nils-herrmann/clean_scirepeval huggingface dataset:
Probing light nonthermal dark matter at the LHC

This paper investigates the collider phenomenolgy of a minimal nonthermal dark matter model with a 1-GeV dark matter candidate, which naturally explain baryongensis. Since the light dark matter is not parity-protected, it can be singly produced at the LHC. This leads to large missing energy associated with an energetic jet whose transverse momentum distribution is featured by a Jacobian-like shape. The monojet, dijet, paired dijet and 2 jets + missing energy channels are studied. Currently existing data at Tevatron and LHC offer significant bounds on our model.
Dynamics of a first-order transition to an absorbing state.

A granular system confined in a quasi-two-dimensional box that is vertically vibrated can transit to an absorbing state in which all particles bounce vertically in phase with the box, with no horizontal motion. In principle, this state can be reached for any density lower than the one corresponding to one complete monolayer, which is then the critical density. Below this critical value, the transition to the absorbing state is of first order, with long metastable periods, followed by rapid transitions driven by homogeneous nucleation. Molecular dynamics simulations and experiments show that there is a dramatic increase on the metastable times far below the critical density; in practice, it is impossible to observe spontaneous transitions close to the critical density. This peculiar feature is a consequence of the nonequilibrium nature of this first-order transition to the absorbing state. A Ginzburg-Landau model, with multiplicative noise, describes qualitatively the observed phenomena and explains the macroscopic size of the critical nuclei. The nuclei become of small size only close to a second critical point where the active phase becomes unstable via a saddle node bifurcation. It is only close to this second critical point that experiments and simulations can evidence spontaneous transitions to the absorbing state while the metastable times grow dramatically moving away from it.
Robust large-scale non-negative matrix factorization using Proximal Point algorithm

A robust algorithm for non-negative matrix factorization (NMF) is presented in this paper with the purpose of dealing with large-scale data, where the separability assumption is satisfied. In particular, we modify the Linear Programming (LP) algorithm of [6] by introducing a reduced set of constraints for exact NMF. In contrast to the previous approaches, the proposed algorithm does not require the knowledge of factorization rank (extreme rays [3] or topics ). Furthermore, motivated by a similar problem arising in the context of metabolic network analysis [16], we consider an entirely different regime where the number of extreme rays or topics can be much larger than the dimension of the data vectors. The performance of the algorithm for different synthetic data sets is provided.
Informational Efficiency under Short Sale Constraints

A constrained informationally efficient market is defined to be one whose price process arises as the outcome of some equilibrium where agents face restrictions on trade. This paper investigates the case of short sale constraints, a setting which despite its simplicity, generates new insights. In particular, it is shown that short sale constrained informationally efficient markets always admit equivalent supermartingale measures and local martingale deflators, but not necessarily local martingale measures. And if in addition some local martingale deflator turns the price process into a true martingale, then the market is constrained informationally efficient. Examples are given to illustrate the subtle phenomena that can arise in the presence of short sale constraints, with particular attention to representative agent equilibria and the different notions of no arbitrage.
Pricing of basket options I

Pricing of high-dimensional options is a deep problem of the Theoret- ical Financial Mathematics. In this article we give a transparent and self contained treatment of this problem. Namely, we present and study a new class of Levy driven models of stock markets. In our opinion, any market model should be based on a transparent and intuitively easily acceptable pre-axiomatic concept. In our case this is the system of stochastic equa- tions (2). Our market model is based on the principle of inheritance, i.e. for the particular choice of parameters it coincides with known mod- els. Also, our model is effectively numerically realisable. For the class of models proposed, we give an explicit representations of characteristic functions. This allows us us to construct a sequence of approximation formulas to price basket options. We show that our approximation for- mulas have almost optimal rate of convergence in the sense of respective n-widths.
Skew in parallel query processing

We study the problem of computing a conjunctive query q in parallel, using p of servers, on a large database. We consider algorithms with one round of communication, and study the complexity of the communication. We are especially interested in the case where the data is skewed, which is a major challenge for scalable parallel query processing. We establish a tight connection between the fractional edge packing of the query and the amount of communication in two cases. First, in the case when the only statistics on the database are the cardinalities of the input relations, and the data is skew-free, we provide matching upper and lower bounds (up to a polylogarithmic factor of p) expressed in terms of fractional edge packings of the query q. Second, in the case when the relations are skewed and the heavy hitters and their frequencies are known, we provide upper and lower bounds expressed in terms of packings of residual queries obtained by specializing the query to a heavy hitter. All our lower bounds are expressed in the strongest form, as number of bits needed to be communicated between processors with unlimited computational power. Our results generalize prior results on uniform databases (where each relation is a matching) , and lower bounds for the MapReduce model .
Efficient unimodality test in clustering by signature testing

This paper provides a new unimodality test with application in hierarchical clustering methods. The proposed method denoted by signature test (Sigtest), transforms the data based on its statistics. The transformed data has much smaller variation compared to the original data and can be evaluated in a simple proposed unimodality test. Compared with the existing unimodality tests, Sigtest is more accurate in detecting the overlapped clusters and has a much less computational complexity. Simulation results demonstrate the efficiency of this statistic test for both real and synthetic data sets.
On the Real-time Prediction Problems of Bursting Hashtags in Twitter

Hundreds of thousands of hashtags are generated every day on Twitter. Only a few become bursting topics. Among the few, only some can be predicted in real-time. In this paper, we take the initiative to conduct a systematic study of a series of challenging real-time prediction problems of bursting hashtags. Which hashtags will become bursting? If they do, when will the burst happen? How long will they remain active? And how soon will they fade away? Based on empirical analysis of real data from Twitter, we provide insightful statistics to answer these questions, which span over the entire lifecycles of hashtags.
Automated Code Generation for Lattice Quantum Chromodynamics and beyond

We present here our ongoing work on a Domain Specific Language which aims to simplify Monte-Carlo simulations and measurements in the domain of Lattice Quantum Chromodynamics. The tool-chain, called Qiral, is used to produce high-performance OpenMP C code from LaTeX sources. We discuss conceptual issues and details of implementation and optimization. The comparison of the performance of the generated code to the well-established simulation software is also made.
2+1 flavour thermal studies on an anisotropic lattice

The FASTSUM collaboration has initiated a detailed study of thermal QCD using 2+1 flavours of improved Wilson quarks on anisotropic lattices. Spatial volumes of (3fm)^3 and (4fm)^3 are used at fixed cut-off with temperatures ranging from 40 to 350 MeV (corresponding to temporal lattice extents of 128 to 16 lattice units). Results presented here include the deconfinement temperature and a study of the restoration of chiral symmetry, together with a brief summary of our collaboration's other results from these ensembles.
Ten Simple Rules for the Care and Feeding of Scientific Data

In the early 1600s, Galileo Galilei turned a telescope toward Jupiter. In his log book each night, he drew to-scale schematic diagrams of Jupiter and some oddly moving points of light near it. Galileo labeled each drawing with the date. Eventually he used his observations to conclude that the Earth orbits the Sun, just as the four Galilean moons orbit Jupiter. History shows Galileo to be much more than an astronomical hero, though. His clear and careful record keeping and publication style not only let Galileo understand the solar system, they continue to let anyone understand how Galileo did it. Galileo's notes directly integrated his data (drawings of Jupiter and its moons), key metadata (timing of each observation, weather, and telescope properties), and text (descriptions of methods, analysis, and conclusions). Critically, when Galileo included the information from those notes in Sidereus Nuncius, this integration of text, data, and metadata was preserved, as shown in Figure 1. Galileo's work advanced the “Scientific Revolution,” and his approach to observation and analysis contributed significantly to the shaping of today's modern “scientific method”.
Can a light Higgs impostor hide in composite gauge models

The frequently discussed strongly interacting gauge theory with a fermion flavor doublet in the two-index symmetric (sextet) representation of the SU(3) color gauge group is investigated. In previous studies  the chiral condensate and the mass spectrum were shown to be consistent with chiral symmetry breaking (χSB) at vanishing fermion mass. The recently reported β -function  is not inconsistent with this observation, suggesting that the model is very close to the conformal window and a light “Higgs impostor” could emerge as a composite state. In this work we describe the methodology and preliminary results of studying the emergence of the light composite scalar with 0++ quantum numbers.
Jumping the Gap: The Formation Conditions and Mass Function of 'Pebble-Pile' Planetesimals

In a turbulent proto-planetary disk, dust grains undergo large density fluctuations and under the right circumstances, these grain overdensities can overcome shear, turbulent, and gas pressure support to collapse under self-gravity (forming a “pebble pile” planetesimal). Using a simple analytic model for the fluctuations predicted in simulations, we estimate the rate-of-formation and mass function of self-gravitating, rapidly-collapsing planetesimal-mass bodies formed by this mechanism. The statistics of this process depend sensitively on the size/stopping time of the grains, disk surface density, and turbulent Mach numbers. However, when it occurs, we predict that the resulting planetesimal mass function is broad and quasi-universal, with a slope dN/dM ∝ M^(-(1-2)), spanning a size/mass range ~ 10-10^4 km (10^(-9)-5M_⊕). Collapse to planetesimal through super-Earth masses is possible. The key condition is that grain density fluctuations reach large amplitudes on large scales, where gravitational instability proceeds most easily (collapse of small grains is strongly suppressed by turbulent vorticity). We show this leads to a new criterion for “pebble-pile” formation: Ƭs ≳0.05 ln (Q^(1/2)/Z_d)/ln(1+10ɑ^(1/4))~0.3ψ(Q,Z,ɑ) where Ƭ_s=t_s Ω is the dimensionless particle stopping time. In a MMSN, this requires grains larger than ɑ = (50, 1, 0.1)cm at r = (1, 30, 100)au. So at large radii (beyond the ice line), this may easily occur and seed core accretion. At small radii, it would depend on the existence of large “boulders.” However, because density fluctuations depend super-exponentially on T_s (inversely proportional to disk surface density), lower-density disks are more unstable. In fact, we predict that cm-sized grains at ~ 1 au will form pebble piles in a disk with ~ 10% the MMSN density, so planet formation at ~ au may generically occur “late” as disks are evaporating. We also predict that conditions become progressively more favorable for pebble-pile formation around lower-mass, cooler stars.
Antihelium from dark matter

Cosmic-ray anti-nuclei provide a promising discovery channel for the indirect detection of particle dark matter. Hadron showers produced by the pair-annihilation or decay of Galactic dark matter generate anti-nucleons which can in turn form light anti-nuclei. Previous studies have only focused on the spectrum and flux of low energy antideuterons which, although very rarely, are occasionally also produced by cosmic-ray spallation. Heavier elements ($A\geq3$) have instead entirely negligible astrophysical background and a primary yield from dark matter which could be detectable by future experiments. Using a Monte Carlo event generator and an event-by-event phase space analysis, we compute, for the first time, the production spectrum of \antihe and \antiT for dark matter annihilating or decaying to $b\bar{b}$ and ${W^+}{W^-}$ final states. We then employ a semi-analytic model of interstellar and heliospheric propagation to calculate the \antihe flux as well as to provide tools to relate the anti-helium spectrum corresponding to an arbitrary antideuteron spectrum. Finally, we discuss prospects for current and future experiments, including GAPS and AMS-02.
Combined calculi for photon orbital and spin angular momenta

Wavelength, photon spin angular momentum (PSAM), and photon orbital angular momentum (POAM), completely describe the state of a photon or an electric field (an ensemble of photons). Wavelength relates directly to energy and linear momentum, the corresponding kinetic quantities. PSAMand POAM, themselves kinetic quantities, are colloquially known as polarization and optical vortices, respectively. Astrophysical sources emit photons that carry this information.  PSAM characteristics of an electric field (intensity) are compactly described by the Jones (Stokes/Mueller) calculus. Similarly, I created calculi to represent POAM characteristics of electric fields and intensities in an astrophysical context. Adding wavelength dependence to all of these calculi is trivial. The next logical steps are to 1) form photon total angular momentum (PTAM = POAM + PSAM) calculi; 2) prove their validity using operators and expectation values; and 3) show that instrumental PSAM can affect measured POAM values for certain types electric fields.  I derive the PTAM calculi of electric fields and intensities by combining the POAM and PSAM calculi. I show how these quantities propagate from celestial sphere to image plane. I also form the PTAMoperator (the sum of the POAMand PSAMoperators), with and without instrumental PSAM, and calculate the corresponding expectation values.  Apart from the vector, matrix, dot product, and direct product symbols, the PTAM and POAM calculi appear superficially identical. I provide tables with all possible forms of PTAM calculi. I prove that PTAM expectation values are correct for instruments with and without instrumental PSAM. I also show that POAM measurements of "unfactored" PTAM electric fields passing through non-zero instrumental circular PSAM can be biased.  The combined PTAM calculi provide insight into how to mathematically model PTAM sources and calibrate POAMand PSAM- induced POAM measurement errors.
Quantization of a Complex Higher Order Derivative Theory using Path Integrals

This work addresses the quantization of a self-interacting higher order time derivative theory using path integrals. To quantize this system and avoid the problems of energy not bounded from below and states of negative norm, we observe the following steps: 1) We extend the theory to the complex plane and in this sense we double the degrees of freedom. 2) We add a total derivative to fix the convenient boundary conditions. 3) We check that the complex structure is consistent. 4) To map from the complex space to the real space we introduce reality conditions as second class constraints and we check that the interactions do not generate more constraints. 5) We built the measure of the complex path integral and we show that including currents the theory is projected to a self-interacting real theory that is renormalizable.
Mutual Information Rate-Based Networks in Financial Markets

In the last years efforts in econophysics have been shifted to study how network theory can facilitate understanding of complex financial markets. Main part of these efforts is the study of correlation-based hierarchical networks. This is somewhat surprising as the underlying assumptions of research looking at financial markets is that they behave chaotically. In fact it’s common for econophysicists to estimate maximal Lyapunov exponent for log returns of a given financial asset to confirm that prices behave chaotically. Chaotic behaviour is only displayed by dynamical systems which are either non-linear or infinite-dimensional. Therefore it seems that non-linearity is an important part of financial markets, which is proved by numerous studies confirming financial markets display significant non-linear behaviour, yet network theory is used to study them using almost exclusively correlations and partial correlations, which are inherently dealing with linear dependencies only. In this paper we introduce a way to incorporate non-linear dynamics and dependencies into hierarchical networks to study financial markets using mutual information and its dynamical extension: the mutual information rate. We estimate it using multidimensional Lempel-Ziv complexity and then convert it into an Euclidean metric in order to find appropriate topological structure of networks modelling financial markets. We show that this approach leads to different results than correlation-based approach used in most studies, on the basis of 15 biggest companies listed on Warsaw Stock Exchange in the period of 2009-2012 and 91 companies listed on NYSE100 between 2003 and 2013, using minimal spanning trees and planar maximally filtered graphs.
Bifurcation in epigenetics: implications in development, proliferation, and diseases.

Cells often exhibit different and stable phenotypes from the same DNA sequence. Robustness and plasticity of such cellular states are controlled by diverse transcriptional and epigenetic mechanisms, among them the modification of biochemical marks on chromatin. Here, we develop a stochastic model that describes the dynamics of epigenetic marks along a given DNA region. Through mathematical analysis, we show the emergence of bistable and persistent epigenetic states from the cooperative recruitment of modifying enzymes. We also find that the dynamical system exhibits a critical point and displays, in the presence of asymmetries in recruitment, a bifurcation diagram with hysteresis. These results have deep implications for our understanding of epigenetic regulation. In particular, our study allows one to reconcile within the same formalism the robust maintenance of epigenetic identity observed in differentiated cells, the epigenetic plasticity of pluripotent cells during differentiation, and the effects of epigenetic misregulation in diseases. Moreover, it suggests a possible mechanism for developmental transitions where the system is shifted close to the critical point to benefit from high susceptibility to developmental cues.
GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation

Scientists often express their understanding of the world through a computationally demanding simulation program. Analyzing the posterior distribution of the parameters given observations (the inverse problem) can be extremely challenging. The Approximate Bayesian Computation (ABC) framework is the standard statistical tool to handle these likelihood free problems, but they require a very large number of simulations. In this work we develop two new ABC sampling algorithms that significantly reduce the number of simulations necessary for posterior inference. Both algorithms use confidence estimates for the accept probability in the Metropolis Hastings step to adaptively choose the number of necessary simulations. Our GPS-ABC algorithm stores the information obtained from every simulation in a Gaussian process which acts as a surrogate function for the simulated statistics. Experiments on a challenging realistic biological problem illustrate the potential of these algorithms.
Defining and detecting quantum speedup

How to benchmark a quantum computer Quantum machines offer the possibility of performing certain computations much faster than their classical counterparts. However, how to define and measure quantum speedup is a topic of debate. Rønnow et al. describe methods for fairly evaluating the difference in computational power between classical and quantum processors. They define various types of quantum speedup and consider quantum processors that are designed to solve a specific class of problems. Science, this issue p. 420 What makes a quantum machine quantum? The development of small-scale quantum devices raises the question of how to fairly assess and detect quantum speedup. Here, we show how to define and measure quantum speedup and how to avoid pitfalls that might mask or fake such a speedup. We illustrate our discussion with data from tests run on a D-Wave Two device with up to 503 qubits. By using random spin glass instances as a benchmark, we found no evidence of quantum speedup when the entire data set is considered and obtained inconclusive results when comparing subsets of instances on an instance-by-instance basis. Our results do not rule out the possibility of speedup for other classes of problems and illustrate the subtle nature of the quantum speedup question.
A sequence of nitrogen-rich very red giants in the globular cluster NGC 1851

We present the abundances of N in a sample of 62 stars on the red giant branch (RGB) in the peculiar globular cluster NGC 1851. The values of [N/Fe] ratio were obtained by comparing the flux measured in the observed spectra with that from synthetic spectra for up to about 15 features of CN. This is the first time that N abundances are obtained for such a large sample of RGB stars from medium-resolution spectroscopy in this cluster. With these abundances we provide a chemical tagging of the split red giant branch found from several studies in NGC 1851. The secondary, reddest sequence on the RGB is populated almost exclusively by N-rich stars, confirming our previous suggestion based on Stromgren magnitudes and colours. These giants are also, on average, enriched in s-process elements such as Ba, and are likely the results of pollution from low mass stars that experienced episodes of third dredge-up in the asymptotic giant branch phase.