How Can I Generate Reproducible Random Numbers in JavaScript?

Seeding the Random Number Generator in JavaScript

Background:

JavaScript's native random number generator, Math.random(), lacks the ability to be seeded, limiting its randomness. This becomes problematic when reproducible or predictable sequences of random numbers are required.

Solution:

To overcome this limitation, it is necessary to implement external PRNG functions that support seeding. These algorithms accept a seed as input, ensuring the generation of deterministic and repeatable random sequences.

Implementation:

Various PRNG algorithms have been developed for JavaScript that offer high-quality randomness. Here are a few popular options:

sfc32 (Simple Fast Counter)

sfc32 is a fast and reliable PRNG with a 128-bit state. It passes the PractRand random number testing suite and is highly recommended for its speed and performance in JavaScript.

splitmix32

splitmix32 is another high-quality PRNG with a slightly different approach than sfc32. It also offers fast performance and is suitable for a wide range of applications.

Seed Generation:

Properly initializing your PRNGs is crucial. You can use methods such as hash functions or dummy data padded with Phi, Pi, and E to generate high-entropy seeds. Advancement of the generator before using its output is also recommended to mix the initial state thoroughly.

Usage:

Once you have a seeded PRNG function, you can generate reproducible sequences of random numbers using it. These numbers are constrained to a floating-point range between 0 and 1, similar to Math.random().

Conclusion:

By utilizing these external PRNG functions and ensuring proper seeding, you can achieve true randomness in JavaScript, making your applications and simulations more reliable and unpredictable.

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