nils-herrmann/clean_scirepeval huggingface dataset:
Reconstruction, thermodynamics and stability of the ΛCDM model in f ( T ,  ) gravity

We reconstruct the ΛCDM model for f ( T ,  ) theory, where T is the torsion scalar and  the trace of the energy-momentum tensor. The result shows that the action of ΛCDM is a combination of a linear term, a constant ( − 2 Λ ) and a nonlinear term given by the product − T F g [ ( T 1 / 3 / 16 π G ) ( 16 π G  + T + 8 Λ ) ] , with Fg being a generic function. We show that to maintain conservation of the energy-momentum tensor, we should impose that F g [ y ] must be linear on the trace  . This reconstruction decays in f (T) theory for F g ≡ Q , with Q a constant. Our reconstruction describes the cosmological eras to the present time. The model present stability within the geometric and matter perturbations for the choice F g = y , where y = ( T 1 / 3 / 16 π G ) ( 16 π G  + T + 8 Λ ) , except for the geometric part in the de Sitter model. We impose the first and second laws of thermodynamics to ΛCDM and find the condition where they are satisfied, that is, T A , G eff > 0 , however where this is not possible in the cases that we choose, this leads to a breakdown of positive entropy and Misner–Sharp energy.
Dirac phenomenological analyses of unpolarized proton inelastic scattering from 22Ne

Unpolarized 800-MeV proton inelastic scatterings from an s-d shell nucleus 22Ne are analyzed by using phenomenological optical potentials in the Dirac coupled channel formalism. The first-order rotational collective model is used to obtain the transition optical potentials for the low-lying excited collective states that belong to the ground-state rotational band of the nucleus. The optical potential parameters of a Woods-Saxon shape and the deformation parameters of the excited states are varied phenomenologically by using the sequential iteration method to reproduce the experimental differential cross-section data. The effective central and spin-orbit optical potentials are obtained by reducing the Dirac equations to a Schrödinger-like second-order differential equations, and the surface-peaked phenomena are observed at the real effective central potentials when the scattering from 22Ne is considered. The obtained deformation parameters of the excited states are compared with those of the nonrelativistic calculations and with those for another s-d shell nucleus 20Ne. The deformation parameters for the 2+ and the 4+ states of the ground-state rotational band for the nucleus 22Ne are found to be smaller than those of 20Ne, indicating that the couplings of those states to the ground state are weaker for the 22Ne than for the 20Ne nucleus. The multistep channel coupling effect is confirmed to be important for the 4+ state excitation of the ground-state rotational band for proton inelastic scattering from the s-d shell nucleus 22Ne.
Hostile intent identification by movement pattern analysis: Using artificial neural networks

In the recent years, the problem of identifying suspicious behavior has gained importance and identifying this behavior using computational systems and autonomous algorithms is highly desirable in a tactical scenario. So far, the solutions have been primarily manual which elicit human observation of entities to discern the hostility of the situation. To cater to this problem statement, a number of fully automated and partially automated solutions exist. But, these solutions lack the capability of learning from experiences and work in conjunction with human supervision which is extremely prone to error. In this paper, a generalized methodology to predict the hostility of a given object based on its movement patterns is proposed which has the ability to learn and is based upon the mechanism of humans of “learning from experiences”. The methodology so proposed has been implemented in a computer simulation. The results show that the posited methodology has the potential to be applied in real world tactical scenarios.
Protein interaction networks and biology: towards the connection

Protein interaction networks (PIN) are popular means to visualize the proteome. However, PIN datasets are known to be noisy, incomplete and biased by the experimental protocols used to detect protein interactions. This paper aims at understanding the connection between true protein interactions and the protein interaction datasets that have been obtained using the most popular experimental techniques, i.e. mass spectronomy (MS) and yeast two-hybrid (Y2H). We show that the most natural adjacency matrix of protein interaction networks has a separable form, and this induces precise relations between moments of the degree distribution and the number of short loops. These relations provide powerful tools to test the reliability of datasets and hint at the underlying biological mechanism with which proteins and complexes recruit each other.
Sparse and low-rank multivariate Hawkes processes

We consider the problem of unveiling the implicit network structure of node interactions (such as user interactions in a social network), based only on high-frequency timestamps. Our inference is based on the minimization of the least-squares loss associated with a multivariate Hawkes model, penalized by $\ell_1$ and trace norm of the interaction tensor. We provide a first theoretical analysis for this problem, that includes sparsity and low-rank inducing penalizations. This result involves a new data-driven concentration inequality for matrix martingales in continuous time with observable variance, which is a result of independent interest. A consequence of our analysis is the construction of sharply tuned $\ell_1$ and trace-norm penalizations, that leads to a data-driven scaling of the variability of information available for each users. Numerical experiments illustrate the significant improvements achieved by the use of such data-driven penalizations.
A Deep-Structured Conditional Random Field Model for Object Silhouette Tracking

In this work, we introduce a deep-structured conditional random field (DS-CRF) model for the purpose of state-based object silhouette tracking. The proposed DS-CRF model consists of a series of state layers, where each state layer spatially characterizes the object silhouette at a particular point in time. The interactions between adjacent state layers are established by inter-layer connectivity dynamically determined based on inter-frame optical flow. By incorporate both spatial and temporal context in a dynamic fashion within such a deep-structured probabilistic graphical model, the proposed DS-CRF model allows us to develop a framework that can accurately and efficiently track object silhouettes that can change greatly over time, as well as under different situations such as occlusion and multiple targets within the scene. Experiment results using video surveillance datasets containing different scenarios such as occlusion and multiple targets showed that the proposed DS-CRF approach provides strong object silhouette tracking performance when compared to baseline methods such as mean-shift tracking, as well as state-of-the-art methods such as context tracking and boosted particle filtering.
Hashing with binary autoencoders

An attractive approach for fast search in image databases is binary hashing, where each high-dimensional, real-valued image is mapped onto a low-dimensional, binary vector and the search is done in this binary space. Finding the optimal hash function is difficult because it involves binary constraints, and most approaches approximate the optimization by relaxing the constraints and then binarizing the result. Here, we focus on the binary autoencoder model, which seeks to reconstruct an image from the binary code produced by the hash function. We show that the optimization can be simplified with the method of auxiliary coordinates. This reformulates the optimization as alternating two easier steps: one that learns the encoder and decoder separately, and one that optimizes the code for each image. Image retrieval experiments show the resulting hash function outperforms or is competitive with state-of-the-art methods for binary hashing.
Mathematical model for hit phenomena and its application to analyze popularity of weekly tv drama

Mathematical model for hit phenomena presented by A Ishii et al in 2012 has been extended to analyze and predict a lot of hit subject using social network system. The equation for each individual consumers is assumed and the equation of social response to each hit subject is derived as stochastic process of statistical physics. The advertisement effect is included as external force and the communication effects are included as two-body and three-body interaction. The applications of this model are demonstrated for analyzing population of weekly TV drama. Including both the realtime view data and the playback view data, we found that the indirect communication correlate strongly to the TV viewing rate data for recent Japanese 20 TV drama.
Signs of dependence and heavy tails in non-life insurance data

In this paper, we study data from the yearly reports the four major Swedish non-life insurers have sent to the Swedish Financial Supervisory Authority (FSA). We aim at finding marginal distributions of, and dependence between, losses on the five largest lines of business (LoBs) in order to create models for solvency capital requirement (SCR) calculation. We try to use data in an optimal way by sensibly defining an accounting year loss in terms of actuarial liability predictions and by pooling observations from several companies when possible to decrease the uncertainty about the underlying distributions and their parameters. We find that dependence between LoBs is weaker in our data than what is assumed in the Solvency II standard formula. We also find dependence between companies that may affect financial stability and must be taken into account when estimating loss distribution parameters. Moreover, we discuss under what circumstances an insurer is better (or worse) off using an internal model for SCR calculation, instead of the standard formula.
A SERENDIPITOUS ALL SKY SURVEY FOR BRIGHT OBJECTS IN THE OUTER SOLAR SYSTEM

We use seven yearʼs worth of observations from the Catalina Sky Survey and the Siding Spring Survey covering most of the northern and southern hemisphere at galactic latitudes higher than 20° to search for serendipitously imaged moving objects in the outer solar system. These slowly moving objects would appear as stationary transients in these fast cadence asteroids surveys, so we develop methods to discover objects in the outer solar system using individual observations spaced by months, rather than spaced by hours, as is typically done. While we independently discover eight known bright objects in the outer solar system, the faintest having V = 19.8 ± 0.1 , ?> no new objects are discovered. We find that the survey is nearly 100% efficient at detecting objects beyond 25 AU for V ≲ 19.1 ?> ( V ≲ 18.6 ?> in the southern hemisphere) and that the probability that there is one or more remaining outer solar system object of this brightness left to be discovered in the unsurveyed regions of the galactic plane is approximately 32%.
Characterizing the Google Books Corpus: Strong Limits to Inferences of Socio-Cultural and Linguistic Evolution

It is tempting to treat frequency trends from the Google Books data sets as indicators of the “true” popularity of various words and phrases. Doing so allows us to draw quantitatively strong conclusions about the evolution of cultural perception of a given topic, such as time or gender. However, the Google Books corpus suffers from a number of limitations which make it an obscure mask of cultural popularity. A primary issue is that the corpus is in effect a library, containing one of each book. A single, prolific author is thereby able to noticeably insert new phrases into the Google Books lexicon, whether the author is widely read or not. With this understood, the Google Books corpus remains an important data set to be considered more lexicon-like than text-like. Here, we show that a distinct problematic feature arises from the inclusion of scientific texts, which have become an increasingly substantive portion of the corpus throughout the 1900s. The result is a surge of phrases typical to academic articles but less common in general, such as references to time in the form of citations. We use information theoretic methods to highlight these dynamics by examining and comparing major contributions via a divergence measure of English data sets between decades in the period 1800–2000. We find that only the English Fiction data set from the second version of the corpus is not heavily affected by professional texts. Overall, our findings call into question the vast majority of existing claims drawn from the Google Books corpus, and point to the need to fully characterize the dynamics of the corpus before using these data sets to draw broad conclusions about cultural and linguistic evolution.
Quantum dimer model for the pseudogap metal

The most interesting states of the copper oxide compounds are not the superconductors with high critical temperatures. Instead, the novelty lies primarily in the higher temperature metallic “normal” states from which the superconductors descend. Here, we develop a simple, intuitive model for the physics of the metal at low carrier density, in the “pseudogap” regime. This model describes an exotic metal that is similar in many respects to simple metals like silver. However, the simple metallic character coexists with “topological order” and long-range quantum entanglement previously observed only in exotic insulators or fractional quantum Hall states in very high magnetic fields. Our model is compatible with many recent observations, and we discuss more definitive experimental tests. We propose a quantum dimer model for the metallic state of the hole-doped cuprates at low hole density, p. The Hilbert space is spanned by spinless, neutral, bosonic dimers and spin S=1/2, charge +e fermionic dimers. The model realizes a “fractionalized Fermi liquid” with no symmetry breaking and small hole pocket Fermi surfaces enclosing a total area determined by p. Exact diagonalization, on lattices of sizes up to 8×8, shows anisotropic quasiparticle residue around the pocket Fermi surfaces. We discuss the relationship to experiments.
Limit-cycle phase in driven-dissipative spin systems

We explore the phase diagram of interacting spin-$1/2$ systems in the presence of anisotropic interactions, spontaneous decay and driving. We find a rich phase diagram featuring a limit cycle phase in which the magnetization oscillates in time. We analyze the spatio-temporal fluctuations of this limit cycle phase at the Gaussian level, and show that spatial fluctuations lead to quasi-long-range limit cycle ordering for dimension $d = 2$. This result can be interpreted in terms of a spatio-temporal Goldstone mode corresponding to phase fluctuations of the limit cycle. We also demonstrate that the limit-cycle phase exhibits an asymmetric power spectrum measurable in fluorescence experiments.
Reanalysis of radial velocity data from the resonant planetary system HD128311

The multi-planetary system HD128311 hosts at least two planets. Its dynamical formation history has been studied extensively in the literature. We reanalyse the latest radial velocity data for this system with the affine-invariant Markov chain Monte Carlo sampler EMCEE. Using the high order integrator IAS15, we perform a fully dynamical fit, allowing the planets to interact during the sampling process. A stability analysis using the MEGNO indicator reveals that the system is located in a stable island of the parameter space. In contrast to a previous study, we find that the system is locked in a 2:1 mean motion resonance. The resonant angle $\varphi_1$ is librating with a libration amplitude of approximately 37{\deg}. The existence of mean motion resonances has important implication for planet formation theories. Our results confirm predictions of models involving planet migration and stochastic forces.
A DYNAMICAL STUDY OF THE BLACK HOLE X-RAY BINARY NOVA MUSCAE 1991

We present a dynamical study of the Galactic black hole binary system Nova Muscae 1991 (GS/GRS 1124–683). We utilize 72 high-resolution Magellan Echellette spectra and 72 strictly simultaneous V-band photometric observations; the simultaneity is a unique and crucial feature of this dynamical study. The data were taken on two consecutive nights and cover the full 10.4 hr orbital cycle. The radial velocities of the secondary star are determined by cross-correlating the object spectra with the best-match template spectrum obtained using the same instrument configuration. Based on our independent analysis of five orders of the echellette spectrum, the semi-amplitude of the radial velocity of the secondary is measured to be K 2 = 406.8 ± 2.7 ?> km s−1, which is consistent with previous work, while the uncertainty is reduced by a factor of 3. The corresponding mass function is f ( M ) = 3.02 ± 0.06 M ⊙ ?> . We have also obtained an accurate measurement of the rotational broadening of the stellar absorption lines ( v sin i = 85.0 ± 2.6 ?> km s−1), and hence the mass ratio of the system q = 0.079 ± 0.007 ?> . Finally, we have measured the spectrum of the non-stellar component of emission that veils the spectrum of the secondary. In a future paper, we will use our veiling-corrected spectrum of the secondary and accurate values of K2 and q to model multi-color light curves and determine the systemic inclination and the mass of the black hole.
DISCOVERY OF LARGE MOLECULAR GAS RESERVOIRS IN POST-STARBURST GALAXIES

Post-starburst (or “E+A”) galaxies are characterized by low Hα emission and strong Balmer absorption, suggesting a recent starburst, but little current star formation. Although many of these galaxies show evidence of recent mergers, the mechanism for ending the starburst is not yet understood. To study the fate of the molecular gas, we search for CO(1–0) and (2–1) emission with the IRAM 30 m and SMT 10 m telescopes in 32 nearby (0.01  <  z  <  0.12) post-starburst galaxies drawn from the Sloan Digital Sky Survey. We detect CO in 17 (53%). Using CO as a tracer for molecular hydrogen, and a Galactic conversion factor, we obtain molecular gas masses of M(H2) = 108.6–109.8 M☉ and molecular gas mass to stellar mass fractions of ∼10−2–10−0.5, comparable to those of star-forming galaxies. The large amounts of molecular gas rule out complete gas consumption, expulsion, or starvation as the primary mechanism that ends the starburst in these galaxies. The upper limits on M(H2) for the 15 undetected galaxies range from 107.7 M☉ to 109.7 M☉, with the median more consistent with early-type galaxies than with star-forming galaxies. Upper limits on the post-starburst star formation rates (SFRs) are lower by ∼10 × than for star-forming galaxies with the same M(H2). We also compare the molecular gas surface densities () to upper limits on the SFR surface densities (ΣSFR), finding a significant offset, with lower ΣSFR for a given than is typical for star-forming galaxies. This offset from the Kennicutt–Schmidt relation suggests that post-starburst galaxies have lower star formation efficiency, a low CO-to-H2 conversion factor characteristic of ultraluminous infrared galaxies, and/or a bottom-heavy initial mass function, although uncertainties in the rate and distribution of current star formation remain.
Dimension-6 Operator Constraints from Boosted VBF Higgs

We discuss the constraints on new physics from Higgs production through vector boson fusion in the context of an eective eld theory that preserves Standard Model gauge symmetries. We nd that the constraints on dimension-6 operators are signicantly improved over those from the VBF signal strength by studying the Higgs transverse momentum distribution. Focusing on the OHW operator, we nd that boosted VBF decaying to photons yields constraints competitive with boosted WW production in the fully leptonic nal state, and calculate projected limits for both at the 14 TeV LHC. The pT cuts required to maximize the the reach of VBF searches are substantially softer, making the use of the eective eld theory more robust than in the case of WW production which requires very highpT cuts to obtain similar limits. Boosted VBF Higgs is thus an important probe of new physics.
Using Atomic Clocks to Detect Gravitational Waves

Atomic clocks have recently reached a fractional timing precision of $<10^{-18}$. We point out that an array of atomic clocks, distributed along the Earth's orbit around the Sun, will have the sensitivity needed to detect the time dilation effect of mHz gravitational waves (GWs), such as those emitted by supermassive black hole binaries at cosmological distances. Simultaneous measurement of clock-rates at different phases of a passing GW provides an attractive alternative to the interferometric detection of temporal variations in distance between test masses separated by less than a GW wavelength, currently envisioned for the eLISA mission.
Missing top of the AdS resonance structure

We study a massless scalar field in AdS(d+1) with a nonlinear coupling phi(N) and not limited to spherical symmetry. The free-field-eigenstate spectrum is strongly resonant, and it is commonly believed that the nonlinear coupling leads to energy transfer between eigenstates. We prove that when Nd is even, the most efficient resonant channels to transfer energy are always absent. In particular, for N = 3 this means no energy transfer at all. For N = 4, this effectively kills half of the channels, leading to the same set of extra conservation laws recently derived for gravitational interactions within spherical symmetry.
Conservation of reactive EM energy in reactive time

The complex Poynting theorem (CPT) is extended to a canonical time-scale domain (t, s). Time-harmonic phasors are replaced by the positive-frequency parts of general fields, which extend analytically to complex time t + is, with s > 0 interpreted as a time resolution scale. The real part of the extended CPT gives conservation in t of a time-averaged field energy, and its imaginary part gives conservation in s of a time-averaged reactive energy. In both cases, the averaging windows are determined by a Cauchy kernel of duration Δt ~ ±s. This completes the time-harmonic CPT, whose imaginary part is vaguely supposed to be “related to” reactive energy without giving a conservation law, or even an expression, for the latter. The interpretation of s as reactive time, tracking the leads and lags associated with stored capacitative and inductive energy, gives a simple explanation of the volt-ampere reactive (var) unit measuring reactive power: a var is simply one Joule per reactive second. The related complex radiation impedance density is introduced to represent the field's local reluctance to radiate.
Superlinear growth of Rayleigh scattering-induced intensity noise in single-mode fibers.

Rayleigh scattering generates intensity noise close to an optical carrier that propagates in a single-mode optical fiber. This noise degrades the performance of optoelectronic oscillators and RF-photonic links. When using a broad linewidth laser, we previously found that the intensity noise power scales linearly with optical power and fiber length, which is consistent with guided entropy mode Rayleigh scattering (GEMRS), a third order nonlinear scattering process, in the spontaneous limit. In this work, we show that this behavior changes significantly with the use of a narrow linewidth laser. Using a narrow linewidth laser, we measured the bandwidth of the intensity noise plateau to be 10 kHz. We found that the scattered noise power scales superlinearly with fiber length up to lengths of 10 km in the frequency range of 500 Hz to 10 kHz, while it scales linearly in the frequency range of 10 Hz to 100 Hz. These results suggest that the Rayleigh-scattering-induced intensity noise cannot be explained by third-order nonlinear scattering in the spontaneous limit, as previously hypothesized.