PPolySim OS
Use case · powered by Markov Chains

Markov Chains for a dice distribution

Simulate a dice distribution live in your browser. This runs the real Markov Chains solver — adjust the inputs, watch it respond instantly, and export the result. No install, no account.

Markov ChainLive
A100.0%
B0.0%
C0.0%

Controls

A system hops between states by fixed probabilities. From any start it converges to the same stationary distribution — the math behind PageRank and queueing.

Presets

▶ Run in Python

Data Inspector

Step0
P(A)1.000
P(B)0.000
P(C)0.000

Governing equation

Reading this result: State A has the stickiest self-loop (0.70), so it keeps the largest share of the stationary distribution no matter where you start.

Runs locally in your browser — free forever. Scale to the cloud when reality gets heavy.

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About this simulation

The full Markov Chains tool models a dice distribution with the same numerics engineers and scientists use — running entirely client-side. Change any parameter and the result updates in real time, so you can build intuition, check a design, or teach the concept without spreadsheets or installs.

More you can do with Markov Chains

Other ways to simulate a dice distribution

Frequently asked questions

How do I simulate a dice distribution?
Open this page and use the live Markov Chains tool below — set your inputs and the simulation runs instantly in your browser using real numerics. No install, no account needed.
Is it free?
Yes. The simulation runs free in your browser. A one-time unlock or a Pro plan adds advanced parameters, saved presets, data import, and clean exports.
Can I use my own numbers?
Absolutely — every input is adjustable, and with data import you can drive a dice distribution from your own measurements.