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By editing the properties of the particles, simulation can be performed with high performance using WebGPU. The following proof of concept shows so, live demo link:

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BlueFries---Particle-Charge-Simulation-on-WebGPU

By editing the properties of the particles, simulation can be performed with high performance using WebGPU. The following proof of concept shows so:

Live demo link with WebGPU: https://jayadityashah.github.io/BlueFries_ParticleChargeSimulation-on-WebGPU/?balls=600&width=1400&height=650

Live demo Without Web GPU: https://jayadityashah.github.io/BlueFries_ParticleChargeSimulation-WOGPU/?balls=2000&width=1400&height=650

repository for w/o gpu: https://github.com/jayadityashah/BlueFries_ParticleChargeSimulation-WOGPU

You can edit the following parameters, by passing them to the url above by using the ?tag:

balls parameter - number of balls
min/max_radius parameter - min and max particle radius
plus_probability - the probability of the particle to have a +1 charge. if -1, all particles are neutral
width, height - width and height of the canvas

A key on the particle color and charges:

White - neutral
Dark Blue - positive	
Pink - negetive

(Charges behave so simmilars attract for the demo but this can be changed by changing the charge co-relation to negetive in the wgsl file)

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By editing the properties of the particles, simulation can be performed with high performance using WebGPU. The following proof of concept shows so, live demo link:

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