nils-herrmann/clean_scirepeval huggingface dataset:
Markets Evolution after the Credit Crunch

We review the main changes in the interbank market after the financial crisis started in August 2007. In particular, we focus on the fixed income market and we analyse the most relevant empirical evidences regarding the divergence of the existing basis between interbank rates with different tenor, such as Libor and OIS. We also discuss a qualitative explanation of these effects based on the consideration of credit and liquidity variables. Then, we focus our attention on the diffusion of collateral agreements among OTC derivatives market counterparties, and on the consequent change of paradigm for pricing derivatives. We illustrate the main qualitative features of the new market practice, called CSA discounting, and we point out the most relevant issues for market players associated to its adoption.
Calling patterns in human communication dynamics

Modern technologies not only provide a variety of communication modes (e.g., texting, cell phone conversation, and online instant messaging), but also detailed electronic traces of these communications between individuals. These electronic traces indicate that the interactions occur in temporal bursts. Here, we study intercall duration of communications of the 100,000 most active cell phone users of a Chinese mobile phone operator. We confirm that the intercall durations follow a power-law distribution with an exponential cutoff at the population level but find differences when focusing on individual users. We apply statistical tests at the individual level and find that the intercall durations follow a power-law distribution for only 3,460 individuals (3.46%). The intercall durations for the majority (73.34%) follow a Weibull distribution. We quantify individual users using three measures: out-degree, percentage of outgoing calls, and communication diversity. We find that the cell phone users with a power-law duration distribution fall into three anomalous clusters: robot-based callers, telecom fraud, and telephone sales. This information is of interest to both academics and practitioners, mobile telecom operators in particular. In contrast, the individual users with a Weibull duration distribution form the fourth cluster of ordinary cell phone users. We also discover more information about the calling patterns of these four clusters (e.g., the probability that a user will call the cr-th most contact and the probability distribution of burst sizes). Our findings may enable a more detailed analysis of the huge body of data contained in the logs of massive users.
Approximate Counting of Graphical Models via MCMC Revisited

We apply Markov chain Monte Carlo (MCMC) sampling to approximately calculate some quantities, and discuss their implications for learning directed and acyclic graphs (DAGs) from data. Specifically, we calculate the approximate ratio of essential graphs (EGs) to DAGs for up to 31 nodes. Our ratios suggest that the average Markov equivalence class is small. We show that a large majority of the classes seem to have a size that is close to the average size. This suggests that one should not expect more than a moderate gain in efficiency when searching the space of EGs instead of the space of DAGs. We also calculate the approximate ratio of connected EGs to connected DAGs, of connected EGs to EGs, and of connected DAGs to DAGs. These new ratios are interesting because, as we will see, the DAG or EG learnt from some given data is likely to be connected. Furthermore, we prove that the latter ratio is asymptotically 1. Finally, we calculate the approximate ratio of EGs to largest chain graphs for up to 25 nodes. Our ratios suggest that Lauritzen–Wermuth–Frydenberg chain graphs are considerably more expressive than DAGs. We also report similar approximate ratios and conclusions for multivariate regression chain graphs.
Calculating effective gun policies

Author(s): Wodarz, Dominik; Komarova, Natalia L |  Following recent shootings in the USA, a debate has erupted, one side favoring stricter gun control, the other promoting protection through more weapons. We provide a scientific foundation to inform this debate, based on mathematical, epidemiological models that quantify the dependence of firearm-related death rates of people on gun policies. We assume a shooter attacking a single individual or a crowd. Two strategies can minimize deaths in the model, depending on parameters: either a ban of private firearms possession, or a policy allowing the general population to carry guns. In particular, the outcome depends on the fraction of offenders that illegally possess a gun, on the degree of protection provided by gun ownership, and on the fraction of the population who take up their right to own a gun and carry it with them when attacked, parameters that can be estimated from statistical data. With the measured parameters, the model suggests that if the gun law is enforced at a level similar to that in the United Kingdom, gun-related deaths are minimized if private possession of firearms is banned. If such a policy is not practical or possible due to constitutional or cultural constraints, the model and parameter estimation indicate that a partial reduction in firearm availability can lead to a reduction in gun-induced death rates, even if they are not minimized. Most importantly, our analysis identifies the crucial parameters that determine which policy reduces the death rates, providing guidance for future statistical studies that will be necessary for more refined quantitative predictions.
Why quantum computing is hard - and quantum cryptography is not provably secure

Despite high hopes for quantum computation in the 1990s, progress in the past decade has been slow; we still cannot perform computation with more than about three qubits and are no closer to solving problems of real interest than a decade ago. Separately, recent experiments in fluid mechanics have demonstrated the emergence of a full range of quantum phenomena from completely classical motion. We present two specific hypotheses. First, Kuramoto theory may give a basis for geometrical thinking about entanglement. Second, we consider a recent soliton model of the electron, in which the quantum-mechanical wave function is a phase modulation of a carrier wave. Both models are consistent with one another and with observation. Both models suggest how entanglement and decoherence may be related to device geometry. Both models predict that it will be dicult to maintain phase coherence of more than three qubits in the plane, or four qubits in a three-dimensional structure. The soliton model also shows that the experimental work which appeared to demonstrate a violation of Bell’s inequalities might not actually do so; regardless of whether it is a correct description of the world, it exposes a flaw in the logic of the Bell tests. Thus the case for the security of EPR-based quantum cryptography has just not been made. We propose experiments in quantum computation to test this. Finally, we examine two possible interpretations of such soliton models: one is consistent with the transactional interpretation of quantum mechanics, while the other is an entirely classical model in which we do not have to abandon the idea of a single world where action is local and causal.
Cosmological behavior in extended nonlinear massive gravity

We perform a detailed dynamical analysis of various cosmological scenarios in extended (varying-mass) nonlinear massive gravity. Due to the enhanced freedom in choosing the involved free functions, this cosmological paradigm allows for a huge variety of solutions that can attract the universe at late times, compared to scalar-field cosmology or usual nonlinear massive gravity. Amongst others, it accepts quintessence, phantom or cosmological-constant-like late-time solutions, which moreover can alleviate the coincidence problem. These features seem to be general and non-sensitive to the imposed ansantzes and model parameters, and thus extended nonlinear massive gravity can be a good candidate for the description of nature.
Dark radiation constraints on mixed Axion/Neutralino dark matter

Recent analyses of CMB data combined with the measurement of BAO and H0 show that dark radiation — parametrized by the apparent number of additional neutrinos ΔNeff contributing to the cosmic expansion — is bounded from above by about ΔNeff1.6 at 95% CL. We consider the mixed axion/neutralino cold dark matter scenario which arises in R-parity conserving supersymmetric (SUSY) models wherein the strong CP problem is solved by hadronic axions with a concommitant axion(a)/saxion(s)/axino(a) supermultiplet. Our new results include improved calculations of thermal axion and saxion production and include effects of saxion decay to axinos and axions. We show that the above bound on ΔNeff is easily satisfied if saxions are mainly thermally produced and mLSP < mams. However, if the dominant mechanism of saxion production is through coherent oscillations, the CMB data provides a strong bound on saxion production followed by saxion decays to axions. Furthermore we show that scenarios with mixed neutralino/axion dark matter are highly constrained by combined CMB, BBN and Xe-100 constraints. In particular, supersymmetric models with a standard overabundance of neutralino dark matter are excluded for all values of the Peccei-Quinn breaking scale. Next generation WIMP direct detection experiments may be able to discover or exclude mixed axion-neutralino CDM scenarios where s → aa is the dominant saxion decay mode.
The Citation Wake of Publications Detects Nobel Laureates' Papers

For several decades, a leading paradigm of how to quantitatively assess scientific research has been the analysis of the aggregated citation information in a set of scientific publications. Although the representation of this information as a citation network has already been coined in the 1960s, it needed the systematic indexing of scientific literature to allow for impact metrics that actually made use of this network as a whole, improving on the then prevailing metrics that were almost exclusively based on the number of direct citations. However, besides focusing on the assignment of credit, the paper citation network can also be studied in terms of the proliferation of scientific ideas. Here we introduce a simple measure based on the shortest-paths in the paper's in-component or, simply speaking, on the shape and size of the wake of a paper within the citation network. Applied to a citation network containing Physical Review publications from more than a century, our approach is able to detect seminal articles which have introduced concepts of obvious importance to the further development of physics. We observe a large fraction of papers co-authored by Nobel Prize laureates in physics among the top-ranked publications.
Fluctuation theorem and natural time analysis

Upon employing a natural time window of fixed length sliding through a time series, an explicit interrelation between the variability $\beta$ of the variance $\kappa_1$($= - ^2$) of natural time $\chi$ and events' correlations is obtained. In addition, we investigate the application of the fluctuation theorem, which is a general result for systems far from equilibrium, to the variability $\beta$. We consider for example, major earthquakes that are nonequilibrium critical phenomena. We find that four (out of five) mainshocks in California during 1979-2003 were preceded by $\beta$ minima lower than the relative thresholds deduced from the fluctuation theorem, thus signalling an impending major event.
Equitability, mutual information, and the maximal information coefficient

Attention has recently focused on a basic yet unresolved problem in statistics: How can one quantify the strength of a statistical association between two variables without bias for relationships of a specific form? Here we propose a way of mathematically formalizing this “equitability” criterion, using core concepts from information theory. This criterion is naturally satisfied by a fundamental information-theoretic measure of dependence called “mutual information.” By contrast, a recently introduced dependence measure called the “maximal information coefficient” is seen to violate equitability. We conclude that estimating mutual information provides a natural and practical method for equitably quantifying associations in large datasets. How should one quantify the strength of association between two random variables without bias for relationships of a specific form? Despite its conceptual simplicity, this notion of statistical “equitability” has yet to receive a definitive mathematical formalization. Here we argue that equitability is properly formalized by a self-consistency condition closely related to Data Processing Inequality. Mutual information, a fundamental quantity in information theory, is shown to satisfy this equitability criterion. These findings are at odds with the recent work of Reshef et al. [Reshef DN, et al. (2011) ], which proposed an alternative definition of equitability and introduced a new statistic, the “maximal information coefficient” (MIC), said to satisfy equitability in contradistinction to mutual information. These conclusions, however, were supported only with limited simulation evidence, not with mathematical arguments. Upon revisiting these claims, we prove that the mathematical definition of equitability proposed by Reshef et al. cannot be satisfied by any (nontrivial) dependence measure. We also identify artifacts in the reported simulation evidence. When these artifacts are removed, estimates of mutual information are found to be more equitable than estimates of MIC. Mutual information is also observed to have consistently higher statistical power than MIC. We conclude that estimating mutual information provides a natural (and often practical) way to equitably quantify statistical associations in large datasets.
Possible latitude effects of Chern-Simons gravity on quantum interference

It has been recently suggested that possible effects of Chern-Simons gravity on a quantum interferometer are dependent on the latitude and direction of the interferometer on Earth in orbital motion around Sun. Continuing work initiated in the earlier publication [Okawara, Yamada and Asada,  (2012)], we perform numerical calculations of time variation in the induced phase shifts for nonequatorial cases. We show that the maximum phase shift at any latitude might occur at 6, 0 (and 12), and 18 hours (in local time) of each day, when the normal vector to the interferometer is vertical, eastbound and northbound, respectively. If two identical interferometers were located at different latitudes, the difference between two phase shifts that are measured at the same local time would be $O(\sin \delta\varphi)$ for a small latitude difference $\delta\varphi$. It might thus become maximally $\sim 20$ percents for $\delta\varphi \sim 10$ degrees, for instance.
A Complete Model for R-parity Violation

We present a complete model whose low energy eective theory is the R-parity violating NMSSM with a baryon number violating u d d vertex of the MFV SUSY form, leading to prompt LSP decay and evading the ever stronger LHC bounds on low-scale R-parity conserving supersymmetry. MFV avor structure is enforced by gauging an SU(3) avor symmetry at high energies. After the avor group is spontaneously broken, mass mixing between the standard model elds and heavy vector-like quarks and leptons induces hierarchical Yukawa couplings which depend on the mixing angles. The same mechanism generates the u d d coupling, explaining its shared structure. A discrete R-symmetry is imposed which forbids all other dangerous lepton and baryon-number violating operators (including Planck-suppressed operators) and simultaneously solves the problem. While avor constraints require the avor gauge bosons to be outside of the reach of the LHC, the vector-like top partners could lie below 1 TeV.
im3shape: a maximum likelihood galaxy shear measurement code for cosmic gravitational lensing

We present and describe IM3SHAPE, a new publicly available galaxy shape measurement code for weak gravitational lensing shear. IM3SHAPE performs a maximum likelihood fit of a bulgeplus-disc galaxy model to noisy images, incorporating an applied point spread function. We detail challenges faced and choices made in its design and implementation, and then discuss various limitations that affect this and other maximum like lihood methods. We assess the bias arising from fitting an incorrect galaxy model using simple n oise-free images and find that it should not be a concern for current cosmic shear surveys. We test IM3SHAPE on the GREAT08 Challenge image simulations, and meet the requirements for upcoming cosmic shear surveys in the case that the simulations are encompassed by the fitted model, using a simple correction for image noise bias. For the fiducial branch of GREAT08 we obt ain a negligible additive shear bias and sub-two percent level multiplicative bias, which i s suitable for analysis of current surveys. We fall short of the sub-percent level requirement for upcoming surveys, which we attribute to a combination of noise bias and the mis-match between our galaxy model and the model used in the GREAT08 simulations. We meet the requirements for current surveys across all branches of GREAT08, except those with small or high noise galaxies, which we would cut from our analysis. Using the GREAT08 metric we we obtain a score of Q=717 for the usable branches, relative to the goal of Q=1000 for futur e experiments. The code is freely available from https://bitbucket.org/joezuntz/im3shap e.
The mass profile and accretion history of cold dark matter haloes

We use the Millennium Simulation series to investigate the relation between the accretion history and mass profile of cold dark matter (CDM) haloes. We find that the mean inner density within the scale radius, r(-2) (where the halo density profile has isothermal slope), is directly proportional to the critical density of the Universe at the time when the virial mass of the main progenitor equals the mass enclosed within r(-2). Scaled to these characteristic values of mass and density, the average mass accretion history, expressed in terms of the critical density of the Universe, M((crit)(z)), resembles that of the enclosed density profile, M( >), at z = 0. Both follow closely the Navarro, Frenk & White (NFW) profile, which suggests that the similarity of halo mass profiles originates from the mass-independence of halo accretion histories. Support for this interpretation is provided by outlier haloes whose accretion histories deviate from the NFW shape; their mass profiles show correlated deviations from NFW and are better approximated by Einasto profiles. Fitting both M( >) and M((crit)) with either NFW or Einasto profiles yield concentration and shape parameters that are correlated, confirming and extending earlier work that has linked the concentration of a halo with its accretion history. These correlations also confirm that halo structure is insensitive to initial conditions: only haloes whose accretion histories differ greatly from the NFW shape show notable deviations from NFW in their mass profiles. As a result, the NFW profile provides acceptable fits to hot dark matter haloes, which do not form hierarchically, and for fluctuation power spectra other than CDM. Our findings, however, predict a subtle but systematic dependence of mass profile shape on accretion history which, if confirmed, would provide strong support for the link between accretion history and halo structure we propose here.
Sparse Multiple Kernel Learning with Geometric Convergence Rate

In this paper, we study the problem of sparse multiple kernel learning (MKL), where the goal is to efficiently learn a combination of a fixed small number of kernels from a large pool that could lead to a kernel classifier with a small prediction error. We develop an efficient algorithm based on the greedy coordinate descent algorithm, that is able to achieve a geometric convergence rate under appropriate conditions. The convergence rate is achieved by measuring the size of functional gradients by an empirical $\ell_2$ norm that depends on the empirical data distribution. This is in contrast to previous algorithms that use a functional norm to measure the size of gradients, which is independent from the data samples. We also establish a generalization error bound of the learned sparse kernel classifier using the technique of local Rademacher complexity.
CVA and FVA to Derivatives Trades Collateralized by Cash

In this paper, we consider replication pricing of derivatives that are partially collateralized by cash. We let issuer replicate the derivatives payout using shares and cash, and let buyer replicate the loss given the counterparty default using credit default swaps. The costs of funding for replication and collateral posting are taken into account in the pricing process. A partial differential equation (PDE) for the derivatives price is established, and its solution is provided in a Feynman–Kac formula, which decomposes the derivatives value into the risk-free value of the derivative plus credit valuation adjustment (CVA) and funding valuation adjustment (FVA). For most derivatives, we show that CVAs can be evaluated analytically or semi-analytically, while FVAs as well as the derivatives values can be solved recursively through numerical procedures due to their interdependence. In numerical demonstrations, continuous and discrete margin revisions are considered, respectively, for an equity call option and a vanilla interest-rate swap.
Robust hedging with proportional transaction costs

A duality for robust hedging with proportional transaction costs of path-dependent European options is obtained in a discrete-time financial market with one risky asset. The investor’s portfolio consists of a dynamically traded stock and a static position in vanilla options, which can be exercised at maturity. Trading of both options and stock is subject to proportional transaction costs. The main theorem is a duality between hedging and a Monge–Kantorovich-type optimization problem. In this dual transport problem, the optimization is over all probability measures that satisfy an approximate martingale condition related to consistent price systems, in addition to an approximate marginal constraint.
Two Types of Well Followed Users in the Followership Networks of Twitter

In the Twitter blogosphere, the number of followers is probably the most basic and succinct quantity for measuring popularity of users. However, the number of followers can be manipulated in various ways; we can even buy follows. Therefore, alternative popularity measures for Twitter users on the basis of, for example, users' tweets and retweets, have been developed. In the present work, we take a purely network approach to this fundamental question. First, we find that two relatively distinct types of users possessing a large number of followers exist, in particular for Japanese, Russian, and Korean users among the seven language groups that we examined. A first type of user follows a small number of other users. A second type of user follows approximately the same number of other users as the number of follows that the user receives. Then, we compare local (i.e., egocentric) followership networks around the two types of users with many followers. We show that the second type, which is presumably uninfluential users despite its large number of followers, is characterized by high link reciprocity, a large number of friends (i.e., those whom a user follows) for the followers, followers' high link reciprocity, large clustering coefficient, large fraction of the second type of users among the followers, and a small PageRank. Our network-based results support that the number of followers used alone is a misleading measure of user's popularity. We propose that the number of friends, which is simple to measure, also helps us to assess the popularity of Twitter users.