the newly generated ensembles, which presently cover lattice spacings between 0.05 fm and 0.11 fm and pion masses between 150 MeV and 415 MeV.
Unruh effect without Rindler horizon

We investigate the Unruh effect for a massless scalar field in the two-dimensional Minkowski space in the presence of a uniformly accelerated perfect mirror, with the trajectory of the mirror chosen in such a way that the mirror completely masks the Rindler horizon from the space–time region of interest. We find that the characteristic thermodynamical properties of the effect remain unchanged, i.e. the response of a uniformly co-accelerated Unruh detector and the distribution of the Rindler particles retain their thermal form. However, since in this setup there are no unobserved degrees of freedom of the field, the thermal statistics of the Rindler particles are inconsistent with an initial pure vacuum, which leads us to reconsider the problem for the more physical case when the mirror is inertial in the past. In these conditions we find that the distribution of the Rindler particles is non-thermal even in the limit of infinite acceleration times, but effective thermal statistics can be recovered provided that one is restricted to the expectation values of smeared operators associated with finite norm Rindler states. We explain how the thermal statistics in our problem can be understood in analogy with those in the conventional version of the effect.
Highlights from COMPASS in hadron spectroscopy

Since Quantum Choromdynamics allows for gluon self-coupling, quarks and gluons cannot be observed as free particles, but only their bound states, the hadrons. This so-called confinement phenomenon is responsible for $98\%$ of the mass in the visible universe. The measurement of the hadron excitation spectra therefore gives valuable input for theory and phenomenology to quantitatively understand this phenomenon. One simple model to describe hadrons is the Constituent Quark Model (CQM), which knows two types of hadrons: mesons, consisting of a quark and an antiquark, and baryons, which are made out of three quarks. More advanced models, which are inspired by QCD as well as calculations within Lattice QCD predict the existence of other types of hadrons, which may be e.g. described solely by gluonic excitations (glueballs) or mixed quark and gluon excitations (hybrids). In order to search for such states, the COMPASS experiment at the Super Proton Synchrotron at CERN has collected large data sets, which allow to study the light-quark meson and baryon spectra in unmatched precision. The overview shown here focuses on the light meson sector, presenting a detailed Partial-Wave Analysis of the processes: $\pi^- p \to \pi^-\pi^+\pi^- p$ and $\pi^-p\to \pi^-\pi^0\pi^0p$. A new state, the $a_1(1420)$ with $J^{PC}=1^{++}$ is observed. Its Breit-Wigner parameters are found to be in the ranges: $m = 1412-1422\,\mathrm{MeV}/c^2$ and $\Gamma = 130-150\,\mathrm{MeV}/c^2$. In the same analysis, a signal in a wave with $J^{PC}=1^{-+}$ is observed. A resonant origin of this signal would not be explicable within the CQM. In addition to this possibility of an exotic state, a possible non resonant origin of this signal is discussed.
An event-driven approach for studying gene block evolution in bacteria

Gene blocks are genes co-located on the chromosome. In many cases, gene blocks are conserved between bacterial species, sometimes as operons, when genes are co-transcribed. The conservation is rarely absolute: gene loss, gain, duplication, block splitting and block fusion are frequently observed. An open question in bacterial molecular evolution is that of the formation and breakup of gene blocks, for which several models have been proposed. These models, however, are not generally applicable to all types of gene blocks, and consequently cannot be used to broadly compare and study gene block evolution. To address this problem, we introduce an event-based method for tracking gene block evolution in bacteria.  We show here that the evolution of gene blocks in proteobacteria can be described by a small set of events. Those include the insertion of genes into, or the splitting of genes out of a gene block, gene loss, and gene duplication. We show how the event-based method of gene block evolution allows us to determine the evolutionary rateand may be used to trace the ancestral states of their formation. We conclude that the event-based method can be used to help us understand the formation of these important bacterial genomic structures. Availability and implementation: The software is available under GPLv3 license on http://github.com/reamdc1/gene_block_evolution.git.
Spaser as Novel Versatile Biomedical Tool

Fluorescence imaging and spectroscopy remain the most powerful tools for visualization with chemical and immunological specificity of labeled biomolecules, viruses, cellular organelles, and living cells in complex biological backgrounds. However, a common drawback of fluorescence labels is that their brightness is limited by optical saturation and photobleaching. As an alternative, plasmonic metal nanoparticles are very promising as optical labels with no photobleaching and low optical saturation at realistic exciting intensities as was demonstrated in photoacoustic and photothermal sensing, imaging, and theranostics. However, plasmonic nanoparticles have wide absorption spectra and are not fluorescent, which limits their spectral selectivity and multimodal functionality, respectively. Here we demonstrate experimentally, both in vitro and in vivo, that spaser (surface plasmon amplification by stimulated emission of radiation) provides unprecedented efficiency as a versatile tool in biomedical research and applications. This is due to the unique combination of intense near-monochromatic stimulated emission and strongly enhanced absorption, free of optical saturation. Using soluble and biocompatible uranine dye as a gain medium surrounding the gold nanocore as a plasmonic resonator, we demonstrate unprecedented spaser stimulated emission intensity ("giant spasing") and a narrow spectral width (0.8 nm), which are more than ~380-fold and ~30-fold, respectively, better than in quantum dots as the best conventional fluorescent nanoprobes. At the same time, the plasmonic spaser nanocore served as excellent photoacoustic and photothermal contrast agents for imaging and nanobubble-based theranostics of cancer cells. This makes the spasers, arguably, the best multifunctional, super-contrast, low-toxicity optical probes in biomedical research, especially with single-pulse excitation.
Passing Expectation Propagation Messages with Kernel Methods

We propose to learn a kernel-based message operator which takes as input all expectation propagation (EP) incoming messages to a factor node and produces an outgoing message. In ordinary EP, computing an outgoing message involves estimating a multivariate integral which may not have an analytic expression. Learning such an operator allows one to bypass the expensive computation of the integral during inference by directly mapping all incoming messages into an outgoing message. The operator can be learned from training data (examples of input and output messages) which allows automated inference to be made on any kind of factor that can be sampled.
Minimizing the Probability of Ruin in Retirement

Retirees who exhaust their savings while still alive are said to experience financial ruin. These savings are typically grown during the accumulation phase then spent during the retirement decumulation phase. Extensive research into invest-and-harvest decumulation strategies has been conducted, but recommendations differ markedly. This has likely been a source of concern and confusion for the retiree. Our goal is to find what has heretofore been elusive, namely an optimal decumulation strategy. Optimality implies that no alternate strategy exists or can be constructed that delivers a lower probability of ruin, given a fixed inflation-adjusted withdrawal rate.
An introduction to inflation after Planck: from theory to observations

These lecture notes have been written for a short introductory course on the status of inflation after Planck and BICEP2, given at the Xth Modave School of Mathematical Physics. The first objective is to give an overview of the theory of inflation: mo tivations, homogeneous scalar field dynamics, slow-roll approximation, linear theory of cosmological perturbations, classification of single field potentials and their observable predictions. T his includes a pedagogical derivation of the primordial scalar and tensor power spectra for any effective single field potential. The second goal is to present the most recent results of Planck and BICEP2 and to discuss their implications for inflation. Bayesian statistical methods a re introduced as a tool for model analysis and comparison. Based on the recent work of J. Martin et al., the best inflationary models after Planck and BICEP2 are presented. Finally a series of open questions and issues related to inflation are mentioned and briefly discussed.
Dynamical behavior in mimetic F(R) gravity

We investigate the cosmological behavior of mimetic F(R) gravity. This scenario is the F(R) extension of usual mimetic gravity classes, which are based on re-parametrizations of the metric using new, but not propagating, degrees of freedom, that can lead to a wider family of solutions. Performing a detailed dynamical analysis for exponential, power-law, and arbitrary F(R) forms, we extracted the corresponding critical points. Interestingly enough, we found that although the new features of mimetic F(R) gravity can affect the universe evolution at early and intermediate times, at late times they will not have any effect, and the universe will result at stable states that coincide with those of usual F(R) gravity. However, this feature holds for the late-time background evolution only. On the contrary, the behavior of the perturbations is expected to be different since the new term contributes to the perturbations even if it does not contribute at the background level.
HOPS 383: AN OUTBURSTING CLASS 0 PROTOSTAR IN ORION

We report the dramatic mid-infrared brightening between 2004 and 2006 of Herschel Orion Protostar Survey (HOPS) 383, a deeply embedded protostar adjacent to NGC 1977 in Orion. By 2008, the source became a factor of 35 brighter at 24 μm with a brightness increase also apparent at 4.5 μm. The outburst is also detected in the submillimeter by comparing APEX/SABOCA to SCUBA data, and a scattered-light nebula appeared in NEWFIRM Ks imaging. The post-outburst spectral energy distribution indicates a Class 0 source with a dense envelope and a luminosity between 6 and 14 L ⊙ ?> . Post-outburst time-series mid- and far-infrared photometry show no long-term fading and variability at the 18% level between 2009 and 2012. HOPS 383 is the first outbursting Class 0 object discovered, pointing to the importance of episodic accretion at early stages in the star formation process. Its dramatic rise and lack of fading over a 6 year period hint that it may be similar to FU Ori outbursts, although the luminosity appears to be significantly smaller than the canonical luminosities of such objects.
A FIRST LOOK AT THE X-RAY POPULATION OF THE YOUNG MASSIVE CLUSTER VVV CL077

Multi-wavelength analysis of the young massive cluster VVV CL077 is presented for the first time. Our Chandra survey of this region enabled the detection of three X-ray emitting stellar members of the cluster, as well as a possible diffuse X-ray component that extends a few arcseconds from the cluster core with an intrinsic flux of (9  ±  3) × 10−14 erg cm−2 s−1 in the 0.5–10 keV band. Infrared spectra we obtained for two of these X-ray point sources show absorption lines typical of the atmospheres of massive O stars. The X-ray spectrum from the visible extent of VVV CL077 i.e., a 15″ radius around the cluster, can be modeled with an absorbed power law with NH = cm−2 and Γ = 2  ±  1. In addition, the X-ray core of VVV CL077 coincides with diffuse emission seen in the infrared band and with a local maximum in the radio continuum map. A possible association with a neighboring H ii region would place VVV CL077 at a distance of around 11 kpc, on the far side of the Norma Arm. At this distance, the cluster is 0.8 pc wide with a mass density of (1–4) × 103 M☉ pc−3.
Virial Expansion Bounds Through Tree Partition Schemes

In this paper, we use tree partition schemes and an algebraic expression for the virial coefficients in terms of the cluster coefficients in order to derve upper bounds on the virial coefficients and consequently lower bounds on the radius of convergence of the virial expansion $\mathcal{R}_{\textrm{Vir}}$. The bound on the radius of convergence in the case of the Penrose partition scheme is the same as that proposed by Groeneveld and improves the bound achieved by Lebowitz and Penrose.
PT-symmetric $\varphi^4$ theory in d=0 dimensions

A detailed study of a PT-symmetric zero-dimensional quartic theory is presented and a comparison between the properties of this theory and those of a conventional quartic theory is given. It is shown that the PT-symmetric quartic theory evades the consequences of the Mermin-Wagner-Coleman theorem regarding the absence of symmetry breaking in d<2 dimensions. Furthermore, the PT-symmetric theory does not satisfy the usual Bogoliubov limit for the construction of the Green's functions because one obtains different results for the $h\to0^-$ and the $h\to0^+$ limits.
A theoretical foundation of the target-decoy search strategy for false discovery rate control in proteomics

Target-decoy search (TDS) is currently the most popular strategy for estimating and controlling the false discovery rate (FDR) of peptide identifications in mass spectrometry-based shotgun proteomics. While this strategy is very useful in practice and has been intensively studied empirically, its theoretical foundation has not yet been well established.  In this work, we systematically analyze the TDS strategy in a rigorous statistical sense. We prove that the commonly used concatenated TDS provides a conservative estimate of the FDR for any given score threshold, but it cannot rigorously control the FDR. We prove that with a slight modification to the commonly used formula for FDR estimation, the peptide-level FDR can be rigorously controlled based on the concatenated TDS. We show that the spectrum-level FDR control is difficult. We verify the theoretical conclusions with real mass spectrometry data.
Prospects and merits of metal-clad semiconductor lasers from nearly UV to far IR.

Using metal-clad (or plasmonic) waveguide structures in semiconductor lasers carries a promise of reduced size, threshold, and power consumption. This promise is put to a rigorous theoretical test, that takes into account increased waveguide loss, Auger recombination, and Purcell enhancement of spontaneous recombination. The conclusion is that purported benefits of metal waveguides are small to nonexistent for all the band-to-band and intersubband lasers operating from UV to Mid-IR range, with a prominent exception of far-IR and THz quantum cascade lasers. For these devices, however, metal waveguides already represent the state of the art, and the guiding mechanism in them has far more in common with a ubiquitous transmission line than with plasmonics.
Five-partite entanglement generation in a high-Q microresonator

We propose to produce five-partite entanglement via cascaded four-wave mixing in a high-Q microresonator that may become a key to future one-way quantum computation on chip. A theoretical model is presented for the underlying continuous-variable entanglement among the generated comb modes that is expansible to more complicated scenarios. We analyze the entanglement condition when the van Loock and Furusawa criteria are violated, and discuss the device parameters for potential experimental realization that may be utilized to build an integrated compact five-partite entanglement generator. The proposed approach exhibits great potential for future large-scale integrated full optical quantum computation on chip.
Cost–benefit analysis for commissioning decisions in GEO 600

Gravitational wave (GW) interferometers are complex instruments, requiring years of commissioning to achieve the required sensitivities for the detection of GWs, of order ≲10−21 in dimensionless detector strain, in the tens of Hz to several kHz frequency band. Investigations carried out by the GEO 600 detector characterization group have shown that detector characterization techniques are useful when planning for commissioning work. At the time of writing, GEO 600 is the only large scale laser interferometer currently in operation running with a high duty factor, ∼ 70 % ?> , limited chiefly by the time spent commissioning the detector. The number of observable GW sources scales as the product of the volume of space to which the detector is sensitive and the observation time, so the goal of commissioning is to improve the detector sensitivity with the least possible detector down-time. We demonstrate a method for increasing the number of sources observable by such a detector, by assessing the severity of non-astrophysical noise contaminations to efficiently guide commissioning. This method will be particularly useful in the early stages and during the initial science runs of the aLIGO and adVirgo detectors, as they are brought up to design performance.
Ultimate Intelligence Part I: Physical Completeness and Objectivity of Induction

We argue that Solomonoff induction is universal and complete in the physical sense via several strong physical arguments. We argue that Solomonoff induction is fully applicable to quantum mechanics. We show how to choose an objective reference machine for universal induction by defining a physical message complexity for the presently considered ultimate intelligence research program. We introduce physical measures and limits of intelligence that are rigorously objective. We propose volume and energy measures that are more appropriate for physical computations. We extend logical depth and conceptual jump size measures in AIT to stochastic domains and physical measures that involve volume and energy. We show the relations between energy, logical depth and volume of computation for AI. We also introduce a highly relaxed, general physical model of computation that we believe to be more appropriate for our universe than other low level automata models previously considered. We briefly apply our ideas to the physical limits of computation in our universe to show the relation to ultimate intelligence.
A Taxonomy of Big Data for Optimal Predictive Machine Learning and Data Mining

Big data comes in various ways, types, shapes, forms and sizes. Indeed, almost all areas of science, technology, medicine, public health, economics, business, linguistics and social science are bombarded by ever increasing flows of data begging to analyzed efficiently and effectively. In this paper, we propose a rough idea of a possible taxonomy of big data, along with some of the most commonly used tools for handling each particular category of bigness. The dimensionality p of the input space and the sample size n are usually the main ingredients in the characterization of data bigness. The specific statistical machine learning technique used to handle a particular big data set will depend on which category it falls in within the bigness taxonomy. Large p small n data sets for instance require a different set of tools from the large n small p variety. Among other tools, we discuss Preprocessing, Standardization, Imputation, Projection, Regularization, Penalization, Compression, Reduction, Selection, Kernelization, Hybridization, Parallelization, Aggregation, Randomization, Replication, Sequentialization. Indeed, it is important to emphasize right away that the so-called no free lunch theorem applies here, in the sense that there is no universally superior method that outperforms all other methods on all categories of bigness. It is also important to stress the fact that simplicity in the sense of Ockham's razor non plurality principle of parsimony tends to reign supreme when it comes to massive data. We conclude with a comparison of the predictive performance of some of the most commonly used methods on a few data sets.