# gst: droplet bag formation in turbulent airflows.

AA << present numerical simulations investigating the evolution of liquid droplets into baglike structures in turbulent airflows. The droplet bag breakup problem is of significance for many multiphase processes in scientific and engineering applications. Turbulent fluctuations are introduced synthetically into a mean flow, and the droplet is inserted when the air-phase turbulence reaches a statistically stationary state. The morphological evolution of the droplet under different turbulence configurations is retrieved and analyzed in comparison with laminar aerobreakup results. While the detailed evolution history of individual droplets varies widely between different realizations of the turbulent flow, common dynamic and morphological evolution patterns are observed. >>

<< The presence of turbulence is found to enhance the drag coefficient of the droplet as it flattens. At late times, the droplet becomes tilted and increasingly corrugated under strong turbulence intensity. (AA) quantify these phenomena and discuss their possible governing mechanisms associated with turbulence intermittency. >>

<< Lastly, the influences of liquid-gas viscosity ratio are examined and the implications of air-phase turbulence on the later bag film breakup process are discussed. >>️

Kaitao Tang, Thomas A. A. Adcock, Wouter Mostert. Droplet bag formation in turbulent airflows. Phys. Rev. Fluids 10, 033604. March 19, 2025.

https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.10.033604

Also: drop, droplet, droploid, turbulence, fluctuations, intermittency, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, drop, droplet, droploid, turbulence, fluctuations, intermittency

# gst: from alternating stripes to alternating labyrinths, the Belousov−Zhabotinsky transition

<< Alternating (temporally period-2) stripes and labyrinths have been observed in media of chemical and biochemical reactions; however, the mechanisms underlying the formation of these spatiotemporal patterns remain unclear. >>

AA << conduct computer simulation using a modified model of Belousov−Zhabotinsky reaction that incorporates a global feedback loop with a spatial strength profile of Gaussian distribution. The simulation results demonstrate that the transition from alternating stripes to alternating labyrinths occurs when the feedback is negative with a certain width of the Gaussian function. (AA) add the same Gaussian-weighted feedback loop to an amplitude equation to describe the amplitude dynamics of the period-2 oscillation and show that the pattern dynamics of the Belousov−Zhabotinsky reaction can be well captured by this amplitude equation. >>

<< Analyses of the amplitude equation demonstrate that the transition from stripes to labyrinths arises from the transverse instabilities of bistable fronts caused by the Gaussian-weighted negative global feedback. >>️

Chunli Huang, Zhen Song, Zhilin Qu. Transition from alternating stripes to alternating labyrinths in oscillatory media. Phys. Rev. E 111, L032201. Mar 13, 2025.

https://journals.aps.org/pre/abstract/10.1103/PhysRevE.111.L032201

Also: transition, in https://www.inkgmr.net/kwrds.html 

Also: Orologio chimico. Notes (quasi-stochastic poetry). Apr 08, 2005.

https://inkpi.blogspot.com/2005/04/1558-orologio-chimico.html  

Keywords: gst, transitions, BZ reaction, labyrinths, alternating labyrinths

# gst: First-passage-time statistics of active Brownian particles: a perturbative approach.

AA << study the first-passage-time (FPT) properties of active Brownian particles to reach an absorbing wall in two dimensions. Employing a perturbation approach (They) obtain exact analytical predictions for the survival and FPT distributions for small Péclet numbers, measuring the importance of self-propulsion relative to diffusion. >>

<< While randomly oriented active agents reach the wall faster than their passive counterpart, their initial orientation plays a crucial role in the FPT statistics. Using the median as a metric, (AA) quantify this anisotropy and find that it becomes more pronounced at distances where persistent active motion starts to dominate diffusion. >>️

Yanis Baouche, Magali Le Goff, et al. First-passage-time statistics of active Brownian particles: a perturbative approach. arXiv: 2503.05401v1 [cond-mat.soft]. Mar 7, 2025.

https://arxiv.org/abs/2503.05401

Also: particle, random, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, particles, active particles, perturbation approach, randomness, stochasticity, stochastic resetting, rotational diffusion, anisotropy

# poe: onda di gioco

<<  

Nota a far mescole coll' endogeno docile avo melode /

declamando su traccia nevale di dondolio di geco /

l' evento d' onde nella forma di compressa logica ode /

che, se liberata, s' autoespande in frange d' agile eco.

>>

14.31 13/09/2004

'solebat quid esset litus ita definire: "qua fluctus eluderet"'. In: Cicerone. 'de natura deorum'.

https://inkpi.blogspot.com/2005/03/1782-onda-di-gioco.html  

Anche:  waves, in   

Notes (quasi-stochastic poetry)  https://inkpi.blogspot.com/search?q=onda 

FonT  https://flashontrack.blogspot.com/search?q=waves 

inkgmr.net  https://www.inkgmr.net/kwrds.html 

Anche: World Poetry Day, in

 https://en.m.wikipedia.org/wiki/World_Poetry_Day     https://nationaltoday.com/world-poetry-day

Keywords: poe, poetry, quasi-stochastic poetry, PoetryDay, WorldPoetryDay, InternationalPoetryDay, waves, rogue waves, shock waves, solitons, turbulence, instability

# aibot: I think, therefore I hallucinate: minds, machines, and the art of being wrong.

<< This theoretical work examines 'hallucinations' in both human cognition and large language models, comparing how each system can produce perceptions or outputs that deviate from reality. Drawing on neuroscience and machine learning research, (AA) highlight the predictive processes that underlie human and artificial thought. >>

<< In humans, complex neural mechanisms interpret sensory information under uncertainty, sometimes filling in gaps and creating false perceptions. This inference occurs hierarchically: higher cortical levels send top-down predictions to lower-level regions, while mismatches (prediction errors) propagate upward to refine the model. LLMs, in contrast, rely on auto-regressive modeling of text and can generate erroneous statements in the absence of robust grounding. >>

<< Despite these different foundations - biological versus computational - the similarities in their predictive architectures help explain why hallucinations occur. (AA) propose that the propensity to generate incorrect or confabulated responses may be an inherent feature of advanced intelligence. In both humans and AI, adaptive predictive processes aim to make sense of incomplete information and anticipate future states, fostering creativity and flexibility, but also introducing the risk of errors. (Their) analysis illuminates how factors such as feedback, grounding, and error correction affect the likelihood of 'being wrong' in each system. (AA) suggest that mitigating AI hallucinations (e.g., through improved training, post-processing, or knowledge-grounding methods) may also shed light on human cognitive processes, revealing how error-prone predictions can be harnessed for innovation without compromising reliability. By exploring these converging and divergent mechanisms, the paper underscores the broader implications for advancing both AI reliability and scientific understanding of human thought. >>️

Sebastian Barros. I Think, Therefore I Hallucinate: Minds, Machines, and the Art of Being Wrong. arXiv: 2503.05806v1 [q-bio.NC]. 4 Mar 4, 2025.

https://arxiv.org/abs/2503.05806

Also: brain, curiosity, novelty, uncertainty, error, mistake, jazz, ai (artificial intell), in https://www.inkgmr.net/kwrds.html 

Keywords: brain, cognition, perceptions, curiosity, novelty, hallucinations, errors, prediction, prediction errors, error-prone predictions, AI, artificial intelligence, LLMs

# behav: the benefit of ignorance for traffic through a random congestible network.

<< When traffic is routed through a network that is susceptible to congestion, the self-interested decisions made by individual users do not, in general, produce the optimal flow. This discrepancy is quantified by the so-called "price of anarchy." >>

AA << consider whether the traffic produced by self-interested users is made better or worse when users have uncertain knowledge about the cost functions of the links in the network, and define a parallel concept that (They) call the "price of ignorance."  >>

AA << introduce a simple model in which fast, congestible links and slow, incongestible links are mixed randomly in a large network and users plan their routes with finite uncertainty about which of the two cost functions describes each link. >>

<< One of (Their) key findings is that a small level of user ignorance universally improves traffic, regardless of the network composition. Further, there is an optimal level of ignorance which, in (the) model, causes the self-interested user behavior to coincide with the optimum. Many features of (AA) model can be understood analytically, including the optimal level of user ignorance and the existence of critical scaling near the percolation threshold for fast links, where the potential benefit of user ignorance is greatest. >>️

Alican Saray, Calvin Pozderac, et al. The benefit of ignorance for traffic through a random congestible network. arXiv: 2503.09684v1 [cond-mat.dis-nn]. Mar 12, 2025.

https://arxiv.org/abs/2503.09684

Also:  network, behav, random, uncertainty, in https://www.inkgmr.net/kwrds.html 

Keywords: gst, networks, behavior,  randomness, uncertainty, price of anarchy, price of ignorance

# qubit: stability of classical shadows under gate-dependent noise

<< Expectation values of observables are routinely estimated using so-called classical shadows—the outcomes of randomized bases measurements on a repeatedly prepared quantum state. In order to trust the accuracy of shadow estimation in practice, it is crucial to understand the behavior of the estimators under realistic noise. >>

<< In this Letter, (AA) prove that any shadow estimation protocol involving Clifford unitaries is stable under gate-dependent noise for observables with bounded stabilizer norm—originally introduced in the context of simulating Clifford circuits. In contrast, (They) demonstrate with concrete examples that estimation of “magic” observables can lead to highly misleading results in the presence of miscalibration errors and a worst case bias scaling exponentially in the system size. >>

AA << further find that so-called robust shadows, aiming at mitigating noise, can introduce a large bias in the presence of gate-dependent noise compared to unmitigated classical shadows. Nevertheless, (AA) guarantee the functioning of robust shadows for a more general noise setting than in previous works. On a technical level, (They) identify average noise channels that affect shadow estimators and allow for a more fine-grained control of noise-induced biases. >>️

Raphael Brieger, Markus Heinrich, et al. Stability of Classical Shadows under Gate-Dependent Noise. Phys. Rev. Lett. 134, 090801. Mar 4, 2025. 

https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.134.090801  arXiv: 2310.19947v3 [quant-ph]. Feb 19, 2025.   https://arxiv.org/abs/2310.19947

Also: qubit, in FonT  https://flashontrack.blogspot.com/search?q=qubit  noise, ai (artificial intell) (bot), in https://www.inkgmr.net/kwrds.html   

Keywords: qubit, noise, realistic noise, shadows, robust shadows