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Scientists ponder how jugglers seem to defy limits to human reaction times, Ars Technica

Scientists ponder how jugglers seem to defy limits to human reaction times, Ars Technica
    

      Juggle me this –

             

The accuracy required is a measure of how unstable and difficult a juggling pattern is.

      

      

Master jugglers are clearly very good at multitasking, and since balls aren’t being thrown randomly, each ball need not be tracked and caught independently. But Botvinick-Greenhouse and Shinbrot still wondered how it was possible for jugglers with reaction times of milliseconds to routinely catch balls every milliseconds. “Jugglers rely on making accurate throws and predictions of where the balls will travel,” the authors wrote . “The accuracy required is a measure of how unstable — and thus how difficult — a particular juggling pattern is.”

Juggling has a long and glorious history dating back to ancient Egypt; there are hieroglyphics circa and (BCE that historians consider to be the earliest historical record of juggling. There were juggling warriors in China (801 – BCE) —apparently it was viewed as an effective diversionary tactic — and the practice eventually spread to ancient Greece and Rome. By the mid – s CE, juggling was largely practiced by circus and street performers , and it has fascinated scientists since at least . That’s when Edgar James Swift published a paper Looking at the psychology and physiology of learning in the American Journal of Psychology, which discussed the rate at which students learned to toss two balls in one hand.

As Peter Beek and Arthur Lewbel wrote in (a) article

Standard particle dynamics works fine as a model for juggling balls, while clubs and rings are best modeled as a rigid body system . Whatever the juggled objects of choice, they essentially follow a classic parabolic motion in periodic cycles — there’s just more than one object at play, and the various paths interweave. Since the number of possible patterns is small, one might think this would make it fairly easy to model the process mathematically. But variables like the angle of release, height of the throw, release velocity, and so forth ensure that no two throws or catches are precisely the same. The best jugglers can control all those variables with impressive consistency.

      
  • juggling machines .

    There are three basic patterns in juggling: the “cascade,” in which an odd number of balls are tossed from one hand to another (the most common pattern); the “fountain,” in which an even number of balls are thrown and caught with the same hand; and the “shower,” in which all the objects are tossed in a circle. There’s also the “multiplex,” where the juggler will throw more than one object from a single hand simultaneously.

    The standard mathematical notation for juggling patterns is known as (siteswap theory) (aka quantum juggling, aka the Cambridge Notation), invented in by Paul Klimek and further developed in by Cambridge Mathematicians Colin Wright and Adam Chalcraft (among others). Strings of numbers are used to represent the patterns, and the average of the numbers in the strings is equal to the number of balls being juggled in the pattern. For example, a simple three-ball pattern has a site swap of three (3,3,3), whereby each ball lands three beats after it is thrown.

    As Botvinick-Greenhouse and Shinbrot wrote in (their Physics Today article

    Plays a role .

    In short, “Complex tasks like juggling can be successfully performed without understanding the physiology behind motor control, although a deeper understanding is both intriguing and useful, “Botvinick-Greenhouse and Shinbrot concluded. “Unraveling the secrets behind how our nervous systems pull that off may pave the way for more dexterous robots.”

    DOI: Physics Today, 4417. . 1781 / PT.3. ( About DOIs (Read More) Brave Browser

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