Relevant bibliographies by topics / Run-And-Tumble particles

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Run-And-Tumble particles'

Author: Grafiati
Published: 23 November 2024

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Journal articles on the topic "Run-And-Tumble particles"

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Paoluzzi, Matteo, Andrea Puglisi, and Luca Angelani. "Entropy Production of Run-and-Tumble Particles." Entropy 26, no. 6 (May 24, 2024): 443. http://dx.doi.org/10.3390/e26060443.

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We analyze the entropy production in run-and-tumble models. After presenting the general formalism in the framework of the Fokker–Planck equations in one space dimension, we derive some known exact results in simple physical situations (free run-and-tumble particles and harmonic confinement). We then extend the calculation to the case of anisotropic motion (different speeds and tumbling rates for right- and left-oriented particles), obtaining exact expressions of the entropy production rate. We conclude by discussing the general case of heterogeneous run-and-tumble motion described by space-dependent parameters and extending the analysis to the case of d-dimensional motions.
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Redig, F., and H. van Wiechen. "Stationary Fluctuations of Run-and-Tumble Particles." Markov Processes And Related Fields 30, no. 2024 №2 (30) (August 26, 2024): 297–331. http://dx.doi.org/10.61102/1024-2953-mprf.2024.30.2.003.

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We study the stationary fluctuations of independent run-and-tumble particles. We prove that the joint densities of particles with given internal state converges to an infinite dimensional Ornstein-Uhlenbeck process. We also consider an interacting case, where the particles are subjected to exclusion. We then study the fluctuations of the total density, which is a non-Markovian Gaussian process, and obtain its covariance in closed form. By considering small noise limits of this non-Markovian Gaussian process, we obtain in a concrete example a large deviation rate function containing memory terms.
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Paoluzzi, M., R. Di Leonardo, and L. Angelani. "Run-and-tumble particles in speckle fields." Journal of Physics: Condensed Matter 26, no. 37 (August 8, 2014): 375101. http://dx.doi.org/10.1088/0953-8984/26/37/375101.

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Solon, A. P., M. E. Cates, and J. Tailleur. "Active brownian particles and run-and-tumble particles: A comparative study." European Physical Journal Special Topics 224, no. 7 (July 2015): 1231–62. http://dx.doi.org/10.1140/epjst/e2015-02457-0.

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Martinez, Raul, Francisco Alarcon, Juan Luis Aragones, and Chantal Valeriani. "Trapping flocking particles with asymmetric obstacles." Soft Matter 16, no. 20 (2020): 4739–45. http://dx.doi.org/10.1039/c9sm02427a.

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Gutiérrez, C. Miguel Barriuso, Christian Vanhille-Campos, Francisco Alarcón, Ignacio Pagonabarraga, Ricardo Brito, and Chantal Valeriani. "Collective motion of run-and-tumble repulsive and attractive particles in one-dimensional systems." Soft Matter 17, no. 46 (2021): 10479–91. http://dx.doi.org/10.1039/d1sm01006a.

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Peruani, Fernando, and Gustavo J. Sibona. "Reaction processes among self-propelled particles." Soft Matter 15, no. 3 (2019): 497–503. http://dx.doi.org/10.1039/c8sm01502c.

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Bijnens, Bram, and Christian Maes. "Pushing run-and-tumble particles through a rugged channel." Journal of Statistical Mechanics: Theory and Experiment 2021, no. 3 (March 1, 2021): 033206. http://dx.doi.org/10.1088/1742-5468/abe29e.

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Singh, Chamkor. "Correction: Guided run-and-tumble active particles: wall accumulation and preferential deposition." Soft Matter 18, no. 3 (2022): 684. http://dx.doi.org/10.1039/d1sm90221k.

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Elgeti, Jens, and Gerhard Gompper. "Run-and-tumble dynamics of self-propelled particles in confinement." EPL (Europhysics Letters) 109, no. 5 (March 1, 2015): 58003. http://dx.doi.org/10.1209/0295-5075/109/58003.

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Dissertations / Theses on the topic "Run-And-Tumble particles"

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Hahn, Léo. "Interacting run-and-tumble particles as piecewise deterministic Markov processes : invariant distribution and convergence." Electronic Thesis or Diss., Université Clermont Auvergne (2021-...), 2024. http://www.theses.fr/2024UCFA0084.

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1. Simuler des systèmes actifs et métastables avec des processus de Markov déterministes par morceaux (PDMPs): quelle dynamique choisir pour simuler efficacement des états métastables? comment exploiter directement la nature hors équilibre des PDMPs pour étudier les systèmes physiques modélisés? 2. Modéliser des systèmes actifs avec des PDMPs: quelles conditions doit remplir un système pour être modélisable par un PDMP? dans quels cas le système a-t-il un distribution stationnaire? comment calculer des quantités dynamiques (ex: rates de transition) dans ce cadre? 3. Améliorer les techniques de simulation de systèmes à l'équilibre: peut-on utiliser les résultats obtenus dans le cadre de systèmes hors équilibre pour accélérer la simulation de systèmes à l'équilibre? comment utiliser l'information topologique pour adapter la dynamique en temps réel?
1. Simulating active and metastable systems with piecewise deterministic Markov processes (PDMPs): - Which dynamics to choose to efficiently simulate metastable states? - How to directly exploit the non-equilibrium nature of PDMPs to study the modeled physical systems? 2. Modeling active systems with PDMPs: - What conditions must a system meet to be modeled by a PDMP? - In which cases does the system have a stationary distribution? - How to calculate dynamic quantities (e.g., transition rates) in this framework? 3. Improving simulation techniques for equilibrium systems: - Can results obtained in the context of non-equilibrium systems be used to accelerate the simulation of equilibrium systems? - How to use topological information to adapt the dynamics in real-time?
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Conference papers on the topic "Run-And-Tumble particles"

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Vourc’h, Thomas, Julien Léopoldès, and Hassan Peerhossaini. "Phototactic Behaviour of Active Fluids: Effects of Light Perturbation on Diffusion Coefficient of Bacterial Suspensions." In ASME-JSME-KSME 2019 8th Joint Fluids Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/ajkfluids2019-4904.

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Abstract Active fluids refer to the fluids that contain self-propelled particles such as bacteria or micro-algae, whose properties differ fundamentally from the passive fluids. Such particles often exhibit an intermittent motion; with high-motility “run” periods separated by low-motility “tumble” periods. The average motion can be modified with external stresses, such as nutrient or light gradient, leading to a directed movement called chemotaxis and phototaxis, respectively. Using cyanobacterium Synechocystis sp.PCC 6803, a model micro-organism to study photosynthesis, we track the bacterial response to light stimuli, under isotropic and non-isotropic conditions. In particular, we investigate how the intermittent motility is influenced by illumination. We find that just after a rise in light intensity, the probability to be in the run state increases. This feature vanishes after a typical time of about 1 hour, when initial probability is recovered. Our results are well described by a model based on the linear response theory. When the perturbation is anisotropic, the characteristic time of runs is longer whatever the direction, similar to what is observed with isotropic conditions. Yet we observe a collective motion toward the light source (phototaxis) and show that the bias emerges because of more frequent runs towards the light.
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Journal articles
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