nils-herrmann/clean_scirepeval huggingface dataset:
A STATISTICAL RECONSTRUCTION OF THE PLANET POPULATION AROUND KEPLER SOLAR-TYPE STARS

Using the cumulative catalog of planets detected by the NASA Kepler mission, we reconstruct the intrinsic occurrence of Earth- to Neptune-size (1–4 R⊕) planets and their distributions with radius and orbital period. We analyze 76,711 solar-type (0.8 < R*/R☉ < 1.2) stars with 430 planets on 20–200 day orbits, excluding close-in planets that may have been affected by the proximity to the host star. Our analysis considers errors in planet radii and includes an “iterative simulation” technique that does not bin the data. We find a radius distribution that peaks at 2–2.8 Earth radii, with lower numbers of smaller and larger planets. These planets are uniformly distributed with logarithmic period, and the mean number of such planets per star is 0.46 ± 0.03. The occurrence is ∼0.66 if planets interior to 20 days are included. We estimate the occurrence of Earth-size planets in the “habitable zone” (defined as 1–2 R⊕, 0.99–1.7 AU for solar-twin stars) as . Our results largely agree with those of Petigura et al., although we find a higher occurrence of 2.8–4 Earth-radii planets. The reasons for this excess are the inclusion of errors in planet radius, updated Huber et al. stellar parameters, and also the exclusion of planets that may have been affected by proximity to the host star.
Matter creation in a nonsingular bouncing cosmology

We examine reheating in the two-field matter bounce cosmology. In this model, the universe evolves from a matter-dominated phase of contraction to an Ekpyrotic phase of contraction before the nonsingular bounce. The Ekpyrotic phase frees the model from unwanted anisotropies, but leaves the universe cold and empty of particles after the bounce. For this reason, we explore two particle production mechanisms which take place during the course of the cosmological evolution: Parker particle production where the matter field couples only to gravity and particle creation via interactions between the matter field and the bounce field. Although we show that both mechanisms can produce particles in this model, we find that Parker particle production is sufficient to reheat the universe to high temperatures. Thus there is {\it{a priori}} no need to add an interaction term to the Lagrangian of the model. Still, particle creation via interactions can contribute to the formation of matter and radiation, but only if the coupling between the fields is tuned to be large.
Generalized Mixability via Entropic Duality

textabstract Mixability is a property of a loss which characterizes when 
 constant regret is possible in the game of prediction with expert 
 advice. We show that a key property of mixability generalizes, and 
 the $\exp$ and $\log$ operations present in the usual theory are not as 
 special as one might have thought. 
 In doing so we introduce a 
 more general notion of $\Phi$-mixability where $\Phi$ is a general 
 entropy (\ie, any convex function on probabilities). We show how a property 
 shared by the convex dual of any such entropy yields a natural 
 algorithm (the minimizer of a regret bound) which, analogous to the 
 classical Aggregating Algorithm, is guaranteed a constant regret 
 when used with $\Phi$-mixable losses. 
 We characterize which $\Phi$ have non-trivial $\Phi$-mixable losses and 
 relate $\Phi$-mixability and its associated Aggregating 
 Algorithm to potential-based methods, a Blackwell-like 
 condition, mirror descent, and risk measures from finance. 
 We also define a notion of ``dominance'' between different 
 entropies in terms of bounds they guarantee and 
 conjecture that classical mixability gives optimal bounds, for which we 
 provide some supporting empirical evidence.
How to hedge extrapolated yield curves

We present a framework on how to hedge the interest rate sensitivity of liabilities discounted by an extrapolated yield curve. The framework is based on functional analysis in that we consider the extrapolated yield curve as a functional of an observed yield curve and use its Gâteaux variation to understand the sensitivity to any possible yield curve shift. We apply the framework to analyse the Smith-Wilson method of extrapolation that is proposed by the European Insurance and Occupational Pensions Authority (EIOPA) in the coming EU legislation Solvency II, and the method recently introduced, and currently prescribed, by the Swedish Financial Supervisory Authority.
Fast, Robust and Non-convex Subspace Recovery

This work presents a fast and non-convex algorithm for robust subspace recovery. The data sets considered include inliers drawn around a low-dimensional subspace of a higher dimensional ambient space, and a possibly large portion of outliers that do not lie nearby this subspace. The proposed algorithm, which we refer to as Fast Median Subspace (FMS), is designed to robustly determine the underlying subspace of such data sets, while having lower computational complexity than existing methods. We prove convergence of the FMS iterates to a stationary point. Further, under a special model of data, FMS converges to a point which is near to the global minimum with overwhelming probability. Under this model, we show that the iteration complexity is globally bounded and locally $r$-linear. The latter theorem holds for any fixed fraction of outliers (less than 1) and any fixed positive distance between the limit point and the global minimum. Numerical experiments on synthetic and real data demonstrate its competitive speed and accuracy.
Mathematical modeling applied to the left ventricle of heart

How can mathematics help us to understand the mechanism of the cardiac motion? The best known approach is to take a mathematical model of the fibered structure, insert it into a more-or-less complex model of cardiac architecture, and then study the resulting fibers of activation that propagate through the myocardium. In our paper, we have attempted to create a novel software capable of demonstrate left ventricular (LV) model in normal hearts. 
 Echocardiography was performed on 70 healthy volunteers. Data evaluated included: velocity (radial, longitudinal, rotational and vector point), displacement (longitudinal and rotational), strain rate (longitudinal and circumferential) and strain (radial, longitudinal and circumferential) of all 16 LV myocardial segments. Using these data, force vectors of myocardial samples were estimated by MATLAB software, interfaced in the echocardiograph system. Dynamic orientation contraction (through the cardiac cycle) of every individual myocardial fiber could be created by adding together the sequential steps of the multiple fragmented sectors of that fiber. This way we attempted to mechanically illustrate the global LV model. 
Result: Our study shows that in normal cases myocardial fibers initiate from the posterior basal region of the heart, continues through the LV free wall, reaches the septum, loops around the apex, ascends, and ends at the superior-anterior edge of LV. 
 We were able to define the whole LV myocardial model mathematically, by MATLAB software in normal subjects. This will enable physicians to diagnose and follow up many cardiac diseases when this software is interfaced within echocardiographic machines.
GPU Accelerated Hybrid Tree Algorithm for Collision Less N-body Simulations

We propose a hybrid tree algorithm for reducing calculation and communication cost of collision-less N-body simulations. The concept of our algorithm is that we split interaction force into two parts: hard-force from neighbor particles and soft-force from distant particles, and applying different time integration for the forces. For hard-force calculation, we can efficiently reduce the calculation and communication cost of the parallel tree code because we only need data of neighbor particles for this part. We implement the algorithm on GPU clusters to accelerate force calculation for both hard and soft force. As the result of implementing the algorithm on GPU clusters, we were able to reduce the communication cost and the total execution time to 40% and 80% of that of a normal tree algorithm, respectively. In addition, the reduction factor relative the normal tree algorithm is smaller for large number of processes, and we expect that the execution time can be ultimately reduced down to about 70% of the normal tree algorithm.
Optimal Investment with Time-Varying Stochastic Endowments

This paper considers a utility maximization and optimal asset allocation problem in the presence of a stochastic endowment that cannot be fully hedged through trading in the financial market. We rely on the dynamic programming approach to solve the optimization problem. The properties of the value function, particularly the homogeneity, are used to reduce the HJB equation by one dimension. Furthermore, the optimal strategy is derived, and its asymptotic behavior is discussed.
Further heuristics for $k$-means: The merge-and-split heuristic and the $(k, l)$-means

Finding the optimal $k$-means clustering is NP-hard in general and many heuristics have been designed for minimizing monotonically the $k$-means objective. We first show how to extend Lloyd's batched relocation heuristic and Hartigan's single-point relocation heuristic to take into account empty-cluster and single-point cluster events, respectively. Those events tend to increasingly occur when $k$ or $d$ increases, or when performing several restarts. First, we show that those special events are a blessing because they allow to partially re-seed some cluster centers while further minimizing the $k$-means objective function. Second, we describe a novel heuristic, merge-and-split $k$-means, that consists in merging two clusters and splitting this merged cluster again with two new centers provided it improves the $k$-means objective. This novel heuristic can improve Hartigan's $k$-means when it has converged to a local minimum. We show empirically that this merge-and-split $k$-means improves over the Hartigan's heuristic which is the {\em de facto} method of choice. Finally, we propose the $(k,l)$-means objective that generalizes the $k$-means objective by associating the data points to their $l$ closest cluster centers, and show how to either directly convert or iteratively relax the $(k,l)$-means into a $k$-means in order to reach better local minima.
Practical Applications of Cosmology to Human Society

Complex systems throughout Nature display structures and functions that are built and maintained, at least in part, by optimal energies flowing through them—not specific, ideal values, rather ranges in energy rate density below which systems are starved and above which systems are destroyed. Cosmic evolution, as a physical cosmology that notably includes life, is rich in empirical findings about many varied systems that can potentially help assess global problems facing us here on Earth. Despite its grand and ambitious objective to unify theoretical understanding of all known complex systems from big bang to humankind, cosmic evolution does have useful, practical applications from which humanity could benefit. Cosmic evolution’s emphasis on quantitative data analyses might well inform our attitudes toward several serious issues now challenging 21 st -century society, including global warming, smart machines, world economics, and cancer research. This paper comprises one physicist’s conjectures about each of these applied topics, suggesting how energy-flow modeling can guide our search for viable solutions to real-world predicaments confronting civilization today.
Monolayer graphene bolometer as a sensitive far-IR detector

In this paper we give a detailed analysis of the expected sensitivity and operating conditions in the power detection mode of a hot-electron bolometer (HEB) made from a few μm2 of monolayer graphene (MLG) flake which can be embedded into either a planar antenna or waveguide circuit via NbN (or NbTiN) superconducting contacts with critical temperature ~ 14 K. Recent data on the strength of the electron-phonon coupling are used in the present analysis and the contribution of the readout noise to the Noise Equivalent Power (NEP) is explicitly computed. The readout scheme utilizes Johnson Noise Thermometry (JNT) allowing for Frequency-Domain Multiplexing (FDM) using narrowband filter coupling of the HEBs. In general, the filter bandwidth and the summing amplifier noise have a significant effect on the overall system sensitivity. The analysis shows that the readout contribution can be reduced to that of the bolometer phonon noise if the detector device is operated at 0.05 K and the JNT signal is read at about 10 GHz where the Johnson noise emitted in equilibrium is substantially reduced. Beside the high sensitivity (NEP < 10-20 W/Hz1/2), this bolometer does not have any hard saturation limit and thus can be used for far-IR sky imaging with arbitrary contrast. By changing the operating temperature of the bolometer the sensitivity can be fine tuned to accommodate the background photon flux in a particular application. By using a broadband low-noise kinetic inductance parametric amplifier, ~100s of graphene HEBs can be read simultaneously without saturation of the system output.
Extrinsic photodiodes for integrated mid-infrared silicon photonics

Silicon photonics has recently been proposed for a diverse set of applications at mid-infrared wavelengths including spectroscopy, chemical and biological sensing, free-space communications, and nonlinear optics. While optical-to-electronic signal conversion is essential to these applications, on-chip photodetection remains an important and challenging task. In this Letter, we present room temperature operation of Zn+-implanted Si waveguide photodiodes from 2.2 to 2.4 μm, with measured responsivities of up to 87±29  mA/W and low dark currents of <10  μA. Photocurrent generation is achieved by transitions from dopant-induced sub-bandgap trap states located ≈0.58  eV above the valence band to the conduction band, resulting in a peak detection wavelength of ≈2.3  μm. The wavelength of operation can be increased by choosing a dopant with an appropriate trap level, opening the possibility for on-chip detection throughout the mid-infrared.
Compressive Imaging and Characterization of Sparse Light Deflection Maps

Light rays incident on a transparent object of uniform refractive index undergo deflections, which uniquely characterize the surface geometry of the object. Associated with each point on the surface is a deflection map (or spectrum) which describes the pattern of deflections in various directions. This article presents a novel method to efficiently acquire and reconstruct sparse deflection spectra induced by smooth object surfaces. To this end, we leverage the framework of compressed sensing (CS) in a particular implementation of a schlieren deflectometer, i.e., an optical system providing linear measurements of deflection spectra with programmable spatial light modulation patterns. In particular, we design those modulation patterns on the principle of spread spectrum CS for reducing the number of observations. Interestingly, the ability of our device to simultaneously observe the deflection spectra on a dense discretization of the object surface is related to a particular multiple measurement vector mode...
Analysis of the microbunching instability in a mid-energy electron linac

Microbunching instability usually exists in the linear accelerator (linac) of a free electron laser (FEL) facility. If it is not controlled effectively, the beam quality will be damaged seriously and the machine will not operate properly. In the electron linac of a soft X-ray FEL device, because the electron energy is not very high, the problem can become even more serious. As a typical example, the microbunching instability in the linac of the proposed Shanghai Soft X-ray Free Electron Laser facility (SXFEL) is investigated in detail by means of both analytical formulae and simulation tools. In the study, a new mechanism introducing random noise into the beam current profile as the beam passes through a chicane-type bunch compressor is proposed. The higher-order modes that appear in the simulations suggest that further improvement of the current theoretical model of the instability is needed.
Carrying capacity in growing networks

In this work, a growing network model that can generate a random network with a finite degree in infinite time is studied. The dynamics are governed by a rule where the degree increases under a scheme similar to the Malthus–Verhulst model in the context of population growth. The degree distribution is analysed in both stationary and time-dependent regimes through some exact results and simulations, and a scaling behaviour is found in asymptotically large time. For finite times, the time-dependent degree distribution displays an accumulation of hubs as a result of competition between attractive and repulsive terms in linking probability.
The Links Have It: Infobox Generation by Summarization over Linked Entities

Online encyclopedia such as Wikipedia has become one of the best sources of knowledge. Much effort has been devoted to expanding and enriching the structured data by automatic information extraction from unstructured text in Wikipedia. Although remarkable progresses have been made, their effectiveness and efficiency is still limited as they try to tackle an extremely difficult natural language understanding problems and heavily relies on supervised learning approaches which require large amount effort to label the training data. In this paper, instead of performing information extraction over unstructured natural language text directly, we focus on a rich set of semi-structured data in Wikipedia articles: linked entities. The idea of this paper is the following: If we can summarize the relationship between the entity and its linked entities, we immediately harvest some of the most important information about the entity. To this end, we propose a novel rank aggregation approach to remove noise, an effective clustering and labeling algorithm to extract knowledge.
Magnetic ordered structure dependence of magnetic refrigeration efficiency

We have investigated the relation between magnetic ordered structure and magnetic refrigeration efficiency in the Ising model on a simple cubic lattice using Monte Carlo simulations. The magnetic entropy behaviors indicate that the protocol, which was first proposed in [ (2014).], can produce the maximum isothermal magnetic entropy change and the maximum adiabatic temperature change in antiferromagnets. Furthermore, the total amount of heat transfer under the proposed protocol reaches a maximum. The relation between measurable physical quantities and magnetic refrigeration efficiency is also discussed.
Independent measurement of the neutrino mixing angle theta(13) via neutron capture on hydrogen at Daya Bay

A new measurement of the θ_(13) mixing angle has been obtained at the Daya Bay Reactor Neutrino Experiment via the detection of inverse beta decays tagged by neutron capture on hydrogen. The antineutrino events for hydrogen capture are distinct from those for gadolinium capture with largely different systematic uncertainties, allowing a determination independent of the gadolinium-capture result and an improvement on the precision of the θ_(13) measurement. With a 217-day antineutrino data set obtained with six antineutrino detectors and from six 2.9 GW_(th) reactors, the rate deficit observed at the far hall is interpreted as sin^2 2θ_(13) = 0.083±0.018 in the three-flavor oscillation model. When combined with the gadolinium-capture result from Daya Bay, we obtain sin^2 2θ_(13) = 0.089±0.008 as the final result for the six-antineutrino-detector configuration of the Daya Bay experiment.
Thermodynamic phase transition in the rainbow Schwarzschild black hole

We study the thermodynamic phase transition in the rainbow Schwarzschild black hole where the metric depends on the energy of the test particle. Identifying the black hole temperature with the energy from the modified dispersion relation, we obtain the modified entropy and thermodynamic energy along with the modified local temperature in the cavity to provide well defined black hole states. It is found that apart from the conventional critical temperature related to Hawking-Page phase transition there appears an additional critical temperature which is of relevance to the existence of a locally stable tiny black hole; however, the off-shell free energy tells us that this black hole should eventually tunnel into the stable large black hole. Finally, we discuss the reason why the temperature near the horizon is finite in the rainbow black hole by employing the running gravitational coupling constant, whereas it is divergent near the horizon in the ordinary Schwarzschild black hole.
Variance Competitiveness for Monotone Estimation: Tightening the Bounds

Random samples are extensively used to summarize massive data sets and facilitate scalable analytics. Coordinated sampling, where samples of different data sets "share" the randomization, is a powerful method which facilitates more accurate estimation of many aggregates and similarity measures. We recently formulated a model of {\it Monotone Estimation Problems} (MEP), which can be applied to coordinated sampling, projected on a single item. MEP estimators can then be used to estimate sum aggregates, such as distances, over coordinated samples. For MEP, we are interested in estimators that are unbiased and nonnegative. We proposed {\it variance competitiveness} as a quality measure of estimators: For each data vector, we consider the minimum variance attainable on it by an unbiased and nonnegative estimator. We then define the competitiveness of an estimator as the maximum ratio, over data, of the expectation of the square to the minimum possible. We also presented a general construction of the L$^*$ estimator, which is defined for any MEP for which a nonnegative unbiased estimator exists, and is at most 4-competitive. 
Our aim here is to obtain tighter bounds on the {\em universal ratio}, which we define to be the smallest competitive ratio that can be obtained for any MEP. We obtain an upper bound of 3.375, improving over the bound of $4$ of the L$^*$ estimator. We also establish a lower bound of 1.44. The lower bound is obtained by constructing the {\it optimally competitive} estimator for particular MEPs. The construction is of independent interest, as it facilitates estimation with instance-optimal competitiveness.
Strong Regularities in Growth and Decline of Popularity of Social Media Services

We analyze general trends and pattern in time series that characterize the dynamics of collective attention to social media services and Web-based businesses. Our study is based on search frequency data available from Google Trends and considers 175 different services. For each service, we collect data from 45 different countries as well as global averages. This way, we obtain more than 8,000 time series which we analyze using diffusion models from the economic sciences. We find that these models accurately characterize the empirical data and our analysis reveals that collective attention to social media grows and subsides in a highly regular and predictable manner. Regularities persist across regions, cultures, and topics and thus hint at general mechanisms that govern the adoption of Web-based services. We discuss several cases in detail to highlight interesting findings. Our methods are of economic interest as they may inform investment decisions and can help assessing at what stage of the general life-cycle a Web service is at.
Chiral mass-gap in curved space.

We discuss a new type of QCD phenomenon induced in curved space. In the QCD vacuum, a mass-gap of Dirac fermions is attributed to the spontaneous breaking of chiral symmetry. If the curvature is positive large, the chiral condensate melts but a chiral invariant mass-gap can still remain, which we name the chiral gap effect in curved space. This leads to decoupling of quark deconfinement which implies a view of black holes surrounded by a first-order QCD phase transition.