Characterizing small-scale migration behavior of sequestered CO2 in a realistic geological fabric

For typical reservoir conditions, buoyancy and capillary forces grow dominant over viscous forces within a few hundred meters of the injection wells as the pressure gradient due to injection decreases, resulting in qualitatively different plume migration regimes. The migration regime depends on two factors: the capillary pressure of the leading edge of the plume and the range of threshold entry pressures within the rock at the leading edge of the plume. A capillary channel regime arises when these two factors have the same magnitude. Flow patterns within this regime vary from finger-like structures with minimal rock contact to back-filling structures with compact volumes of saturation distributed between fingers. Reservoir heterogeneity is one of the principal factors influencing CO2 migration pathway in the capillary channel regime. Here we characterize buoyancy-driven migration in a natural 2D geologic domain (1 m × 0.5 m peel from an alluvium) in which sedimentologic heterogeneity has been resolved at sub-millimeter (depositional) resolution. The relevant features of the heterogeneity are grain size distribution, which determines the mean and range of threshold pressures and correlation lengths of threshold pressures in horizontal and vertical directions. The relevant physics for this migration regime is invasion percolation, and simulations indicate that CO2 migrates through the peel in a few narrow pathways which cannot be captured by conventional coarse-grid simulations. The storage efficiency of the capillary channel regime would be low and consequently CO2 would also migrate greater distances than expected from models or simulations that neglect the capillary channel flow regime.Bureau of Economic Geolog

Liquid-liquid transition in supercooled silicon determined by first-principles simulation

First principles molecular dynamics simulations reveal a liquid-liquid phase transition in supercooled elemental silicon. Two phases coexist below $T_c\approx 1232K$. The low density phase is nearly tetra-coordinated, with a pseudogap at the Fermi surface, while the high density phase is more highly coordinated and metallic in nature. The transition is observed through the formation of van der Waals loops in pressure-volume isotherms below $T_c$.Comment: 9 pages 4 figure

CCNN: An Artificial Intelligent based Classifier to Credit Card Fraud Detection System with Optimized Cognitive Learning Model

Nowadays digital transactions play a vital role in money transaction processes. Last 5 years statistical report portrays the growth of internet money transaction especially credit card and unified payments interface. Mean time increasing numerous banking threats and digital transaction fraud rates also growing significantly. Data engineering techniques provide ultra supports to detect credit card forgery problems in online and offline mode transactions. This credit card fraud detection (CCFD) and prevention-based data processing issues raising because of two major reasons first, classification rate of legitimate and forgery uses is frequently changing, and next one is fraud detection dataset values are vastly asymmetric. Through this research work investigating performance of various existing classifier with our proposed cognitive convolutional neural network (CCNN) classifier. Existing classifiers like Logistic Regression (LR), K-nearest neighbor (KNN), Decision Tree (DT) and Support Vector Machine (SVM). These models are facing various challenges of low performance rate and high complexity because of low hit rate and accuracy. Through this research work we introduce cognitive learning-based CCNN classifier methodology with artificial intelligence for achieve maximum accuracy rate and minimal complexity issues. For experimental data analysis uses dataset of credit card transactions attained from specific region cardholders containing 284500 transactions and its various features. Also, this dataset contains unstructured and non-dimensional data are converted into structured data with the help of over sample and under sample method. Performance analysis shows proposed CCNN classifier model provide significant improvement on accuracy, specificity, sensitivity and hit rate. The results are shown in comparison. After cross-validation, the accuracy of the CCNN classification algorithm model for transaction fraudulent detection archived 99% which using the over-sampling model

Spreading entanglement through pairwise exchange interactions

The spread of entanglement is a problem of great interest. It is particularly relevant to quantum state synthesis, where an initial direct-product state is sought to be converted into a highly entangled target state. In devices based on pairwise exchange interactions, such a process can be carried out and optimized in various ways. As a benchmark problem, we consider the task of spreading one excitation among $N$ two-level atoms or qubits. Starting from an initial state where one qubit is excited, we seek a target state where all qubits have the same excitation-amplitude -- a generalized-W state. This target is to be reached by suitably chosen pairwise exchange interactions. For example, we may have a a setup where any pair of qubits can be brought into proximity for a controllable period of time. We describe three protocols that accomplish this task, each with $N-1$ tightly-constrained steps. In the first, one atom acts as a flying qubit that sequentially interacts with all others. In the second, qubits interact pairwise in sequential order. In these two cases, the required interaction times follow a pattern with an elegant geometric interpretation. They correspond to angles within the spiral of Theodorus -- a construction known for more than two millennia. The third protocol follows a divide-and-conquer approach -- dividing equally between two qubits at each step. For large $N$, the flying-qubit protocol yields a total interaction time that scales as $\sqrt{N}$, while the sequential approach scales linearly with $N$. For the divide-and-conquer approach, the time has a lower bound that scales as $\log N$. With any such protocol, we show that the phase differences in the final state cannot be independently controlled. For instance, a W-state (where all phases are equal) cannot be generated by pairwise exchange.Comment: 6 pages, 3 figure

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Peephole optimization of asynchronous macromodule networks

Journal ArticleAbstract- Most high-level synthesis tools for asynchronous circuits take descriptions in concurrent hardware description languages and generate networks of macromodules or handshake components. In this paper, we propose a peephole optimizer for these networks. Our peephole optimizer first deduces an equivalent blackbox behavior for the network using Dill's tracetheoretic parallel composition operator. It then applies a new procedure called burst-mode reduction to obtain burst-mode machines from the deduced behavior. In a significant number of examples, our optimizer achieves gate-count improvements by a factor of five, and speed (cycle-time) improvements by a factor of two. Burst-mode reduction can be applied to any macromodule network that is delay insensitive as well as deterministic. A significant number of asynchronous circuits, especially those generated by asynchronous high-level synthesis tools, fall into this class, thus making our procedure widely applicable

A correctness criterion for asynchronous circuit validation and optimization

technical reportIn order to reason about the correctness of asynchronous circuit implementations and specifications, Dill has developed a variant of trace theory [1]. Trace theory describes the behavior of an asynchronous circuit by representing its possible executions as strings called "traces" A useful relation defined in this theory is called conformance which holds when one trace specification can be safely substituted for another. We propose a new relation in the context of Dill's trace theory called strong conformance. We show that this relation is capable of detecting certain errors in asynchronous circuits that cannot be detected through conformance, Strong conformance also helps to justify circuit optimization rules where a component is replaced by another component having extra capabilities (e.g., it can accept more inputs). The structural operators of Dill's trace theory compose rename and hide - are shown to be monotonic with respect to strong conformance. Experiments are presented using a modified version of Dill's trace theory verifier which implements the check for strong conformance

Performance analysis and optimization of asynchronous circuits

Journal ArticleAsynchronous/Self-timed circuits are beginning to attract renewed attention as promising means of dealing with the complexity of modern VZSI designs. Very few analysis techniques or tools are available for estimating their performance. In this paper we adapt the theory of Generalized Timed Petri-nets (GTPN) for analyzing and comparing asynchronous circuits ranging from purely control-oriented circuits to those with data dependent control. Experiments with the GTPN analyzer are found to track the observed performance of actual asynchronous circuits, thereby offering empirical evidence toward the soundness of the modeling approach

Spiral order by disorder and lattice nematic order in a frustrated Heisenberg antiferromagnet on the honeycomb lattice

Motivated by recent experiments on Bi$_3$Mn$_4$O$_{12}$(NO$_3$), we study a frustrated $J_1$-$J_2$ Heisenberg model on the two dimensional (2D) honeycomb lattice. The classical $J_1$-$J_2$ Heisenberg model on the two dimensional (2D) honeycomb lattice has N\'eel order for $J_2 J_1/6$, it exhibits a one-parameter family of degenerate incommensurate spin spiral ground states where the spiral wave vector can point in any direction. Spin wave fluctuations at leading order lift this accidental degeneracy in favor of specific wave vectors, leading to spiral order by disorder. For spin $S=1/2$, quantum fluctuations are, however, likely to be strong enough to melt the spiral order parameter over a wide range of $J_2/J_1$. Over a part of this range, we argue that the resulting state is a valence bond solid (VBS) with staggered dimer order - this VBS is a nematic which breaks lattice rotational symmetry. Our arguments are supported by comparing the spin wave energy with the energy of the dimer solid obtained using a bond operator formalism. Turning to the effect of thermal fluctuations on the spiral ordered state, any nonzero temperature destroys the magnetic order, but the discrete rotational symmetry of the lattice remains broken resulting in a thermal analogue of the nematic VBS. We present arguments, supported by classical Monte Carlo simulations, that this nematic transforms into the high temperature symmetric paramagnet via a thermal phase transition which is in the universality class of the classical 3-state Potts (clock) model in 2D. We discuss the possible relevance of our results for honeycomb magnets, such as Bi$_3$M$_4$O$_{12}$(NO$_3$) (with M=Mn,V,Cr), and bilayer triangular lattice magnets.Comment: Slightly revise