Similarities between insect swarms and isothermal globular clusters

Gorbonos, Dan; Vaart, Kasper van der; Sinhuber, Michael; Puckett, James G.; Reynolds, Anne; Ouellette, Nicholas T.; Gov, Nir S.

doi:10.1103/physrevresearch.2.013271

“…More recent studies have uncovered more striking analogies with self-gravitating systems: including the occurrence of polytropic distributions (which constitute the simplest, physically plausible models for self-gravitating stellar systems), together with biological correlates of Jean's instabilities, black hole entropies, Mach's Principle, surface pressures, and dark matter (see refs. [10,[12][13][14]31] and Electronic Supplementary Material). By providing a revision to Okubo [1] I have uncovered another biological correlate of self-gravitating systems: namely dark energy.…”

Section: Discussionmentioning

confidence: 99%

“…The collective behaviours of laboratory swarms of Chironomus riparius midges are predicted by stochastic trajectory simulation models [5,[7][8][9][10][11]. This and other modelling [12][13][14] have also uncovered striking similarities between insect swarms and self-gravitating systems such as globular clusters, as foreseen by Okubo [1]. Okubo [1] noted that if the internal forces between individuals were like Newtonian gravitational attraction, then the resultant attraction on an individual within a uniform spherical swarm would be directly proportional to the distance from the swarm centre, as observed [1,2] and as predicted by the stochastic models.…”

Section: Introductionmentioning

confidence: 99%

Intrinsic stochasticity and the emergence of collective behaviours in insect swarms

Reynolds

¹

2021

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The cohesion of insect swarms has been attributed to the fact that the resultant internal interactions of the swarming insects produce, on the average, a centrally attractive force that acts on each individual. Here it is shown how insect swarms can also be bound together by centrally forces that on the average are repulsive (outwardly directed from the swarm centres). This is predicted to arise when velocity statistics are heterogeneous (position-dependent). Evidence for repulsive forces is found in laboratory swarms of Chironomus riparius midges. In homogeneous swarms, the net inward acceleration balances the tendency of diffusion (stochastic noise) to transport individuals away from the centre of the swarm. In heterogenous swarms, turbophoresis-the tendency for individuals to migrate in the direction of decreasing kinetic energy-is operating. The new finding adds to the growing realization that insect swarms are analogous to self-gravitating systems. By acting in opposition to central attraction (gravity), the effects of heterogeneous velocities (energies) are analogous to the effects of dark energy. The emergence of resultant forces from collective behaviours would not be possible if individual flight patterns were themselves unstable. It is shown how individuals reduce the potential for the loose of flight control by minimizing the influence of jerks to which they are subjected.

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“…More recent studies have uncovered more striking analogies with self-gravitating systems: including the occurrence of polytropic distributions (which constitute the simplest, physically plausible models for self-gravitating stellar systems), together with biological correlates of Jean's instabilities, black hole entropies, Mach's Principle, surface pressures, and dark matter (see refs. [10,[12][13][14]31] and Electronic Supplementary Material). By providing a revision to Okubo [1] I have uncovered another biological correlate of self-gravitating systems: namely dark energy.…”

Section: Discussionmentioning

confidence: 99%

“…The collective behaviours of laboratory swarms of Chironomus riparius midges are predicted by stochastic trajectory simulation models [5,[7][8][9][10][11]. This and other modelling [12][13][14] have also uncovered striking similarities between insect swarms and self-gravitating systems such as globular clusters, as foreseen by Okubo [1]. Okubo [1] noted that if the internal forces between individuals were like Newtonian gravitational attraction, then the resultant attraction on an individual within a uniform spherical swarm would be directly proportional to the distance from the swarm centre, as observed [1,2] and as predicted by the stochastic models.…”

Section: Introductionmentioning

confidence: 99%

Insect swarms can be bound together by repulsive forces

Reynolds

¹

2020

Eur. Phys. J. E

4

0

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Abstract. The cohesion of insect swarms has been attributed to the fact that the resultant internal interactions of the swarming insects produce, on the average, a centrally attractive force that acts on each individual. Here it is shown how insect swarms can also be bound together by centrally forces that on the average are repulsive (outwardly directed from the swarm centres). This is predicted to arise when velocity statistics are heterogeneous (position-dependent). Evidence for repulsive forces is found in laboratory swarms of Chironomus riparius midges. In homogeneous swarms, the net inward acceleration balances the tendency of diffusion (stochastic noise) to transport individuals away from the centre of the swarm. In heterogenous swarms, turbophoresis --the tendency for individuals to migrate in the direction of decreasing kinetic energy-- is operating. The new finding adds to the growing realization that insect swarms are analogous to self-gravitating systems. By acting in opposition to central attraction (gravity), the effects of heterogeneous velocities (energies) are analogous to the effects of dark energy. The emergence of resultant forces from collective behaviours would not be possible if individual flight patterns were themselves unstable. It is shown how individuals reduce the potential for the loose of flight control by minimizing the influence of jerks to which they are subjected. Graphical abstract

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“…Inverse-square laws are, of course, very common-perhaps most notably in gravitation. This observation led us to model swarms as a kind of self-gravitating system [53][54][55][56][57], following a line of reasoning that goes back to Okubo [58]. This framework is very appealing, as it allows us to translate intuition gained from studying gravitation to collective behavior.…”

Section: Midge Swarmsmentioning

confidence: 99%

Goals and Limitations of Modeling Collective Behavior in Biological Systems

Ouellette

¹

,

Gordon

²

2021

Self Cite

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Local social interactions among individuals in animal groups generate collective behavior, allowing groups to adjust to changing conditions. Historically, scientists from different disciplines have taken different approaches to modeling collective behavior. We describe how each can contribute to the goal of understanding natural systems. Simple bottom-up models that describe individuals and their interactions directly have demonstrated that local interactions far from equilibrium can generate collective states. However, such simple models are not likely to describe accurately the actual mechanisms and interactions in play in any real biological system. Other classes of top-down models that describe group-level behavior directly have been proposed for groups where the function of the collective behavior is understood. Such models cannot necessarily explain why or how such functions emerge from first principles. Because modeling approaches have different strengths and weaknesses and no single approach will always be best, we argue that models of collective behavior that are aimed at understanding real biological systems should be formulated to address specific questions and to allow for validation. As examples, we discuss four forms of collective behavior that differ both in the interactions that produce the collective behavior and in ecological context, and thus require very different modeling frameworks. 1) Harvester ants use local interactions consisting of brief antennal contact, in which one ant assesses the cuticular hydrocarbon profile of another, to regulate foraging activity, which can be modeled as a closed-loop excitable system. 2) Arboreal turtle ants form trail networks in the canopy of the tropical forest, using trail pheromone; one ant detects the volatile chemical that another has recently deposited. The process that maintains and repairs the trail, which can be modeled as a distributed algorithm, is constrained by the physical configuration of the network of vegetation in which they travel. 3) Swarms of midges interact acoustically and non-locally, and can be well described as agents moving in an emergent potential well that is representative of the swarm as a whole rather than individuals. 4) Flocks of jackdaws change their effective interactions depending on ecological context, using topological distance when traveling but metric distance when mobbing. We discuss how different research questions about these systems have led to different modeling approaches.

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Similarities between insect swarms and isothermal globular clusters

Cited by 9 publications

References 26 publications

Intrinsic stochasticity and the emergence of collective behaviours in insect swarms

Intrinsic stochasticity and the emergence of collective behaviours in insect swarms

Insect swarms can be bound together by repulsive forces

Goals and Limitations of Modeling Collective Behavior in Biological Systems

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