nils-herrmann/clean_scirepeval huggingface dataset:
Multiple random walks to uncover short paths in power law networks

Developing simple distributed algorithms to allow nodes to perform topology discovery and message routing using incomplete topological information is a problem of great interest in network science. Consider the following routing problem in the context of a large power law network G. A small number of nodes want to exchange messages over short paths on G. These nodes do not have access to the topology of G but are allowed to crawl the network subject to a budget constraint. Only crawlers whose paths cross are allowed to exchange topological information. In this work we study the use of random walks (RWs) to crawl G. We show that RWs have the ability to find short paths and that this bears no relation to the paths that they take. Instead, it relies on two properties of RWs on power law networks: · The RW ability to observe a sizable fraction of the network edges; · The near certainty that two distinct RW sample paths cross after a small percentage of the nodes have been visited. We show promising simulation results on several real world networks.
A Social Influence Model Based On Circuit Theory

Understanding the behaviors of information propagation is essential for the effective exploitation of social influence in social networks. However, few existing influence models are tractable and efficient for describing the information propagation process, especially when dealing with the difficulty of incorporating the effects of combined influences from multiple nodes. To this end, in this paper, we provide a social influence model that alleviates this obstacle based on electrical circuit theory. This model vastly improves the efficiency of measuring the influence strength between any pair of nodes, and can be used to interpret the real-world influence propagation process in a coherent way. In addition, this circuit theory model provides a natural solution to the social influence maximization problem. When applied to realworld data, the circuit theory model consistently outperforms the state-of-the-art methods and can greatly alleviate the computation burden of the influence maximization problem.
Learning Dictionaries With Bounded Self-Coherence

Sparse coding in learned dictionaries has been established as a successful approach for signal denoising, source separation and solving inverse problems in general. A dictionary learning method adapts an initial dictionary to a particular signal class by iteratively computing an approximate factorization of a training data matrix into a dictionary and a sparse coding matrix. The learned dictionary is characterized by two properties: the coherence of the dictionary to observations of the signal class, and the self-coherence of the dictionary atoms. A high coherence to the signal class enables the sparse coding of signal observations with a small approximation error, while a low self-coherence of the atoms guarantees atom recovery and a more rapid residual error decay rate for the sparse coding algorithm. The two goals of high signal coherence and low self-coherence are typically in conflict, therefore one seeks a trade-off between them, depending on the application. We present a dictionary learning method with an effective control over the self-coherence of the trained dictionary, enabling a trade-off between maximizing the sparsity of codings and approximating an equi-angular tight frame.
Structure and Overlaps of Communities in Networks

One of the main organizing principles in real-world social, information and technological networks is that of network communities, where sets of nodes organize into densely linked clusters. Even though detection of such communities is of great interest, understanding the structure communities in large networks remains relatively limited. Due to unavailability of labeled ground-truth data it is practically impossible to evaluate and compare different models and notions of communities on a large scale. 
In this paper we identify 6 large social, collaboration, and information networks where nodes explicitly state their community memberships. We define ground-truth communities by using these explicit memberships. We then empirically study how such ground-truth communities emerge in networks and how they overlap. We observe some surprising phenomena. First, ground-truth communities contain high-degree hub nodes that reside in community overlaps and link to most of the members of the community. Second, the overlaps of communities are more densely connected than the non-overlapping parts of communities, in contrast to the conventional wisdom that community overlaps are more sparsely connected than the communities themselves. 
Existing models of network communities do not capture dense community overlaps. We present the Community-Affiliation Graph Model (AGM), a conceptual model of network community structure, which reliably captures the overall structure of networks as well as the overlapping nature of network communities.
Constraints on Light Dark Matter from Big Bang Nucleosynthesis

We examine the effects of relic dark matter annihilations on big bang nucleosynthesis (BBN). The magnitude of these effects have scale simply with the dark matter mass and annihilation cross-section, which we derive. Estimates based on these scaling behaviors indicate that BBN severely constrains hadronic and radiative dark matter annihilation channels in the previously unconsidered dark matter mass region MeV $\lesssim m_{\chi} \lesssim 10$ GeV. Interestingly, we find that BBN constraints on hadronic annihilation channels are competitive with similar bounds derived from the cosmic microwave background.
150 new transiting planet candidates from Kepler Q1–Q6 data

We have performed an extensive search for planet candidates in the publicly available Kepler Long Cadence data from quarters Q1 through Q6. The search method consists of initial de-trending of the data, applying the trend filtering algorithm, searching for transit signals with the Box Least Squares fitting method in three frequency domains, visual inspection of the potential transit candidates, and in-depth analysis of the shortlisted candidates. In this paper we present 150 new periodic planet candidates and 7 single transit events, 72 of which are in multiple systems. The periods of these planet candidates vary from $\sim$0.17\,day to $\sim$ 440\,day. 124 of the planet candidates have radii smaller than 3 \rearth. We recover 82.5% of the Batalha et al. (2012) KOI catalog. We also report 40 newly identified false positives---systems that look like transiting planets, but are probably due to blended eclipsing binaries. Our search improves the statistics in the short period and small planet radii parameter ranges.
A novel method of data analysis for hadronic physics

A novel method for extracting physical parameters from experimental and simulation data is presented. The method is based on statistical concepts and it relies on Monte Carlo simulation techniques. It identifies and determines with maximal precision parameters that are sensitive to the data. The method has been extensively studied and it is shown to produce unbiased results. It is applicable to a wide range of scientific and engineering problems. It has been successfully applied in the analysis of experimental data in hadronic physics and of lattice QCD correlators.
COLLATERALIZED CVA VALUATION WITH RATING TRIGGERS AND CREDIT MIGRATIONS

In this paper we discuss the issue of computation of the bilateral credit valuation adjustment (CVA) under rating triggers, and in presence of ratings-linked margin agreements. Specifically, we consider collateralized OTC contracts, that are subject to rating triggers, between two parties — an investor and a counterparty. Moreover, we model the margin process as a functional of the credit ratings of the counterparty and the investor. We employ a Markovian approach for modeling of the rating transitions of the two parties to the contract. In this framework, we derive the representation for bilateral CVA. We also introduce a new component in the decomposition of the counterparty risky price: namely the rating valuation adjustment (RVA) that accounts for the rating triggers. We give two examples of dynamic collateralization schemes where the margin thresholds are linked to the credit ratings of the parties. Our results are illustrated via computation of various counterparty risk adjustments for a CDS contract and for an IRS contract.
Friendship networks and social status

In empirical studies of friendship networks, participants are typically asked, in interviews or questionnaires, to identify some or all of their close friends, resulting in a directed network in which friendships can, and often do, run in only one direction between a pair of individuals. Here we analyze a large collection of such networks representing friendships among students at US high and junior-high schools and show that the pattern of unreciprocated friendships is far from random. In every network, without exception, we find that there exists a ranking of participants, from low to high, such that almost all unreciprocated friendships consist of a lower ranked individual claiming friendship with a higher ranked one. We present a maximum-likelihood method for deducing such rankings from observed network data and conjecture that the rankings produced reflect a measure of social status. We note in particular that reciprocated and unreciprocated friendships obey different statistics, suggesting different formation processes, and that rankings are correlated with other characteristics of the participants that are traditionally associated with status, such as age and overall popularity as measured by total number of friends.
The origin of space-time as seen from matrix model simulations

The AdS/CFT correspondence, or more generally the gauge/gravity duality, is a remarkable conjecture obtained from superstring theory with various D-brane backgrounds. According to this conjecture, a higher-dimensional curved space-time emerges from supersymmetric gauge theory in lower-dimensional flat space-time. In the first part of this article, we review Monte Carlo studies of U(N) supersymmetric gauge theories, which confirmed the gauge/gravity duality for various observables. In particular, Monte Carlo results for thermodynamic quantities enable us to understand the microscopic origin of the black hole entropy associated with the dual geometry. We also discuss results for Wilson loops and correlation functions, which agree nicely with the predictions from the gravity side. In the second part, we review recent developments in a nonperturbative formulation of superstring theory, which may be regarded as a counterpart of the lattice gauge theory in QCD. In particular, we discuss Monte Carlo results for the Lorentzian matrix model, which suggest that (3+1)-dimensional expanding universe emerges dynamically from type IIB superstring theory in (9+1) dimensions if one treats the theory nonperturbatively.
GRAVITATIONAL WAVES VERSUS X-RAY AND GAMMA-RAY EMISSION IN A SHORT GAMMA-RAY BURST

Recent progress in the understanding of the physical nature of neutron star equilibrium configurations and the first observational evidence of a genuinely short gamma-ray burst (GRB), GRB 090227B, allows us to give an estimate of the gravitational waves versus the X-ray and gamma-ray emission in a short GRB.
Hidden symmetries of Eisenhart-Duval lift metrics and the Dirac equation with flux

setting. In this paper we study the lift from the point of view of the Dirac equation and its hidden symmetries. We show that dimensional reduction of the Dirac equation for the Eisenhart-Duval metric in general gives rise to the non-relativistic Levy-Leblond equation in lower dimension. We study in detail in which specific cases the lower dimensional limit is given by the Dirac equation, with scalar and vector flux, and the relation between lift, reduction and the hidden symmetries of the Dirac equation. While there is a precise correspondence in the case of the lower dimensional massive Dirac equation with no flux, we find that for generic fluxes it is not possible to lift or reduce all solutions and hidden symmetries. As a by-product of this analysis we construct new Lorentzian metrics with special tensors by lifting Killing-Yano and Closed Conformal Killing-Yano tensors and describe the general Conformal Killing-Yano tensor of the Eisenhart-Duval lift metrics in terms of lower dimensional forms. Lastly, we show how dimensionally reducing the higher dimensional operators of the massless Dirac equation that are associated to shared hidden symmetries it is possible to recover hidden symmetry operators for the Dirac equation with flux.
Stochastic volatility with heterogeneous time scales

Agents' heterogeneity is recognized as a driver mechanism for the persistence of financial volatility. We focus on the multiplicity of investment strategies' horizons, we embed this concept in a continuous time stochastic volatility framework and prove that a parsimonious, two-scale version effectively captures the long memory as measured from the real data. Since estimating parameters in a stochastic volatility model is challenging, we introduce a robust methodology based on the Generalized Method of Moments supported by a heuristic selection of the orthogonal conditions. In addition to the volatility clustering, the estimated model also captures other relevant stylized facts, emerging as a minimal but realistic and complete framework for modelling financial time series.
Analytically solvable driven time-dependent two-level quantum systems.

Analytical solutions to the time-dependent Schrödinger equation describing a driven two-level system are invaluable to many areas of physics, but they are also extremely rare. Here, we present a simple algorithm that generates an unlimited number of exact analytical solutions. We show that a general single-axis driving term and its corresponding evolution operator are determined by a single real function which is constrained only by a certain inequality and initial conditions. Any function satisfying these constraints yields an exact analytical solution. We demonstrate this method by presenting several new exact solutions to the time-dependent Schrödinger equation. Our general method and many of the new solutions we present are particularly relevant to qubit control in quantum computing applications.
GRB 120422A: A LOW-LUMINOSITY GAMMA-RAY BURST DRIVEN BY A CENTRAL ENGINE

GRB 120422A is a low-luminosity gamma-ray burst (GRB) associated with a bright supernova, which distinguishes itself by its relatively short T90 (∼5 s) and an energetic and steep-decaying X-ray tail. We analyze the Swift Burst Alert Telescope and X-ray Telescope data and discuss the physical implications. We show that the steep decline early in the X-ray light curve can be interpreted as the curvature tail of a late emission episode around 58–86 s, with a curved instantaneous spectrum at the end of the emission episode. Together with the main activity in the first ∼20 s and the weak emission from 40 s to 60 s, the prompt emission is variable, which points to a central engine origin in contrast to a shock-breakout origin, which is used to interpret some other nearby low-luminosity supernova GRBs. Both the curvature effect model and interpreting the early shallow decay as the coasting external forward shock emission in a wind medium provide a constraint on the bulk Lorentz factor Γ to be around several. Comparing the properties of GRB 120422A and other supernova GRBs, we find that the main criterion to distinguish engine-driven GRBs from shock-breakout GRBs is the time-averaged γ-ray luminosity. Engine-driven GRBs likely have a luminosity above ∼1048 erg s−1.
The effect of market power on risk-sharing

The paper studies an oligopolistic equilibrium model of financial agents who aim to share their random endowments. The risk-sharing securities and their prices are endogenously determined as the outcome of a strategic game played among all the participating agents. In the complete-market setting, each agent’s set of strategic choices consists of the security payoffs and the pricing kernel that are consistent with the optimal-sharing rules; while in the incomplete setting, agents respond via demand functions on a vector of given tradeable securities. It is shown that at the (Nash) risk-sharing equilibrium, the sharing securities are suboptimal, since agents submit for sharing different risk exposures than their true endowments. On the other hand, the Nash equilibrium prices stay unaffected by the game only in the special case of agents with the same risk aversion. In addition, agents with sufficiently lower risk aversion act as predatory traders, since they absorb utility surplus from the high risk averse agents and reduce the efficiency of sharing. The main results of the paper also hold under the generalized models that allow the presence of noise traders and heterogeneity in agents’ beliefs.
Non-Gaussian signatures of Tachyacoustic Cosmology

I investigate non-Gaussian signatures in the context of tachyacoustic cosmology, that is, a noninflationary model with superluminal speed of sound. I calculate the full non-Gaussian amplitude , its size fNL, and corresponding shapes for a red-tilted spectrum of primordial scalar perturbations. Specifically, for cuscuton-like models I show that fNL ~ (1), and the shape of its non-Gaussian amplitude peaks for both equilateral and local configurations, the latter being dominant. These results, albeit similar, are quantitatively distinct from the corresponding ones obtained by Magueijo et al. in the context of superluminal bimetric models.
Application of Fractional Fourier Transform in Cepstrum Analysis

Source wavelet estimation is the key in seismic signal processing for resolving subsurface structural properties. Homomorphic deconvolution using cepstrum analysis has been an effective method for wavelet estimation for decades. In general, the inverse of the Fourier transform of the logarithm of a signal’s Fourier transform is the cepstral domain representation of that signal. The convolution operation of two signals in the time domain becomes an addition in the cepstral domain. The fractional Fourier transform (FRFT) is the generalization of the standard Fourier transform (FT). In an FRFT, the transformation kernel is a set of linear chirps whereas the kernel is composed of complex sinusoids for the FT. Depending on the fractional order, signals can be represented in multiple domains. This gives FRFT an extra degree of freedom in signal analysis over the standard FT. In this paper, we have taken advantage of the multidomain nature of the FRFT and applied it to cepstral analysis. We term this combination the Fractional-Cepstrum (FC). We derive the real FC formulation, and give an example using wavelets to show the multidomain representation of the traditional cepstrum with different fractional orders of the FRFT.
Microlensing of the broad line region in 17 lensed quasars

When an image of a strongly lensed quasar is microlensed, the different components of its spectrum are expected to be differentially magnified owing to the different sizes of the corresponding emitting region. Chromatic changes are expected to be observed in the continuum while the emission lines should be deformed as a function of the size, geometry and kinematics of the regions from which they originate. Microlensing of the emission lines has been reported only in a handful of systems so far. In this paper we search for microlensing deformations of the optical spectra of pairs of images in 17 lensed quasars with bolometric luminosities between 10(44.7) (47.4) erg/s and black hole masses 10(7.6) (9.8) M-circle dot. This sample is composed of 13 pairs of previously unpublished spectra and four pairs of spectra from literature. Our analysis is based on a simple spectral decomposition technique which allows us to isolate the microlensed fraction of the flux independently of a detailed modeling of the quasar emission lines. Using this technique, we detect microlensing of the continuum in 85% of the systems. Among them, 80% show microlensing of the broad emission lines. Focusing on the most common emission lines in our spectra (CIII right perpendicular and MgII) we detect microlensing of either the blue or the red wing, or of both wings with the same amplitude. This observation implies that the broad line region is not in general spherically symmetric. In addition, the frequent detection of microlensing of the blue and red wings independently but not simultaneously with a different amplitude, does not support existing microlensing simulations of a biconical outflow. Our analysis also provides the intrinsic flux ratio between the lensed images and the magnitude of the microlensing affecting the continuum. These two quantities are particularly relevant for the determination of the fraction of matter in clumpy form in galaxies and for the detection of dark matter substructures via the identification of flux ratio anomalies.
A Meet-in-the-Middle Algorithm for Fast Synthesis of Depth-Optimal Quantum Circuits

We present an algorithm for computing depth-optimal decompositions of logical operations, leveraging a meet-in-the-middle technique to provide a significant speedup over simple brute force algorithms. As an illustration of our method, we implemented this algorithm and found factorizations of commonly used quantum logical operations into elementary gates in the Clifford+T set. In particular, we report a decomposition of the Toffoli gate over the set of Clifford and T gates. Our decomposition achieves a total T-depth of 3, thereby providing a 40% reduction over the previously best known decomposition for the Toffoli gate. Due to the size of the search space, the algorithm is only practical for small parameters, such as the number of qubits, and the number of gates in an optimal implementation.
The Quantum Frontier

The success of the abstract model of computation, in terms of bits, logical operations, programming language constructs, and the like, makes it easy to forget that computation is a physical process. Our cherished notions of computation and information are grounded in classical mechanics, but the physics underlying our world is quantum. In the early 80s researchers began to ask how computation would change if we adopted a quantum mechanical, instead of a classical mechanical, view of computation. Slowly, a new picture of computation arose, one that gave rise to a variety of faster algorithms, novel cryptographic mechanisms, and alternative methods of communication. Small quantum information processing devices have been built, and efforts are underway to build larger ones. Even apart from the existence of these devices, the quantum view on information processing has provided significant insight into the nature of computation and information, and a deeper understanding of the physics of our universe and its connections with computation. 
We start by describing aspects of quantum mechanics that are at the heart of a quantum view of information processing. We give our own idiosyncratic view of a number of these topics in the hopes of correcting common misconceptions and highlighting aspects that are often overlooked. A number of the phenomena described were initially viewed as oddities of quantum mechanics. It was quantum information processing, first quantum cryptography and then, more dramatically, quantum computing, that turned the tables and showed that these oddities could be put to practical effect. It is these application we describe next. We conclude with a section describing some of the many questions left for future work, especially the mysteries surrounding where the power of quantum information ultimately comes from.