nils-herrmann/clean_scirepeval huggingface dataset:
Quantum Side Information: Uncertainty Relations, Extractors, Channel Simulations

In the first part of this thesis, we discuss the algebraic approach to classical and quantum physics and develop information theoretic concepts within this setup. 
In the second part, we discuss the uncertainty principle in quantum mechanics. The principle states that even if we have full classical information about the state of a quantum system, it is impossible to deterministically predict the outcomes of all possible measurements. In comparison, the perspective of a quantum observer allows to have quantum information about the state of a quantum system. This then leads to an interplay between uncertainty and quantum correlations. We provide an information theoretic analysis by discussing entropic uncertainty relations with quantum side information. 
In the third part, we discuss the concept of randomness extractors. Classical and quantum randomness are an essential resource in information theory, cryptography, and computation. However, most sources of randomness exhibit only weak forms of unpredictability, and the goal of randomness extraction is to convert such weak randomness into (almost) perfect randomness. We discuss various constructions for classical and quantum randomness extractors, and we examine especially the performance of these constructions relative to an observer with quantum side information. 
In the fourth part, we discuss channel simulations. Shannon's noisy channel theorem can be understood as the use of a noisy channel to simulate a noiseless one. Channel simulations as we want to consider them here are about the reverse problem: simulating noisy channels from noiseless ones. Starting from the purely classical case (the classical reverse Shannon theorem), we develop various kinds of quantum channel simulation results. We achieve this by using classical and quantum randomness extractors that also work with respect to quantum side information.
Time from quantum entanglement: an experimental illustration

In the last years several theoretical papers discussed if time can be an emergent property deriving from quantum correlations. Here, to provide an insight into how this phenomenon can occur, we present an experiment that illustrates Page and Wootters' mechanism of "static" time, and Gambini et al. subsequent refinements. A static, entangled state between a clock system and the rest of the universe is perceived as evolving by internal observers that test the correlations between the two subsystems. We implement this mechanism using an entangled state of the polarization of two photons, one of which is used as a clock to gauge the evolution of the second: an "internal" observer that becomes correlated with the clock photon sees the other system evolve, while an "external" observer that only observes global properties of the two photons can prove it is static.
Astrophysical black holes may radiate, but they do not evaporate

This paper argues that the effect of Hawking radiation on an astrophysical black hole situated in a realistic cosmological context is not total evaporation of the black hole; rather there will always be a remnant mass. The key point is that the locus of emission of Hawking radiation is not the globally defined event horizon. Rather the emission domain lies just outside a timelike Marginal Outer Trapped Surface that is locally defined. The emission domain is mainly located inside the event horizon. A spacelike singularity forms behind the event horizon, and most of the Hawking radiation ends up at this singularity rather than at infinity. Whether any Hawking radiation reaches infinity depends on the relation between the emission domain and the event horizon. From the outside view, even if radiation is seen as always being emitted, the black hole never evaporates away, rather its mass and entropy asymptote to finite non-zero limits, and the event horizon always acts as a sink for matter and information. From an inside view, the matter and information disappear into the singularity, which is the boundary of spacetime. The argument is based on the nature of the processes at work plus a careful delineation of the relevant causal domains; in order to confirm this model and determine details of the outcome, detailed calculations of the expectation value of the stress-energy-momentum tensor are needed to determine back reaction effects.
A latent factor model with a mixture of sparse and dense factors to model gene expression data with confounding effects

One important problem in genome science is to determine sets of co-regulated genes based on measurements of gene expression levels across samples, where the quantification of expression levels includes substantial technical and biological noise. To address this problem, we developed a Bayesian sparse latent factor model that uses a three parameter beta prior to flexibly model shrinkage in the loading matrix. By applying three layers of shrinkage to the loading matrix (global, factor-specific, and element-wise), this model has non-parametric properties in that it estimates the appropriate number of factors from the data. We added a two-component mixture to model each factor loading as being generated from either a sparse or a dense mixture component; this allows dense factors that capture confounding noise, and sparse factors that capture local gene interactions. We developed two statistics to quantify the stability of the recovered matrices for both sparse and dense matrices. We tested our model on simulated data and found that we successfully recovered the true latent structure as compared to related models. We applied our model to a large gene expression study and found that we recovered known covariates and small groups of co-regulated genes. We validated these gene subsets by testing for associations between genotype data and these latent factors, and we found a substantial number of biologically important genetic regulators for the recovered gene subsets.
Chimera: a hybrid approach to numerical loop quantum cosmology

The existence of a quantum bounce in isotropic spacetimes is a key result in loop quantum cosmology (LQC), which has been demonstrated to arise in all the models studied so far. In most of the models, the bounce has been studied using numerical simulations involving states which are sharply peaked and which bounce at volumes much larger than the Planck volume. An important issue is to confirm the existence of the bounce for states which have a wide spread, or which bounce closer to the Planck volume. Numerical simulations with such states demand large computational domains, making them very expensive and practically infeasible with the techniques which have been implemented so far. To overcome these difficulties, we present an efficient hybrid numerical scheme using the property that at the small spacetime curvature, the quantum Hamiltonian constraint in LQC, which is a difference equation with uniform discretization in volume, can be approximated by a Wheeler–DeWitt differential equation. By carefully choosing a hybrid spatial grid allowing the use of partial differential equations at large volumes, and with a simple change of geometrical coordinate, we obtain a surprising reduction in the computational cost. This scheme enables us to explore regimes which were so far unachievable for the isotropic model in LQC. Our approach also promises to significantly reduce the computational cost for numerical simulations in anisotropic LQC using high performance computing.
The first law of soliton and black hole mechanics in five dimensions

We derive a mass formula and a mass variation law for asymptotically flat, stationary spacetimes, invariant under two commuting rotational symmetries, in a general five dimensional theory of gravity coupled to an arbitrary set of Maxwell fields and uncharged scalar fields. If the spacetime is everywhere regular, these mass formulas reduce to a sum of magnetic flux terms defined on its non-trivial 2-cycles. If there is a black hole, we obtain a mass variation law more general than previously obtained, which also has contributions from the 2-cycles exterior to the black hole. This can be interpreted as the first law of black hole mechanics in a background soliton containing bubbles.
A TIDALLY STRIPPED STELLAR COMPONENT OF THE MAGELLANIC BRIDGE

Deep photometry of the Small Magellanic Cloud (SMC) stellar periphery (R = 4°, 4.2 kpc) is used to study its line-of-sight depth with red clump (RC) stars. The RC luminosity function is affected little by young (≲1 Gyr) blue-loop stars in these regions because their main-sequence counterparts are not observed in the color–magnitude diagrams. The SMCs eastern side is found to have a large line-of-sight depth (∼23 kpc) while the western side has a much shallower depth (∼10 kpc), consistent with previous photographic plate photometry results. We use a model SMC RC luminosity function to deconvolve the observed RC magnitudes and construct the density function in distance for our fields. Three of the eastern fields show a distance bimodality with one component at the “systemic” ∼67 kpc SMC distance and a second component at ∼55 kpc. Our data are not reproduced well by the various extant Magellanic Cloud and Stream simulations. However, the models predict that the known H i Magellanic Bridge (stretching from the SMC eastward toward the Large Magellanic Cloud, LMC) has a decreasing distance with angle from the SMC and should be seen in both the gaseous and stellar components. From comparison with these models, we conclude that the most likely explanation for our newly identified ∼55 kpc stellar structure in the eastern SMC is a stellar counterpart of the H i Magellanic Bridge that was tidally stripped from the SMC ∼200 Myr ago during a close encounter with the LMC. This discovery has important implications for microlensing surveys of the SMC.
Search for CP violating signature of intergalactic magnetic helicity in the gamma-ray sky

The existence of a cosmological magnetic field could be revealed by the effects of non-trivial helicity on large scales. We evaluate a CP (conjugation plus parity) odd statistic, Q ,u sing gamma-ray data obtained from Fermi satellite observations at high galactic latitudes to search forsuchasignature.ObservedvaluesofQarefoundtobenon-zero;theprobabilityofasimilar signal in Monte Carlo simulations is ∼0.2 per cent. Contamination from the Milky Way does not seem to be responsible for the signal since it is present even for data at very high galactic latitudes. Assuming that the signal is indeed due to a helical cosmological magnetic field, our results indicate left-handed magnetic helicity and field strength ∼10 −14 Go n∼10Mpc scales.
Asymptotic Glosten-Milgrom Equilibrium

This paper studies the Glosten Milgrom model whose risky asset value admits an arbitrary discrete distribution. Contrast to existing results on insider’s models, the insider’s optimal strategy in this model, if exists, is not of feedback type. Therefore a weak formulation of equilibrium is proposed. In this weak formulation, the inconspicuous trade theorem still holds, but the optimality for the insider’s strategy is not enforced. However, the insider can employ some feedback strategy whose associated expected profit is close to the optimal value, when the order size is small. Moreover this discrepancy converges to zero when the order size diminishes. The existence of such a weak equilibrium is established, in which the insider’s strategy converges to the Kyle optimal strategy when the order size goes to zero.
Strong Planck constraints on braneworld and non-commutative inflation

We place observational likelihood constraints on braneworld and non-commutative inflation for a number of inflaton potentials, using Planck, WMAP polarization and BAO data. Both braneworld and non-commutative scenarios of the kind considered here are limited by the most recent data even more severely than standard general-relativity models. At more than 95 % confidence level, the monomial potential V(ϕ)∝ϕp is ruled out for p ⩾ 2 in the Randall-Sundrum (RS) braneworld cosmology and, for p > 0, also in the high-curvature limit of the Gauss-Bonnet (GB) braneworld and in the infrared limit of non-commutative inflation, due to a large scalar spectral index. Some parameter values for natural inflation, small-varying inflaton models and Starobinsky inflation are allowed in all scenarios, although some tuning is required for natural inflation in a non-commutative spacetime.
GPatt: Fast Multidimensional Pattern Extrapolation with Gaussian Processes

Gaussian processes are typically used for smoothing and interpolation on small datasets. We introduce a new Bayesian nonparametric framework -- GPatt -- enabling automatic pattern extrapolation with Gaussian processes on large multidimensional datasets. GPatt unifies and extends highly expressive kernels and fast exact inference techniques. Without human intervention -- no hand crafting of kernel features, and no sophisticated initialisation procedures -- we show that GPatt can solve large scale pattern extrapolation, inpainting, and kernel discovery problems, including a problem with 383400 training points. We find that GPatt significantly outperforms popular alternative scalable Gaussian process methods in speed and accuracy. Moreover, we discover profound differences between each of these methods, suggesting expressive kernels, nonparametric representations, and exact inference are useful for modelling large scale multidimensional patterns.
Bayesian Extensions of Kernel Least Mean Squares

The kernel least mean squares (KLMS) algorithm is a computationally efficient nonlinear adaptive filtering method that "kernelizes" the celebrated (linear) least mean squares algorithm. We demonstrate that the least mean squares algorithm is closely related to the Kalman filtering, and thus, the KLMS can be interpreted as an approximate Bayesian filtering method. This allows us to systematically develop extensions of the KLMS by modifying the underlying state-space and observation models. The resulting extensions introduce many desirable properties such as "forgetting", and the ability to learn from discrete data, while retaining the computational simplicity and time complexity of the original algorithm.
Rewiring the network. What helps an innovation to diffuse?

A fundamental question related to innovation diffusion is how the structure of the social network influences the process. Empirical evidence regarding real-world networks of influence is very limited. On the other hand, agent-based modeling literature reports different, and at times seemingly contradictory, results. In this paper we study innovation diffusion processes for a range of Watts–Strogatz networks in an attempt to shed more light on this problem. Using the so-called Sznajd model as the backbone of opinion dynamics, we find that the published results are in fact consistent and allow us to predict the role of network topology in various situations. In particular, the diffusion of innovation is easier on more regular graphs, i.e. with a higher clustering coefficient. Moreover, in the case of uncertainty—which is particularly high for innovations connected to public health programs or ecological campaigns—a more clustered network will help the diffusion. On the other hand, when social influence is less important (i.e. in the case of perfect information), a shorter path will help the innovation to spread in the society and—as a result—the diffusion will be easiest on a random graph.
MuPAD codes which implement limit-computable functions that cannot be bounded by any computable function

Let E<sub>n</sub> = {x<sub>k</sub> = 1, x<sub>i</sub> + x<sub>j</sub> = x<sub>k</sub>, x<sub>i</sub> · x<sub>j</sub> = x<sub>k</sub> : i, j, k ∈ {1, ..., n}}. For a positive integer n, let f (n) denote the smallest non-negative integer b such that for each system S ⊆ E<sub>n</sub> with a solution in non-negative integers x<sub>1</sub>, ..., x<sub>n</sub> there exists a solution of S in non-negative integers not greater than b. We prove that if a function Γ : ℕ \ {0} → ℕ is computable, then f dominates Γ i.e. there exists a positive integer m such that Γ(n) <; f (n) for any n ≥ m. For positive integers n, m, let g(n,m) denote the smallest non-negative integer b such that for each system S ⊆ E<sub>n</sub> with a solution in {0, ..., m - 1}<sup>n</sup> there exists a solution of S in {0, ..., b}<sup>n</sup>. Then, equations and equation We present an infinite loop in MuPAD which takes as input a positive integer n and returns g(n,m) on the m-th iteration.
Frequency effects on predictability of stock returns

We propose that predictability is linked with profitability in a complex manner. We look at ways to measure predictability of price changes using information theoretic approach and employ them on historical data for NYSE 100 stocks. This allows us to determine whether frequency of sampling price changes affects the predictability of those. We also study relations between price changes predictability and the deviation of the price formation processes from iid as well as the stock's sector. We also briefly comment on the complicated relationship between predictability of price changes and the profitability of algorithmic trading.
The return of the proplyds - understanding the dynamics of ionization triggered stars

Proplyds and stars inside HII-regions are a well studied phenomenon. It is possiblethat they were triggered by the expansion of the HII-region itself. Here, we presentcalculationsonthe dynamicsofHII-regions.We showthat the triggeredstarsthat formin the expanding shell of swept up material around the HII region rarelyreturn into theHII regions on timescales that are inferred for the proplyds and observed young stars.However, in very dense environments like Orion, the triggered stars return in time.Thus, our model can explain why proplydsare barelyobservedin other HII regions.Wepropose that the properties of young stellar objects in HII regions in general dependcritically on the distance from the massive, ionizing central star cluster. Closest in,there are proplyds, where the disk of a young star interacts directly with the feedbackof the massive star. Further out are Class II protostars, where the ionization alreadyremoved the envelope. Even further away, one should ﬁnd Class I stars, which eitherhave been triggered by the ionizing radiation or pre-existed and have not lost theirenvelope yet. This radial sequence is not necessarily an age sequence but rather a resultof the dwindling importance of stellar winds and ionizing radiation with distance. Weinvestigate the observational signature of triggered star formation and ﬁnd that thestellar distribution for ionization triggered star formation shows a distinct feature, apeak at the current position of the ionization front. Therefore, it is generally possibleto tell triggered and in situ distributions of stars apart. (ISM:) H II regions, ISM: globules, ISM: kinematics and dynamics,stars: formation, stars: kinematics, methods: analytical
Higgs Bosons in the Standard Model and Beyond

In these proceedings I cover the latest results on the production and decay of the recently discovered Higgs boson. While the spin and properties of the new boson, such as its mass and couplings to bosons and fermions, are covered in a separate report, I focus on individual results in the main channels we use to study the properties of the new boson and to search for its possible cousins, with the focus on the latest results from the LHC and the Tevatron collaborations.
Cascading Failures in Networks with Proximate Dependent Nodes

We study the mutual percolation of a system composed of two interdependent random regular networks. We introduce a notion of distance to explore the effects of the proximity of interdependent nodes on the cascade of failures after an initial attack. We find a nontrivial relation between the nature of the transition through which the networks disintegrate and the parameters of the system, which are the degree of the nodes and the maximum distance between interdependent nodes. We explain this relation by solving the problem analytically for the relevant set of cases. In the process, we solve a variant of Rényi's parking problem on treelike graphs.
ROP: Matrix Recovery via Rank-One Projections

Estimation of low-rank matrices is of significant interest in a range of contemporary applications. In this paper, we introduce a rank-one projection model for low-rank matrix recovery and propose a constrained nuclear norm minimization method for stable recovery of low-rank matrices in the noisy case. The procedure is adaptive to the rank and robust against small perturbations. Both upper and lower bounds for the estimation accuracy under the Frobenius norm loss are obtained. The proposed estimator is shown to be rate-optimal under certain conditions. The estimator is easy to implement via convex programming and performs well numerically. The techniques and main results developed in the paper also have implications to other related statistical problems. An application to estimation of spiked covariance matrices from one-dimensional random projections is considered. The results demonstrate that it is still possible to accurately estimate the covariance matrix of a high-dimensional distribution based only on one-dimensional projections.
Extreme Scaling of Lattice Quantum Chromodynamics

As the complexity and size of challenges in science and engineering are continually increasing, it is highly important that applications are able to scale strongly to very large numbers of cores (>100,000 cores) to enable HPC systems to be utilised efficiently. This paper presents results of strong scaling tests performed with an MPI only and a hybrid MPI + OpenMP version of the Lattice QCD application BQCD on the European Tier-0 system SuperMUC at LRZ.
PLANET HUNTERS. VI. AN INDEPENDENT CHARACTERIZATION OF KOI-351 AND SEVERAL LONG PERIOD PLANET CANDIDATES FROM THE KEPLER ARCHIVAL DATA

We report the discovery of 14 new transiting planet candidates in the Kepler field from the Planet Hunters citizen science program. None of these candidates overlapped with Kepler Objects of Interest (KOIs) at the time of submission. We report the discovery of one more addition to the six planet candidate system around KOI-351, making it the only seven planet candidate system from Kepler. Additionally, KOI-351 bears some resemblance to our own solar system, with the inner five planets ranging from Earth to mini-Neptune radii and the outer planets being gas giants; however, this system is very compact, with all seven planet candidates orbiting ≲ 1 AU from their host star. A Hill stability test and an orbital integration of the system shows that the system is stable. Furthermore, we significantly add to the population of long period transiting planets; periods range from 124 to 904 days, eight of them more than one Earth year long. Seven of these 14 candidates reside in their host star's habitable zone.
Simple implementation of general dark energy models

We present a formalism for the numerical implementation of general theories of dark energy, combining the computational simplicity of the equation of state for perturbations approach with the generality of the effective field theory approach. An effective fluid description is employed, based on a general action describing single-scalar field models. The formalism is developed from first principles, and constructed keeping the goal of a simple implementation into CAMB in mind. Benefits of this approach include its straightforward implementation, the generality of the underlying theory, the fact that the evolved variables are physical quantities, and that model-independent phenomenological descriptions may be straightforwardly investigated. We hope this formulation will provide a powerful tool for the comparison of theoretical models of dark energy with observational data.