scholarly journals Entanglement revive and information flow within the decoherent environment

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Jia-dong Shi ◽  
Dong Wang ◽  
Liu Ye
Keyword(s):  
Information Flow ◽  
Composite System ◽  
Theoretic Approach ◽  
Noisy Environment ◽  
Bipartite Entanglement ◽  
State Information ◽  
Information Theoretic ◽  
Correlation Distribution ◽  
Information Theoretic Approach ◽  
Insight Into

Abstract In this paper, the dynamics of entanglement is investigated in the presence of a noisy environment. We reveal its revival behavior and probe the mechanisms of this behavior via an information-theoretic approach. By analyzing the correlation distribution and the information flow within the composite system including the qubit subsystem and a noisy environment, it has been found that the subsystem-environment coupling can induce the quasi-periodic entanglement revival. Furthermore, the dynamical relationship among tripartite correlations, bipartite entanglement and local state information is explored, which provides a new insight into the non-Markovian mechanisms during the evolution.

scholarly journals Mining explainable local and global subgraph patterns with surprising densities

2020 ◽  
Author(s):  
Junning Deng ◽  
Bo Kang ◽  
Jefrey Lijffijt ◽  
Tijl De Bie
Keyword(s):  
Level Structure ◽  
Theoretic Approach ◽  
Dense Subgraphs ◽  
Information Theoretic ◽  
Different Types ◽  
Residence Location ◽  
Information Theoretic Approach ◽  
High Level ◽  
Special Case ◽  
Insight Into

Abstract The connectivity structure of graphs is typically related to the attributes of the vertices. In social networks for example, the probability of a friendship between any pair of people depends on a range of attributes, such as their age, residence location, workplace, and hobbies. The high-level structure of a graph can thus possibly be described well by means of patterns of the form ‘the subgroup of all individuals with certain properties X are often (or rarely) friends with individuals in another subgroup defined by properties Y’, ideally relative to their expected connectivity. Such rules present potentially actionable and generalizable insight into the graph. Prior work has already considered the search for dense subgraphs (‘communities’) with homogeneous attributes. The first contribution in this paper is to generalize this type of pattern to densities between a pair of subgroups, as well as between all pairs from a set of subgroups that partition the vertices. Second, we develop a novel information-theoretic approach for quantifying the subjective interestingness of such patterns, by contrasting them with prior information an analyst may have about the graph’s connectivity. We demonstrate empirically that in the special case of dense subgraphs, this approach yields results that are superior to the state-of-the-art. Finally, we propose algorithms for efficiently finding interesting patterns of these different types.

scholarly journals Information Flow between Bitcoin and Other Investment Assets

Entropy ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. 1116 ◽  
Author(s):  
Jang ◽  
Yi ◽  
Kim ◽  
Ahn
Keyword(s):  
Granger Causality ◽  
Information Flow ◽  
Transfer Entropy ◽  
Asset Markets ◽  
Theoretic Approach ◽  
Causality Test ◽  
Information Theoretic ◽  
Symbolic Transfer Entropy ◽  
Information Theoretic Approach

This paper studies the causal relationship between Bitcoin and other investment assets. We first test Granger causality and then calculate transfer entropy as an information-theoretic approach. Unlike the Granger causality test, we discover that transfer entropy clearly identifies causal interdependency between Bitcoin and other assets, including gold, stocks, and the U.S. dollar. However, for symbolic transfer entropy, the dynamic rise–fall pattern in return series shows an asymmetric information flow from other assets to Bitcoin. Our results imply that the Bitcoin market actively interacts with major asset markets, and its long-term equilibrium, as a nascent market, gradually synchronizes with that of other investment assets.

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