nils-herrmann/clean_scirepeval huggingface dataset:
A novel scheme for the wave function renormalization of the composite operators

We propose a novel renormalization scheme for the hadronic operators. The renormalization factor of the operator in this scheme is normalized by the correlation function at tree level. If we focus on the pseudo scalar operator, then its renormalization factor is related to the mass renormalization factor of the fermion through the partially conserved axial-vector current (PCAC) relation. Using the renormalization factor for the pseudo scalar operator in our scheme, we obtain the mass anomalous dimension of the SU(3) gauge theory coupled to Nf = 12 massless fundamental fermions, which has an infrared fixed point (IRFP). The mass anomalous dimension at the IRFP is estimated as γ∗ m = 0.044 +0.025 −0.024(stat.) +0.057 −0 (syst.) +0 −0.032(syst.). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Subject Index B32, B38, B44
Corruption drives the emergence of civil society

Centralized sanctioning institutions have been shown to emerge naturally through social learning, displace all other forms of punishment and lead to stable cooperation. However, this result provokes a number of questions. If centralized sanctioning is so successful, then why do many highly authoritarian states suffer from low levels of cooperation? Why do states with high levels of public good provision tend to rely more on citizen-driven peer punishment? Here, we consider how corruption influences the evolution of cooperation and punishment. Our model shows that the effectiveness of centralized punishment in promoting cooperation breaks down when some actors in the model are allowed to bribe centralized authorities. Counterintuitively, a weaker centralized authority is actually more effective because it allows peer punishment to restore cooperation in the presence of corruption. Our results provide an evolutionary rationale for why public goods provision rarely flourishes in polities that rely only on strong centralized institutions. Instead, cooperation requires both decentralized and centralized enforcement. These results help to explain why citizen participation is a fundamental necessity for policing the commons.
Where Do Thin Tails Come From

The literature of heavy tails (typically) starts with a random walk and finds mechanisms that lead to fat tails under aggregation. We follow the inverse route and show how starting with fat tails we get to thin-tails when deriving the probability distribution of the response to a random variable. We introduce a general dose-response curve and argue that the left and right-boundedness or saturation of the response in natural things leads to thin-tails, even when the "underlying" random variable at the source of the exposure is fat-tailed.
Quantum Tunneling of Stock Price in Range Bound Market Conditions

Applications of Quantum Tunneling effect have long gone beyond the traditional physical meaning. Initially created by Gamow to explain {\alpha}-decay of nuclear particles, along the time, quantum tunneling found fertile domain of research in chemistry and recently in biology, where the new discipline of Quantum Biology emerges. The present paper extends the applicability of quantum tunneling to financial markets. In a recent paper  a time-independent equation for pricing the options having the underlying stock in a range bound markets is found. The equation is identical with a time-independent Schrodinger equation but incorporates elements of finance. The financial time-independent equation for option pricing is solved to explain a particular explosive violent movement of stock price in range bound markets. The aforementioned particular stock price movement is assimilated with a quantum tunneling effect. The probability of stock price to quantum tunneling out of the bounded region, known as transmission coefficient, is deduced. Quantum aspects of tunneling effect in financial markets are discussed. Recent evidences of price quantum tunneling in stock market are also shown.
Electrical conductivity of the quark-gluon plasma across the deconfinement transition.

A lattice calculation is presented for the electrical conductivity σ of the QCD plasma with 2+1 dynamical flavors at nonzero temperature. We employ the conserved lattice current on anisotropic lattices using a tadpole-improved clover action and study the behavior of the conductivity over a wide range of temperatures, both below and above the deconfining transition. The conductivity is extracted from a spectral-function analysis using the maximal entropy method, and a discussion of its systematics is provided. We find an increase of σ/T across the transition.
Streaming Variational Bayes

We present SDA-Bayes, a framework for (S)treaming, (D)istributed, (A)synchronous computation of a Bayesian posterior. The framework makes streaming updates to the estimated posterior according to a user-specified approximation batch primitive. We demonstrate the usefulness of our framework, with variational Bayes (VB) as the primitive, by fitting the latent Dirichlet allocation model to two large-scale document collections. We demonstrate the advantages of our algorithm over stochastic variational inference (SVI) by comparing the two after a single pass through a known amount of data—a case where SVI may be applied—and in the streaming setting, where SVI does not apply.
Structure of triadic relations in multiplex networks

Recent advances in the study of networked systems have highlighted that our interconnected world is composed of networks that are coupled to each other through different ‘layers’ that each represent one of many possible subsystems or types of interactions. Nevertheless, it is traditional to aggregate multilayer networks into a single weighted network in order to take advantage of existing tools. This is admittedly convenient, but it is also extremely problematic, as important information can be lost as a result. It is therefore important to develop multilayer generalizations of network concepts. In this paper, we analyze triadic relations and generalize the idea of transitivity to multiplex networks. By focusing on triadic relations, which yield the simplest type of transitivity, we generalize the concept and computation of clustering coefficients to multiplex networks. We show how the layered structure of such networks introduces a new degree of freedom that has a fundamental effect on transitivity. We compute multiplex clustering coefficients for several real multiplex networks and illustrate why one must take great care when generalizing standard network concepts to multiplex networks. We also derive analytical expressions for our clustering coefficients for ensemble averages of networks in a family of random multiplex networks. Our analysis illustrates that social networks have a strong tendency to promote redundancy by closing triads at every layer and that they thereby have a different type of multiplex transitivity from transportation networks, which do not exhibit such a tendency. These insights are invisible if one only studies aggregated networks.
Bayesian inference of epidemics on networks via Belief Propagation

We study several Bayesian inference problems for irreversible stochastic epidemic models on networks from a statistical physics viewpoint. We derive equations which allow us to accurately compute the posterior distribution of the time evolution of the state of each node given some observations. At difference with most existing methods, we allow very general observation models, including unobserved nodes, state observations made at different or unknown times, and observations of infection times, possibly mixed together. Our method, which is based on the belief propagation algorithm, is efficient, naturally distributed, and exact on trees. As a particular case, we consider the problem of finding the "zero patient" of a susceptible-infected-recovered or susceptible-infected epidemic given a snapshot of the state of the network at a later unknown time. Numerical simulations show that our method outperforms previous ones on both synthetic and real networks, often by a very large margin.
Natural orbitals and occupation numbers for harmonium: Fermions versus bosons

For a quantum system of N identical, harmonically interacting particles in a one-dimensional harmonic trap we calculate for the bosonic and fermionic ground state the corresponding one-particle reduced density operator ˆρ1 analytically. In case of bosons ˆρ1 is a Gibbs state for an effective harmonic oscillator. Hence the natural orbitals are Hermite functions and their occupation numbers obey a Boltzmann distribution. Intriguingly, for fermions with not too large couplings the natural orbitals coincide up to just a small error with the bosonic ones. In case of strong coupling this still holds qualitatively. Moreover, the decay of the decreasingly ordered fermionic natural occupation numbers is given by the bosonic one, but modified by an algebraic prefactor. Significant differences to bosons occur only for the largest occupation numbers. After all, the “gap” at the “Fermi level” decreases with increasing coupling strength but remains well pronounced even for strong interaction.
Lyα HEATING OF INHOMOGENEOUS HIGH-REDSHIFT INTERGALACTIC MEDIUM

The intergalactic medium (IGM) prior to the epoch of reionization consists mostly of neutral hydrogen gas. Lyman-α (Lyα) photons produced by early stars resonantly scatter off hydrogen atoms, causing energy exchange between the radiation field and the gas. This interaction results in moderate heating of the gas due to the recoil of the atoms upon scattering, which is of great interest for future studies of the pre-reionization IGM in the H i 21 cm line. We investigate the effect of this Lyα heating in the IGM with linear density, temperature, and velocity perturbations. Perturbations smaller than the diffusion length of photons could be damped due to heat conduction by Lyα photons. The scale at which damping occurs and the strength of this effect depend on various properties of the gas, the flux of Lyα photons, and the way in which photon frequencies are redistributed upon scattering. To find the relevant length scale and the extent to which Lyα heating affects perturbations, we calculate the gas heating rates by numerically solving linearized Boltzmann equations in which scattering is treated by the Fokker-Planck approximation. We find that (1) perturbations add a small correction to the gas heating rate, and (2) the damping of temperature perturbations occurs at scales with comoving wavenumber k ≳ 104 Mpc−1, which are much smaller than the Jeans scale and thus unlikely to substantially affect the observed 21 cm signal.
Searching for light dark matter with the SLAC millicharge experiment.

New sub-GeV gauge forces ("dark photons") that kinetically mix with the photon provide a promising scenario for MeV-GeV dark matter and are the subject of a program of searches at fixed-target and collider facilities around the world. In such models, dark photons produced in collisions may decay invisibly into dark-matter states, thereby evading current searches. We reexamine results of the SLAC mQ electron beam dump experiment designed to search for millicharged particles and find that it was strongly sensitive to any secondary beam of dark matter produced by electron-nucleus collisions in the target. The constraints are competitive for dark photon masses in the ~1-30 MeV range, covering part of the parameter space that can reconcile the apparent (g-2)(μ) anomaly. Simple adjustments to the original SLAC search for millicharges may extend sensitivity to cover a sizable portion of the remaining (g-2)(μ) anomaly-motivated region. The mQ sensitivity is therefore complementary to ongoing searches for visible decays of dark photons. Compared to existing direct-detection searches, mQ sensitivity to electron-dark-matter scattering cross sections is more than an order of magnitude better for a significant range of masses and couplings in simple models.
Fermi Bubbles under Dark Matter Scrutiny. Part I: Astrophysical Analysis

The quest for Dark Matter signals in the gamma-ray sky is one of the most intriguing and exciting challenges in astrophysics. In this paper we perform the analysis of the energy spectrum of the \textit{Fermi bubbles} at different latitudes, making use of the gamma-ray data collected by the Fermi Large Area Telescope. By exploring various setups for the full-sky analysis we achieve stable results in all the analyzed latitudes. At high latitude, $|b|=20^{\circ}-50^{\circ}$, the \textit{Fermi bubbles} energy spectrum can be reproduced by gamma-ray photons generated by inverse Compton scattering processes, assuming the existence of a population of high-energy electrons. At low latitude, $|b|=10^{\circ}-20^{\circ}$, the presence of a bump at $E_{\gamma}\sim 1-4$ GeV, reveals the existence of an extra component compatible with Dark Matter annihilation. Our best-fit candidate corresponds to annihilation into $b\bar{b}$ with mass $M_{\rm DM}= 61.8^{+6.9}_{-4.9}$ GeV and cross section $ = 3.30^{+0.69}_{-0.49}\times 10^{-26}$ cm$^{3}$s$^{-1}$. In addition, using the energy spectrum of the \textit{Fermi bubbles}, we derive new conservative but stringent upper limits on the Dark Matter annihilation cross section.
Network Topologies of Financial Market During the Global Financial Crisis

We consider the effects of the global financial crisis through a local Korean financial market around the 2008 crisis. We analyze 185 individual stock prices belonging to the KOSPI (Korea Composite Stock Price Index), cosidering three time periods: the time before, during, and after the crisis. The complex networks generate from the fully connected correlation network by using the cross-correlation coefficients among the stock price time series of the companies. We generate the threshold networks (TN), the minimal spanning tees (MST), and the hierarchical network (HN) from the fully connected cross-correlation networks. By assigning a threshold value of the cross-correlation coefficient, we obtain the threshold networks. We observe the power law of the degree distribution in the limited range of the threshold. The degree distribution of the largest cluster in the threshold networks during the crisis is fatter than other periods. The clustering coefficient of the threshold networks follows the power law in the scaling range. We also generate the minimal spanning trees from the fully connected correlation networks. The MST during the crisis period shrinks in comparison to the periods before and after the crisis. The cophenetic correlation coefficient increases during the crisis, indicating that the hierarchical structure increases during this period. When the crisis hit the market, the companies behave synchronously and their correlations become stronger than the normal period.
Running coupling constant and mass anomalous dimension of six-flavor SU(2) gauge theory

In the exploration of viable models of dynamical electroweak symmetry breaking, it is essential to locate the lower end of the conformal window and know the mass anomalous dimensions there for a variety of gauge theories. We calculate, with the Schr\"odinger functional scheme, the running coupling constant and the mass anomalous dimension of SU(2) gauge theory with six massless Dirac fermions in the fundamental representation. The calculations are performed on ${6}^{4}--{24}^{4}$ lattices over a wide range of lattice bare couplings to take the continuum limit. The discretization errors for both quantities are removed perturbatively. We find that the running slows down and comes to a stop at $0.06\ensuremath{\lesssim}1/{g}^{2}\ensuremath{\lesssim}0.15$ where the mass anomalous dimension is estimated to be $0.26\ensuremath{\lesssim}{\ensuremath{\gamma}}_{m}^{*}\ensuremath{\lesssim}0.74$.
The complex dynamics of wishful thinking: the critical positivity ratio.

We examine critically the claims made by Fredrickson and Losada (2005) concerning the construct known as the "positivity ratio." We find no theoretical or empirical justification for the use of differential equations drawn from fluid dynamics, a subfield of physics, to describe changes in human emotions over time; furthermore, we demonstrate that the purported application of these equations contains numerous fundamental conceptual and mathematical errors. The lack of relevance of these equations and their incorrect application lead us to conclude that Fredrickson and Losada's claim to have demonstrated the existence of a critical minimum positivity ratio of 2.9013 is entirely unfounded. More generally, we urge future researchers to exercise caution in the use of advanced mathematical tools, such as nonlinear dynamics, and in particular to verify that the elementary conditions for their valid application have been met.
THE SOLAR NEIGHBORHOOD XXIX: THE HABITABLE REAL ESTATE OF OUR NEAREST STELLAR NEIGHBORS

We use the sample of known stars and brown dwarfs within 5 pc of the Sun, supplemented with AFGK stars within 10 pc, to determine which stellar spectral types provide the most habitable real estate—defined as locations where liquid water could be present on Earth-like planets. Stellar temperatures and radii are determined by fitting model spectra to spatially resolved broadband photometric energy distributions for stars in the sample. Using these values, the locations of the habitable zones are calculated using an empirical formula for planetary surface temperature and assuming the condition of liquid water, called here the empirical habitable zone (EHZ). Systems that have dynamically disruptive companions are considered not habitable. We consider companions to be disruptive if the separation ratio of the companion to the habitable zone is less than 5:1. We use the results of these calculations to derive a simple formula for predicting the location of the EHZ for main sequence stars based on V − K color. We consider EHZ widths as more useful measures of the habitable real estate around stars than areas because multiple planets are not expected to orbit stars at identical stellar distances. This EHZ provides a qualitative guide on where to expect the largest population of planets in the habitable zones of main sequence stars. Because of their large numbers and lower frequency of short-period companions, M stars provide more EHZ real estate than other spectral types, possessing 36.5% of the habitable real estate en masse. K stars are second with 21.5%, while A, F, and G stars offer 18.5%, 6.9%, and 16.6%, respectively. Our calculations show that three M dwarfs within 10 pc harbor planets in their EHZs—GJ 581 may have two planets (d with msin i = 6.1 M⊕; g with msin i = 3.1 M⊕), GJ 667 C has one (c with msin i = 4.5 M⊕), and GJ 876 has two (b with msin i = 1.89 MJup and c with msin i = 0.56 MJup). If Earth-like planets are as common around low-mass stars as recent Kepler results suggest, M stars will harbor more Earth-like planets in habitable zones than any other stellar spectral type.
Finite size scaling study of $N_{\text{f}}=4$ finite density QCD on the lattice

We explore the phase space spanned by the temperature and the chemical potential for 4-flavor lattice QCD using the Wilson-clover quark action. In order to determine the order of the phase transition, we apply finite size scaling analyses to gluonic and quark observables including plaquette, Polyakov loop and quark number density, and examine their susceptibility, skewness, kurtosis and Challa-Landau-Binder cumulant. Simulations were carried out on lattices of a temporal size fixed at $N_{\text{t}}=4$ and spatial sizes chosen from $6^3$ up to $10^3$. Configurations were generated using the phase reweighting approach, while the value of the phase of the quark determinant were carefully monitored. The $\mu$-parameter reweighting technique is employed to precisely locate the point of the phase transition. Among various approximation schemes for calculating the ratio of quark determinants needed for $\mu$-reweighting, we found the Taylor expansion of the logarithm of the quark determinant to be the most reliable. Our finite-size analyses show that the transition is first order at $(\beta, \kappa, \mu/T)=(1.58, 0.1385, 0.584\pm 0.008)$ where $(m_\pi/m_\rho, T/m_\rho)=(0.822, 0.154)$. It weakens considerably at $(\beta, \kappa, \mu/T)=(1.60, 0.1371, 0.821\pm 0.008)$ where $(m_\pi/m_\rho, T/m_\rho)=(0.839, 0.150)$, and a crossover rather than a first order phase transition cannot be ruled out.
Dispersion measure variations in a sample of 168 pulsars

We analyse dispersion measure (DM) variations in six years of radio observations ofmore than 160 young pulsars, all gamma ray candidates for the Fermi gamma raytelescope mostly located close to the Galactic plane. DMs were t across 256 MHzof bandwidth for observations centred at 1.4 GHz and across three frequencies {0.7 GHz, 1.4 GHz, and 3.1 GHz { where multifrequency observations were available.Changes in dispersion measure, dDM/dt, were calculated using a weighted linear tacross all epochs of available DMs. DM variations were detected at a 3˙level in 11pulsars, four of which were above 5˙: PSRs J0835 4510, . We nd that after 28 years of gradual decline, the DM of PSRJ0835 4510 is now increasing. The magnitude of variations in three of the four (PSRsJ0835 4510,  4913, and J1833 0827) are above what models would predict foran ISM dominated by Kolmogorov turbulence. We attribute this excess as likely dueto the pulsar’s local environment - the supernova remnants near PSRs J0835 4510and J1833 0827 and the pulsar wind nebula around  Upper limitswere determined for all pulsars without detectable values of dDM/dt, most limits werefound to lie above the levels of variations predicted by ISM theory. We nd our resultsto be consistent with scattering estimates from the NE2001 model along these lines ofsight. pulsars: general | pulsars: individual: PSR J0835 4510 | pulsars:individual:
Extracting information from the signature of a financial data stream

Market events such as order placement and order cancellation are examples of the complex and substantial flow of data that surrounds a modern financial engineer. New mathematical techniques, developed to describe the interactions of complex oscillatory systems (known as the theory of rough paths) provides new tools for analysing and describing these data streams and extracting the vital information. In this paper we illustrate how a very small number of coefficients obtained from the signature of financial data can be sufficient to classify this data for subtle underlying features and make useful predictions. This paper presents financial examples in which we learn from data and then proceed to classify fresh streams. The classification is based on features of streams that are specified through the coordinates of the signature of the path. At a mathematical level the signature is a faithful transform of a multidimensional time series. (Ben Hambly and Terry Lyons \cite{uniqueSig}), Hao Ni and Terry Lyons \cite{NiLyons} introduced the possibility of its use to understand financial data and pointed to the potential this approach has for machine learning and prediction. We evaluate and refine these theoretical suggestions against practical examples of interest and present a few motivating experiments which demonstrate information the signature can easily capture in a non-parametric way avoiding traditional statistical modelling of the data. In the first experiment we identify atypical market behaviour across standard 30-minute time buckets sampled from the WTI crude oil future market (NYMEX). The second and third experiments aim to characterise the market "impact" of and distinguish between parent orders generated by two different trade execution algorithms on the FTSE 100 Index futures market listed on NYSE Liffe.