nils-herrmann/clean_scirepeval huggingface dataset:
Fermion Particle Production in Dynamical Casimir Effect in a Three-Dimensional Box

In this paper, we investigate the problem of fermion creation inside a three-dimensional cubic box. We present an appropriate wave function which satisfies the Dirac equation in this geometry with MIT bag model boundary condition. We consider the box with oscillating walls and introduce the time evolution of the quantized field by expanding it over the instantaneous basis. We explain how we can obtain the average number of particles created. In this regard, we find the Bogoliubov coefficients. We consider an oscillation and determine the coupling conditions between different modes that can be satisfied depending on the cavity's spectrum. Assuming the parametric resonance case we obtain an expression for the mean number of created fermions in each mode of an oscillation and their dynamical Casimir energy.
Dark matter constraints from box-shaped gamma-ray features

The observation of a sharp spectral feature in the gamma-ray sky would be one of the cleanest ways to identify dark matter and pinpoint its properties. Over the years a lot of attention has been paid to two specific features, namely gamma-ray lines and internal bremsstrahlung. Here, we explore a third class of spectral signatures, box-shaped gamma-ray spectra, that naturally arise in dark matter cascade annihilations or decays into intermediate particles that in turn decay into photons. Using Fermi-LAT data, we derive constraints on the dark matter parameter space for both annihilating and decaying dark matter, and show explicitly that our limits are competitive to strategies employing standard spectral features. More importantly, we find robust limits even in the case of non-degenerate dark matter and intermediate particle masses. This result is particularly relevant in constraining dark matter frameworks with gamma-ray data. We conclude by illustrating the power of box-shaped gamma-ray constraints on concrete particle physics scenarios.
A Market for Unbiased Private Data: Paying Individuals According to Their Privacy Attitudes

Since there is, in principle, no reason why third parties should not pay individuals for the use of their data, we introduce a realistic market that would allow these payments to be made while taking into account the privacy attitude of the participants. And since it is usually important to use unbiased samples to obtain credible statistical results, we examine the properties that such a market should have and suggest a mechanism that compensates those individuals that participate according to their risk attitudes. Equally important, we show that this mechanism also benefits buyers, as they pay less for the data than they would if they compensated all individuals with the same maximum fee that the most concerned ones expect.
Percolation Computation in Complex Networks

K-clique percolation is an overlapping community finding algorithm which extracts particular structures, comprised of overlapping cliques, from complex networks. While it is conceptually straightforward, and can be elegantly expressed using clique graphs, certain aspects of k-clique percolation are computationally challenging in practice. In this paper we investigate aspects of empirical social networks, such as the large numbers of overlapping maximal cliques contained within them, that make clique percolation, and clique graph representations, computationally expensive. We motivate a simple algorithm to conduct clique percolation, and investigate its performance compared to current best-in-class algorithms. We present improvements to this algorithm, which allow us to perform k-clique percolation on much larger empirical datasets. Our approaches perform much better than existing algorithms on networks exhibiting pervasively overlapping community structure, especially for higher values of k. However, clique percolation remains a hard computational problem, current algorithms still scale worse than some other overlapping community finding algorithms.
Non-Universality in Semi-Directed Barabasi-Albert Networks

In usual scale-free networks of Barabasi-Albert type, a newly added node selects randomly m neighbors from the already existing network nodes, proportionally to the number of links these had before. Then the number N(k) of nodes with k links each decays as 1/k^gamma where gamma=3 is universal, i.e. independent of m. Now we use a limited directedness in the construction of the network, as a result of which the exponent gamma decreases from 3 to 2 for increasing m.
Fractal Profit Landscape of the Stock Market

We investigate the structure of the profit landscape obtained from the most basic, fluctuation based, trading strategy applied for the daily stock price data. The strategy is parameterized by only two variables, p and q Stocks are sold and bought if the log return is bigger than p and less than –q, respectively. Repetition of this simple strategy for a long time gives the profit defined in the underlying two-dimensional parameter space of p and q. It is revealed that the local maxima in the profit landscape are spread in the form of a fractal structure. The fractal structure implies that successful strategies are not localized to any region of the profit landscape and are neither spaced evenly throughout the profit landscape, which makes the optimization notoriously hard and hypersensitive for partial or limited information. The concrete implication of this property is demonstrated by showing that optimization of one stock for future values or other stocks renders worse profit than a strategy that ignores fluctuations, i.e., a long-term buy-and-hold strategy.
Constraining primordial non-Gaussianity with CMB–21 cm cross-correlations?

We investigate the effect of primordial non-Gaussianity on the cross-correlation between the CMB anisotropies and the 21 cm fluctuations from the epoch of reionization. We assume an analytic reionization model and an ionization fraction with $f_{\rm NL}$ induced scale dependent bias. We estimate the angular power spectrum of the cross-correlation of the CMB and 21 cm. In order to evaluate the detectability, the signal-to-noise (S/N) ratio for only a single redshift slice is also calculated for current and future observations, such as CMB observations by Planck satellite and 21 cm observations by Omniscope. The existence of the $f_{\rm NL}$ increases the signal of the cross-correlation at large scales and the amplification does not depend on the reionization parameters in our reionization model. However the cosmic variance is significant on such scales and the S/N ratio is suppressed. The obtained S/N ratio is 2.8 (2.4) for $f_{\rm NL}=10$ (100) in our fiducial reionization model. Our work suggests in the absence of significant foregrounds and systematics, the auto-correlations of 21 cm is a better probe of $f_{\rm NL}$ than the cross-correlations (as expected since it depends on $b^2$), while the cross-correlations contain only one factor of $b$. Nevertheless, it is interesting to examine the cross-correlations between 21 cm and CMB, as the signal-to-noise ratio is not negligible and it is more likely we can rid ourselves of systematics and foregrounds that are common to both CMB and 21 cm experiments than completely clean 21 cm of all of the possible foregrounds and systematics in large scales.
Is Eternal Inflation Past-Eternal? And What if It Is?

As a result of discussions with Bousso and Vilenkin I want to return to the question of whether the multiverse is past-eternal or if there was a beginning. Not surprisingly, given three people, there were three answers. However, the discussions have led to some common ground. 
The multiverse being past-eternal, or at least extremely old has content and potential phenomenological implications. I will discuss how the oldness of the multiverse is connected with recent speculations of Douglas.
Complex Networks from Simple Rewrite Systems

Complex networks are all around us, and they can be generated by simple mechanisms. Understanding what kinds of networks can be produced by following simple rules is therefore of great importance. We investigate this issue by studying the dynamics of extremely simple systems where are `writer' moves around a network, and modifies it in a way that depends upon the writer's surroundings. Each vertex in the network has three edges incident upon it, which are colored red, blue and green. This edge coloring is done to provide a way for the writer to orient its movement. We explore the dynamics of a space of 3888 of these `colored trinet automata' systems. We find a large variety of behaviour, ranging from the very simple to the very complex. We also discover simple rules that generate forms which are remarkably similar to a wide range of natural objects. We study our systems using simulations (with appropriate visualization techniques) and analyze selected rules mathematically. We arrive at an empirical classification scheme which reveals a lot about the kinds of dynamics and networks that can be generated by these systems.
On the calculation of percentile-based bibliometric indicators

A percentile-based bibliometric indicator is an indicator that values publications based on their position within the citation distribution of their field. The most straightforward percentile-based indicator is the proportion of frequently cited publications, for instance, the proportion of publications that belong to the top 10% most frequently cited of their field. Recently, more complex percentile-based indicators have been proposed. A difficulty in the calculation of percentile-based indicators is caused by the discrete nature of citation distributions combined with the presence of many publications with the same number of citations. We introduce an approach to calculating percentile-based indicators that deals with this difficulty in a more satisfactory way than earlier approaches suggested in the literature. We show in a formal mathematical framework that our approach leads to indicators that do not suffer from biases in favor of or against particular fields of science.
On measuring the absolute scale of baryon acoustic oscillations

The baryon acoustic oscillation (BAO) feature in the distribution of galaxies provides a fundamental standard ruler which is widely used to constrain cosmological parameters. In most analyses, the comoving length of the ruler is inferred from a combination of cosmic microwave background (CMB) observations and theory. However, this inferred length may be biased by various non-standard effects in early universe physics; this can lead to biased inferences of cosmological parameters such as H0, Ωm and w, so it would be valuable to measure the absolute BAO length by combining a galaxy redshift survey and a suitable direct low-z distance measurement. One obstacle is that low-redshift BAO surveys mainly constrain the ratio rS/DV(z), where DV is a dilation scale which is not directly observable by standard candles. Here, we find a new approximation which connects DV to the standard luminosity distance DL at a somewhat higher redshift; this is shown to be very accurate (relative error <0.2 per cent) for all Wilkinson Microwave Anisotropy Probe compatible Friedmann models at z < 0.4, with very weak dependence on cosmological parameters H0, Ωm, Ωk, w. This provides a route to measure the absolute BAO length using only observations at z ≲ 0.3, including Type Ia supernovae, and potentially future H0-free physical distance indicators such as gravitational lenses or gravitational wave standard sirens. This would provide a zero-parameter check of the standard cosmology at 103 ≲ z ≲ 105, and can constrain the number of relativistic species Neff with fewer degeneracies than the CMB.
Statistical anomalies in 2011-2012 Russian elections revealed by 2D correlation analysis

Here we perform a statistical analysis of the official data from recent Russian parliamentary and presidential elections (held on December 4th, 2011 and March 4th, 2012, respectively). A number of anomalies are identified that persistently skew the results in favour of the pro-government party, United Russia (UR), and its leader Vladimir Putin. The main irregularities are: (i) remarkably high correlation between turnout and voting results; (ii) a large number of polling stations where the UR/Putin results are given by a round number of percent; (iii) constituencies showing improbably low or (iv) anomalously high dispersion of results across polling stations; (v) substantial difference between results at paper-based and electronic polling stations. These anomalies, albeit less prominent in the presidential elections, hardly conform to the assumptions of fair and free voting. The approaches proposed here can be readily extended to quantify fingerprints of electoral fraud in any other problematic elections.
Exact Wavelets on the Ball

We develop an exact wavelet transform on the three-dimensional ball (i.e. on the solid sphere), which we name the flaglet transform. For this purpose we first construct an exact transform on the radial half-line using damped Laguerre polynomials and develop a corresponding quadrature rule. Combined with the spherical harmonic transform, this approach leads to a sampling theorem on the ball and a novel three-dimensional decomposition which we call the Fourier-Laguerre transform. We relate this new transform to the well-known Fourier-Bessel decomposition and show that band-limitedness in the Fourier-Laguerre basis is a sufficient condition to compute the Fourier-Bessel decomposition exactly. We then construct the flaglet transform on the ball through a harmonic tiling, which is exact thanks to the exactness of the Fourier-Laguerre transform (from which the name flaglets is coined). The corresponding wavelet kernels are well localised in real and Fourier-Laguerre spaces and their angular aperture is invariant under radial translation. We introduce a multiresolution algorithm to perform the flaglet transform rapidly, while capturing all information at each wavelet scale in the minimal number of samples on the ball. Our implementation of these new tools achieves floating-point precision and is made publicly available. We perform numerical experiments demonstrating the speed and accuracy of these libraries and illustrate their capabilities on a simple denoising example.
The nature of the present

The feeling of a moving present or `now' seems to form part of our most basic perceptions about reality. Such a present, however, is not reflected in any of our theories of the physical world. In this short note I argue for a tenseless view of time, where what we call `the present' is just an emergent secondary quality arising from the interaction of perceiving self-conscious individuals with their environment. I maintain that there is no flow of time, but just an ordered system of events.
Precision astrometry of the exoplanet host candidate GD 66

The potential existence of a giant planet orbiting within a few au of a stellar remnant has profound implications for both the survival and possible regeneration of planets during postmain-sequence stellar evolution. This paper reports Hubble Space Telescope Fine Guidance Sensor and US Naval Observatory relative astrometry of GD 66, a white dwarf thought to harbour a giant planet between 2 and 3 au based on stellar pulsation arrival times. Combined with existing infrared data, the precision measurements here rule out all stellar-mass and brown dwarf companions, implying that only a planet remains plausible, if orbital motion is indeed the cause of the variations in pulsation timing.
THE METALLICITY OF THE MONOCEROS STREAM

We present low-resolution MMT Hectospec spectroscopy of 594 candidate Monoceros stream member stars. Based on strong color–magnitude diagram overdensities, we targeted three fields within the stream's footprint, with 178° ⩽ l ⩽ 203° and −25° ⩽ b ⩽ 25°. By comparing the measured iron abundances with those expected from smooth Galactic components alone, we measure, for the first time, the spectroscopic metallicity distribution function for Monoceros. We find the stream to be chemically distinct from both the thick disk and halo, with [Fe/H] = −1, and do not detect a trend in the stream's metallicity with Galactic longitude. Passing from b = +25° to b = −25°, the median Monoceros metallicity trends upward by 0.1 dex, though uncertainties in modeling sample contamination by the disk and halo make this a marginal detection. In each field, we find Monoceros to have an intrinsic [Fe/H] dispersion of 0.10–0.22 dex. From the Ca ii K line, we measure [Ca/Fe] for a subsample of metal-poor program stars with −1.1 < [Fe/H] < −0.5. In two of three fields, we find calcium deficiencies qualitatively similar to previously reported [Ti/Fe] underabundances in Monoceros and the Sagittarius tidal stream. Further, using 90 spectra of thick disk stars in the Monoceros pointings with b ≈ ±25°, we detect a 0.22 dex north/south metallicity asymmetry coincident with known stellar density asymmetry at RGC ≈ 12 kpc and |Z| ≈ 1.7 kpc. Our median Monoceros [Fe/H] = −1.0 and its relatively low dispersion naturally fit the expectation for an appropriately luminous MV ∼ − 13 dwarf galaxy progenitor.
Blue Fermi flat spectrum radio quasars

Many blazars detected by the Fermi satellite, observed spectroscopically in the optical, are line-less, and have been classified as BL Lac objects. Optical–ultraviolet (UV) photometry of nearly 100 of them allowed us to determine the redshift for a handful of objects and redshift upper limits in the great majority. A few of these are candidates to be ‘blue quasars’, namely flat spectrum radio quasars whose broad emission lines are hidden by an overwhelming synchrotron emission peaking in the UV. This implies that the emitting electrons have high energies. In turn, this requires relatively weak radiative cooling, a condition that can be met if the main radiative dissipation of the jet power occurs outside the broad-line region. We confirm this hypothesis by studying and modelling the spectral energy distributions of the four ‘blue quasars’ recently discovered. Furthermore, we discuss the distribution of Fermi blazars in the γ-ray spectral index–γ-ray luminosity plane, and argue that ‘blue quasars’ objects are a minority within the blazar populations.
Data Analysis of Gravitational Waves Signals from Millisecond Pulsars

The present work is devoted to the detection of monochromatic gravitational wave signals emitted by pulsars using ALLEGRO's data detector. We will present the region (in frequency) of millisecond pulsars of the globular cluster 47 Tucanae (NGC 104) in the band of detector. With this result it was possible to analyse the data in the frequency ranges of the pulsars J1748-2446L and J1342+2822c, searching for annual Doppler variations using power spectrum estimates for the year 1999. We tested this method injecting a simulated signal in real data and we were able to detect it.
Constraining the unHiggs model with LHC data

Recent measurements by the ATLAS and CMS experiments have excluded the standard model Higgs boson in the high mass region, even if it is produced with a significantly smaller cross section than expected. The bounds are dominated by the nonobservation of a signal in the clean gold-plated mode h→ZZ→4l and, hence, are directly related to the special role of the Higgs in electroweak symmetry breaking. A smaller cross section in comparison to the standard model is expected if the Higgs is realized as an unparticle in the unHiggs scenario. With the LHC probing σ/σSM<1, we can therefore reinterpret the h→ZZ→4l exclusion limits as bounds on the unHiggs’ scaling dimension. Throughout the high Higgs mass range, where we expect a large signal in the presence of the standard model Higgs for the 2011 ATLAS and CMS data sets, the observed limits translate into mild bounds on the unHiggs scaling dimension in the high mass region.
Parallel Clustering with Cfinder

The amount of available data about complex systems is increasing every year, measurements of larger and larger systems are collected and recorded. A natural representation of such data is given by networks, whose size is following the size of the original system. The current trend of multiple cores in computing infrastructures call for a parallel reimplementation of earlier methods. Here we present the grid version of CFinder, which can locate overlapping communities in directed, weighted or undirected networks based on the clique percolation method (CPM). We show that the computation of the communities can be distributed among several CPU-s or computers. Although switching to the parallel version not necessarily leads to gain in computing time, it definitely makes the community structure of extremely large networks accessible.
Credit Default Swaps Drawup Networks: Too Interconnected to Be Stable?

We analyse time series of CDS spreads for a set of major US and European institutions in a period overlapping the recent financial crisis. We extend the existing methodology of -drawdowns to the one of joint -drawups, in order to estimate the conditional probabilities of spike-like co-movements among pairs of spreads. After correcting for randomness and finite size effects, we find that, depending on the period of time, 50% of the pairs or more exhibit high probabilities of joint drawups and the majority of spread series are trend-reinforced, i.e. drawups tend to be followed by drawups in the same series. We then carry out a network analysis by taking the probability of joint drawups as a proxy of financial dependencies among institutions. We introduce two novel centrality-like measures that offer insights on how both the systemic impact of each node as well as its vulnerability to other nodes' shocks evolve in time.
EUROPEAN OPTION PRICING WITH LIQUIDITY SHOCKS

We study the valuation and hedging problem of European options in a market subject to liquidity shocks. Working within a Markovian regime-switching setting, we model illiquidity as the inability to trade. To isolate the impact of such liquidity constraints, we focus on the case where the market is completely static in the illiquid regime. We then consider derivative pricing using either equivalent martingale measures or exponential indifference mechanisms. Our main results concern the analysis of the semi-linear coupled Hamilton–Jacobi–Bellman (HJB) equation satisfied by the indifference price, as well as its asymptotics when the probability of a liquidity shock is small. A comparative analysis between the model price and the classical Black–Scholes benchmark is given using the concepts of implied and adjusted time to maturity. We then present several numerical studies of the liquidity risk premia obtained in our models leading to practical guidelines on how to adjust for liquidity risk in option valuation and hedging.
From Risk Measures to Research Measures

In order to evaluate the quality of the scientific research, we introduce a new family of scientific performance measures, called Scientific Research Measures (SRM). Our proposal originates from the more recent developments in the theory of risk measures and is an attempt to resolve the many problems of the existing bibliometric indices. The SRM that we introduce are based on the whole scientist's citation record and are: coherent, as they share the same structural properties; flexible to fit peculiarities of different areas and seniorities; granular, as they allow a more precise comparison between scientists, and inclusive, as they comprehend several popular indices. Another key feature of our SRM is that they are planned to be calibrated to the particular scientific community. We also propose a dual formulation of this problem and explain its relevance in this context.