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N. F. Johnson

Publications and source records attributed to N. F. Johnson.

At least 37 records · Page 2Linked to original sources
arXiv2017

Multiscale dynamical network mechanisms underlying aging from birth to death

How self-organized networks develop, mature and degenerate is a key question for sociotechnical, cyberphysical and biological systems with potential applications from tackling violent extremism through to neurological diseases. So far, it has proved impossible to measure the continuous-time evolution of any in vivo organism network from birth to death. Here we provide such a study which crosses all organizational and temporal scales, from individual components (10^1) through to the mesoscopic (10^3) and entire system scale (10^6). These continuous-time data reveal a lifespan driven by punctuated, real-time co-evolution of the structural and functional networks. Aging sees these structural and functional networks gradually diverge in terms of their small-worldness and eventually their connectivity. Dying emerges as an extended process associated with the formation of large but disjoint functional sub-networks together with an increasingly detached core. Our mathematical model quantifies the very different impacts that interventions will have on the overall lifetime, period of initial growth, peak of potency, and duration of old age, depending on when and how they are administered. In addition to their direct relevance to online extremism, our findings offer fresh insight into aging in any network system of comparable complexity for which extensive in vivo data is not yet available.

physics.soc-ph↗
arXiv2016

Quantum Hysteresis in Coupled Light-Matter Systems

We investigate the non-equilibrium quantum dynamics of a canonical light-matter system, namely the Dicke model, when the light-matter interaction is ramped up and down through a cycle across the quantum phase transition. Our calculations reveal a rich set of dynamical behaviors determined by the cycle times, ranging from the slow, near adiabatic regime through to the fast, sudden quench regime. As the cycle time decreases, we uncover a crossover from an oscillatory exchange of quantum information between light and matter that approaches a reversible adiabatic process, to a dispersive regime that generates large values of light-matter entanglement. The phenomena uncovered in this work have implications in quantum control, quantum interferometry, as well as in quantum information theory.

cond-mat.quant-gas↗
arXiv2015

Large dynamic light-matter entanglement from driving neither too fast nor too slow

A significant problem facing next-generation quantum technologies is how to generate and manipulate macroscopic entanglement in light and matter systems. Here we report a new regime of dynamical light-matter behavior in which a giant, system-wide entanglement is generated by varying the light-matter coupling at \emph{intermediate} velocities. This enhancement is far larger and broader-ranged than that occurring near the quantum phase transition of the same model under adiabatic conditions. By appropriate choices of the coupling within this intermediate regime, the enhanced entanglement can be made to spread system-wide or to reside in each subsystem separately.

quant-ph↗
arXiv2015

Robust quantum correlations in out-of-equilibrium matter-light systems

High precision macroscopic quantum control in interacting light-matter systems remains a significant goal toward novel information processing and ultra-precise metrology. We show that the out-of-equilibrium behavior of a paradigmatic light-matter system (Dicke model) reveals two successive stages of enhanced quantum correlations beyond the traditional schemes of near-adiabatic and sudden quenches. The first stage features magnification of matter-only and light-only entanglement and squeezing due to effective non-linear self-interactions. The second stage results from a highly entangled light-matter state, with enhanced superradiance and signatures of chaotic and highly quantum states. We show that these new effects scale up consistently with matter system size, and are reliable even in dissipative environments.

quant-ph↗
arXiv2013

New dynamical scaling universality for quantum networks across adiabatic quantum phase transitions

We reveal universal dynamical scaling behavior across adiabatic quantum phase transitions (QPTs) in networks ranging from traditional spatial systems (Ising model) to fully connected ones (Dicke and Lipkin-Meshkov-Glick models). Our findings, which lie beyond traditional critical exponent analysis and adiabatic perturbation approximations, are applicable even where excitations have not yet stabilized and hence provide a time-resolved understanding of QPTs encompassing a wide range of adiabatic regimes. We show explicitly that even though two systems may traditionally belong to the same universality class, they can have very different adiabatic evolutions. This implies more stringent conditions need to be imposed than at present, both for quantum simulations where one system is used to simulate the other, and for adiabatic quantum computing schemes.

quant-ph↗
arXiv2007

A non-Markovian optical signature for detecting entanglement in coupled excitonic qubits

We identify an optical signature for detecting entanglement in experimental nanostructure systems comprising coupled excitonic qubits. This signature owes its strength to non-Markovian dynamical effects in the second-order temporal coherence function of the emitted radiation. We calculate autocorrelation and cross-correlation functions for both selective and collective light excitation, and prove that the coherence properties of the emitted light do indeed carry information about the entanglement of the initial multi-qubit state. We also show that this signature can survive in the presence of a noisy environment.

cond-mat.mes-hall↗
arXiv2005

Transitions in collective response in multi-agent models of competing populations driven by resource level

We aim to study the effects of controlling the resource level in agent-based models. We study, both numerical and analytically, a Binary-Agent-Resource (B-A-R) model in which $N$ agents are competing for resources described by a resource level $1/2 \leq {\cal L} < 1$, where ${\cal L} = L/N$ with $L$ being the maximum amount of resource per turn available to the agents. Each agent picks the momentarily best-performing strategy for decision with the performance of the strategy being a result of the cumulative collective decisions of the agents. The agents may or may not be networked for information sharing. Detailed numerical simulations reveal that the system exhibits well-defined plateaux regions in the success rate which are separated from each other by abrupt transitions. As $L$ increases, the maximum success rate forms a well defined sequence of simple fractions. We analyze the features by studying the outcome time series, the dynamics of the strategies' performance ranking pattern and the dynamics in the history space. While the system tends to explore the whole history space due to its competitive nature, an increasing $L$ has the effect of driving the system to a restricted portion of the history space. Thus the underlying cause of the observed features is an interesting self-organized phenomena in which the system, in response to the global resource level, effectively avoids particular patterns of history outcomes. We also compare results in networked population with those in non-networked population.

cond-mat.dis-nn↗
arXiv2005

Theory of enhanced performance emerging in a sparsely-connected competitive population

We provide an analytic theory to explain Anghel et al.'s recent numerical finding whereby a maximum in the global performance emerges for a sparsely-connected competitive population [Phys. Rev. Lett. 92, 058701 (2004)]. We show that the effect originates in the highly-correlated dynamics of strategy choice, and can be significantly enhanced using a simple modification to the model.

cond-mat.dis-nn↗
arXiv2004

Plateaux formation, abrupt transitions, and fractional states in a competitive population with limited resources

We study, both numerically and analytically, a Binary-Agent-Resource (B-A-R) model consisting of N agents who compete for a limited resource 1/2<L/N <1, where L is the maximum available resource per turn for all N agents. As L increases, the system exhibits well-defined plateaux regions in the success rate which are separated from each other by abrupt transitions. Both the maximum and the mean success rates over each plateau are 'quantized' -- for example, the maximum success rate forms a well-defined sequence of simple fractions as L increases. We present an analytic theory which explains these surprising phenomena both qualitatively and quantitatively. The underlying cause of this complex behavior is an interesting self-organized phenomenon in which the system, in response to the global resource level, effectively avoids particular patterns of historical outcomes.

cond-mat.dis-nn↗
arXiv2004

Theory of Networked Minority Games based on Strategy Pattern Dynamics

We formulate a theory of agent-based models in which agents compete to be in a winning group. The agents may be part of a network or not, and the winning group may be a minority group or not. The novel feature of the present formalism is its focus on the dynamical pattern of strategy rankings, and its careful treatment of the strategy ties which arise during the system's temporal evolution. We apply it to the Minority Game (MG) with connected populations. Expressions for the mean success rate among the agents and for the mean success rate for agents with $k$ neighbors are derived. We also use the theory to estimate the value of connectivity $p$ above which the Binary-Agent-Resource system with high resource level goes into the high-connectivity state.

cond-mat.dis-nn↗
arXiv2004

Enhanced Winning in a Competing Population by Random Participation

We study a version of the minority game in which one agent is allowed to join the game in a random fashion. It is shown that in the crowded regime, i.e., for small values of the memory size $m$ of the agents in the population, the agent performs significantly well if she decides to participate the game randomly with a probability $q$ {\em and} she records the performance of her strategies only in the turns that she participates. The information, characterized by a quantity called the inefficiency, embedded in the agent's strategies performance turns out to be very different from that of the other agents. Detailed numerical studies reveal a relationship between the success rate of the agent and the inefficiency. The relationship can be understood analytically in terms of the dynamics in which the various possible histories are being visited as the game proceeds. For a finite fraction of randomly participating agents up to 60% of the population, it is found that the winning edge of these agents persists.

cond-mat.stat-mech↗
arXiv2004

Dynamical interplay between local connectivity and global competition in a networked population

We show, both numerically and analytically, that the consequences of 'wiring up' a competitive population depend quite dramatically on the interplay between the local connectivity and the global resources. With modest global resources, adding small amounts of local connectivity yields an increasingly heterogeneous population. With substantial global resources, high-performing yet reasonably homogenous collective states emerge instead.

cond-mat.dis-nn↗
arXiv2002

Ultrafast optical signature of quantum superpositions in a nanostructure

We propose an unambiguous signature for detecting quantum superposition states in a nanostructure, based on current ultrafast spectroscopy techniques. The reliable generation of such superposition states via Hadamard-like quantum gates is crucial for implementing solid-state based quantum information schemes. The signature originates from a remarkably strong photon antibunching effect which is enhanced by non-Markovian dynamics.

cond-mat.mes-hall↗
arXiv2002

Optimal combinations of imperfect objects

We address the question of 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.

cond-mat.stat-mech↗
arXiv2001

Herd Formation and Information Transmission in a Population: Non-universal behaviour

We present generalized dynamical models describing the sharing of information, and the corresponding herd behavior, in a population based on the recent model proposed by Egu\'ıluz and Zimmermann (EZ) [Phys. Rev. Lett. 85, 5659 (2000)]. The EZ model, which is a dynamical version of the herd formation model of Cont and Bouchaud (CB), gives a reasonable model for the formation of clusters of agents and for actions taken by clusters of agents. Both the EZ and CB models give a cluster size distribution characterized by a power law with an exponent -5/2. By introducing a size-dependent probability for dissociation of a cluster of agents, we show that the exponent characterizing the cluster size distribution becomes model-dependent and non-universal, with an exponential cutoff for large cluster sizes. The actions taken by the clusters of agents generate the price returns, the distribution of which is also characterized by a model-dependent exponent. When a size-dependent transaction rate is introduced instead of a size-dependent dissociation rate, it is found that the distribution of price returns is characterized by a model-dependent exponent while the exponent for the cluster-size distribution remains unchanged. The resulting systems provide simplified models of a financial market and yield power law behaviour with an easily tunable exponent.

cond-mat.stat-mech↗
arXiv2001

Non-universal scaling in a model of information transmission and herd behavior

We present a generalized dynamical model describing the sharing of information, and corresponding herd behavior, in a population based on the recent model proposed by Eguiluz and Zimmermann. By introducing a size-dependent probability for dissociation of a cluster, we show that the exponent characterizing the distribution of cluster sizes becomes model-dependent and non-universal. The resulting system, which provides a simplified model of a financial market, yields power law behavior with an easily tunable exponent.

cond-mat.dis-nn↗
arXiv2001

Application of multi-agent games to the prediction of financial time-series

We report on a technique based on multi-agent games which has potential use in the prediction of future movements of financial time-series. A third-party game is trained on a black-box time-series, and is then run into the future to extract next-step and multi-step predictions. In addition to the possibility of identifying profit opportunities, the technique may prove useful in the development of improved risk management strategies.

cond-mat.dis-nn↗