Interplay Of Noise Research Articles

Interplay of noise, memory and entangling operator in quantum Stackelberg-Bertrand duopoly game

In this work, we make an attempt to understand how noise, memory and entangling operators collectively decide the profit of the firms Here we have studied the quantum version of Stackelberg-Bertrand duopoly game using modified EWL scheme in both correlated and uncorrelated noise channels. When this game is analyzed for amplitude damping channels following interesting results are obtained: Firstly, decoherence in channel 2 effects the profit function of the firms more than that of channel 1. Secondly, in the case of correlated noise memory prevents the death of entanglement at maximum noise. Finally, the profit function of the firms depends upon noise, memory, strategies, and entangling operator in any given game setting.

Emergent noise-aided logic through synchronization.

In this article, we present a dynamical scheme to obtain a reconfigurable noise-aided logic gate that yields all six fundamental two-input logic operations, including the xor operation. The setup consists of two coupled bistable subsystems that are each driven by one subthreshold logic input signal, in the presence of a noise floor. The synchronization state of their outputs robustly maps to two-input logic operations of the driving signals, in an optimal window of noise and coupling strengths. Thus the interplay of noise, nonlinearity, and coupling leads to the emergence of logic operations embedded within the collective state of the coupled system. This idea is manifested using both numerical simulations and proof-of-principle circuit experiments. The regions in parameter space that yield reliable logic operations were characterized through a stringent measure of reliability, using both numerical and experimental data.

Scarring in classical chaotic dynamics with noise.

We report the numerical observation of scarring, which is enhancement of probability density around unstable periodic orbits of a chaotic system, in the eigenfunctions of the classical Perron-Frobenius operator of noisy Anosov ("perturbed cat") maps, as well as in the noisy Bunimovich stadium. A parallel is drawn between classical and quantum scars, based on the unitarity or nonunitarity of the respective propagators. For uniformly hyperbolic systems such as the cat map, we provide a mechanistic explanation for the classical phase-space localization detected, based on the distribution of finite-time Lyapunov exponents, and the interplay of noise with deterministic dynamics. Classical scarring can be measured by studying autocorrelation functions and their power spectra.

An advanced perception model combining brain noise and adaptation

We develop an advanced model of bistable perception based on the interplay of noise and adaptation. The model describes the decision-making process in the brain consisting in involuntary switches between perceptual states. We study the effects of noise and the stimulus duty cycle on the dominance of a particular externally biased perceptual state. We discuss the biological relevance of our model and compare the obtained numerical results with neurophysiological experiments on brain dynamics. The model qualitatively describes the results of neurophysiological experiments on human perception using bistable images, such as gamma distribution of average dominance times and the effect of brain noise on sustained attention.

Noise-induced switching in two adaptively coupled excitable systems

We demonstrate that the interplay of noise and plasticity gives rise to slow stochastic fluctuations in a system of two adaptively coupled active rotators with excitable local dynamics. Depending on the adaptation rate, two qualitatively different types of switching behavior are observed. For slower adaptation, one finds alternation between two modes of noise-induced oscillations, whereby the modes are distinguished by the different order of spiking between the units. In case of faster adaptation, the system switches between the metastable states derived from coexisting attractors of the corresponding deterministic system, whereby the phases exhibit a bursting-like behavior. The qualitative features of the switching dynamics are analyzed within the framework of fast-slow analysis.

Noise-induced polarization switching in complex networks.

The combination of bistability and noise is ubiquitous in complex systems, from biology to social interactions, and has important implications for their functioning and resilience. Here we use a simple three-state dynamical process, in which nodes go from one pole to another through an intermediate state, to show that noise can induce polarization switching in bistable systems if dynamical correlations are significant. In large, fully connected networks, where dynamical correlations can be neglected, increasing noise yields a collapse of bistability to an unpolarized configuration where the three possible states of the nodes are equally likely. In contrast, increased noise induces abrupt and irreversible polarization switching in sparsely connected networks. In multiplexes, where each layer can have a different polarization tendency, one layer is dominant and progressively imposes its polarization state on the other, offsetting or promoting the ability of noise to switch its polarization. Overall, we show that the interplay of noise and dynamical correlations can yield discontinuous transitions between extremes, which cannot be explained by a simple mean-field description.

Noise-induced transport in the motion of trapped ions

The interplay of noise and quantum coherence in transport gives rise to rich dynamics relevant for a variety of systems. In this work, we put forward a proposal for an experiment testing noise-induced transport in the vibrational modes of a chain of trapped ions. We focus on the case of transverse modes, considering multiple-isotope chains and an "angle trap", where the transverse trapping varies along the chain. This variation induces localization of the motional modes and therefore suppresses transport. By suitably choosing the action of laser fields that couple to the internal and external degrees of freedom of the ions, we show how to implement effective local dephasing on the modes, broadening the vibrational resonances. This leads to an overlap of the local mode frequencies, giving rise to a pronounced increase in the transport of excitations along the chain. We propose an implementation and measurement scheme which require neither ground-state cooling nor low heating rates, and we illustrate our results with a simulation of the dynamics for a chain of three ions.

Effect of noise on tasks in operating theatres: a survey of the perceptions of healthcare staff

Noise in the operating theatre has an adverse impact on healthcare professionals, both physically and psychologically. It can be distracting, make communication difficult, and contribute to a perceived increase in stress. Staff in theatre must deliver high quality care, and overlook noise as a potentially damaging influence. The aim of this survey was to obtain further information about the perspective of healthcare professionals on how noise can affect their practice and whether it affects their work in theatre. We distributed six closed-ended questions in the form of a Survey Monkey® questionnaire to about 50 hospitals across the UK and target groups such as medical students, the Leeds Advanced Trauma Life Support faculty group, the Court of Examiners of the Royal College of Surgeons of England, and surgical trainees sitting the Member of the Royal College of Surgeons examination.We received 519 responses of which 415 respondents (83%) thought that noise contributed to human errors. A total of 282 participants (57%) thought that the theatre was the noisiest area within the theatre suite. Both communication among staff (n=400, 80%) and concentration (n=384, 77%) were thought to be adversely affected by noise. However, 385 (78%) did not feel that music adversely affected their performance. The results provide insights into the interplay of noise and its effect on people. Although the role of music remains contentious, our results suggest that it might have a calming influence.

Object extraction from underwater images through logical stochastic resonance.

Logical stochastic resonance (LSR), the phenomenon in which the interplay of noise and nonlinearity can raise the accurate probability of response to feeble input signals, is studied in this Lettter to extract objects from highly degraded underwater images. Images captured under water, especially in the turbid areas, always suffer from interference through heavy noise caused by the suspended particles. Inherent noise and nonlinearity cause difficulty in processing these images through conventional image processing methods. However, LSR can optimally address such issues. A heavily degraded image is first extended to a 1D form in the direction determined by the illumination condition, and then normalized to be placed in the LSR system as an input signal. Additional Gaussian noise is added to the system as the auxiliary power to help separate the object and the background. Results in the natural offshore area demonstrate the effect of LSR on image processing, and the proposed method creates an interesting direction in the processing of heavily degraded images.

Modeling valuations from experience: A comment on Ashby and Rakow (2014).

What are the cognitive mechanisms underlying subjective valuations formed on the basis of sequential experiences of an option's possible outcomes? Ashby and Rakow (2014) have proposed a sliding window model (SWIM), according to which people's valuations represent the average of a limited sample of recent experiences (the size of which is estimated by the model) formed after sampling has been terminated (i.e., an end-of-sequence process). Ashby and Rakow presented results from which they concluded, on the basis of model-selection criteria, that the SWIM performs well compared with alternative models (e.g., value-updating model, summary model). Further, they reported that the individual window sizes estimated by the SWIM correlated with a measure of working-memory capacity. In a reanalysis of the Ashby and Rakow data, we find no clear evidence in support of any of the models tested, and a slight advantage for the summary model. Further, we demonstrate that individual differences in the window-size estimated by the SWIM can reflect differences in noise. In computer simulations, we examine the more general question of how well the models tested by Ashby and Rakow can actually be discriminated. The results reveal that the models' ability to fit data depends on a complex interplay of noise and the sample size of outcomes on which a valuation response is based. This can critically influence model performance and conclusions regarding the underlying cognitive mechanisms. We discuss the implications of these findings and suggest ways of improving model comparisons in valuations from experience. (PsycINFO Database Record

Noise-assisted charge pump in elastically deformable molecular junctions

We study a charge pump realized with an elastically deformable quantum dot whose center of mass follows a nonlinear stochastic dynamics. The interplay of noise, nonlinear effects, dissipation and interaction with an external time-dependent driving on the pumped charge is fully analyzed. The results show that the quantum pumping mechanism not only is not destroyed by the force fluctuations, but it becomes stronger when the forcing signal frequency is tuned close to the resonance of the vibrational mode. The robustness of the quantum pump with temperature is also investigated and an exponential decay of the pumped charge is found when the coupling to the vibrational mode is present. Implications of our results for nanoelectromechanical systems are also discussed.

Stability, coherent spiking and synchronization in noisy excitable systems with coupling and internal delays

We study the onset and the adjustment of different oscillatory modes in a system of excitable units subjected to two forms of noise and delays cast as external or internal according to whether they are associated with inter- or intra-unit activity. Conditions for stability of a single unit are derived in case of the linearized perturbed system, whereas the interplay of noise and internal delay in shaping the oscillatory motion is analyzed by the method of statistical linearization. It is demonstrated that the internal delay, as well as its coaction with external noise, drive the unit away from the bifurcation controlled by the excitability parameter. For the pair of interacting units, it is shown that the external/internal character of noise primarily influences frequency synchronization and the competition between the noise-induced and delay-driven oscillatory modes, while coherence of firing and phase synchronization substantially depend on internal delay. Some of the important effects include: (i) loss of frequency synchronization under external noise; (ii) existence of characteristic regimes of entrainment, where under variation of coupling delay, the optimized unit (noise intensity fixed at resonant value) may be controlled by the adjustable unit (variable noise) and vice versa, or both units may become adjusted to coupling delay; (iii) phase synchronization achieved both for noise-induced and delay-driven modes.

An experimental study of noise and asynchrony in elementary cellular automata with sampling compensation

This article focuses on the set of 32 legal elementary cellular automata (ECA). We perform an exhaustive study of the systems' response under: (i) ?-asynchronous dynamics, from full asynchronism to perfect synchrony, (ii) ?-scaling, which extends ?-asynchrony to compensate for less cell activity, and (iii) ?-noise scheme, a perturbation that affects the local transition function and causes a cell to probabilistically miscalculate the new state when it is updated. We propose a new classification in three classes under asynchronous conditions: ?-invariant, ?-robust, and ?-dependent. We classify the 32 legal ECA according to the degree of behavioural modification, and we show that our classifying scheme provides results coherent with the density-based classification. We also show that ?-scaling provides results comparable to synchronous systems, both quantitatively and qualitatively. Subsequently, we analyse the effects of including different levels of noise in synchronous systems. We identify different responses to noise, including systems that are robust to asynchrony and susceptible to noise. To conclude, we investigate the behavioural changes caused by simultaneous asynchrony and noise in models tolerant to both perturbations. We describe a number of effects caused by the interplay of noise and asynchrony, thus further reinforcing that both aspects are pertinent for future studies.

Signaling Noise Enhances Chemotactic Drift ofE. coli

Noise in the transduction of chemotactic stimuli to the flagellar motor of E. coli will affect the random run-and-tumble motion of the cell and the ability to perform chemotaxis. Here we use numerical simulations to show that an intermediate level of noise in the slow methylation dynamics enhances drift while not compromising localization near concentration peaks. A minimal model shows how such an optimal noise level arises from the interplay of noise and the dependence of the motor response on the network output. Our results suggest that cells can exploit noise to improve chemotactic performance.

Spatiotemporal pattern formation in two-dimensional neural circuits: roles of refractoriness and noise

Refractoriness is one of the most fundamental states of neural firing activity, in which neurons that have just fired are unable to produce another spike, regardless of the strength of afferent stimuli. Another essential and unavoidable feature of neural systems is the existence of noise. To study the role of these essential factors in spatiotemporal pattern formation in neural systems, a spatially expended neural network model is constructed, with the dynamics of its individual neurons capturing the three most essential states of the neural firing behavior: firing, refractory and resting, and the network topology consistent with the widely observed center-surround coupling manner in the real brain. By changing the refractory period with and without noise in a systematic way in the network, it is shown numerically and analytically that without refractoriness, or when the refractory period is smaller than a certain value, the collective activity pattern of the system consists of localized, oscillating patterns. However, when the refractory period is greater than a certain value, crescent-shaped, localized propagating patterns emerge in the presence of noise. It is further illustrated that the formation of the dynamical spiking patterns is due to a symmetry breaking mechanism, refractoriness-induced symmetry breaking; that is generated by the interplay of noise and refractoriness in the network model. This refractoriness-induced symmetry breaking provides a novel perspective on the emergence of localized, spiking wave patterns or spike timing sequences as ubiquitously observed in real neural systems; it therefore suggests that refractoriness may benefit neural systems in their temporal information processing, rather than limiting the performance of neurons, as has been conventionally thought. Our results also highlight the importance of considering noise in studying spatially extended neural systems, where it may facilitate the formation of spatiotemporal order.

Coherence and decoherence in biological systems: principles of noise-assisted transport and the origin of long-lived coherences

The quantum dynamics of transport networks in the presence of noisy environments has recently received renewed attention with the discovery of long-lived coherences in different photosynthetic complexes. This experimental evidence has raised two fundamental questions: firstly, what are the mechanisms supporting long-lived coherences; and, secondly, how can we assess the possible functional role that the interplay of noise and quantum coherence might play in the seemingly optimal operation of biological systems under natural conditions? Here, we review recent results, illuminate them by means of two paradigmatic systems (the Fenna-Matthew-Olson complex and the light-harvesting complex LHII) and present new progress on both questions.

Control of coherence in excitable systems by the interplay of noise and time-delay

The control of coherence and spectral properties of noise-induced oscillations by time delayed feedback is studied in a FitzHugh-Nagumo system and analyzed by reduced non-Markovian models. A two-state approach is considered as an abstract simplification of this excitable system. Rest and excited states are characterized by different waiting time distributions. This non-Markovian approach allows one to predict quantitatively the increase of coherence measured by the correlation time, and the modulation of the main frequencies of the stochastic dynamics in dependence on the delay time below Hopf bifurcations. Beyond the Hopf bifurcation, bulk oscillations of an ensemble of excitable two-state rotators emerge in the onset of coherent activation in case of delayed mean field coupling of the ensemble.

Transient low-frequency fluctuations in semiconductor lasers with optical feedback

Time-delayed systems often exhibit multistability of coexisting attractors, which can result in long chaotic transients on the way to one of the coexisting states. Strong enough noise can transform this transient chaos into noise-sustained dynamics. Here we study the interplay between delay-induced multistability, chaotic transients, and noise, in the case of a semiconductor laser with optical feedback from an external reflector. The time-delayed feedback renders the laser multistable, with a set of coexisting fixed points, and induces dynamical events called low-frequency fluctuations (LFFs), consisting of sudden intensity dropouts at irregular times. The deterministic Lang-Kobayashi model shows that, for a large range of realistic laser parameters, the LFFs are just a transient dynamics toward a stable fixed point. Here we analyze the statistical properties of the transient LFF dynamics and investigate the influence of various parameters. We find that realistic values of the noise strength do not affect the average transient time or its distribution, provided the model includes an explicit delay. On the other hand, nonlinear gain saturation has a strong effect: it increases both the duration of the LFF transients and the probability of noise-induced escapes from the stable fixed point. Our results suggest that the LFFs observed experimentally can be, at least in part, sustained by the interplay of noise and various nonlinear effects, which are phenomenologically represented by a gain saturation coefficient.

Interplay of noise and coupling in heterogeneous ensembles of phase oscillators

We study the effects of noise on the collective dynamics of an ensemble of coupled phase oscillators whose natural frequencies are all identical, but whose coupling strengths are not the same all over the ensemble. The intensity of noise can also be heterogeneous, representing diversity in the individual responses to external fluctuations. We show that the desynchronization transition induced by noise may be completely suppressed, even for arbitrarily large noise intensities, is the distribution of coupling strengths decays slowly enough for large couplings. Equivalently, if the response to noise of a sufficiently large fraction of the ensemble is weak enough, desynchronization cannot occur. The two effects combine with each other when the response to noise and the coupling strength of each oscillator are correlated. This combination is quantitatively characterized and illustrated with explicit examples.

Variability-induced transition in a net of neural elements: From oscillatory to excitable behavior

Starting with an oscillatory net of neural elements, increasing variability induces a phase transition to excitability. This transition is explained by a systematic effect of the variability, which stabilizes the formerly unstable, spatially uniform, temporally constant solution of the net. Multiplicative noise may also influence the net in a systematic way and may thus induce a similar transition. Adding noise into the model, the interplay of noise and variability with respect to the reported transition is investigated. Finally, pattern formation in a diffusively coupled net is studied, because excitability implies the ability of pattern formation and information transmission.