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Biomedical subjects

Neil F Johnson

Publications and source records attributed to Neil F Johnson.

9 recordsLinked to original sources

Interplay between function and structure in complex networks.

We show that abrupt structural transitions can arise in functionally optimal networks, driven by small changes in the level of transport congestion. Our results offer an explanation as to why so many diverse species of network structure arise in nature (e.g., fungal systems) under essentially the same environmental conditions. Our findings are based on an exactly solvable model system which mimics a variety of biological and social networks. We then extend our analysis by introducing a renormalization scheme involving cost motifs, to describe analytically the average shortest path across multiple-ring-and-hub networks. As a consequence, we uncover a "skin effect" whereby the structure of the inner multi-ring core can cease to play any role in terms of determining the average shortest path across the network.

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Detecting a currency's dominance or dependence using foreign exchange network trees.

In a system containing a large number of interacting stochastic processes, there will typically be many nonzero correlation coefficients. This makes it difficult to either visualize the system's interdependencies, or identify its dominant elements. Such a situation arises in foreign exchange (FX), which is the world's biggest market. Here we develop a network analysis of these correlations using minimum spanning trees (MSTs). We show that not only do the MSTs provide a meaningful representation of the global FX dynamics, but they also enable one to determine momentarily dominant and dependent currencies. We find that information about a country's geographical ties emerges from the raw exchange-rate data. Most importantly from a trading perspective, we discuss how to infer which currencies are "in play" during a particular period of time.

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Robust one-step catalytic machine for high fidelity anticloning and W-state generation in a multiqubit system.

We propose a physically realizable machine which can either generate multiparticle W-like states, or implement high-fidelity 1-->M (M=1,2,...infinity) anticloning of an arbitrary qubit state, in a single step. This universal machine acts as a catalyst in that it is unchanged after either procedure, effectively resetting itself for its next operation. It possesses an inherent immunity to decoherence. Most importantly in terms of practical multiparty quantum communication, the machine's robustness in the presence of decoherence actually increases as the number of qubits M increases.

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Effect of congestion costs on shortest paths through complex networks.

We analyze analytically the effect of congestion costs within a physically relevant, yet exactly solvable, network model featuring central hubs. These costs lead to a competition between centralized and decentralized transport pathways. In stark contrast to conventional no-cost networks, there now exists an optimal number of connections to the central hub in order to minimize the shortest path. Our results shed light on an open problem in biology, informatics, and sociology, concerning the extent to which decentralized versus centralized design benefits real-world complex networks.

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Error-driven global transition in a competitive population on a network.

We show, both analytically and numerically, that erroneous data transmission generates a global transition within a competitive population playing the "Minority Game" on a network. This transition, which resembles a phase transition, is driven by a "temporal symmetry breaking" in the global outcome series. The phase boundary, which is a function of the network connectivity p and the error probability q, is described quantitatively by the crowd-anticrowd theory.

Adaptation, Physiological↗

Memory and self-induced shocks in an evolutionary population competing for limited resources.

We present a detailed discussion of the role played by memory, and the nature of self-induced shocks, in an evolutionary population competing for limited resources. Our study builds on a previously introduced multiagent system [Phys. Rev. Lett. 82, 3360 (1999)] which has attracted significant attention in the literature. This system exhibits self-segregation of the population based on the "gene" value p (where 0< or =p< or =1 ), transitions to "frozen" populations as a function of the global resource level, and self-induced large changes which spontaneously arise as the dynamical system evolves. We find that the large, macroscopic self-induced shocks that arise are controlled by microscopic changes within extreme subgroups of the population (i.e., subgroups with "gene" values p approximately 0 and p approximately 1).

Adaptation, Physiological↗

First-order superradiant phase transitions in a multiqubit cavity system.

We predict the existence of novel first-order phase transitions in a general class of multiqubit cavity systems. Apart from atomic systems, the associated superradiant phase transition should be observable in a variety of solid-state experimental systems, including the technologically important case of interacting quantum dots coupled to an optical cavity mode.

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Winning combinations of history-dependent games.

The Parrondo effect describes the seemingly paradoxical situation in which two losing games can, when combined, become a winning game [Parrondo, Harmer, and Abbott, Phys. Rev. Lett. 85, 24 (2000)]. Here, we generalize this analysis to the case where both games are history dependent, i.e., there is an intrinsic memory in the dynamics of each game. Results are presented for the cases of both random and periodic switching between the two games.

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Optimal combinations of imperfect objects.

We consider how to make best use of imperfect objects, such as defective analog and digital components. We show that perfect, or near-perfect, devices can be constructed by taking combinations of such defects. Any remaining objects can be recycled efficiently. In addition to its practical applications, our "defect combination problem" provides a novel generalization of classical optimization problems.

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