Droplet Microfluidics: Poisson Arrival Timeline (2D)

Every droplet-based single-cell RNA-seq run — 10x Genomics Chromium, inDrop, Drop-seq — begins with cells entering a flow-focusing junction as a genuine continuous-time random arrival process. This 2D simulator draws that process exactly right: each cell's arrival gap is sampled from a true exponential distribution, so the scrolling event timeline shows real, irregular Poisson arrivals rather than an evenly-spaced approximation. Every time the fixed pinch clock ticks, the cells that arrived since the last pinch become one droplet, rendered into a filling gallery and colour-coded by outcome (empty, singlet, doublet, 3+ cells), with an independent Knuth-sampled bead count layered on top. A live Fano-factor readout (variance ÷ mean of cells per droplet) is the simulator's built-in correctness check: a genuine Poisson process always reads ≈1, and this page shows that value next to the same statistic computed from a naive fixed-rate accumulator model, which reads far below 1 — a concrete, numerically verifiable demonstration of why the arrival model matters, not just the mean loading rate.