nils-herrmann/clean_scirepeval huggingface dataset:
Concurrent Hyland-Ong games

We build a cartesian closed category, called CHO, based on event structures. It allows an interpretation of higher-order stateful concurrent programs that is refined and precise: on the one hand it is conservative with respect to standard Hyland-Ong games when interpreting purely functional programs as innocent strategies, while on the other hand it is much more expressive. The interpretation of programs constructs compositionally a representation of their execution that exhibits causal dependencies and remembers the points of non-deterministic branching. 
 
The construction is in two stages. First, we build a compact closed category TCG. It is a variant of Rideau and Winskel's category CG, with the 
difference that games and strategies in TCG are equipped with symmetry to express that certain events are essentially the same. This 
is analogous to the underlying category of AJM games enriching simple games with an equivalence relations on plays. Building on this category, we construct the cartesian closed category CHO as having as objects the standard arenas of Hyland-Ong games, with 
strategies, represented by certain events structures, playing on games with symmetry obtained as expanded forms of these arenas. 
 
To illustrate and give an operational light on these constructions, we interpret (a close variant of) Idealized Parallel Algol in CHO.
Magnetic field reversals and long-time memory in conducting flows.

Employing a simple ideal magnetohydrodynamic model in spherical geometry, we show that the presence of either rotation or finite magnetic helicity is sufficient to induce dynamical reversals of the magnetic dipole moment. The statistical character of the model is similar to that of terrestrial magnetic field reversals, with the similarity being stronger when rotation is present. The connection between long-time correlations, 1/f noise, and statistics of reversals is supported, consistent with earlier suggestions.
Topic similarity networks: Visual analytics for large document sets

We investigate ways in which to improve the interpretability of LDA topic models by better analyzing and visualizing their outputs. We focus on examining what we refer to as topic similarity networks: graphs in which nodes represent latent topics in text collections and links represent similarity among topics. We describe efficient and effective approaches to both building and labeling such networks. Visualizations of topic models based on these networks are shown to be a powerful means of exploring, characterizing, and summarizing large collections of unstructured text documents. They help to “tease out” non-obvious connections among different sets of documents and provide insights into how topics form larger themes. We demonstrate the efficacy and practicality of these approaches through two case studies: 1) NSF grants for basic research spanning a 14 year period and 2) the entire English portion of Wikipedia.
Transmission spectral properties of clouds for hot Jupiter exoplanets

Clouds have an important role in the atmospheres of planetary bodies. It is expected that, like all the planetary bodies in our solar system, exoplanet atmospheres will also have substantial cloud coverage, and evidence is mounting for clouds in a number of hot Jupiters. In order to better characterise planetary atmospheres we need to consider the effects these clouds will have on the observed broadband transmission spectra. Here we examine the expected cloud condensate species for hot Jupiter exoplanets and the effects of various grain sizes and distributions on the resultant transmission spectra from the optical to infrared, which can be used as a broad framework when interpreting exoplanet spectra. We note that significant infrared absorption features appear in the computed transmission spectrum, the result of vibrational modes between the key species in each condensate, which can potentially be very constraining. While it may be hard to differentiate between individual condensates in the broad transmission spectra, it may be possible to discern different vibrational bonds, which can distinguish between cloud formation scenarios such as condensate clouds or photochemically generated species. Vibrational mode features are shown to be prominent when the clouds are composed of small sub-micron sized particles and can be associated with an accompanying optical scattering slope. These infrared features have potential implications for future exoplanetary atmosphere studies conducted with JWST, where such vibrational modes distinguishing condensate species can be probed at longer wavelengths.
Hydrogen delivery onto white dwarfs from remnant exo-Oort cloud comets

The origin of trace hydrogen in white dwarfs (WDs) with He-dominated atmospheres is a long-standing problem, one that cannot satisfactorily be explained by the historically-favoured hypothesis of accretion from the interstellar medium. Here we explore the possibility that the gradual accretion of exo-Oort cloud comets, which are a rich source of H, contributes to the apparent increase of trace H with WD cooling age. We determine how often remnant exo-Oort clouds, freshly excited from post-main-sequence stellar mass loss, dynamically inject comets inside the WD's Roche radius. We improve upon previous studies by considering a representative range of single WD masses (0.52-1.00 Solar masses) and incorporating different cloud architectures, giant branch stellar mass loss, stellar flybys, Galactic tides and a realistic escape ellipsoid in self-consistent numerical simulations that integrate beyond 8 Gyr ages of WD cooling. We find that about 10^{-5} of the material in an exo-Oort cloud is typically amassed onto the WD, and that the H deposits accumulate even as the cloud dissipates. This accumulation may account for the relatively large amount of trace H, 10^{22}-10^{25} g, that is determined frequently among WDs with cooling ages >= 1 Gyr. Our results also reaffirm the notion that exo-Oort cloud comets are not the primary agents of the metal budgets observed in polluted WD atmospheres.
On consistent kinetic and derivative interactions for gravitons

The only known fully ghost-free and consistent Lorentz-invariant kinetic term for a graviton (or indeed for any spin-2 field) is the Einstein-Hilbert term. Here we propose and investigate a new candidate family of kinetic interactions and their extensions to derivative interactions involving several spin-2 fields. These new terms generically break diffeomorphism invariance(s) and as a result can lead to the propagation of 5 degrees of freedom for a single spin-2 field—analogous to ghost-free Massive Gravity. We discuss under what circumstances these new terms can be used to build healthy effective field theories and in the process establish the `Jordan' and `Einstein' frame pictures for Massive-, Bi- and Multi-Gravity.
CLUSTERING OF MODERATE LUMINOSITY X-RAY-SELECTED TYPE 1 AND TYPE 2 AGNS AT Z ∼ 3

We investigate, for the first time at z ∼ 3, the clustering properties of 189 Type 1 and 157 Type 2 X-ray active galactic nuclei (AGNs) of moderate luminosity (〈Lbol〉 = 1045.3 erg s−1), with photometric or spectroscopic redshifts in the range 2.2 < z  < 6.8. These samples are based on Chandra and XMM-Newton data in COSMOS. We find that Type 1 and Type 2 COSMOS AGNs at z ∼ 3 inhabit DMHs with typical mass of log Mh = 12.84 and 11.73 h−1M☉, respectively. This result requires a drop in the halo masses of Type 1 and 2 COSMOS AGNs at z ∼ 3 compared to z  ≲ 2 XMM-COSMOS AGNs with similar luminosities. Additionally, we infer that unobscured COSMOS AGNs at z ∼ 3 reside in 10 times more massive halos compared to obscured COSMOS AGNs, at the 2.6σ level. This result extends to z ∼ 3 the results found in COSMOS at z  ≲ 2, and rules out the picture in which obscuration is purely an orientation effect. A model which assumes that the AGNs activity is triggered by major mergers is quite successful in predicting both the low halo mass of COSMOS AGNs and the typical mass of luminous SDSS quasars at z ∼ 3, with the latter inhabiting more massive halos respect to moderate luminosity AGNs. Alternatively we can argue, at least for Type 1 COSMOS AGNs, that they are possibly representative of an early phase of fast (i.e., Eddington limited) BH growth induced by cosmic cold flows or disk instabilities. Given the moderate luminosity, these new fast growing BHs have masses of ∼107–8 M☉ at z ∼ 3 which might evolve into ∼108.5–9 M☉ mass BHs at z = 0. Following our clustering measurements, we argue that this fast BH growth at z ∼ 3 in AGNs with moderate luminosity occurs in DMHs with typical mass of ∼ 6× 1012 h−1M☉.
Risk premia: asymmetric tail risks and excess returns

We present extensive evidence that “risk premium” is strongly correlated with tail-risk skewness but very little with volatility. We introduce a new, intuitive definition of skewness and elicit a linear relation between the Sharpe ratio of various risk premium strategies (Equity, Fama-French, FX Carry, Short Vol, Bonds, Credit) and their negative skewness. We find a clear exception to this rule: trend following (and perhaps the FamaFrench “High minus Low”), that has positive skewness and positive excess returns, suggesting that some strategies are not risk premia but genuine market anomalies. Based on our results, we propose an objective criterion to assess the quality of a risk-premium portfolio.
Higgs-like mechanism for spontaneous spacetime symmetry breaking

The study of spontaneous breakdown of spacetime symmetries leads to the discovery of another type of Higgs mechanism operating in a chiral SU(2) model. Some of the Nambu-Goldstone vector mesons emergent from simultaneous violations of gauge and Lorentz symmetries are, in this case, absorbed by a left-handed doublet and endow one of the fermions with a right-handed state, while another part becomes emergent as photons. Accordingly, this mechanism allows a chiral fermion to acquire a mass, and it may enable the emergent theory to reproduce the electromagnetism equivalent to the QED sector in the standard theory. It is also mentioned that the "fermion-boson puzzle" known in the presence of a 't Hooft--Polyakov monopole does not exist in our theory.
A White Paper on SoLID (Solenoidal Large Intensity Device)

At the time of this writing, the highly anticipated 12 GeV upgrade of the CEBAFaccelerator is nearing completion and its rich physics program is about to commence inearnest.The 12 GeV upgrade is accompanied by new detector upgrades that include CLAS12,SHMS, and an entirely new experimental hall featuring searches for QCD exotic states(GlueX). Although the currently envisioned program includes both high rate capabilityand large acceptance devices, there does not exist a single device capable of handling highluminosity (10
Black hole with a Dirac field in 3+1 dimensions

We study a complex Dirac field in the chiral representation minimally coupled to gravity in 3+1 dimensions in the context of Einstein-Cartan theory. Generically the matter content gravitates in two different ways: On the one hand, the energy-momentum induces spacetime curvature; on the other hand, the presence of spin acts as a source for the spacetime torsion, which does not propagate. In this setup we consider the most general stationary spherically symmetric ansatz and we find an analytic black hole solution that supports a nontrivial spinor configuration. The spinor field affects the geometry by inducing spacetime torsion, though, remarkably, it does not alter the black hole metric, which retains its Schwarzschild form. We find solutions both in asymptotically flat and asymptotically (Anti) de Sitter spaces. Additionally, we consider how the solution gets deformed when the so-called Holst term is included in the gravity action. We discuss possible observational effects due to the coupling of fermions in the nonvanishing torsion background. Additionally we include a Maxwell field into the problem and find that it forces the spinor field to be zero. Finally, nonminimal couplings of the spinor with spacetime curvature are considered, obtaining any effect on the spherically symmetric solutions.
Using Answer Set Programming for pattern mining

Serial pattern mining consists in extracting the frequent sequential patterns from a unique sequence of itemsets. This paper explores the ability of a declarative language, such as Answer Set Programming (ASP), to solve this issue efficiently. We propose several ASP implementations of the frequent sequential pattern mining task: a non-incremental and an incremental resolution. The results show that the incremental resolution is more efficient than the non-incremental one, but both ASP programs are less efficient than dedicated algorithms. Nonetheless, this approach can be seen as a first step toward a generic framework for sequential pattern mining with constraints.
Pleiotropic consequences of adaptation across gradations of environmental stress in budding yeast

Adaptation to one environment often results in fitness gains and losses in other conditions. To characterize how these consequences of adaptation depend on the physical similarity between environments, we evolved 180 populations of Saccharomyces cerevisiae at different degrees of stress induced by either salt, temperature, pH, or glucose depletion. We measure how the fitness of clones adapted to each environment depends on the intensity of the corresponding type of stress. We find that clones evolved in a given type and intensity of stress tend to gain fitness in other similar intensities of that stress, and lose progressively more fitness in more physically dissimilar environments. These fitness trade-offs are asymmetric: adaptation to permissive conditions incurred a smaller trade-off in stressful conditions than vice versa. We also find that fitnesses of clones are highly correlated across similar intensities of stress, but these correlations decay towards zero in more dissimilar environments. To interpret these results, we introduce the concept of a joint distribution of fitness effects of new mutations in multiple environments (the JDFE), which describes the probability that a given mutation has particular fitness effects in some set of conditions. We find that our observations are consistent with JDFEs that are highly correlated between physically similar environments, and that become less correlated and asymmetric as the environments become more dissimilar. The JDFE provides a framework for quantifying evolutionary similarity between conditions, and forms a useful basis for theoretical work aimed at predicting the outcomes of evolution in fluctuating environments.
Parametric Risk Parity

Any optimization algorithm based on the risk parity approach requires the formulation of portfolio total risk in terms of marginal contributions. In this paper we use the independence of the underlying factors in the market to derive the centered moments required in the risk decomposition process when the modified versions of Value at Risk and Expected Shortfall are considered. The choice of the Mixed Tempered Stable distribution seems adequate for fitting skewed and heavy tailed distributions. The ensuing detailed description of the optimization procedure is due to the existence of analytical higher order moments. Better results are achieved in terms of out of sample performance and greater diversification.
The Utility of Text: The Case of Amicus Briefs and the Supreme Court

We explore the idea that authoring a piece of text is an act of maximizing one's expected utility.To make this idea concrete, we consider the societally important decisions of the Supreme Court of the United States.Extensive past work in quantitative political science provides a framework for empirically modeling the decisions of justices and how they relate to text.We incorporate into such a model texts authored by amici curiae (``friends of the court'' separate from the litigants) who seek to weigh in on the decision, then explicitly model their goals in a random utility model.We demonstrate the benefits of this approach in improved vote prediction and the ability to perform counterfactual analysis.
Autonomous Robots and the SP Theory of Intelligence

This paper is about how the SP theory of intelligence and its realization in the SP machine (both outlined in this paper) may help in the design of the brains of autonomous robots, meaning robots that do not depend on external intelligence or power supplies, are mobile, and have human-like versatility and adaptability in intelligence. This paper addresses three main problems: 1) how to increase the computational and energy efficiency of computers and to reduce their size and weight; 2) how to achieve human-like versatility in intelligence; and 3) likewise for human-like adaptability in intelligence. Regarding the first problem, the SP system has the potential for substantial gains in computational efficiency, with corresponding cuts in energy consumption and the bulkiness of computers: 1) by reducing the size of data to be processed; 2) by exploiting statistical information that the system gathers as an integral part of how it works; and 3) via a new version of Donald Hebb's concept of a cell assembly. Toward human-like versatility in intelligence, the SP system has strengths in unsupervised learning, natural language processing, pattern recognition, information retrieval, several kinds of reasoning, planning, problem solving, and more, with seamless integration among structures and functions. The SP system's strengths in unsupervised learning and other aspects of intelligence may help in achieving human-like adaptability in intelligence via: 1) one-trial learning; 2) learning of natural language; 3) learning to see; 4) building 3-D models of objects and of a robot's surroundings; 5) learning regularities in the workings of a robot and in the robot's environment; 6) exploration and play; 7) learning major skills; and 8) learning via demonstration. Also discussed are how the SP system may process parallel streams of information, generalization of knowledge, correction of over-generalizations, learning from dirty data, how to cut the cost of learning, and reinforcements and motivations.
Adaptive Low-Complexity Sequential Inference for Dirichlet Process Mixture Models

We develop a sequential low-complexity inference procedure for Dirichlet process mixtures of Gaussians for online clustering and parameter estimation when the number of clusters are unknown a-priori. We present an easily computable, closed form parametric expression for the conditional likelihood, in which hyperparameters are recursively updated as a function of the streaming data assuming conjugate priors. Motivated by large-sample asymptotics, we propose a novel adaptive low-complexity design for the Dirichlet process concentration parameter and show that the number of classes grow at most at a logarithmic rate. We further prove that in the large-sample limit, the conditional likelihood and data predictive distribution become asymptotically Gaussian. We demonstrate through experiments on synthetic and real data sets that our approach is superior to other online state-of-the-art methods.
New gravitational scales in cosmological surveys

In the quasistatic regime, generic modifications to gravity can give rise to novel scale-dependence of the gravitational field equations. Crucially, the detectability of the new scale-dependent terms hinges upon the existence of an effective mass scale or length scale at which corrections to General Relativity become relevant. Starting from only a few basic principles, we derive the general form of this scale-dependence. Our method recovers results previously known in the specific case of Horndeski gravity, but also shows that they are valid more generally, beyond the regime of scalar field theories. We forecast the constraints that upcoming experiments will place on the existence of a new fundamental mass scale or length scale in cosmology.
Double beta decay searches of 134 Xe, 126 Xe and 124 Xe with large scale Xe detectors

The sensitivity for double beta decay studies of 134Xe and 124Xe is investigated assuming a potential large scale Xe experiment developed for dark matter searches depleted in 136Xe. The opportunity for an observation of the 2νββ - decay of 134Xe is explored for various scenarios. A positive observation should be possible for all calculated nuclear matrix elements. The detection of ECEC of 124Xe can be probed in all scenarios covering the theoretical predicted half-life uncertainties and a potential search for 126Xe is discussed. The sensitivity to decay of 124Xe is discussed and a positive observation might be possible, while decay still remains unobservable. The performed studies take into account solar pp–neutrino interactions, 85Kr beta decay and remaining 136Xe double beta decay as background components in the depleted detector.
Observation of soliton explosions in a passively mode-locked fiber laser

Soliton explosions are among the most exotic dissipative phenomena studied in mode-locked lasers. In this regime, a dissipative soliton circulating in the laser cavity experiences an abrupt structural collapse, but within a few roundtrips returns to its original quasi-stable state. In this Letter, we report on the first observation, to the best of our knowledge, of such events in a fiber laser. Specifically, we identify clear explosion signatures in measurements of shot-to-shot spectra of a Yb-doped mode-locked fiber laser that is operating in a transition regime between stable and noise-like emission. The comparatively long, all-normal-dispersion cavity used in our experiments also permits direct time-domain measurements, and we show that the explosions manifest themselves as abrupt temporal shifts in the output pulse train. Our experimental results are in good agreement with realistic numerical simulations based on an iterative cavity map.
Distributed Detection: Finite-Time Analysis and Impact of Network Topology

This paper addresses the problem of distributed detection in multi-agent networks. Agents receive private signals about an unknown state of the world. The underlying state is globally identifiable, yet informative signals may be dispersed throughout the network. Using an optimization-based framework, we develop an iterative local strategy for updating individual beliefs. In contrast to the existing literature which focuses on asymptotic learning, we provide a finite-time analysis. Furthermore, we introduce a Kullback-Leibler cost to compare the efficiency of the algorithm to its centralized counterpart. Our bounds on the cost are expressed in terms of network size, spectral gap, centrality of each agent and relative entropy of agents' signal structures. A key observation is that distributing more informative signals to central agents results in a faster learning rate. Furthermore, optimizing the weights, we can speed up learning by improving the spectral gap. We also quantify the effect of link failures on learning speed in symmetric networks. We finally provide numerical simulations for our method which verify our theoretical results.