Spatial Characterization of Wetting in Porous Media Using Local Lattice-Boltzmann Simulations

Wettability is one of the critical parameters affecting multiphase flow in porous media. The wettability is determined by the affinity of fluids to the rock surface, which varies due to factors such as mineral heterogeneity, roughness, ageing, and pore-space geometry. It is well known that wettability varies spatially in natural rocks, and it is still generally considered a constant parameter in pore-scale simulation studies. The accuracy of pore-scale simulation of multiphase flow in porous media is undermined by such inadequate wettability models. The advent of in situ visualization techniques, e.g. X-ray imaging and microtomography, enables us to characterize the spatial distribution of wetting more accurately. There are several approaches for such characterization. Most include the construction of a meshed surface of the interface surfaces in a segmented X-ray image and are known to have significant errors arising from insufficient resolution and surface-smoothing algorithms. This work presents a novel approach for spatial determination of wetting properties using local lattice-Boltzmann simulations. The scheme is computationally efficient as the segmented X-ray image is divided into subdomains before conducting the lattice-Boltzmann simulations, enabling fast simulations. To test the proposed method, it was applied to two synthetic cases with known wettability and three datasets of imaged fluid distributions. The wettability map was obtained for all samples using local lattice-Boltzmann calculations on trapped ganglia and optimization on surface affinity parameters. The results were quantitatively compared with a previously developed geometrical contact angle determination method. The two synthetic cases were used to validate the results of the developed workflow, as well as to compare the wettability results with the geometrical analysis method. It is shown that the developed workflow accurately characterizes the wetting state in the synthetic porous media with an acceptable uncertainty and is better to capture extreme wetting conditions. For the three datasets of imaged fluid distributions, our results show that the obtained contact angle distributions are consistent with the geometrical method. However, the obtained contact angle distributions tend to have a narrower span and are considered more realistic compared to the geometrical method. Finally, our results show the potential of the proposed scheme to efficiently obtain wettability maps of porous media using X-ray images of multiphase fluid distributions. The developed workflow can help for more accurate characterization of the wettability map in the porous media using limited experimental data, and hence more accurate digital rock analysis of multiphase flow in porous media

Infall of gas as the formation mechanism of stars up to 20 times more massive than the Sun

Theory predicts and observations confirm that low-mass stars (like the Sun) in their early life grow by accreting gas from the surrounding material. But for stars ~ 10 times more massive than the Sun (~10 M_sun), the powerful stellar radiation is expected to inhibit accretion and thus limit the growth of their mass. Clearly, stars with masses >10 M_sun exist, so there must be a way for them to form. The problem may be solved by non-spherical accretion, which allows some of the stellar photons to escape along the symmetry axis where the density is lower. The recent detection of rotating disks and toroids around very young massive stars has lent support to the idea that high-mass (> 8 M_sun) stars could form in this way. Here we report observations of an ammonia line towards a high-mass star forming region. We conclude from the data that the gas is falling inwards towards a very young star of ~20 M_sun, in line with theoretical predictions of non-spherical accretion.Comment: 11 pages, 2 figure

Local Detection of Quantum Correlations with a Single Trapped Ion

As one of the most striking features of quantum mechanics, quantum correlations are at the heart of quantum information science. Detection of correlations usually requires access to all the correlated subsystems. However, in many realistic scenarios this is not feasible since only some of the subsystems can be controlled and measured. Such cases can be treated as open quantum systems interacting with an inaccessible environment. Initial system-environment correlations play a fundamental role for the dynamics of open quantum systems. Following a recent proposal, we exploit the impact of the correlations on the open-system dynamics to detect system-environment quantum correlations without accessing the environment. We use two degrees of freedom of a trapped ion to model an open system and its environment. The present method does not require any assumptions about the environment, the interaction or the initial state and therefore provides a versatile tool for the study of quantum systems.Comment: 6 Pages, 5 Figures + 6 Pages, 1 Figure of Supplementary Materia

Self-supervised Contrastive Video-Speech Representation Learning for Ultrasound

In medical imaging, manual annotations can be expensive to acquire and sometimes infeasible to access, making conventional deep learning-based models difficult to scale. As a result, it would be beneficial if useful representations could be derived from raw data without the need for manual annotations. In this paper, we propose to address the problem of self-supervised representation learning with multi-modal ultrasound video-speech raw data. For this case, we assume that there is a high correlation between the ultrasound video and the corresponding narrative speech audio of the sonographer. In order to learn meaningful representations, the model needs to identify such correlation and at the same time understand the underlying anatomical features. We designed a framework to model the correspondence between video and audio without any kind of human annotations. Within this framework, we introduce cross-modal contrastive learning and an affinity-aware self-paced learning scheme to enhance correlation modelling. Experimental evaluations on multi-modal fetal ultrasound video and audio show that the proposed approach is able to learn strong representations and transfers well to downstream tasks of standard plane detection and eye-gaze prediction.Comment: MICCAI 2020 (early acceptance

Game theory of mind

This paper introduces a model of ‘theory of mind’, namely, how we represent the intentions and goals of others to optimise our mutual interactions. We draw on ideas from optimum control and game theory to provide a ‘game theory of mind’. First, we consider the representations of goals in terms of value functions that are prescribed by utility or rewards. Critically, the joint value functions and ensuing behaviour are optimised recursively, under the assumption that I represent your value function, your representation of mine, your representation of my representation of yours, and so on ad infinitum. However, if we assume that the degree of recursion is bounded, then players need to estimate the opponent's degree of recursion (i.e., sophistication) to respond optimally. This induces a problem of inferring the opponent's sophistication, given behavioural exchanges. We show it is possible to deduce whether players make inferences about each other and quantify their sophistication on the basis of choices in sequential games. This rests on comparing generative models of choices with, and without, inference. Model comparison is demonstrated using simulated and real data from a ‘stag-hunt’. Finally, we note that exactly the same sophisticated behaviour can be achieved by optimising the utility function itself (through prosocial utility), producing unsophisticated but apparently altruistic agents. This may be relevant ethologically in hierarchal game theory and coevolution

Monodromy--like Relations for Finite Loop Amplitudes

We investigate the existence of relations for finite one-loop amplitudes in Yang-Mills theory. Using a diagrammatic formalism and a remarkable connection between tree and loop level, we deduce sequences of amplitude relations for any number of external legs.Comment: 24 pages, 6 figures, v2 typos corrected, reference adde

Vertex importance extension of betweenness centrality algorithm

Variety of real-life structures can be simplified by a graph. Such simplification emphasizes the structure represented by vertices connected via edges. A common method for the analysis of the vertices importance in a network is betweenness centrality. The centrality is computed using the information about the shortest paths that exist in a graph. This approach puts the importance on the edges that connect the vertices. However, not all vertices are equal. Some of them might be more important than others or have more significant influence on the behavior of the network. Therefore, we introduce the modification of the betweenness centrality algorithm that takes into account the vertex importance. This approach allows the further refinement of the betweenness centrality score to fulfill the needs of the network better. We show this idea on an example of the real traffic network. We test the performance of the algorithm on the traffic network data from the city of Bratislava, Slovakia to prove that the inclusion of the modification does not hinder the original algorithm much. We also provide a visualization of the traffic network of the city of Ostrava, the Czech Republic to show the effect of the vertex importance adjustment. The algorithm was parallelized by MPI (http://www.mpi-forum.org/) and was tested on the supercomputer Salomon (https://docs.it4i.cz/) at IT4Innovations National Supercomputing Center, the Czech Republic.808726

A variant approach to the overlap action

I describe an implementation of the overlap action, which is built from an action which is itself an approximate overlap action. It appears to be about a factor of 15-20 less expensive to use, than the usual overlap action with the Wilson fermion action as its kernel. Ingredients include a fat link to suppress coupling to dislocations and a free field action with a spectrum which resembles an overlap; much of the gain comes from the use of eigenmodes of the approximate action to begin the overlap calculation. As a physics example, I compute the quark condensate in finite volume in the quenched approximation.Comment: 15 pages, Revtex, postscript figures. COLO-HEP-44

Metallic atomically-thin layered silicon epitaxially grown on silicene/ZrB2

Using low energy electron diffraction (LEED) and scanning tunnelling microscopy (STM), we observe a new two-dimensional (2D) silicon crystal that is formed by depositing additional Si atoms onto spontaneously-formed epitaxial silicene on a ZrB2 thin film. From scanning tunnelling spectroscopy (STS) studies, we find that this atomically-thin layered silicon has distinctly different electronic properties. Angle resolved photoelectron spectroscopy (ARPES) reveals that, in sharp contrast to epitaxial silicene, the layered silicon exhibits significantly enhanced density of states at the Fermi level resulting from newly formed metallic bands. The 2D growth of this material could allow for direct contacting to the silicene surface and demonstrates the dramatic changes in electronic structure that can occur by the addition of even a single monolayer amount of material in 2D systems

The Formation of the First Low-Mass Stars From Gas With Low Carbon and Oxygen Abundances

The first stars in the Universe are predicted to have been much more massive than the Sun. Gravitational condensation accompanied by cooling of the primordial gas due to molecular hydrogen, yields a minimum fragmentation scale of a few hundred solar masses. Numerical simulations indicate that once a gas clump acquires this mass, it undergoes a slow, quasi-hydrostatic contraction without further fragmentation. Here we show that as soon as the primordial gas - left over from the Big Bang - is enriched by supernovae to a carbon or oxygen abundance as small as ~0.01-0.1% of that found in the Sun, cooling by singly-ionized carbon or neutral oxygen can lead to the formation of low-mass stars. This mechanism naturally accommodates the discovery of solar mass stars with unusually low (10^{-5.3} of the solar value) iron abundance but with a high (10^{-1.3} solar) carbon abundance. The minimum stellar mass at early epochs is partially regulated by the temperature of the cosmic microwave background. The derived critical abundances can be used to identify those metal-poor stars in our Milky Way galaxy with elemental patterns imprinted by the first supernovae.Comment: 14 pages, 2 figures (appeared today in Nature