nils-herrmann/clean_scirepeval huggingface dataset:
Statistical Basis for Predicting Technological Progress

Forecasting technological progress is of great interest to engineers, policy makers, and private investors. Several models have been proposed for predicting technological improvement, but how well do these models perform? An early hypothesis made by Theodore Wright in 1936 is that cost decreases as a power law of cumulative production. An alternative hypothesis is Moore's law, which can be generalized to say that technologies improve exponentially with time. Other alternatives were proposed by Goddard, Sinclair et al., and Nordhaus. These hypotheses have not previously been rigorously tested. Using a new database on the cost and production of 62 different technologies, which is the most expansive of its kind, we test the ability of six different postulated laws to predict future costs. Our approach involves hindcasting and developing a statistical model to rank the performance of the postulated laws. Wright's law produces the best forecasts, but Moore's law is not far behind. We discover a previously unobserved regularity that production tends to increase exponentially. A combination of an exponential decrease in cost and an exponential increase in production would make Moore's law and Wright's law indistinguishable, as originally pointed out by Sahal. We show for the first time that these regularities are observed in data to such a degree that the performance of these two laws is nearly the same. Our results show that technological progress is forecastable, with the square root of the logarithmic error growing linearly with the forecasting horizon at a typical rate of 2.5% per year. These results have implications for theories of technological change, and assessments of candidate technologies and policies for climate change mitigation.
In search of lost spacetime: philosophical issues arising in quantum gravity

This paper issues a call to arms and seeks to entice the reader with some of the most captivating philosophical puzzles arising in quantum gravity. The analysis will be prefaced, in Section 1, by general considerations concerning the need for finding a quantum theory of gravity and the methods used in the pursuit of this goal. After mapping the field in Section 2, loop quantum gravity is introduced as an important competitor and particularly rich source of philosophical trouble in Section 3. The so-called problem of time, i.e. the puzzle that no genuine physical quantity can change, is discussed in Section 4. Finally, Section 5 analyzes how the familiar continuous spacetime structure might re-emerge from the fundamental, non-spatiotemporal structure.
Two Photon Exchange for Exclusive Pion Electroproduction

We perform detailed calculations of two-photon-exchange QED corrections to the cross section of pion electroproduction. The results are obtained with and without the soft-photon approximation; analytic expressions for the radiative corrections are derived. The relative importance of the two-photon correction is analyzed for the kinematics of several experiments at Jefferson Lab. A significant, over 20%, effect due to two-photon exchange is predicted for the backward angles of electron scattering at large transferred momenta.
The Keynesian theory and the manufactured industry in Portugal

This work aims to test the Verdoorn Law, with the alternative specifications of (1)Kaldor (1966), for the five Portuguese regions (NUTS II), from 1986 to 1994 and from 1995 to 1999. It is intended to test, yet in this work, the alternative interpretation of (2)Rowthorn (1975) about the Verdoorn's Law for the same regions and periods. The results of this study are about each one of the manufactured industries operating in the Portuguese regions.
Optimal deterministic routing and sorting on the congested clique

Consider a clique of <i>n</i> nodes, where in each synchronous round each pair of nodes can exchange <i>O(log n)</i> bits. We provide deterministic constant-time solutions for two problems in this model. The first is a routing problem where each node is source and destination of <i>n</i> messages of size <i>O(log n)</i>. The second is a sorting problem where each node <i>i</i> is given <i>n</i> keys of size <i>O(log n)</i> and needs to receive the <i>i<sup>th</sup></i> batch of <i>n</i> keys according to the global order of the keys. The latter result also implies deterministic constant-round solutions for related problems such as selection or determining modes.
JIGSAW PERCOLATION: WHAT SOCIAL NETWORKS CAN COLLABORATIVELY SOLVE A PUZZLE?

We introduce a new kind of percolation on finite graphs called jigsaw percolation. This model attempts to capture networks of people who innovate by merging ideas and who solve problems by piecing together solutions. Each person in a social network has a unique piece of a jigsaw puzzle. Acquainted people with compatible puzzle pieces merge their puzzle pieces. More generally, groups of people with merged puzzle pieces merge if the groups know one another and have a pair of compatible puzzle pieces. The social network solves the puzzle if it eventually merges all the puzzle pieces. For an Erd\H{o}s-R\'{e}nyi social network with $n$ vertices and edge probability $p_n$, we define the critical value $p_c(n)$ for a connected puzzle graph to be the $p_n$ for which the chance of solving the puzzle equals $1/2$. We prove that for the $n$-cycle (ring) puzzle, $p_c(n)=\Theta(1/\log n)$, and for an arbitrary connected puzzle graph with bounded maximum degree, $p_c(n)=O(1/\log n)$ and $\omega(1/n^b)$ for any $b>0$. Surprisingly, with probability tending to 1 as the network size increases to infinity, social networks with a power-law degree distribution cannot solve any bounded-degree puzzle. This model suggests a mechanism for recent empirical claims that innovation increases with social density, and it might begin to show what social networks stifle creativity and what networks collectively innovate.
Who Replaces Whom? Local versus Non-local Replacement in Social and Evolutionary Dynamics

In this paper, we inspect well-known population genetics and social dynamics models. In these models, interacting individuals, while participating in a self-organizing process, give rise to the emergence of complex behaviors and patterns. While one main focus in population genetics is on the adaptive behavior of a population, social dynamics is more often concerned with the splitting of a connected array of individuals into a state of global polarization, that is, the emergence of speciation. Applying computational and mathematical tools we show that the way the mechanisms of selection, interaction and replacement are constrained and combined in the modeling have an important bearing on both adaptation and the emergence of speciation. Differently (un)constraining the mechanism of individual replacement provides the conditions required for either speciation or adaptation, since these features appear as two opposing phenomena, not achieved by one and the same model. Even though natural selection, operating as an external, environmental mechanism, is neither necessary nor sufficient for the creation of speciation, our modeling exercises highlight the important role played by natural selection in the interplay of the evolutionary and the self-organization modeling methodologies.
Pseudo-likelihood methods for community detection in large sparse networks

Many algorithms have been proposed for fitting network models with communities, but most of them do not scale well to large networks, and often fail on sparse networks. Here we propose a new fast pseudo-likelihood method for fitting the stochastic block model for networks, as well as a variant that allows for an arbitrary degree distribution by conditioning on degrees. We show that the algorithms perform well under a range of settings, including on very sparse networks, and illustrate on the example of a network of political blogs. We also propose spectral clustering with perturbations, a method of independent interest, which works well on sparse networks where regular spectral clustering fails, and use it to provide an initial value for pseudo-likelihood. We prove that pseudo-likelihood provides consistent estimates of the communities under a mild condition on the starting value, for the case of a block model with two communities.
Compression of next-generation sequencing reads aided by highly efficient de novo assembly

We present Quip, a lossless compression algorithm for next-generation sequencing data in the FASTQ and SAM/BAM formats. In addition to implementing reference-based compression, we have developed, to our knowledge, the first assembly-based compressor, using a novel de novo assembly algorithm. A probabilistic data structure is used to dramatically reduce the memory required by traditional de Bruijn graph assemblers, allowing millions of reads to be assembled very efficiently. Read sequences are then stored as positions within the assembled contigs. This is combined with statistical compression of read identifiers, quality scores, alignment information and sequences, effectively collapsing very large data sets to <15% of their original size with no loss of information.  Quip is freely available under the 3-clause BSD license from http://cs.washington.edu/homes/dcjones/quip.
Search for a dark matter particle family

I suggest a simple signature for new particles which are unstable partners of a dark matter particle. The suggested mass range is from 8 TeV to 3 PeV, the former being the mass of the dark matter particle and the latter being the knee energy mass scale from the cosmic ray energy spectrum. It can be the energy spectrum of a specific particle such as a muon, a neutrino, jets or any other particles produced in cosmic ray showers, as long as the spectrum is measued. As for the detection of a 3 PeV particle by the neutrino energy spectrum, all dark matter targets throughout the galaxy that are bombarded by high energy cosmic rays and high energy dark matter particles contribute to the process. This is new in the study of dark matter physics.
Revealing the inner circumstellar disk of the T Tauri star S Coronae Australis N using the VLTI

We investigate the structure of the circumstellar disk of the T Tauri star S CrA N and test whether the observations agree with the standard picture proposed for Herbig Ae stars.  Our observations were carried out with the VLTI/AMBER instrument in the H and K bands with the low spectral resolution mode. For the interpretation of our near-infrared AMBER and archival mid-infrared MIDI visibilities, we employed both geometric and temperature-gradient models.  To characterize the disk size, we first fitted geometric models consisting of a stellar point source, a ring-shaped disk, and a halo structure to the visibilities. In the H and K bands, we measured ring-fit radii of 0.73 ± 0.03 mas (corresponding to 0.095 ± 0.018 AU for a distance of 130 pc) and 0.85 ± 0.07 mas (0.111 ± 0.026 AU), respectively. This K-band radius is approximately two times larger than the dust sublimation radius of ≈0.05 AU expected for a dust sublimation temperature of 1500 K and gray dust opacities, but approximately agrees with the prediction of models including backwarming (namely a radius of ≈0.12 AU). The derived temperature-gradient models suggest that the disk is approximately face-on consisting of two disk components with a gap between star and disk. The inner disk component has a temperature close to the dust sublimation temperature and a quite narrow intensity distribution with a radial extension from 0.11 AU to 0.14 AU.  Both our geometric and temperature-gradient models suggest that the T Tauri star S CrA N is surrounded by a circumstellar disk that is truncated at an inner radius of ≈0.11 AU. The narrow extension of the inner temperature-gradient disk component implies that there is a hot inner rim.
Kernelized Supervised Dictionary Learning

In this paper, we propose supervised dictionary learning (SDL) by incorporating information on class labels into the learning of the dictionary. To this end, we propose to learn the dictionary in a space where the dependency between the signals and their corresponding labels is maximized. To maximize this dependency, the recently introduced Hilbert Schmidt independence criterion (HSIC) is used. One of the main advantages of this novel approach for SDL is that it can be easily kernelized by incorporating a kernel, particularly a data-dependent kernel such as normalized compression distance, into the formulation. The learned dictionary is compact and the proposed approach is fast. We show that it outperforms other unsupervised and supervised dictionary learning approaches in the literature, using real-world data.
Cooperation on Social Networks and Its Robustness

In this work we have used computer models of social-like networks to show by extensive numerical simulations that cooperation in evolutionary games can emerge and be stable on this class of networks. The amounts of cooperation reached are at least as much as in scale-free networks but here the population model is more realistic. Cooperation is robust with respect to different strategy update rules, population dynamics, and payoff computation. Only when straight average payoff is used or there is high strategy or network noise does cooperation decrease in all games and disappear in the Prisoner's Dilemma.
The Long Neglected Critically Leveraged Portfolio

We show that the efficient frontier for a portfolio in which short positions precisely offset the long ones is composed of a pair of straight lines through the origin of the risk-return plane. This unique but important case has been overlooked because the original formulation of the mean-variance model by Markowitz as well as all its subsequent elaborations have implicitly excluded it by using portfolio weights rather than actual amounts allocated to individual assets. We also elucidate the properties of portfolios where short positions dominate the long ones, a case which has similarly been obscured by the adoption of portfolio weights.
Substellar Companions to Seven Evolved Intermediate-Mass Stars

We report the detections of substellar companions orbiting around seven evolved intermediate-mass stars from precise Doppler measurements at Okayama Astrophysical Observatory. o UMa (G4 II-III) is a giant with a mass of 3.1 M_sun and hosts a planet with minimum mass of m_2sini=4.1 M_J in an orbit with a period P=1630 d and an eccentricity e=0.13. This is the first planet candidate (< 13 M_J) ever discovered around stars more massive than 3 M_sun. o CrB (K0 III) is a 2.1 M_sun giant and has a planet of m_2sini=1.5 M_J in a 187.8 d orbit with e=0.19. This is one of the least massive planets ever discovered around ~2 M_sun stars. HD 5608 (K0 IV) is an 1.6 M_sun subgiant hosting a planet of m_2sini=1.4 M_J in a 793 d orbit with e=0.19. The star also exhibits a linear velocity trend suggesting the existence of an outer, more massive companion. 75 Cet (G3 III:) is a 2.5 M_sun giant hosting a planet of m_2sini=3.0 M_J in a 692 d orbit with e=0.12. The star also shows possible additional periodicity of about 200 d and 1880 d with velocity amplitude of ~7--10 m/s, although these are not significant at this stage. nu Oph (K0 III) is a 3.0 M_sun giant and has two brown-dwarf companions of m_2sini= 24 M_J and 27 M_J, in orbits with P=530.3 d and 3190 d, and e=0.126 and 0.17, respectively, which were independently announced by Quirrenbach et al. (2011). The ratio of the periods is close to 1:6, suggesting that the companions are in mean motion resonance. We also independently confirmed planets around k CrB (K0 III-IV) and HD 210702 (K1 IV), which had been announced by Johnson et al. (2008) and Johnson et al. (2007a), respectively. All of the orbital parameters we obtained are consistent with the previous results.
Electrical conductivity of quark matter at finite T under external magnetic field

We investigate the electrical conductivity (sigma) of quark matter via the Kubo formula at finite temperature and zero quark density (T>0, mu=0) in the presence of an external strong magnetic field. For this purpose, we employ the dilute instanton-liquid model, taking into account its temperature modification with the trivial-holonomy caloron distribution. By doing that, the momentum and temperature dependences for the effective quark mass and model renormalization scale are carefully evaluated. From the numerical results, it turns out that sigma\approx(0.02 ~ 0.15)/fm for T=(0 ~ 400) MeV with the relaxation time tau=(0.3 ~ 0.9) fm. In addition, we also parameterize the electrical conductivity as sigma/T ~ (0.46,0.77,1.08,1.39)C_EM for tau=(0.3,0.5,0.7,0.9) fm, respectively. These results are well compatible with other theoretical estimations, including those from the lattice QCD simulations. It also turns out that the external magnetic field plays only a minor role for sigma even for the very strong one B_0 ~ m^2_pi*10 and becomes relatively effective for T\lesssim200 MeV. Moreover, we compute the soft photon emission rate from the quark-gluon plasma, using the electrical conductivity calculated.
Binary black-hole mergers in magnetized disks: simulations in full general relativity.

We present results from the first fully general relativistic, magnetohydrodynamic (MHD) simulations of an equal-mass black-hole binary (BHBH) in a magnetized, circumbinary accretion disk. We simulate both the pre- and postdecoupling phases of a BHBH-disk system and both "cooling" and "no-cooling" gas flows. Prior to decoupling, the competition between the binary tidal torques and the effective viscous torques due to MHD turbulence depletes the disk interior to the binary orbit. However, it also induces a two-stream accretion flow and mildly relativistic polar outflows from the BHs. Following decoupling, but before gas fills the low-density "hollow" surrounding the remnant, the accretion rate is reduced, while there is a prompt electromagnetic luminosity enhancement following merger due to shock heating and accretion onto the spinning BH remnant. This investigation, though preliminary, previews more detailed general relativistic, MHD simulations we plan to perform in anticipation of future, simultaneous detections of gravitational and electromagnetic radiation from a merging BHBH-disk system.
On dependence consistency of CoVaR and some other systemic risk measures

This paper is dedicated to the consistency of systemic risk measures with respect to stochastic dependence. It compares two alternative notions of Conditional Value-at-Risk (CoVaR) available in the current literature. These notions are both based on the conditional distribution of a random variable Y given a stress event for a random variable X , but they use different types of stress events. We derive representations of these alternative CoVaR notions in terms of copulas, study their general dependence consistency and compare their performance in several stochastic models. Our central finding is that conditioning on X  ≥ VaR α ( X ) gives a much better response to dependence between X and Y than conditioning on X  = VaR α ( X ). We prove general results that relate the dependence consistency of CoVaR using conditioning on X  ≥ VaR α ( X ) to well established results on concordance ordering of multivariate distributions or their copulas. These results also apply to some other systemic risk measures, such as the Marginal Expected Shortfall (MES) and the Systemic Impact Index (SII). We provide counterexamples showing that CoVaR based on the stress event X  = VaR α ( X ) is not dependence consistent. In particular, if ( X ,  Y ) is bivariate normal, then CoVaR based on X  = VaR α ( X ) is not an increasing function of the correlation parameter. Similar issues arise in the bivariate t model and in the model with t margins and a Gumbel copula. In all these cases, CoVaR based on X  ≥ VaR α ( X ) is an increasing function of the dependence parameter.
MARFCAT: Transitioning to Binary and Larger Data Sets of SATE IV

We present a second iteration of a machine learning approach to static code analysis and fingerprinting for weaknesses related to security, software engineering, and others using the open-source MARF framework and the MARFCAT application based on it for the NIST's SATE IV static analysis tool exposition workshop's data sets that include additional test cases, including new large synthetic cases. To aid detection of weak or vulnerable code, including source or binary on different platforms the machine learning approach proved to be fast and accurate to for such tasks where other tools are either much slower or have much smaller recall of known vulnerabilities. We use signal and NLP processing techniques in our approach to accomplish the identification and classification tasks. MARFCAT's design from the beginning in 2010 made is independent of the language being analyzed, source code, bytecode, or binary. In this follow up work with explore some preliminary results in this area. We evaluated also additional algorithms that were used to process the data.
Bounce and cyclic cosmology in extended nonlinear massive gravity

We investigate non-singular bounce and cyclic cosmological evolutions in a universe governed by the extended nonlinear massive gravity, in which the graviton mass is promoted to a scalar-field potential. The extra freedom of the theory can lead to certain energy conditions violations and drive cyclicity with two different mechanisms: either with a suitably chosen scalar-field potential under a given Stuckelberg-scalar function, or with a suitably chosen Stuckelberg-scalar function under a given scalar-field potential. Our analysis shows that extended nonlinear massive gravity can alter significantly the evolution of the universe at both early and late times.
COLD MOLECULAR GAS ALONG THE COOLING X-RAY FILAMENT IN A1795

We present the results of interferometric observations of the cool core of A1795 at CO(1–0) using the Combined Array for Research in Millimeter-wave Astronomy. In agreement with previous work, we detect a significant amount of cold molecular gas (3.9 ± 0.4 × 109 M☉) in the central ∼10 kpc. We report the discovery of a substantial clump of cold molecular gas at clustercentric radius of 30 kpc (2.9 ± 0.4 × 109 M☉), coincident in both position and velocity with the warm, ionized filaments. We also place an upper limit on the H2 mass at the outer edge of the star-forming filament, corresponding to a distance of 60 kpc (<0.9 × 109 M☉). We measure a strong gradient in the Hα/H2 ratio as a function of radius, suggesting different ionization mechanisms in the nucleus and filaments of A1795. The total mass of cold molecular gas (∼7 × 109 M☉) is roughly 30% of the classical cooling estimate at the same position, assuming a cooling time of 109 yr. Combining the cold molecular gas mass with the UV-derived star formation rate and the warm, ionized gas mass, the spectroscopically derived X-ray cooling rate is fully accounted for and in good agreement with the cooling byproducts over timescales of ∼109 yr. The overall agreement between the cooling rate of the hot intracluster medium and the mass of the cool gas reservoir suggests that, at least in this system, the cooling flow problem stems from a lack of observable cooling in the more diffuse regions at large radii.