nils-herrmann/clean_scirepeval huggingface dataset:
A HUBBLE SPACE TELESCOPE SEARCH FOR A SUB-EARTH-SIZED EXOPLANET IN THE GJ 436 SYSTEM

The detection of small planets orbiting nearby stars is an important step toward the identification of Earth twins. In previous work using the Spitzer Space Telescope, we found evidence to support at least one sub-Earth-sized exoplanet orbiting the nearby mid-M dwarf star GJ 436. As a follow up, here we used the Hubble Space Telescope (HST) to investigate the existence of one of these candidate planets, UCF-1.01, by searching for two transit signals as it passed in front of its host star. Interpretation of the data hinges critically on correctly modeling and removing the Wide Field Camera 3 (WFC3) instrument systematics from the light curves. Building on previous HST work, we demonstrate that WFC3 analyses need to explore the use of a quadratic function to fit a visit-long time-dependent systematic. This is important for establishing absolute transit and eclipse depths in the white light curves of all transiting systems. The work presented here exemplifies this point by putatively detecting the primary transit of UCF-1.01 with the use of a linear trend. However, using a quadratic trend, we achieve a better fit to the white light curves and a reduced transit depth that is inconsistent with previous Spitzer measurements. Furthermore, quadratic trends with or without a transit model component produce comparable fits to the available data. Using extant WFC3 transit light curves for GJ 436b, we further validate the quadratic model component by achieving photon-limited model fit residuals and consistent transit depths over multiple epochs. We conclude that, when we fit for a quadratic trend, our new data contradict the prediction of a sub-Earth-sized planet orbiting GJ 436 with the size, period, and ephemeris posited from the Spitzer data by a margin of 3.1σ.
PRODUCING MAGNETAR MAGNETIC FIELDS IN THE MERGER OF BINARY NEUTRON STARS

The merger of binary neutron stars (BNSs) can lead to large amplifications of the magnetic field due to the development of turbulence and instabilities in the fluid, such as the Kelvin–Helmholtz shear instability, which drive small-scale dynamo activity. In order to properly resolve such instabilities and obtain the correct magnetic field amplification, one would need to employ resolutions that are currently unfeasible in global general relativistic magnetohydrodynamic simulations of BNS mergers. Here, we present a subgrid model that allows global simulations to take into account the small-scale amplification of the magnetic field which is caused by the development of turbulence during BNS mergers. Assuming dynamo saturation, we show that magnetar-level fields ( ∼ 10 16 G ?> ) can be easily reached, and should therefore be expected from the merger of magnetized BNSs. The total magnetic energy can reach values up to ∼ 10 51 erg ?> and the post-merger remnant can therefore emit strong electromagnetic signals and possibly produce short gamma-ray bursts.
Renormalization of lattice-regularized quantum gravity models I. General considerations

Lattice regularization is a standard technique for the nonperturbative definition of a quantum theory of fields. Several approaches to the construction of a quantum theory of gravity adopt this technique either explicitly or implicitly. A crucial complement to lattice regularization is the process of renormalization through which a continuous description of the quantum theory arises. I provide a comprehensive conceptual discussion of the renormalization of lattice-regularized quantum gravity models. I begin with a presentation of the renormalization group from the Wilsonian perspective. I then consider the application of the renormalization group in four contexts: quantum field theory on a continuous nondynamical spacetime, quantum field theory on a lattice-regularized nondynamical spacetime, quantum field theory of continuous dynamical spacetime, and quantum field theory of lattice-regularized dynamical spacetime. The first three contexts serve to identify successively the particular issues that arise in the fourth context. These issues originate in the inescability of establishing all scales solely on the basis of the dynamics. While most of this discussion rehearses established knowledge, the attention that I pay to these issues, especially the previously underappreciated role of standard units of measure, is largely novel. I conclude by briefly reviewing past studies of renormalization of lattice-regularized quantum gravity models. In the second paper of this two-part series, I illustrate the ideas presented here by proposing a renormalization group scheme for causal dynamical triangulations.
Hybridizing matter-wave and classical accelerometers

We demonstrate a hybrid accelerometer that benefits from the advantages of both conventional and atomic sensors in terms of bandwidth (DC to 430 Hz) and long term stability. First, the use of a real time correction of the atom interferometer phase by the signal from the classical accelerometer enables to run it at best performances without any isolation platform. Second, a servo-lock of the DC component of the conventional sensor output signal by the atomic one realizes a hybrid sensor. This method paves the way for applications in geophysics and in inertial navigation as it overcomes the main limitation of atomic accelerometers, namely the dead times between consecutive measurements.
Effects of confinement for single-well potentials

We study bound states generated by a unique potential minimum in the situation where the system is strongly confined to a bounded region containing the minimum (by imposing Dirichlet boundary conditions). In this case the eigenvalues of the confined system differ from those of the unconfined system by an exponentially small quantity in the semiclassical limit. An asymptotic expansion for this shift is established. The formulas are evaluated explicitly for the harmonic oscillator and an application to the Coulomb potential at a fixed angular momentum is given.
Classical mechanics of economic networks

Financial networks are dynamic. To assess their systemic importance to the world-wide economic network and avert losses we need models that take the time variations of the links and nodes into account. Using the methodology of classical mechanics and Laplacian determinism we develop a model that can predict the response of the financial network to a shock. We also propose a way of measuring the systemic importance of the banks, which we call BankRank. Using European Bank Authority 2011 stress test exposure data, we apply our model to the bipartite network connecting the largest institutional debt holders of the troubled European countries (Greece, Italy, Portugal, Spain, and Ireland). From simulating our model we can determine whether a network is in a "stable" state in which shocks do not cause major losses, or a "unstable" state in which devastating damages occur. Fitting the parameters of the model, which play the role of physical coupling constants, to Eurozone crisis data shows that before the Eurozone crisis the system was mostly in a "stable" regime, and that during the crisis it transitioned into an "unstable" regime. The numerical solutions produced by our model match closely the actual time-line of events of the crisis. We also find that, while the largest holders are usually more important, in the unstable regime smaller holders also exhibit systemic importance. Our model also proves useful for determining the vulnerability of banks and assets to shocks. This suggests that our model may be a useful tool for simulating the response dynamics of shared portfolio networks.
Generalized Uncertainty Principle: Approaches and Applications

In this paper, we review some highlights from the String theory, the black hole physics and the doubly special relativity and some thought experiments which were suggested to probe the shortest distances and/or maximum momentum at the Planck scale. Furthermore, all models developed in order to implement the minimal length scale and/or the maximum momentum in different physical systems are analyzed and compared. They entered the literature as the generalized uncertainty principle (GUP) assuming modified dispersion relation, and therefore are allowed for a wide range of applications in estimating, for example, the inflationary parameters, Lorentz invariance violation, black hole thermodynamics, Saleker–Wigner inequalities, entropic nature of gravitational laws, Friedmann equations, minimal time measurement and thermodynamics of the high-energy collisions. One of the higher-order GUP approaches gives predictions for the minimal length uncertainty. A second one predicts a maximum momentum and a minimal length uncertainty, simultaneously. An extensive comparison between the different GUP approaches is summarized. We also discuss the GUP impacts on the equivalence principles including the universality of the gravitational redshift and the free fall and law of reciprocal action and on the kinetic energy of composite system. The existence of a minimal length and a maximum momentum accuracy is preferred by various physical observations. The concern about the compatibility with the equivalence principles, the universality of gravitational redshift and the free fall and law of reciprocal action should be addressed. We conclude that the value of the GUP parameters remain a puzzle to be verified.
Using social network graph analysis for interest detection

A person's interests exist as an internal state and are difficult to define. Since only external actions are observable, a proxy must be used that represents someone's interests. Techniques like collaborative filtering, behavioral targeting, and hashtag analysis implicitly model an individual's interests. I argue that these models are limited to shallow, temporary interests, which do not reflect people's deeper interests or passions. I propose an alternative model of interests that takes advantage of a user's social graph. The basic principle is that people only follow those that interest them, so the social graph is an effective and robust proxy for people's interests.
Reconstruction of the null-test for the matter density perturbations

We systematically study the null-test for the growth rate data first presented in [S. Nesseris and D. Sapone, ] and we reconstruct it using various combinations of data sets, such as the $f\sigma_8$ and $H(z)$ or Type Ia supernovae (SnIa) data. We perform the reconstruction in two different ways, either by directly binning the data or by fitting various dark energy models. We also examine how well the null-test can be reconstructed by future data by creating mock catalogs based on the cosmological constant model, a model with strong dark energy perturbations, the $f(R)$ and $f(G)$ models, and the large void LTB model that exhibit different evolution of the matter perturbations. We find that with future data similar to an LSST-like survey, the null-test will be able to successfully discriminate between these different cases at the $5\sigma$ level.
Generalized Low Rank Models

Principal components analysis (PCA) is a well-known technique for approximating a tabular data set by a low rank matrix. Here, we extend the idea of PCA to handle arbitrary data sets consisting of numerical, Boolean, categorical, ordinal, and other data types. This framework encompasses many well-known techniques in data analysis, such as nonnegative matrix factorization, matrix completion, sparse and robust PCA, k-means, k-SVD, and maximum margin matrix factorization. The method handles heterogeneous data sets, and leads to coherent schemes for compressing, denoising, and imputing missing entries across all data types simultaneously. It also admits a number of interesting interpretations of the low rank factors, which allow clustering of examples or of features. We propose several parallel algorithms for fitting generalized low rank models, and describe implementations and numerical results.
Dark matter voids in the SDSS galaxy survey

What do we know about voids in the dark matter distribution given the Sloan Digital Sky Survey (SDSS) and assuming the ΛCDM model? Recent application of the Bayesian inference algorithm BORG to the SDSS Data Release 7 main galaxy sample has generated detailed Eulerian and Lagrangian representations of the large-scale structure as well as the possibility to accurately quantify corresponding uncertainties. Building upon these results, we present constrained catalogs of voids in the Sloan volume, aiming at a physical representation of dark matter underdensities and at the alleviation of the problems due to sparsity and biasing on galaxy void catalogs. To do so, we generate data-constrained reconstructions of the presently observed large-scale structure using a fully non-linear gravitational model. We then find and analyze void candidates using the VIDE toolkit. Our methodology therefore predicts the properties of voids based on fusing prior information from simulations and data constraints. For usual void statistics (number function, ellipticity distribution and radial density profile), all the results obtained are in agreement with dark matter simulations. Our dark matter void candidates probe a deeper void hierarchy than voids directly based on the observed galaxies alone. The use of our catalogs therefore opens the way to high-precision void cosmology at the level of the dark matter field. We will make the void catalogs used in this work available at http://www.cosmicvoids.net.
Efficient readout of a single spin state in diamond via spin-to-charge conversion.

Efficient readout of individual electronic spins associated with atomlike impurities in the solid state is essential for applications in quantum information processing and quantum metrology. We demonstrate a new method for efficient spin readout of nitrogen-vacancy (NV) centers in diamond. The method is based on conversion of the electronic spin state of the NV to a charge-state distribution, followed by single-shot readout of the charge state. Conversion is achieved through a spin-dependent photoionization process in diamond at room temperature. Using NVs in nanofabricated diamond beams, we demonstrate that the resulting spin readout noise is within a factor of 3 of the spin projection noise level. Applications of this technique for nanoscale magnetic sensing are discussed.
Equilibrium statistical-thermal models in high-energy physics

We review some recent highlights from the applications of statistical–thermal models to different experimental measurements and lattice QCD thermodynamics that have been made during the last decade. We start with a short review of the historical milestones on the path of constructing statistical–thermal models for heavy-ion physics. We discovered that Heinz Koppe formulated in 1948, an almost complete recipe for the statistical–thermal models. In 1950, Enrico Fermi generalized this statistical approach, in which he started with a general cross-section formula and inserted into it, the simplifying assumptions about the matrix element of the interaction process that likely reflects many features of the high-energy reactions dominated by density in the phase space of final states. In 1964, Hagedorn systematically analyzed the high-energy phenomena using all tools of statistical physics and introduced the concept of limiting temperature based on the statistical bootstrap model. It turns to be quite often that many-particle systems can be studied with the help of statistical–thermal methods. The analysis of yield multiplicities in high-energy collisions gives an overwhelming evidence for the chemical equilibrium in the final state. The strange particles might be an exception, as they are suppressed at lower beam energies. However, their relative yields fulfill statistical equilibrium, as well. We review the equilibrium statistical–thermal models for particle production, fluctuations and collective flow in heavy-ion experiments. We also review their reproduction of the lattice QCD thermodynamics at vanishing and finite chemical potential. During the last decade, five conditions have been suggested to describe the universal behavior of the chemical freeze-out parameters. The higher order moments of multiplicity have been discussed. They offer deep insights about particle production and to critical fluctuations. Therefore, we use them to describe the freeze-out parameters and suggest the location of the QCD critical endpoint. Various extensions have been proposed in order to take into consideration the possible deviations of the ideal hadron gas. We highlight various types of interactions, dissipative properties and location-dependences (spatial rapidity). Furthermore, we review three models combining hadronic with partonic phases; quasi-particle model, linear sigma model with Polyakov potentials and compressible bag model.
Vanishing edge currents in non-$p$-wave topological chiral superconductors

The edge currents of two dimensional topological chiral superconductors with nonzero Cooper pair angular momentum---e.g., chiral $p$-, $d$-, and $f$-wave superconductivity---are studied. Bogoliubov-de Gennes and Ginzburg--Landau calculations are used to show that in the continuum limit, \emph{only} chiral $p$-wave states have a nonzero edge current. Outside this limit, when lattice effects become important, edge currents in non-$p$-wave superconductors are comparatively smaller, but can be nonzero. Using Ginzburg--Landau theory, a simple criterion is derived for when edge currents vanish for non-$p$-wave chiral superconductivity on a lattice. The implications of our results for putative chiral superconductors such as Sr2RuO4 and UPt3 are discussed.
INDIFFERENCE PRICING FOR CONTINGENT CLAIMS: LARGE DEVIATIONS EFFECTS

We study utility indifference prices and optimal purchasing quantities for a nontraded contingent claim in an incomplete semimartingale market with vanishing hedging errors. We make connections with the theory of large deviations. We concentrate on sequences of semicomplete markets where in the nth market, the claim Bn admits the decomposition Bn=Dn+Yn . Here, Dn is replicable by trading in the underlying assets Sn , but Yn is independent of Sn . Under broad conditions, we may assume that Yn vanishes in accordance with a large deviations principle (LDP) as n grows. In this setting, for an exponential investor, we identify the limit of the average indifference price pn(qn) , for qn units of Bn , as n→∞ . We show that if |qn|→∞ , the limiting price typically differs from the price obtained by assuming bounded positions supn|qn|<∞ , and the difference is explicitly identifiable using large deviations theory. Furthermore, we show that optimal purchase quantities occur at the large deviations scaling, and hence large positions arise endogenously in this setting.
QCD sum rule study of the d*(2380)

We systematically construct $I(J^P)=0(3^+)$ six-quark local interpolating currents without derivative operators. We discuss the best choice of operator, and select three $\Delta$-$\Delta$ like operators to perform QCD sum rule analyses to calculate the mass of the $d^*(2380)$. The mass extracted from this analysis is $M_{d^*} = 2.4\pm0.2$ GeV, consistent with the $d^*(2380)$ mass observed by the WASA detector at COSY. We also obtain a sum-rule lower mass bound $M_{d^*} > 2.25$ GeV. We also consider the effect of mixing of singlet dibaryon fields with the same quantum numbers, and perform the QCD sum rule analysis of the mixed interpolating current and extract the mass of the $d^*(2380)$ and its lower mass bound. With optimized mixing parameters, we find that the mixed current does not change the numerical result significantly.
Risk Dynamics in Trade Networks

We introduce a new framework to model interactions among agents which seek to trade to minimize their risk with respect to some future outcome. We quantify this risk using the concept of risk measures from finance, and introduce a class of trade dynamics which allow agents to trade contracts contingent upon the future outcome. We then show that these trade dynamics exactly correspond to a variant of randomized coordinate descent. By extending the analysis of these coordinate descent methods to account for our more organic setting, we are able to show convergence rates for very general trade dynamics, showing that the market or network converges to a unique steady state. Applying these results to prediction markets, we expand on recent results by adding convergence rates and general aggregation properties. Finally, we illustrate the generality of our framework by applying it to agent interactions on a scale-free network.
The Dirac point electron in zero-gravity Kerr–Newman spacetime

Dirac’s wave equation for a point electron in the topologically nontrivial maximal analytically extended electromagnetic Kerr–Newman spacetime is studied in a limit G → 0, where G is Newton’s constant of universal gravitation. The following results are obtained: the formal Dirac Hamiltonian on the static spacelike slices is essentially self-adjoint and the spectrum of the self-adjoint extension is symmetric about zero, featuring a continuum with a gap about zero that, under two smallness conditions, contains a point spectrum. The symmetry result extends to the Dirac operator on a generalization of the zero-G Kerr–Newman spacetime with different electric-monopole/magnetic-dipole-moment ratios.
Fair and profitable bilateral prices under funding costs and collateralization

Bielecki and Rutkowski (2014) introduced and studied a generic nonlinear market model, which includes several risky assets, multiple funding accounts and margin accounts. In this paper, we examine the pricing and hedging of contract both from the perspective of the hedger and the counterparty with arbitrary initial endowments. We derive inequalities for unilateral prices and we give the range for either fair bilateral prices or bilaterally profitable prices. We also study the monotonicity of a unilateral price with respect to the initial endowment. Our study hinges on results for BSDE driven by continuous martingales obtained in Nie and Rutkowski (2014), but we also derive the pricing PDEs for path-independent contingent claims of European style in a Markovian framework.
Simulated identification of epidemic threshold on finite-size networks

Epidemic threshold is one of the most important features of the epidemic dynamics. Through a lot of numerical simulations in classic Susceptible-Infected-Recovered (SIR) and Susceptible-Infected-Susceptible (SIS) models on various types of networks, we study the simulated identification of epidemic thresholds on finite-size networks. We confirm that the susceptibility measure goes awry for the SIR model due to the bimodal distribution of outbreak sizes near the critical point, while the simulated thresholds of the SIS and SIR models can be accurately determined by analyzing the peak of the epidemic variability. We further verify the accuracy of theoretical predictions derived by the heterogeneous mean-field theory (HMF) and the quenched mean-field theory (QMF), by comparing them with the simulated threshold of the SIR model obtained from the variability measure. The results show that the HMF prediction agrees very well with the simulated threshold, except the case that the networks are disassortive, in which the QMF prediction is more close to the simulated threshold.